Search results for: learning from history

Authors: Patsy Tan, Dana Baltutis

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This presentation demonstrates the effectiveness of music therapy in co-treatment with speech pathology and occupational therapy as an innovative way when working with children and adolescents with complex individual differences to facilitate communication, emotional, motor and social skills development. Each child with special needs and their carer has an individual profile which encompasses their visual-spatial, auditory, language, learning, mental health, family dynamic, sensory-motor, motor planning and sequencing profiles. The most common issues among children with special needs, especially those diagnosed with Autism Spectrum Disorder, are in the areas of regulation, communication, and social-emotional development. The ability of children living with challenges to communicate and use language and understand verbal and non-verbal information, as well as move their bodies to explore and interact with their environments in social situations, depends on the children being regulated both internally and externally and trusting their communication partners and understanding what is happening in the moment. For carers, it is about understanding the tempo, rhythm, pacing, and timing of their own individual profile, as well as the profile of the child they are interacting with, and how these can sync together. In this study, music therapy is used in co-treatment sessions with a speech pathologist and/or an occupational therapist using the DIRFloortime approach to facilitate the regulation, attention, engagement, reciprocity and social-emotional capacities of children presenting with complex individual differences. Documented changes in 10 domains of children’s development over a 12-month period using the Individual Music Therapy Assessment Profile (IMTAP) were observed. Children were assessed biannually, and results show significant improvements in the social-emotional, musicality and receptive language domains indicating that co-treatment with a music therapist using the DIRFloortime framework is highly effective. This presentation will highlight strategies that facilitate regulation, social-emotional and communication development for children and adolescents with complex individual profiles.

Keywords: communication, shared attention, regulation, social emotional

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Authors: Dacheng Li, Bo Huang, Qinjin Han, Ming Li

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Remotely sensed imagery with the high spatial and temporal characteristics, which it is hard to acquire under the current land observation satellites, has been considered as a key factor for monitoring environmental changes over both global and local scales. On a basis of the limited high spatial-resolution observations, challenged studies called spatiotemporal fusion have been developed for generating high spatiotemporal images through employing other auxiliary low spatial-resolution data while with high-frequency observations. However, a majority of spatiotemporal fusion approaches yield to satisfactory assumption, empirical but unstable parameters, low accuracy or inefficient performance. Although the spatiotemporal fusion methodology via sparse representation theory has advantage in capturing reflectance changes, stability and execution efficiency (even more efficient when overcomplete dictionaries have been pre-trained), the retrieval of high-accuracy dictionary and its response to fusion results are still pending issues. In this paper, we employ additional image pairs (here each image-pair includes a Landsat Operational Land Imager and a Moderate Resolution Imaging Spectroradiometer acquisitions covering the partial area of Baotou, China) only into the coupled dictionary training process based on K-SVD (K-means Singular Value Decomposition) algorithm, and attempt to improve the fusion results of two existing sparse representation based fusion models (respectively utilizing one and two available image-pair). The results show that more eligible image pairs are probably related to a more accurate overcomplete dictionary, which generally indicates a better image representation, and is then contribute to an effective fusion performance in case that the added image-pair has similar seasonal aspects and image spatial structure features to the original image-pair. It is, therefore, reasonable to construct multi-dictionary training pattern for generating a series of high spatial resolution images based on limited acquisitions.

Keywords: spatiotemporal fusion, sparse representation, K-SVD algorithm, dictionary learning

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Authors: Sousan Arafeh

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Educational systems and schools worldwide are increasingly reliant on information and communication technology (ICT). Unfortunately, most educational leadership development programs do not offer formal curricular and/or field experiences that prepare students for managing ICT resources, personnel, and processes. The result is a steep learning curve for the leader and his/her staff and dissipated organizational energy that compromises desired outcomes. To address this gap in education leaders’ development, Arafeh’s Integrated Technology Leadership Model (AITLM) was created. It is a conceptual model and tool that educational leadership students can use to better understand the ICT ecology that exists within their schools. The AITL Model consists of six 'infrastructure types' where ICT activity takes place: technical infrastructure, communications infrastructure, core business infrastructure, context infrastructure, resources infrastructure, and human infrastructure. These six infrastructures are further divided into 16 key areas that need management attention. The AITL Model was created by critically analyzing existing technology/ICT leadership models and working to make something more authentic and comprehensive regarding school leaders’ purview and experience. The AITL Model then served as a tool when it was distributed to over 150 educational leadership students who were asked to review it and qualitatively share their reactions. Students said the model presented crucial areas of consideration that they had not been exposed to before and that the exercise of reviewing and discussing the AITL Model as a group was useful for identifying areas of growth that they could pursue in the leadership development program and in their professional settings. While development in all infrastructures and key areas was important for students’ understanding of ICT, they noted that they were least aware of the importance of the intangible area of the resources infrastructure. The AITL Model will be presented and session participants will have an opportunity to review and reflect on its impact and utility. Ultimately, the AITL Model is one that could have significant policy and practice implications. At the very least, it might help shape ICT content in educational leadership development programs through curricular and pedagogical updates.

Keywords: education leadership, information and communications technology, ICT, leadership capacity building, leadership development

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Authors: Merrick Lopez, Aashish Abraham, Melissa Egge, Marissa Hood, Jui Shah

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A 3 year old male with unknown medical history presented initially with encephalopathy, intubated for respiratory failure, and admitted to the pediatric intensive care unit (PICU) with refractory shock. During resuscitation in the emergency department, he was found to be in severe metabolic acidosis with a pH of 7.03 and escalated on vasopressor drips for hypotension. His initial sodium was 174. He was noted to have burn injuries to his scalp, forehead, right axilla, bilateral arm creases and lower legs. He had rhabdomyolysis (initial creatinine kinase 5,430 U/L with peak levels of 62,340 normal <335 U/L), cardiac injury (initial troponin 88 ng/L with peak at 145 ng/L, normal <15ng/L), hypernatremia (peak 174, normal 140), hypocalcemia, liver injury, acute kidney injury, and neuronal loss on magnetic resonance imaging (MRI). Soft restraints and a shock collar were found in the home. He was critically ill for 8 days, but was gradually weaned off drips, extubated, and started on feeds. Discussion Electrical injury, specifically lightning injury is an uncommon but devastating cause of injury in pediatric patients. This patient with suspected abusive use of a dog shock collar presented similar to a lightning strike. Common entrance points include the hands and head, similar to our patient with linear wounds on his forehead. When current enters, it passes through tissues with the least resistance. Nerves, blood vessels, and muscles, have high fluid and electrolyte content and are commonly affected. Exit points are extremities: our child who had circumferential burns around his arm creases and ankles. Linear burns preferentially follow areas of high sweat concentration, and are thought to be due to vaporization of water on the skin’s surface. The most common cause of death from a lightning strike is due to cardiopulmonary arrest. The massive depolarization of the myocardium can result in arrhythmias and myocardial necrosis. The patient presented in cardiogenic shock with evident cardiac damage. Electricity going through vessels can lead to vaporization of intravascular water. This can explain his severe hypernatremia. He also sustained other internal organ injuries (adrenal glands, pancreas, liver, and kidney). Electrical discharge also leads to direct skeletal muscle injury in addition to prolonged muscular spasm. Rhabdomyolysis, the acute damage of muscle, leads to release of potentially toxic components into the circulation which could lead to acute renal failure. The patient had severe rhabdomyolysis and renal injury. Early hypocalcemia has been consistently demonstrated in patients with rhabdomyolysis. This was present in the patient and led to increased vasopressor needs. Central nervous system injuries are also common which can include encephalopathy, hypoxic injury, and cerebral infarction. The patient had evidence of brain injury as seen on MRI. Conclusion Electrical injuries due to lightning strikes and abusive use of a dog shock collar are rare, but can both present in similar ways with respiratory failure, shock, hypernatremia, rhabdomyolysis, brain injury, and multiorgan damage. Although rare, it is essential for early identification and prompt management for acute and chronic complications in these children.

