Search results for: learning assessment
7768 Variability of Hydrological Modeling of the Blue Nile
Authors: Abeer Samy, Oliver C. Saavedra Valeriano, Abdelazim Negm
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The Blue Nile Basin is the most important tributary of the Nile River. Egypt and Sudan are almost dependent on water originated from the Blue Nile. This multi-dependency creates conflicts among the three countries Egypt, Sudan, and Ethiopia making the management of these conflicts as an international issue. Good assessment of the water resources of the Blue Nile is an important to help in managing such conflicts. Hydrological models are good tool for such assessment. This paper presents a critical review of the nature and variability of the climate and hydrology of the Blue Nile Basin as a first step of using hydrological modeling to assess the water resources of the Blue Nile. Many several attempts are done to develop basin-scale hydrological modeling on the Blue Nile. Lumped and semi distributed models used averages of meteorological inputs and watershed characteristics in hydrological simulation, to analyze runoff for flood control and water resource management. Distributed models include the temporal and spatial variability of catchment conditions and meteorological inputs to allow better representation of the hydrological process. The main challenge of all used models was to assess the water resources of the basin is the shortage of the data needed for models calibration and validation. It is recommended to use distributed model for their higher accuracy to cope with the great variability and complexity of the Blue Nile basin and to collect sufficient data to have more sophisticated and accurate hydrological modeling.Keywords: Blue Nile Basin, climate change, hydrological modeling, watershed
Procedia PDF Downloads 3697767 Emotion Detection in Twitter Messages Using Combination of Long Short-Term Memory and Convolutional Deep Neural Networks
Authors: Bahareh Golchin, Nooshin Riahi
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One of the most significant issues as attended a lot in recent years is that of recognizing the sentiments and emotions in social media texts. The analysis of sentiments and emotions is intended to recognize the conceptual information such as the opinions, feelings, attitudes and emotions of people towards the products, services, organizations, people, topics, events and features in the written text. These indicate the greatness of the problem space. In the real world, businesses and organizations are always looking for tools to gather ideas, emotions, and directions of people about their products, services, or events related to their own. This article uses the Twitter social network, one of the most popular social networks with about 420 million active users, to extract data. Using this social network, users can share their information and opinions about personal issues, policies, products, events, etc. It can be used with appropriate classification of emotional states due to the availability of its data. In this study, supervised learning and deep neural network algorithms are used to classify the emotional states of Twitter users. The use of deep learning methods to increase the learning capacity of the model is an advantage due to the large amount of available data. Tweets collected on various topics are classified into four classes using a combination of two Bidirectional Long Short Term Memory network and a Convolutional network. The results obtained from this study with an average accuracy of 93%, show good results extracted from the proposed framework and improved accuracy compared to previous work.Keywords: emotion classification, sentiment analysis, social networks, deep neural networks
Procedia PDF Downloads 1427766 Competence of the Health Workers in Diagnosing and Managing Complicated Pregnancies: A Clinical Vignette Based Assessment in District and Sub-District Hospitals in Bangladesh
Authors: Abdullah Nurus Salam Khan, Farhana Karim, Mohiuddin Ahsanul Kabir Chowdhury, S. Masum Billah, Nabila Zaka, Alexander Manu, Shams El Arifeen
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Globally, pre-eclampsia (PE) and ante-partum haemorrhage (APH) are two major causes of maternal mortality. Prompt identification and management of these conditions depend on competency of the birth attendants. Since these conditions are infrequent to be observed, clinical vignette based assessment could identify the extent of health worker’s competence in managing emergency obstetric care (EmOC). During June-August 2016, competence of 39 medical officers (MO) and 95 nurses working in obstetric ward of 15 government health facilities (3 district hospital, 12 sub-district hospital) was measured using clinical vignettes on PE and APH. The vignettes resulted in three outcome measures: total vignette scores, scores for diagnosis component, and scores for management component. T-test was conducted to compare mean vignette scores and linear regression was conducted to measure the strength and association of vignette scores with different cadres of health workers, facility’s readiness for