Keywords: cardiogenic shock, dog shock collar, lightning strike, rhabdomyolysis

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Authors: F. Nasser-Abu Alhija

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In many countries, much efforts and resources are devoted to empowering and integrating minorities within the mainstream population. Major ventures in this route are crafted in higher education institutions where different outreach programs and methods such as lenient entry requirements, monitory incentives, learning skills workshops, tutoring and mentoring, are utilized. Although there is some information regarding these programs, their effectiveness still needs to be thoroughly examined. The Ethiopian community In Israel is one of the minority groups that has been targeted by sponsoring foundations and higher education institutions with the aim to ease the access, persistence and success of its young people in higher education and later in the job market. The evaluation study we propose to present focuses on the implementation of a program designed for this purpose. This program offers relevant candidates for study at a prestigious university a variety of generous incentives that include tuitions, livening allowance, tutoring, mentoring, skills and empowerment workshops and cultural meetings. Ten students were selected for the program and they started their studies in different subject areas before three and half years. A longitudinal evaluation has been conducted since the implementation of the program. Data were collected from different sources: participating students, program coordinator, mentors, tutors, program documents and university records. Questionnaires and interviews were used for collecting data on the different components of the program and on participants' perception of their effectiveness. Participants indicate that the lenient entry requirements and the monitory incentives are critical for starting their studies. During the first year, skills and empowering workshops, torturing and mentoring were evaluated as very important for persistence and success in studies. Tutoring was perceived as very important also at the second year but less importance is attributed to mentoring. Mixed results regarding integration in the Israeli culture emerged. The results are discussed with reference to findings from different settings around the world.

Keywords: access to higher education, minority groups, monitory incentives, torturing, mentoring

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Authors: Wellemans Isabelle, Remmelink Myriam, Foucart Annick, Rusu Stefan, Compère Christophe

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Primary pulmonary meningioma (PPM) is a very rare tumor, and its occurrence has been reported only sporadically. Multiple PPMs are even more exceptional, and herein, we report, to the best of our knowledge, the fourth case, focusing on the clinicopathological features of the tumor. Moreover, the possible relationship between the use of progesterone–only contraceptives and the development of these neoplasms will be discussed. Case Report: We report a case of a 51-year-old female presenting three solid pulmonary nodules, with the following localizations: right upper lobe, middle lobe, and left lower lobe, described as incidental findings on computed tomography (CT) during a pre-bariatric surgery check-up. The patient revealed no drinking or smoking history. The physical exam was unremarkable except for the obesity. The lesions ranged in size between 6 and 24 mm and presented as solid nodules with lobulated contours. The largest lesion situated in the middle lobe had mild fluorodeoxyglucose (FDG) uptake on F-18 FDG positron emission tomography (PET)/CT, highly suggestive of primary lung neoplasm. For pathological assessment, video-assisted thoracoscopic middle lobectomy and wedge resection of the right upper nodule was performed. Histological examination revealed relatively well-circumscribed solid proliferation of bland meningothelial cells growing in whorls and lobular nests, presenting intranuclear pseudo-inclusions and psammoma bodies. No signs of anaplasia were observed. The meningothelial cells expressed diffusely Vimentin, focally Progesterone receptors and were negative for epithelial (cytokeratin (CK) AE1/AE3, CK7, CK20, Epithelial Membrane Antigen (EMA)), neuroendocrine markers (Synaptophysin, Chromogranin, CD56) and Estrogenic receptors. The proliferation labelling index Ki-67 was low (<5%). Metastatic meningioma was ruled out by brain and spine magnetic resonance imaging (MRI) scans. The third lesion localized in the left lower lobe was followed-up and resected three years later because of its slow but significant growth (14 mm to 16 mm), alongside two new infra centimetric lesions. Those three lesions showed a morphological and immunohistochemical profile similar to previously resected lesions. The patient was disease-free one year post-last surgery. Discussion: Although PPMs are mostly benign and slow-growing tumors with an excellent prognosis, they do not present specific radiological characteristics, and it is difficult to differentiate it from other lung tumors, histopathologic examination being essential. Aggressive behavior is associated with atypical or anaplastic features (WHO grades II–III) The etiology is still uncertain and different mechanisms have been proposed. A causal connection between sexual hormones and meningothelial proliferation has long been suspected and few studies examining progesterone only contraception and meningioma risk have all suggested an association. In line with this, our patient was treated with Levonorgestrel, a progesterone agonist, intra-uterine device (IUD). Conclusions: PPM, defined by the typical histological and immunohistochemical features of meningioma in the lungs and the absence of central nervous system lesions, is an extremely rare neoplasm, mainly solitary and associating, and indolent growth. Because of the unspecific radiologic findings, it should always be considered in the differential diagnosis of lung neoplasms. Regarding multiple PPM, only three cases are reported in the literature, and this is the first described in a woman treated by a progesterone-only IUD to the best of our knowledge.

Keywords: pulmonary meningioma, multiple meningioma, meningioma, pulmonary nodules

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Authors: Tomiwa, Akinyemi Clement

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Tropical regions experience diverse and complex precipitation patterns, posing significant challenges for accurate rainfall estimation and forecasting. This study addresses the problem of effectively classifying tropical rain types and refining the Z-R (Reflectivity-Rain Rate) relationship to enhance rainfall estimation accuracy. Through a combination of remote sensing, meteorological analysis, and machine learning, the research aims to develop an advanced classification framework capable of distinguishing between different types of tropical rain based on their unique characteristics. This involves utilizing high-resolution satellite imagery, radar data, and atmospheric parameters to categorize precipitation events into distinct classes, providing a comprehensive understanding of tropical rain systems. Additionally, the study seeks to improve the Z-R relationship, a crucial aspect of rainfall estimation. One year of rainfall data was analyzed using a Micro Rain Radar (MRR) located at The Federal University of Technology Akure, Nigeria, measuring rainfall parameters from ground level to a height of 4.8 km with a vertical resolution of 0.16 km. Rain rates were classified into low (stratiform) and high (convective) based on various microstructural attributes such as rain rates, liquid water content, Drop Size Distribution (DSD), average fall speed of the drops, and radar reflectivity. By integrating diverse datasets and employing advanced statistical techniques, the study aims to enhance the precision of Z-R models, offering a more reliable means of estimating rainfall rates from radar reflectivity data. This refined Z-R relationship holds significant potential for improving our understanding of tropical rain systems and enhancing forecasting accuracy in regions prone to heavy precipitation.

Keywords: remote sensing, precipitation, drop size distribution, micro rain radar

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Authors: Taikchan Lildar, Ayesha Samad, Suraj Sookhu

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Atrial fibrillation with rapid ventricular response results in the loss of atrial kick and shortened ventricular filling time, which often leads to decompensated heart failure. Pharmacologic rhythm control is the treatment of choice, and patients frequently benefit from the restoration of sinus rhythm. When pharmacologic treatment is unsuccessful or a patient declines hemodynamically, direct cardioversion is the treatment of choice. Torsades de pointes or “twisting of the points'' in French, is a rare but under-appreciated risk of cardioversion therapy and accounts for a significant number of sudden cardiac death each year. A 61-year-old female with no significant past medical history presented to the Emergency Department with worsening dyspnea. An electrocardiogram showed atrial fibrillation with rapid ventricular response, and a chest X-ray was significant for bilateral pulmonary vascular congestion. Full-dose anticoagulation and diuresis were initiated with moderate improvement in symptoms. A transthoracic echocardiogram revealed biventricular systolic dysfunction with a left ventricular ejection fraction of 30%. After consultation with an electrophysiologist, the consensus was to proceed with the restoration of sinus rhythm, which would likely improve the patient’s heart failure symptoms and possibly the ejection fraction. A transesophageal echocardiogram was negative for left atrial appendage thrombus; the patient was treated with a loading dose of amiodarone and underwent successful direct current cardioversion with 200 Joules. The patient was placed on telemetry monitoring for 24 hours and was noted to have frequent premature ventricular contractions with subsequent degeneration to torsades de pointes. The patient was found unresponsive and pulseless; cardiopulmonary resuscitation was initiated with cardioversion, and return of spontaneous circulation was achieved after four minutes to normal sinus rhythm. Post-cardiac arrest electrocardiogram showed sinus bradycardia with heart-rate corrected QT interval of 592 milliseconds. The patient continued to have frequent premature ventricular contractions and required two additional cardioversions to achieve a return of spontaneous circulation with intravenous magnesium and lidocaine. An automatic implantable cardioverter-defibrillator was subsequently implanted for secondary prevention of sudden cardiac death. The backup pacing rate of the automatic implantable cardioverter-defibrillator was set higher than usual in an attempt to prevent premature ventricular contractions-induced torsades de pointes. The patient did not have any further ventricular arrhythmias after implantation of the automatic implantable cardioverter-defibrillator. Overdrive pacing is a method utilized to treat premature ventricular contractions-induced torsades de pointes by preventing a patient’s susceptibility to R on T-wave-induced ventricular arrhythmias. Pacing at a rate of 90 beats per minute succeeded in controlling the arrhythmia without the need for traumatic cardiac defibrillation. In our patient, conversion of atrial fibrillation with rapid ventricular response to normal sinus rhythm resulted in a slower heart rate and an increased probability of premature ventricular contraction occurring on the T-wave and ensuing ventricular arrhythmia. This case highlights direct current cardioversion for atrial fibrillation with rapid ventricular response resulting in persistent ventricular arrhythmia requiring an automatic implantable cardioverter-defibrillator placement with overdrive pacing to prevent a recurrence.

Keywords: refractory atrial fibrillation, atrial fibrillation, overdrive pacing, torsades de pointes

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Authors: Chinwe Susan Oguejiofor, Daniel Osamwonyi Iyioha

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Over the last two decades, Nigeria has witnessed an upsurge in graduate unemployment occasioned by the lack of industries and proliferation of tertiary institutions churning out thousands of graduates every year to compete for the few available job space. The astronomical rise in the unemployment rate amongst Nigerian graduates however, is principally assumed to be the defective curricula of the universities and other tertiary institutions whose focus is on training for white-collar jobs. Although graduate unemployment has become a global scourge, its adverse economic impact is believed to be more in developing economies like Nigeria with a huge young population within the working age who cannot seem to find gainful employment to make out a respectable livelihood. Thus, higher institutions especially Universities found itself under pressure and intense competition to produce graduates who can think outside the box and create jobs; hence there was the need to focus on instilling hands-on practical job skills into their students that will make them job creators rather than job seekers on graduation. In the same vein stakeholders in education have continued to lend their voices to the philosophy that the undergraduate curricula should be completely overhauled to accomodate the development of hand-on practical skills and innovative capacity relevant to creating solutions to societal problems. In a bid to correct this anomaly, the Federal Government of Nigeria in conjunction with the Ministry of Commerce, Industry and Investment inaugurated a programme tagged “University Entrepreneurship Development Programme” (UNEDEP) whose objective was basically to promote self-employment among the youth right from the institutions of higher learning. But the question is whether the objectives of the programme have actually been achieved. Despite the inclusion in Nigerian educational curriculum close to two decades now,, one wonder if the essence has been aborted. Thus, the paper focused on the concept of entrepreneurship education, objectives of entrepreneurship education, Graduates unemployment, rethinking entrepreneurship education programme in tertiary institution for employment generation , role of entrepreneurship in job creation, challenges of entrepreneurship education in tertiary institution in Nigeria, conclusion and recommendations were drawn accordingly.

Keywords: rethinking, entrepreneurship education, remedy, unemployment, job creation

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Authors: Annika Stechemesser, Rachel Pounds, Emma Lucas, Chris Dawson, Julia Lipecki, Pavle Vrljicak, Jan Brosens, Sean Kehoe, Jason Yap, Lawrence Young, Sascha Ott

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Advances in technology make it now possible to retrieve the genetic information of thousands of single cancerous cells. One of the key challenges in single cell analysis of cancerous tissue is to determine the number of different cell types and their characteristic genes within the sample to better understand the tumors and their reaction to different treatments. For this analysis to be possible, it is crucial to filter out background noise as it can severely blur the downstream analysis and give misleading results. In-depth analysis of the state-of-the-art filtering methods for single cell data showed that they do, in some cases, not separate noisy and normal cells sufficiently. We introduced an algorithm that filters and clusters single cell data simultaneously without relying on certain genes or thresholds chosen by eye. It detects communities in a Shared Nearest Neighbor similarity network, which captures the similarities and dissimilarities of the cells by optimizing the modularity and then identifies and removes vertices with a weak clustering belonging. This strategy is based on the fact that noisy data instances are very likely to be similar to true cell types but do not match any of these wells. Once the clustering is complete, we apply a set of evaluation metrics on the cluster level and accept or reject clusters based on the outcome. The performance of our algorithm was tested on three datasets and led to convincing results. We were able to replicate the results on a Peripheral Blood Mononuclear Cells dataset. Furthermore, we applied the algorithm to two samples of ovarian cancer from the same patient before and after chemotherapy. Comparing the standard approach to our algorithm, we found a hidden cell type in the ovarian postchemotherapy data with interesting marker genes that are potentially relevant for medical research.