EmOC and average annual utilization of normal deliveries after adjusting for type of health facility, health workers’ work experience, training status on managing maternal complication. For each of the seven component of EmOC items (administration of injectable antibiotics, oxytocic and anticonvulsant; manual removal of retained placenta, retained products of conception; blood transfusion and caesarean delivery), if any was practised in the facility within last 6 months, a point was added and cumulative EmOC readiness score (range: 0-7) was generated for each facility. The yearly utilization of delivery cases were identified by taking the average of all normal deliveries conducted during three years (2013-2015) preceding the survey. About 31% of MO and all nurses were female. Mean ( ± sd) age of the nurses were higher than the MO (40.0 ± 6.9 vs. 32.2 ± 6.1 years) and also longer mean( ± sd) working experience (8.9 ± 7.9 vs. 1.9 ± 3.9 years). About 80% health workers received any training on managing maternal complication, however, only 7% received any refresher’s training within last 12 months. The overall vignette score was 8.8 (range: 0-19), which was significantly higher among MO than nurses (10.7 vs. 8.1, p < 0.001) and the score was not associated with health facility types, training status and years of experience of the providers. Vignette score for management component (range: 0-9) increased with higher annual average number of deliveries in their respective working facility (adjusted β-coefficient 0.16, CI 0.03-0.28, p=0.01) and increased with each unit increase in EmOC readiness score (adjusted β-coefficient 0.44, CI 0.04-0.8, p=0.03). The diagnosis component of vignette score was not associated with any of the factors except it was higher among the MO than the nurses (adjusted β-coefficient 1.2, CI 0.13-2.18, p=0.03). Lack of competence in diagnosing and managing obstetric complication by the nurses than the MO is of concern especially when majority of normal deliveries are conducted by the nurses. Better EmOC preparedness of the facility and higher utilization of normal deliveries resulted in higher vignette score for the management component; implying the impact of experiential learning through higher case management. Focus should be given on improving the facility readiness for EmOC and providing the health workers periodic refresher’s training to make them more competent in managing obstetric cases.Keywords: Bangladesh, emergency obstetric care, clinical vignette, competence of health workers
Procedia PDF Downloads 1997765 Full Mini Nutritional Assessment Questionnaire and the Risk of Malnutrition and Mortality in Elderly, Hospitalized Patients: A Cross-Sectional Study
Authors: Christos E. Lampropoulos, Maria Konsta, Tamta Sirbilatze, Ifigenia Apostolou, Vicky Dradaki, Konstantina Panouria, Irini Dri, Christina Kordali, Vaggelis Lambas, Georgios Mavras
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Objectives: Full Mini Nutritional Assessment (MNA) questionnaire is one of the most useful tools in diagnosis of malnutrition in hospitalized patients, which is related to increased morbidity and mortality. The purpose of our study was to assess the nutritional status of elderly, hospitalized patients and examine the hypothesis that MNA may predict mortality and extension of hospitalization. Methods: One hundred fifty patients (78 men, 72 women, mean age 80±8.2) were included in this cross-sectional study. The following data were taken into account in analysis: anthropometric and laboratory data, physical activity (International Physical Activity Questionnaires, IPAQ), smoking status, dietary habits, cause and duration of current admission, medical history (co-morbidities, previous admissions). Primary endpoints were mortality (from admission until 6 months afterwards) and duration of admission. The latter was compared to national guidelines for closed consolidated medical expenses. Logistic regression and linear regression analysis were performed in order to identify independent predictors for mortality and extended hospitalization respectively. Results: According to MNA, nutrition was normal in 54/150 (36%) of patients, 46/150 (30.7%) of them were at risk of malnutrition and the rest 50/150 (33.3%) were malnourished. After performing multivariate logistic regression analysis we found that the odds of death decreased 20% per each unit increase of full MNA score (OR=0.8, 95% CI 0.74-0.89, p < 0.0001). Patients who admitted due to cancer were 23 times more likely to die, compared to those with infection (OR=23, 95% CI 3.8-141.6, p=0.001). Similarly, patients who admitted due to stroke were 7 times more likely to die (OR=7, 95% CI 1.4-34.5, p=0.02), while these with all other causes of admission were less likely (OR=0.2, 95% CI 0.06-0.8, p=0.03), compared to patients with infection. According to multivariate linear regression analysis, each increase of unit of full MNA, decreased the admission duration on average 0.3 days (b:-0.3, 95% CI -0.45 - -0.15, p < 0.0001). Patients admitted due to cancer had on average 6.8 days higher extension of hospitalization, compared to those admitted for infection (b:6.8, 95% CI 3.2-10.3, p < 0.0001). Conclusion: Mortality and extension of hospitalization is significantly increased in elderly, malnourished patients. Full MNA score is a useful diagnostic tool of malnutrition.Keywords: duration of admission, malnutrition, mini nutritional assessment score, prognostic factors for mortality
Procedia PDF Downloads 3167764 Examining Gender Bias in the Sport Concussion Assessment Tool 3 (SCAT3): A Differential Item Functioning Analysis in NCAA Sports
Authors: Rachel M. Edelstein, John D. Van Horn, Karen M. Schmidt, Sydney N. Cushing
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As a consequence of sports-related concussions, female athletes have been documented as reporting more symptoms than their male counterparts, in addition to incurring longer periods of recovery. However, the role of sex and its potential influence on symptom reporting and recovery outcomes in concussion management has not been completely explored. The present aims to investigate the relationship between female concussion symptom severity and the presence of assessment bias. The Sport Concussion Assessment Tool 3 (SCAT3), collected by the NCAA and DoD CARE Consortium, was quantified at five different time points post-concussion. N= 1,258 NCAA athletes, n= 473 female (soccer, rugby, lacrosse, ice hockey) and n=785 male athletes (football, rugby, lacrosse, ice hockey). A polytomous Item Response Theory (IRT) Graded Response Model (GRM) was used to assess the relationship between sex and symptom reporting. Differential Item Functioning (DIF) and Differential Group Functioning (DGF) were used to examine potential group-level bias. Interactions for DIF were utilized to explore the impact of sex on symptom reporting among NCAA male and female athletes throughout and after their concussion recovery. DIF was significantly detected after B-H corrections displayed in limited items; however, one symptom, “Pressure in Head” (-0.29, p=0.04 vs -0.20, p =0.04), was statistically significant at both < 6 hours and 24-48 hours. Thus, implies that at < 6 hours, males were 29% less likely to indicate “Pressure in the Head” compared to female athletes and 20% less likely at 24-48 hours. Overall, the DGF suggested significant group differences, suggesting that male athletes might be at a higher risk for returning to play prematurely (logits = -0.38, p < 0.001). However, after analyzing the SCAT 3, a clinically relevant trend was discovered. Twelve out of the twenty-two symptoms suggest higher difficulty in female athletes within three or more of the five-time points. These symptoms include Balance Problems, Blurry Vision, Confusion, Dizziness, Don’t Feel Right, Feel in Fog, Feel Slow Down, Low Energy, Neck Pain, Sensitivity to Light, Sensitivity to Noise, Trouble Falling Asleep. Despite a lack of statistical significance, this tendency is contrary to current literature stating that males may be unclear on symptoms, but females may be more honest in reporting symptoms. Further research, which includes possible modifying socioecological factors, is needed to determine whether females may consistently experience more symptoms and require longer recovery times or if, parsimoniously, males tend to present their symptoms and readiness for play differently than females. Such research will help to improve the validity of current assumptions concerning male as compared to female head injuries and optimize individualized treatments for sports-related head injuries.Keywords: female athlete, sports-related concussion, item response theory, concussion assessment
Procedia PDF Downloads 817763 Effect of Chemistry Museum Artifacts on Students’ Memory Enhancement and Interest in Radioactivity in Calabar Education Zone, Cross River State, Nigeria
Authors: Hope Amba Neji
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The study adopted a quasi-experimental design. Two schools were used for the experimental study, while one school was used for the control. The experimental groups were subjected to treatment for four weeks with chemistry museum artifacts and a visit as made to the museum so that learners would have real-life learning experiences with museum resources, while the control group was taught with the conventional method. The instrument for the study was a 20-item Chemistry Memory Test (CMT) and a 10-item Chemistry Interest Questionnaire (CIQ). The reliability was ascertained using (KR-20) and alpha reliability coefficient, which yielded a reliability coefficient of .83 and .81, respectively. Data obtained was analyzed using Analysis of Covariance (ANCOVA) and Analysis of variance (ANOVA) at 0.05 level of significance. Findings revealed that museum artifacts have a significant effect on students’ memory enhancement and interest in chemistry. It was recommended chemistry learning should be enhanced, motivating and real with museum artifacts, which significantly aid memory enhancement and interest in chemistry.Keywords: museum artifacts, memory, chemistry, atitude
Procedia PDF Downloads 807762 Recurrent Neural Networks for Complex Survival Models
Authors: Pius Marthin, Nihal Ata Tutkun