Keywords: cancer research, graph theory, machine learning, single cell analysis

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Authors: Lisa Fox, Jill Aylott

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There is a global need to identify ways to engage doctors in non-clinical matters such as medical leadership, service improvement and health system transformation. Using the core principles of Realistic Evaluation (RE), this study examined what works, for doctors of different grades, specialities and experience in an acute NHS Hospital Trust in the UK. Realistic Evaluation is an alternative to more traditional cause and effect evaluation models and seeks to understand the interdependencies of Context, Mechanism and Outcome proposing that Context (C) + Mechanism (M) = Outcome (O). In this study, the context, mechanism and outcome were examined from within individual medical leaders to determine what enables levels of medical engagement in a specific improvement project to reduce hospital inpatient mortality. Five qualitative case studies were undertaken with consultants who had regularly completed mortality reviews over a six month period. The case studies involved semi-structured interviews to test the theory behind the drivers for medical engagement. The interviews were analysed using a theory-driven thematic analysis to identify CMO configurations to explain what works, for whom and in what circumstances. The findings showed that consultants with a longer length of service became more engaged if there were opportunities to be involved in the beginning of an improvement project, with more opportunities to affect the design. Those that are new to a consultant role were more engaged if they felt able to apply any learning directly into their own settings or if they could use it as an opportunity to understand more about the organisation they are working in. This study concludes that RE is a useful methodology for better understanding the complexities of motivation and consultant engagement in a trust wide service improvement project. The study showed that there should be differentiated and bespoke training programmes to maximise each individual doctor’s propensity for medical engagement. The RE identified that there are different ways to ensure that doctors have the right skills to feel confident in service improvement projects.

Keywords: realistic evaluation, medical leadership, medical engagement, patient safety, service improvement

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Authors: Vishal Raj, Noorhan Abbas

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Ambiguity in NLP (Natural language processing) refers to the ability of a word, phrase, sentence, or text to have multiple meanings. This results in various kinds of ambiguities such as lexical, syntactic, semantic, anaphoric and referential am-biguities. This study is focused mainly on solving the issue of Lexical ambiguity. Word Sense Disambiguation (WSD) is an NLP technique that aims to resolve lexical ambiguity by determining the correct meaning of a word within a given context. Most WSD solutions rely on words for training and testing, but we have used lemma and Part of Speech (POS) tokens of words for training and testing. Lemma adds generality and POS adds properties of word into token. We have designed a novel method to create an affinity matrix to calculate the affinity be-tween any pair of lemma_POS (a token where lemma and POS of word are joined by underscore) of given training set. Additionally, we have devised an al-gorithm to create the sense clusters of tokens using affinity matrix under hierar-chy of POS of lemma. Furthermore, three different mechanisms to predict the sense of target word using the affinity/similarity value are devised. Each contex-tual token contributes to the sense of target word with some value and whichever sense gets higher value becomes the sense of target word. So, contextual tokens play a key role in creating sense clusters and predicting the sense of target word, hence, the model is named Contextual SenSe Model (CSM). CSM exhibits a noteworthy simplicity and explication lucidity in contrast to contemporary deep learning models characterized by intricacy, time-intensive processes, and chal-lenging explication. CSM is trained on SemCor training data and evaluated on SemEval test dataset. The results indicate that despite the naivety of the method, it achieves promising results when compared to the Most Frequent Sense (MFS) model.

Keywords: word sense disambiguation (wsd), contextual sense model (csm), most frequent sense (mfs), part of speech (pos), natural language processing (nlp), oov (out of vocabulary), lemma_pos (a token where lemma and pos of word are joined by underscore), information retrieval (ir), machine translation (mt)

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Authors: Xuan Li

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The English language occupies a crucial position in the Chinese educational system and is officially introduced in the school curriculum from the third year of primary school onward. However, it is worth noting that along with the movement to remove primary-oriented education from preschools, the teaching of English is banned in preschools. Considering the worldwide trend of learning English at a young age, whether this ban can be implemented successfully is doubtful. With an initial focus on the interaction of language-in-education planning and policy (LEPP) at the macro level and actual practice at the micro level, this research selected three private preschools and two public preschools to explore what is taking place in terms of English education. All data collected is qualitative and is gained from documentary analysis, school observation, interviews, and focus groups. The findings show that: (1) although the English ban in preschool education aims to regulate all types of preschools and all adult Chinese participants are aware of this ban, there are very different scenarios according to type of preschool, such that no English classes are found in public schools while private preschools commonly provide some kind of English education; (2) even public schools do not have an English-free environment and parents’ demand for English education is high; (3) there is an obvious top-down hierarchy in both public and private schools, in which administrators make the decisions while others have little power to influence the school curriculum; (4) there is a clear gap in the perception of English teaching between children and adults, in which adults prefer foreign English teachers and think English teaching is just playing, while children do not have a clear preference regarding teachers and do not think English class is just for fun; (5) without macro support, there are many challenges involved in preschool English education, including the shortage of qualified teachers and teaching resources, ineffective personnel management and few opportunities for speaking English in daily life. Hopefully, this research will not only highlight the interaction of LEPP at different levels and the importance of individual agency but also raise the awareness of how to provide qualified and equal education for all children.

Keywords: individual agency, language-in-education planning and policy, micro context, preschool English education

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Authors: Afshin Gharib

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Often, instructors prefer to bring into class a guest lecturer who can provide an “experiential” perspective on a particular topic. The assumption is that the personal experience brought into the classroom makes the material resonate more with students and that students would have a preference for material being taught from an experiential perspective. The question we asked in the present study was whether a guest lecture from an “experiential” expert with a disability (e.g. a guest suffering from cone-rod dystrophy lecturing on vision, or a dyslexic lecturing on the psychology of reading) would be more effective than the course instructor in capturing students attention and conveying information in an Introduction to Psychology class. Students in two sections of Introduction to Psychology (N = 25 in each section) listened to guest lecturers with disabilities lecturing on a topic related to their disability, one in the area of Sensation and Perception (the guest lecturer is vision impaired) and one in the area of Language Development (the guest lecturer is dyslexic). The Guest lecturers lectured on the same topic in both sections, however, each lecturer used their own experiences to highlight the topics they cover in one section but not the other (counterbalanced between sections), providing students in one section with experiential testimony. Following each of the 4 lectures (two experiential, two non-experiential) students rated the lecture on several dimensions including overall quality, level of engagement, and performance. In addition, students in both sections were tested on the same test items from the lecture material to ascertain degree of learning, and given identical “pop” quizzes two weeks after the exam to measure retention. It was hypothesized that students would find the experiential lectures from lecturers talking about their disabilities more engaging, learn more from them, and retain the material for longer. We found that students in fact preferred the course instructor to the guests, regardless of whether the guests included a discussion of their own disability in their lectures. Performance on the exam questions and the pop quiz items were not different between “experiential” and “non-experiential” lectures, suggesting that guest lecturers who discuss their own disabilities in lecture are not more effective in conveying material and students are not more likely to retain material delivered by “experiential” guests. In future research we hope to explore the reasons for students preference for their regular instructor over guest lecturers.