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Survival analysis has become one of the paramount procedures in the modeling of time-to-event data. When we encounter complex survival problems, the traditional approach remains limited in accounting for the complex correlational structure between the covariates and the outcome due to the strong assumptions that limit the inference and prediction ability of the resulting models. Several studies exist on the deep learning approach to survival modeling; moreover, the application for the case of complex survival problems still needs to be improved. In addition, the existing models need to address the data structure's complexity fully and are subject to noise and redundant information. In this study, we design a deep learning technique (CmpXRnnSurv_AE) that obliterates the limitations imposed by traditional approaches and addresses the above issues to jointly predict the risk-specific probabilities and survival function for recurrent events with competing risks. We introduce the component termed Risks Information Weights (RIW) as an attention mechanism to compute the weighted cumulative incidence function (WCIF) and an external auto-encoder (ExternalAE) as a feature selector to extract complex characteristics among the set of covariates responsible for the cause-specific events. We train our model using synthetic and real data sets and employ the appropriate metrics for complex survival models for evaluation. As benchmarks, we selected both traditional and machine learning models and our model demonstrates better performance across all datasets.Keywords: cumulative incidence function (CIF), risk information weight (RIW), autoencoders (AE), survival analysis, recurrent events with competing risks, recurrent neural networks (RNN), long short-term memory (LSTM), self-attention, multilayers perceptrons (MLPs)
Procedia PDF Downloads 947761 The Justice of Resources Allocation for People with Disability Base on Activity and Participation Functioning: The Cross-Section Study of National Population
Authors: Chia-Feng Yen, Shyang-Woei Lin
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Background: In Taiwan, people with disability can obtain national social welfare services after evaluation. All subsidies and services in- kind are pronounced in People with Disabilities Rights Protection Act. The new disability eligibility determination system base on ICF has carried out five years in Taiwan. There were no systematic outcomes to discuss the relationships between the evaluation results of activity and participation functioning (AP functioning) and ratification of social services for people with disability. The decision-making of welfare resources allocation is in local government, so the ratification could be affected by resource variations in every area (local governments). The purposes of this study are to compare the ratification rate between different areas (the equity of allocation), and to understand the ratification of social services for people with disability after needs assessment stage that can help to predict the resources allocation for local governments in the further. Methods: A cross-sectional study was used, and the data came from Disability Eligibility Determination System in Taiwan between 2013/11/04-2015/01/12. All samples were evaluated by FUNDES-adult version 7th and they all above 18 years old. The samples were collected face to face by physicians and AP evaluators. Result: In the needs assessment stage, the welfare ratification rates are significant differences between these local governments for the samples with the similar impairment and AP functioning.Keywords: allocation, activity and participation, people with disability, justice
Procedia PDF Downloads 1697760 Hidden Stones When Implementing Artificial Intelligence Solutions in the Engineering, Procurement, and Construction Industry
Authors: Rimma Dzhusupova, Jan Bosch, Helena Holmström Olsson
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Artificial Intelligence (AI) in the Engineering, Procurement, and Construction (EPC) industry has not yet a proven track record in large-scale projects. Since AI solutions for industrial applications became available only recently, deployment experience and lessons learned are still to be built up. Nevertheless, AI has become an attractive technology for organizations looking to automate repetitive tasks to reduce manual work. Meanwhile, the current AI market has started offering various solutions and services. The contribution of this research is that we explore in detail the challenges and obstacles faced in developing and deploying AI in a large-scale project in the EPC industry based on real-life use cases performed in an EPC company. Those identified challenges are not linked to a specific technology or a company's know-how and, therefore, are universal. The findings in this paper aim to provide feedback to academia to reduce the gap between research and practice experience. They also help reveal the hidden stones when implementing AI solutions in the industry.Keywords: artificial intelligence, machine learning, deep learning, innovation, engineering, procurement and construction industry, AI in the EPC industry
Procedia PDF Downloads 1247759 Predicting Machine-Down of Woodworking Industrial Machines
Authors: Matteo Calabrese, Martin Cimmino, Dimos Kapetis, Martina Manfrin, Donato Concilio, Giuseppe Toscano, Giovanni Ciandrini, Giancarlo Paccapeli, Gianluca Giarratana, Marco Siciliano, Andrea Forlani, Alberto Carrotta
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In this paper we describe a machine learning methodology for Predictive Maintenance (PdM) applied on woodworking industrial machines. PdM is a prominent strategy consisting of all the operational techniques and actions required to ensure machine availability and to prevent a machine-down failure. One of the challenges with PdM approach is to design and develop of an embedded smart system to enable the health status of the machine. The proposed approach allows screening simultaneously multiple connected machines, thus providing real-time monitoring that can be adopted with maintenance management. This is achieved by applying temporal feature engineering techniques and training an ensemble of classification algorithms to predict Remaining Useful Lifetime of woodworking machines. The effectiveness of the methodology is demonstrated by testing an independent sample of additional woodworking machines without presenting machine down event.Keywords: predictive maintenance, machine learning, connected machines, artificial intelligence
Procedia PDF Downloads 2297758 Field-Testing a Digital Music Notebook
Authors: Rena Upitis, Philip C. Abrami, Karen Boese
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The success of one-on-one music study relies heavily on the ability of the teacher to provide sufficient direction to students during weekly lessons so that they can successfully practice from one lesson to the next. Traditionally, these instructions are given in a paper notebook, where the teacher makes notes for the students after describing a task or demonstrating a technique. The ability of students to make sense of these notes varies according to their understanding of the teacher’s directions, their motivation to practice, their memory of the lesson, and their abilities to self-regulate. At best, the notes enable the student to progress successfully. At worst, the student is left rudderless until the next lesson takes place. Digital notebooks have the potential to provide a more interactive and effective bridge between music lessons than traditional pen-and-paper notebooks. One such digital notebook, Cadenza, was designed to streamline and improve teachers’ instruction, to enhance student practicing, and to provide the means for teachers and students to communicate between lessons. For example, Cadenza contains a video annotator, where teachers can offer real-time guidance on uploaded student performances. Using the checklist feature, teachers and students negotiate the frequency and type of practice during the lesson, which the student can then access during subsequent practice sessions. Following the tenets of self-regulated learning, goal setting and reflection are also featured. Accordingly, the present paper addressed the following research questions: (1) How does the use of the Cadenza digital music notebook engage students and their teachers?, (2) Which features of Cadenza are most successful?, (3) Which features could be improved?, and (4) Is student learning and motivation enhanced with the use of the Cadenza digital music notebook? The paper describes the results 10 months of field-testing of Cadenza, structured around the four research questions outlined. Six teachers and 65 students took part in the study. Data were collected through video-recorded lesson observations, digital screen captures, surveys, and interviews. Standard qualitative protocols for coding results and identifying themes were employed to analyze the results. The results consistently indicated that teachers and students embraced the digital platform offered by Cadenza. The practice log and timer, the real-time annotation tool, the checklists, the lesson summaries, and the commenting features were found to be the most valuable functions, by students and teachers alike. Teachers also reported that students progressed more quickly with Cadenza, and received higher results in examinations than those students who were not using Cadenza. Teachers identified modifications to Cadenza that would make it an even more powerful way to support student learning. These modifications, once implemented, will move the tool well past its traditional notebook uses to new ways of motivating students to practise between lessons and to communicate with teachers about their learning. Improvements to the tool called for by the teachers included the ability to duplicate archived lessons, allowing for split screen viewing, and adding goal setting to the teacher window. In the concluding section, proposed modifications and their implications for self-regulated learning are discussed.Keywords: digital music technologies, electronic notebooks, self-regulated learning, studio music instruction
Procedia PDF Downloads 2567757 Environmental Impact of Pallets in the Supply Chain: Including Logistics and Material Durability in a Life Cycle Assessment Approach