Keywords: guest lecturer, student perception, retention, experiential

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Authors: N. N. Mosola, S. J. Molete, L. S. Masoebe, M. Letsae

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Hand gesture recognition is a technique used to locate, detect, and recognize a hand gesture. Detection and recognition are concepts of Artificial Intelligence (AI). AI concepts are applicable in Human Computer Interaction (HCI), Expert systems (ES), etc. Hand gesture recognition can be used in sign language interpretation. Sign language is a visual communication tool. This tool is used mostly by deaf societies and those with speech disorder. Communication barriers exist when societies with speech disorder interact with others. This research aims to build a hand recognition system for Lesotho’s Sesotho and English language interpretation. The system will help to bridge the communication problems encountered by the mentioned societies. The system has various processing modules. The modules consist of a hand detection engine, image processing engine, feature extraction, and sign recognition. Detection is a process of identifying an object. The proposed system uses Canny pruning Haar and Haarcascade detection algorithms. Canny pruning implements the Canny edge detection. This is an optimal image processing algorithm. It is used to detect edges of an object. The system employs a skin detection algorithm. The skin detection performs background subtraction, computes the convex hull, and the centroid to assist in the detection process. Recognition is a process of gesture classification. Template matching classifies each hand gesture in real-time. The system was tested using various experiments. The results obtained show that time, distance, and light are factors that affect the rate of detection and ultimately recognition. Detection rate is directly proportional to the distance of the hand from the camera. Different lighting conditions were considered. The more the light intensity, the faster the detection rate. Based on the results obtained from this research, the applied methodologies are efficient and provide a plausible solution towards a light-weight, inexpensive system which can be used for sign language interpretation.

Keywords: canny pruning, hand recognition, machine learning, skin tracking

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Authors: Ahn Christine Myunghee, Sim Wonjin, Cho Kristina, Ahn Mira, Hong Yeju, Kwok Jihae, Lim Sooyeon, Park Hansol

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With a sharp increase in the prevalence rate for mental health issues in Korea, there is a need for specific and effective intervention strategies in counseling and psychotherapy for use with Korean clients. With the cultural emphasis on restraining emotional expression and not disclosing personal and familial problems to outsiders, clients often find it difficult to discuss their emotional issues even to therapists. Exploring a client’s internal psychological processes bypassing this culture-specific mode of therapeutic communication often becomes a challenge in the therapeutic setting. Given this socio-cultural context, the purpose of the current study was to investigate the effectiveness of using dream work to individuals in Korea. The current study conducted one 60-90 minute dream session and analyzed the dream content of 39 Korean young adults to evaluate the effectiveness of the Hill dream model in accessing the intra-psychic materials, determining essential emotional themes, and learning how the individuals interpreted the contents of their dreams. The transcribed data, which included a total of 39 sessions from 39 volunteer university students, were analyzed by the Consensus Qualitative Research (CQR) approach in terms of domains and core ideas. Self-report measures on Dream Salience, Gains from Dream Interpretations and the Session Evaluation Scale were administered before and after each of their dream sessions. The results indicated that dream work appears to be an effective way to understand unconscious motivations, thoughts, and feelings related to a person’s sense of self, and also how these people relate to other people. Current findings need to be replicated with clients referred for counseling and psychotherapy to determine if the dream work is an appropriate and useful intervention in counseling settings. Limitations of the current study and suggestions for future follow-ups are included in the discussion.

Keywords: dream work, dream interpretation, Korean, young adults, CQR

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Authors: A. Calabrese, V. F. Uricchio, D. di Noia, S. Favale, C. Caiati, G. P. Maggi, G. Donvito, D. Diacono, S. Tangaro, A. Italiano, E. Riezzo, M. Zippitelli, M. Toriello, E. Celiberti, D. Festa, A. Colaianni

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Climate change has a severe impact on human health. There is a vast literature demonstrating temperature increase is causally related to cardiovascular problem and represents a high risk for human health, but there are not study that improve a solution. In this work, it is studied how the clime influenced the human parameter through the analysis of climatic conditions in an area of the Apulia Region: Capurso Municipality. At the same time, medical personnel involved identified a set of variables useful to define an index describing health condition. These scientific studies are the base of an innovative alert system, IPPOCRATE, whose aim is to asses climate risk and share information to population at risk to support prevention and mitigation actions. IPPOCRATE is an e-health system, it is designed to provide technological support to analysis of health risk related to climate and provide tools for prevention and management of critical events. It is the first integrated system of prevention of human risk caused by climate change. IPPOCRATE calculates risk weighting meteorological data with the vulnerability of monitored subjects and uses mobile and cloud technologies to acquire and share information on different data channels. It is composed of four components: Multichannel Hub. Multichannel Hub is the ICT infrastructure used to feed IPPOCRATE cloud with a different type of data coming from remote monitoring devices, or imported from meteorological databases. Such data are ingested, transformed and elaborated in order to be dispatched towards mobile app and VoIP phone systems. IPPOCRATE Multichannel Hub uses open communication protocols to create a set of APIs useful to interface IPPOCRATE with 3rd party applications. Internally, it uses non-relational paradigm to create flexible and highly scalable database. WeHeart and Smart Application The wearable device WeHeart is equipped with sensors designed to measure following biometric variables: heart rate, systolic blood pressure and diastolic blood pressure, blood oxygen saturation, body temperature and blood glucose for diabetic subjects. WeHeart is designed to be easy of use and non-invasive. For data acquisition, users need only to wear it and connect it to Smart Application by Bluetooth protocol. Easy Box was designed to take advantage from new technologies related to e-health care. EasyBox allows user to fully exploit all IPPOCRATE features. Its name, Easy Box, reveals its purpose of container for various devices that may be included depending on user needs. Territorial Registry is the IPPOCRATE web module reserved to medical personnel for monitoring, research and analysis activities. Territorial Registry allows to access to all information gathered by IPPOCRATE using GIS system in order to execute spatial analysis combining geographical data (climatological information and monitored data) with information regarding the clinical history of users and their personal details. Territorial Registry was designed for different type of users: control rooms managed by wide area health facilities, single health care center or single doctor. Territorial registry manages such hierarchy diversifying the access to system functionalities. IPPOCRATE is the first e-Health system focused on climate risk prevention.

Keywords: climate change, health risk, new technological system

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Authors: Elizabeth Howarth, Dawn Green, Sean Connolly, Geena Vabulas, Sara Smolley

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Through the EU Horizon 2020 Nuvoic Project, the project team recruited 70 individuals in the UK and Ireland to test the Voiceitt speech recognition app and provide user feedback to developers. The app is designed for people with dysarthric speech, to support communication with unfamiliar people and access to speech-driven technologies such as smart home equipment and smart assistants. Participants with atypical speech, due to a range of conditions such as cerebral palsy, acquired brain injury, Down syndrome, stroke and hearing impairment, were recruited, primarily through organisations supporting disabled people. Most had physical or learning disabilities in addition to dysarthric speech. The project team worked with individuals, their families and local support teams, to provide access to the app, including through additional assistive technologies where needed. Testing was user-led, with participants asked to identify and test use cases most relevant to their daily lives over a period of three months or more. Ongoing technical support and training were provided remotely and in-person throughout the testing period. Structured interviews were used to collect feedback on users' experiences, with delivery adapted to individuals' needs and preferences. Informal feedback was collected through ongoing contact between participants, their families and support teams and the project team. Focus groups were held to collect feedback on specific design proposals. User feedback shared with developers has led to improvements to the user interface and functionality, including faster voice training, simplified navigation, the introduction of gamification elements and of switch access as an alternative to touchscreen access, with other feature requests from users still in development. This work offers a case-study in successful and inclusive co-design with the disabled community.