Authors: Joana Almeida, Kendall Reid, Jonas Bengtsson
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Pallets are devices that are used for moving and storing freight and are nearly omnipresent in supply chains. The market is dominated by timber pallets, with plastic being a common alternative. Either option underpins the use of important resources (oil, land, timber), the emission of greenhouse gases and additional waste generation in most supply chains. This study uses a dynamic approach to the life cycle assessment (LCA) of pallets. It demonstrates that what ultimately defines the environmental burden of pallets in the supply chain is how often the length of its lifespan, which depends on the durability of the material and on how pallets are utilized. This study proposes a life cycle assessment (LCA) of pallets in supply chains supported by an algorithm that estimates pallet durability in function of material resilience and of logistics. The LCA runs from cradle-to-grave, including raw material provision, manufacture, transport and end of life. The scope is representative of timber and plastic pallets in the Australian and South-East Asia markets. The materials included in this analysis are: -tropical mixed hardwood, unsustainably harvested in SE Asia; -certified softwood, sustainably harvested; -conventional plastic, a mix of virgin and scrap plastic; -recycled plastic pallets, 100% mixed plastic scrap, which are being pioneered by Re > Pal. The logistical model purports that more complex supply chains and rougher handling subject pallets to higher stress loads. More stress shortens the lifespan of pallets in function of their composition. Timber pallets can be repaired, extending their lifespan, while plastic pallets cannot. At the factory gate, softwood pallets have the lowest carbon footprint. Re > pal follows closely due to its burden-free feedstock. Tropical mixed hardwood and plastic pallets have the highest footprints. Harvesting tropical mixed hardwood in SE Asia often leads to deforestation, leading to emissions from land use change. The higher footprint of plastic pallets is due to the production of virgin plastic. Our findings show that manufacture alone does not determine the sustainability of pallets. Even though certified softwood pallets have lower carbon footprint and their lifespan can be extended by repair, the need for re-supply of materials and disposal of waste timber offsets this advantage. It also leads to most waste being generated among all pallets. In a supply chain context, Re > Pal pallets have the lowest footprint due to lower replacement and disposal needs. In addition, Re > Pal are nearly ‘waste neutral’, because the waste that is generated throughout their life cycle is almost totally offset by the scrap uptake for production. The absolute results of this study can be confirmed by progressing the logistics model, improving data quality, expanding the range of materials and utilization practices. Still, this LCA demonstrates that considering logistics, raw materials and material durability is central for sustainable decision-making on pallet purchasing, management and disposal.Keywords: carbon footprint, life cycle assessment, recycled plastic, waste
Procedia PDF Downloads 2267756 Nondestructive Prediction and Classification of Gel Strength in Ethanol-Treated Kudzu Starch Gels Using Near-Infrared Spectroscopy
Authors: John-Nelson Ekumah, Selorm Yao-Say Solomon Adade, Mingming Zhong, Yufan Sun, Qiufang Liang, Muhammad Safiullah Virk, Xorlali Nunekpeku, Nana Adwoa Nkuma Johnson, Bridget Ama Kwadzokpui, Xiaofeng Ren
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Enhancing starch gel strength and stability is crucial. However, traditional gel property assessment methods are destructive, time-consuming, and resource-intensive. Thus, understanding ethanol treatment effects on kudzu starch gel strength and developing a rapid, nondestructive gel strength assessment method is essential for optimizing the treatment process and ensuring product quality consistency. This study investigated the effects of different ethanol concentrations on the microstructure of kudzu starch gels using a comprehensive microstructural analysis. We also developed a nondestructive method for predicting gel strength and classifying treatment levels using near-infrared (NIR) spectroscopy, and advanced data analytics. Scanning electron microscopy revealed progressive network densification and pore collapse with increasing ethanol concentration, correlating with enhanced mechanical properties. NIR spectroscopy, combined with various variable selection methods (CARS, GA, and UVE) and modeling algorithms (PLS, SVM, and ELM), was employed to develop predictive models for gel strength. The UVE-SVM model demonstrated exceptional performance, with the highest R² values (Rc = 0.9786, Rp = 0.9688) and lowest error rates (RMSEC = 6.1340, RMSEP = 6.0283). Pattern recognition algorithms (PCA, LDA, and KNN) successfully classified gels based on ethanol treatment levels, achieving near-perfect accuracy. This integrated approach provided a multiscale perspective on ethanol-induced starch gel modification, from molecular interactions to macroscopic properties. Our findings demonstrate the potential of NIR spectroscopy, coupled with advanced data analysis, as a powerful tool for rapid, nondestructive quality assessment in starch gel production. This study contributes significantly to the understanding of starch modification processes and opens new avenues for research and industrial applications in food science, pharmaceuticals, and biomaterials.Keywords: kudzu starch gel, near-infrared spectroscopy, gel strength prediction, support vector machine, pattern recognition algorithms, ethanol treatment