Keywords: co-design, assistive technology, dysarthria, inclusive speech recognition

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Authors: Silvia Benvenuti, Alessandra Cardinali

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In recent years, for instance, in relation to the Covid 19 pandemic and the evidence of climate change, it is becoming quite clear that the development of a young kid into an adult citizen requires a solid scientific background. Citizens are required to exert logical thinking and know the methods of science in order to adapt, understand, and develop as persons. Mathematics sits at the core of these required skills: learning the axiomatic method is fundamental to understand how hard sciences work and helps in consolidating logical thinking, which will be useful for the entire life of a student. At the same time, research shows that the axiomatic study of geometry is a problematic topic for students, even for those with interest in mathematics. With this in mind, the main goals of the research work we will describe are: (1) to show whether non-Euclidean geometries can be a tool to allow students to consolidate the knowledge of Euclidean geometries by developing it in a critical way; (2) to promote the understanding of the modern axiomatic method in geometry; (3) to give students a new perspective on mathematics so that they can see it as a creative activity and a widely discussed topic with a historical background. One of the main issues related to the state-of-the-art in this topic is the shortage of experimental studies with students. For this reason, our aim is to show further experimental evidence of the potential benefits of teaching non-Euclidean geometries at high school, based on data collected from a study started in 2005 in the frame of the Italian National Piano Lauree Scientifiche, continued by a teacher training organized in September 2018, perfected in a pilot study that involved 77 high school students during the school years 2018-2019 and 2019-2020. and finally implemented through an experimental study conducted in 2020-21 with 87 high school students. Our study shows that there is potential for further research to challenge current conceptions of the school mathematics curriculum and of the capabilities of high school mathematics students.

Keywords: Non-Euclidean geometries, beliefs about mathematics, questionnaires, modern axiomatic method

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Authors: Mythri G., Manjunath ML, Girish Babu M., Shireen Swaliha Quadri

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Background: The increase in diabetes among the elderly is of concern because in addition to the wide range of traditional diabetes complications, evidence has been growing that diabetes is associated with increased risk of cognitive decline. Aims and Objectives: To find out if there is any association between blood sugar levels and short-term and working memory status in patients of type 2 diabetes. Materials and Methods: The study was carried out in 200 individuals aged between 40-65 years consisting of 100 diagnosed cases of Type 2 Diabetes Mellitus and 100 non-diabetics from OPD of Mc Gann Hospital, Shivamogga. Rye’s Auditory Verbal Learning Test, Verbal Fluency Test and Visual Reproduction Test, Working Digit Span Test and Validation Span Test were used to assess short-term and working memory. Fasting and Post Prandial blood sugar levels were estimated. Statistical analysis was done using SPSS 21. Results: Memory test scores of type 2 diabetics were significantly reduced (p < 0.001) when compared to the memory scores of age and gender matched non-diabetics. Fasting blood sugar levels were found to have a negative correlation with memory scores for all 5 tests: AVLT (r=-0.837), VFT (r=-0.888), VRT(r=-0.787), WDST (r=-0.795) and VST (r=-0.943). Post- Prandial blood sugar levels were found to have a negative correlation with memory scores for all 5 tests: AVLT (r=-0.922), VFT (r=-0.848), VRT(r=-0.707),WDST (r=-0.729) and VST (r=-0.880) Memory scores in all 5 tests were found to be negatively correlated with the FBS and PPBS levels in diabetic patients (p < 0.001). Conclusion: The decreased memory status in diabetic patients may be due to many factors like hyperglycemia, vascular disease, insulin resistance, amyloid deposition and also some of the factor combine to produce additive effects like, type of diabetes, co-morbidities, age of onset, duration of the disease and type of therapy. These observed effects of blood sugar levels of diabetics on memory status are of potential clinical importance because even mild cognitive impairment could interfere with todays’ activities.

Keywords: diabetes, cognition, diabetes, HRV, respiratory medicine

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Authors: Mahdi Allaoua Seklab, Süleyman BaşTürk

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In the quest to enhance coastal environmental health, this study introduces a fully autonomous beach cleaning machine, a breakthrough in leveraging green energy and advanced artificial intelligence for ecological preservation. Designed to operate independently, the machine is propelled by a solar-powered system, underscoring a commitment to sustainability and the use of renewable energy in autonomous robotics. The vehicle's autonomous navigation is achieved through a sophisticated integration of LIDAR and a camera system, utilizing an SSD MobileNet V2 object detection model for accurate and real-time trash identification. The SSD framework, renowned for its efficiency in detecting objects in various scenarios, is coupled with the lightweight and precise highly MobileNet V2 architecture, making it particularly suited for the computational constraints of on-board processing in mobile robotics. Training of the SSD MobileNet V2 model was conducted on Google Colab, harnessing cloud-based GPU resources to facilitate a rapid and cost-effective learning process. The model was refined with an extensive dataset of annotated beach debris, optimizing the parameters using the Adam optimizer and a cross-entropy loss function to achieve high-precision trash detection. This capability allows the machine to intelligently categorize and target waste, leading to more effective cleaning operations. This paper details the design and functionality of the beach cleaning machine, emphasizing its autonomous operational capabilities and the novel application of AI in environmental robotics. The results showcase the potential of such technology to fill existing gaps in beach maintenance, offering a scalable and eco-friendly solution to the growing problem of coastal pollution. The deployment of this machine represents a significant advancement in the field, setting a new standard for the integration of autonomous systems in the service of environmental stewardship.

Keywords: autonomous beach cleaning machine, renewable energy systems, coastal management, environmental robotics

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Authors: Jerome Dalphinis, Vishal Patel

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The Bailiwick of Jersey is an island British crown dependency situated off the coast of France. Jersey General Hospital’s emergency department sees approximately 40,000 patients a year. It’s outside the NHS, with secondary care being free at the point of care. Sedation is a continuum which extends from a normal conscious level to being fully unresponsive. Procedural sedation produces a minimally depressed level of consciousness in which the patient retains the ability to maintain an airway, and they respond appropriately to physical stimulation. The goals of it are to improve patient comfort and tolerance of the procedure and alleviate associated anxiety. Indications can be stratified by acuity, emergency (cardioversion for life-threatening dysrhythmia), and urgency (joint reduction). In the emergency department, this is most often achieved using a combination of opioids and benzodiazepines. Some departments also use ketamine to produce dissociative sedation, a cataleptic state of profound analgesia and amnesia. The response to pharmacological agents is highly individual, and the drugs used occasionally have unpredictable pharmacokinetics and pharmacodynamics, which can always result in progression between levels of sedation irrespective of the intention. Therefore, practitioners must be able to ‘rescue’ patients from deeper sedation. These practitioners need to be senior clinicians with advanced airway skills (AAS) training. It can lead to adverse effects such as dangerous hypoxia and unintended loss of consciousness if incorrectly undertaken; studies by the National Confidential Enquiry into Patient Outcome and Death (NCEPOD) have reported avoidable deaths. The Royal College of Emergency Medicine, UK (RCEM) released an updated ‘Safe Sedation of Adults in the Emergency Department’ guidance in 2017 detailing a series of standards for staff competencies, and the required environment and equipment, which are required for each target sedation depth. The emergency department in Jersey undertook audit research in 2018 to assess their current practice. It showed gaps in clinical competency, the need for uniform care, and improved documentation. This spurred the development of a checklist incorporating the above RCEM standards, including contraindication for procedural sedation and difficult airway assessment. This was approved following discussion with the relevant heads of departments and the patient safety directorates. Following this, a second audit research was carried out in 2019 with 17 completed checklists (11 relocation of joints, 6 cardioversions). Data was obtained from looking at the controlled resuscitation drugs book containing documented use of ketamine, alfentanil, and fentanyl. TrakCare, which is the patient electronic record system, was then referenced to obtain further information. The results showed dramatic improvement compared to 2018, and they have been subdivided into six categories; pre-procedure assessment recording of significant medical history and ASA grade (2 fold increase), informed consent (100% documentation), pre-oxygenation (88%), staff (90% were AAS practitioners) and monitoring (92% use of non-invasive blood pressure, pulse oximetry, capnography, and cardiac rhythm monitoring) during procedure, and discharge instructions including the documented return of normal vitals and consciousness (82%). This procedural sedation checklist is a safe intervention that identifies pertinent information about the patient and provides a standardised checklist for the delivery of gold standard of care.

Keywords: advanced airway skills, checklist, procedural sedation, resuscitation

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Authors: Mehran Asadi, Afrand Agah

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In data mining, partitioning is used as a fundamental tool for classification. With the help of partitioning, we study the structure of data, which allows us to envision decision rules, which can be applied to classification trees. In this research, we used online social network dataset and all of its attributes (e.g., Node features, labels, etc.) to determine what constitutes an above average chance of being a divergent node. We used the R statistical computing language to conduct the analyses in this report. The data were found on the UC Irvine Machine Learning Repository. This research introduces the basic concepts of classification in online social networks. In this work, we utilize overfitting and describe different approaches for evaluation and performance comparison of different classification methods. In classification, the main objective is to categorize different items and assign them into different groups based on their properties and similarities. In data mining, recursive partitioning is being utilized to probe the structure of a data set, which allow us to envision decision rules and apply them to classify data into several groups. Estimating densities is hard, especially in high dimensions, with limited data. Of course, we do not know the densities, but we could estimate them using classical techniques. First, we calculated the correlation matrix of the dataset to see if any predictors are highly correlated with one another. By calculating the correlation coefficients for the predictor variables, we see that density is strongly correlated with transitivity. We initialized a data frame to easily compare the quality of the result classification methods and utilized decision trees (with k-fold cross validation to prune the tree). The method performed on this dataset is decision trees. Decision tree is a non-parametric classification method, which uses a set of rules to predict that each observation belongs to the most commonly occurring class label of the training data. Our method aggregates many decision trees to create an optimized model that is not susceptible to overfitting. When using a decision tree, however, it is important to use cross-validation to prune the tree in order to narrow it down to the most important variables.

Keywords: online social networks, data mining, social cloud computing, interaction and collaboration

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Authors: Michelangelo Sofo, Giuseppe Labianca

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In recent years, the scientific community's interest in the exploratory analysis of biomedical data has increased exponentially. Considering the field of research of nutritional biologists, the curative process, based on the analysis of clinical data, is a very delicate operation due to the fact that there are multiple solutions for the management of pathologies in the food sector (for example can recall intolerances and allergies, management of cholesterol metabolism, diabetic pathologies, arterial hypertension, up to obesity and breathing and sleep problems). In this regard, in this research work a system was created capable of evaluating various dietary regimes for specific patient pathologies. The system is founded on a mathematical-numerical model and has been created tailored for the real working needs of an expert in human nutrition using the human-centered design (ISO 9241-210), therefore it is in step with continuous scientific progress in the field and evolves through the experience of managed clinical cases (machine learning process). DietAdhoc® is a decision support system nutrition specialists for patients of both sexes (from 18 years of age) developed with an agile methodology. Its task consists in drawing up the biomedical and clinical profile of the specific patient by applying two algorithmic optimization approaches on nutritional data and a symbolic solution, obtained by transforming the relational database underlying the system into a deductive database. For all three solution approaches, particular emphasis has been given to the explainability of the suggested clinical decisions through flexible and customizable user interfaces. Furthermore, the system has multiple software modules based on time series and visual analytics techniques that allow to evaluate the complete picture of the situation and the evolution of the diet assigned for specific pathologies.

Keywords: medical decision support, physiological data extraction, data driven diagnosis, human centered AI, symbiotic AI paradigm

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Authors: Reyhan Tekin Sitrava

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Teachers should have robust and comprehensive content knowledge for effective mathematics teaching. It was explained that content knowledge includes knowing the facts, truths, and concepts; explaining the reasons behind these facts, truths and concepts, and making relationship between the concepts and other disciplines. By virtue of its importance, it will be significant to explore teachers and prospective teachers’ content knowledge related to variety of topics in mathematics. From this point of view, the purpose of this study was to investigate prospective mathematics teachers’ content knowledge. Particularly, it was aimed to reveal the prospective teachers’ knowledge regarding the definition of limit and derivate. To achieve the purpose and to get in-depth understanding, a qualitative case study method was used. The data was collected from 34 prospective mathematics teachers through a questionnaire containing 2 questions. The first question required the prospective teachers to define the limit and the second one required to define the derivative. The data was analyzed using content analysis method. Based on the analysis of the data, although half of the prospective teachers (50%) could write the definition of the limit, nine prospective teachers (26.5%) could not define limit. However, eight prospective teachers’ definition was regarded as partially correct. On the other hand, twenty-seven prospective teachers (79.5%) could define derivative, but seven of them (20.5%) defined it partially. According to the findings, most of the prospective teachers have robust content knowledge on limit and derivative. This result is important because definitions have a virtual role in learning and teaching of mathematics. More specifically, definition is starting point to understand the meaning of a concept. From this point of view, prospective teachers should know the definitions of the concepts to be able to teach them correctly to the students. In addition, they should have knowledge about the relationship between limit and derivative so that they can explain these concepts conceptually. Otherwise, students may memorize the rules of calculating the derivative and the limit. In conclusion, the present study showed that most of the prospective mathematics teachers had enough knowledge about the definition of derivative and limit. However, the rest of them should learn their definition conceptually. The examples of correct, partially correct, and incorrect definition of both concepts will be presented and discussed based on participants’ statements. This study has some implications for instructors. Instructors should be careful about whether students learn the definition of these concepts or not. In order to this, the instructors may give prospective teachers opportunities to discuss the definition of these concepts and the relationship between the concepts.

Keywords: content knowledge, derivative, limit, prospective mathematics teachers

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Authors: Marie Sams, Kate Barnett-Richards, Jacqui Speculand, Gemma Tombs

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Business education in the United Kingdom has seen a number of improvements over the years in moving from delivering traditional chalk and talk lectures to using digital technologies and inviting guest lectures from industry to deliver sessions for students. Engaging topical industry talks to enhance course delivery is generally seen as a positive aspect of enhancing curriculum, however it is acknowledged that perhaps there are better ways in which industry can contribute to the quality of business programmes. Additionally, there is a consensus amongst UK industry managers that a bigger involvement in designing and inputting into business curriculum will have a greater impact on the quality of business ready graduates. Funded by the Disruptive Media Learning Lab at Coventry University in the UK, a project (SOPI - Student Online Projects with Industry) was initiated to enable students to work in project teams to respond and engage with real problems and challenges faced by five managers in various industries including retail, events and manufacturing. Over a semester, approximately 200 students were given the opportunity to develop their management, facilitation, problem solving and reflective skills, whilst having some exposure to real challenges in industry with a focus on supply chain and project management. Face to face seminars were re-designed to enable students to work on live issues in a competitive environment, and were guided to consider the theoretical aspects of their module delivery to underpin the solutions that they were generating. Dialogue between student groups and managers took place using Google+ community; an online social media tool which enables private discussions to take place and can be accessed on mobile devices. Results of the project will be shared in how this development has added value to students experience and understanding of the two subject areas. Student reflections will be analysed and evaluated to assess how the project has contributed to their perception of how the theoretical nature of these two business subjects are applied in practical situations.

Keywords: business, education, industry, projects

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Authors: Jigg Pelayo, Ricardo Villar

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The Philippines is long considered as a valuable producer of high value crops globally. The country’s employment and economy have been dependent on agriculture, thus increasing its demand for the efficient agricultural mechanism. Remote sensing and geographic information technology have proven to effectively provide applications for precision agriculture through image-processing technique considering the development of the aerial scanning technology in the country. Accurate information concerning the spatial correlation within the field is very important for precision farming of high value crops, especially. The availability of height information and high spatial resolution images obtained from aerial scanning together with the development of new image analysis methods are offering relevant influence to precision agriculture techniques and applications. In this study, an algorithm was developed and implemented to detect and count high value crops simultaneously through adaptive scaling of support vector machine (SVM) algorithm subjected to object-oriented approach combining watershed transformation and local maxima filter in enhancing tree counting and detection. The methodology is compared to cutting-edge template matching algorithm procedures to demonstrate its effectiveness on a demanding tree is counting recognition and delineation problem. Since common data and image processing techniques are utilized, thus can be easily implemented in production processes to cover large agricultural areas. The algorithm is tested on high value crops like Palm, Mango and Coconut located in Misamis Oriental, Philippines - showing a good performance in particular for young adult and adult trees, significantly 90% above. The s inventories or database updating, allowing for the reduction of field work and manual interpretation tasks.

Keywords: high value crop, LiDAR, OBIA, precision agriculture

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Authors: Marden Silva, Danielle Guerra

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Some studies have indicated that pronunciation teaching hasn’t been paid enough attention by teachers regarding EFL contexts. In particular, segmental and suprasegmental features through genre-based approach may be an opportunity on how to integrate pronunciation into a more meaningful learning practice. Therefore, the aim of this project was to carry out a survey on some aspects related to English pronunciation that Brazilian students consider more difficult to learn, thus enabling the discussion of strategies that can facilitate the development of oral skills in English classes by integrating the teaching of phonetic-phonological aspects into the genre-based approach. Notions of intelligibility, fluency and accuracy were proposed by some authors as an ideal didactic sequence. According to their proposals, basic learners should be exposed to activities focused on the notion of intelligibility as well as intermediate students to the notion of fluency, and finally more advanced ones to accuracy practices. In order to test this hypothesis, data collection was conducted during three high school English classes at Federal Center for Technological Education of Minas Gerais (CEFET-MG), in Brazil, through questionnaires and didactic activities, which were recorded and transcribed for further analysis. The genre debate was chosen to facilitate the oral expression of the participants in a freer way, making them answering questions and giving their opinion about a previously selected topic. The findings indicated that basic students demonstrated more difficulty with aspects of English pronunciation than the others. Many of the intelligibility aspects analyzed had to be listened more than once for a better understanding. For intermediate students, the speeches recorded were considerably easier to understand, but nevertheless they found it more difficult to pronounce the words fluently, often interrupting their speech to think about what they were going to say and how they would talk. Lastly, more advanced learners seemed to express their ideas more fluently, but still subtle errors related to accuracy were perceptible in speech, thereby confirming the proposed hypothesis. It was also seen that using genre-based approach to promote oral communication in English classes might be a relevant method, considering the socio-communicative function inherent in the suggested approach.

Keywords: EFL, genre-based approach, oral skills, pronunciation

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Authors: Wen Zhen

Abstract:

Compared to content words, function words have been relatively overlooked by English learners especially articles. The article system, to a certain extent, becomes a resistance to know English better, driven by different elements. Three principal factors can be summarized in term of the nature of the articles when referring to the difficulty of the English article system. However, making the article system more complex are difficulties in the second acquisition process, for [-ART] learners have to create another category, causing even most non-native speakers at proficiency level to make errors. According to the sequences of acquisition of the English article, it is showed that the zero article is first acquired and in high inaccuracy. The zero article is often overused in the early stages of L2 acquisition. Although learners at the intermediate level move to underuse the zero article for they realize that the zero article does not cover any case, overproduction of the zero article even occurs among advanced L2 learners. The aim of the study is to investigate noun-phrase factors which give rise to incorrect usage or overuse of the zero article, thus providing suggestions for L2 English acquisition. Moreover, it enables teachers to carry out effective instruction that activate conscious learning of students. The research question will be answered through a corpus-based, data- driven approach to analyze the noun-phrase elements from the semantic context and countability of noun-phrases. Based on the analysis of the International Thurber Thesis corpus, the results show that: (1) Although context of [-definite,-specific] favored the zero article, both[-definite,+specific] and [+definite,-specific] showed less influence. When we reflect on the frequency order of the zero article , prototypicality plays a vital role in it .(2)EFL learners in this study have trouble classifying abstract nouns as countable. We can find that it will bring about overuse of the zero article when learners can not make clear judgements on countability altered from (+definite ) to (-definite).Once a noun is perceived as uncountable by learners, the choice would fall back on the zero article. These findings suggest that learners should be engaged in recognition of the countability of new vocabulary by explaining nouns in lexical phrases and explore more complex aspects such as analysis dependent on discourse.

Keywords: noun phrase, zero article, corpus, second language acquisition

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Authors: Warnakulasuriya Arachichige Malisha Ann Rosary Fernando, Udalamatta Gamage Omila Chalanka Jinadasa, Bihini Pabasara Amandi Amarasinghe, Manul Thisuraka Mandalawatta, Uthpala Samarakoon, Manori Gamage

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The surge in sexually transmitted diseases (STDs) has become a critical public health crisis demanding urgent attention and action. Like many other nations, Sri Lanka is grappling with a significant increase in STDs due to a lack of education and awareness regarding their dangers. Presently, the available applications for tracking and managing STDs cover only a limited number of easily detectable infections, resulting in a significant gap in effectively controlling their spread. To address this gap and combat the rising STD rates, it is essential to leverage technology and data. Employing technology to enhance the tracking and management of STDs is vital to prevent their further propagation and to enable early intervention and treatment. This requires adopting a comprehensive approach that involves raising public awareness about the perils of STDs, improving access to affordable healthcare services for early detection and treatment, and utilizing advanced technology and data analysis. The proposed mobile application aims to cater to a broad range of users, including STD patients, recovered individuals, and those unaware of their STD status. By harnessing cutting-edge technologies like image detection, symptom-based identification, prevention methods, doctor and clinic recommendations, and virtual counselor chat, the application offers a holistic approach to STD management. In conclusion, the escalating STD rates in Sri Lanka and across the globe require immediate action. The integration of technology-driven solutions, along with comprehensive education and healthcare accessibility, is the key to curbing the spread of STDs and promoting better overall public health.

Keywords: STD, machine learning, NLP, artificial intelligence

Procedia PDF Downloads 80