Procedia PDF Downloads 437755 Assessment of the Impact of Atmospheric Air, Drinking Water and Socio-Economic Indicators on the Primary Incidence of Children in Altai Krai
Authors: A. P. Pashkov
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The number of environmental factors that adversely affect children's health is growing every year; their combination in each territory is different. The contribution of socio-economic factors to the health status of the younger generation is increasing. It is the child’s body that is most sensitive to changes in environmental conditions, responding to this with a deterioration in health. Over the past years, scientists have determined the influence of environmental factors and the incidence of children. Currently, there is a tendency to study regional characteristics of the interaction of a combination of environmental factors with the child's body. The aim of the work was to identify trends in the primary non-infectious morbidity of the children of the Altai Territory as a unique region that combines territories with different levels of environmental quality indicators, as well as to assess the effect of atmospheric air, drinking water and socio-economic indicators on the incidence of children in the region. An unfavorable tendency has been revealed in the region for incidence of such nosological groups as neoplasms, including malignant ones, diseases of the endocrine system, including obesity and thyroid disease, diseases of the circulatory system, digestive diseases, diseases of the genitourinary system, congenital anomalies, and respiratory diseases. Between some groups of diseases revealed a pattern of geographical distribution during mapping and a significant correlation. Some nosologies have a relationship with socio-economic indicators for an integrated assessment: circulatory system diseases, respiratory diseases (direct connection), endocrine system diseases, eating disorders, and metabolic disorders (feedback). The analysis of associations of the incidence of children with average annual concentrations of substances that pollute the air and drinking water showed the existence of reliable correlation in areas of critical and intense degree of environmental quality. This fact confirms that the population living in contaminated areas is subject to the negative influence of environmental factors, which immediately affects the health status of children. The results obtained indicate the need for a detailed assessment of the influence of environmental factors on the incidence of children in the regional aspect, the formation of a database, and the development of automated programs that can predict the incidence in each specific territory. This will increase the effectiveness, including economic of preventive measures.Keywords: incidence of children, regional features, socio-economic factors, environmental factors
Procedia PDF Downloads 1187754 Capturing the Stress States in Video Conferences by Photoplethysmographic Pulse Detection
Authors: Jarek Krajewski, David Daxberger
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We propose a stress detection method based on an RGB camera using heart rate detection, also known as Photoplethysmography Imaging (PPGI). This technique focuses on the measurement of the small changes in skin colour caused by blood perfusion. A stationary lab setting with simulated video conferences is chosen using constant light conditions and a sampling rate of 30 fps. The ground truth measurement of heart rate is conducted with a common PPG system. The proposed approach for pulse peak detection is based on a machine learning-based approach, applying brute force feature extraction for the prediction of heart rate pulses. The statistical analysis showed good agreement (correlation r = .79, p<0.05) between the reference heart rate system and the proposed method. Based on these findings, the proposed method could provide a reliable, low-cost, and contactless way of measuring HR parameters in daily-life environments.Keywords: heart rate, PPGI, machine learning, brute force feature extraction
Procedia PDF Downloads 1267753 Prediction of All-Beta Protein Secondary Structure Using Garnier-Osguthorpe-Robson Method
Authors: K. Tejasri, K. Suvarna Vani, S. Prathyusha, S. Ramya
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Proteins are chained sequences of amino acids which are brought together by the peptide bonds. Many varying formations of the chains are possible due to multiple combinations of amino acids and rotation in numerous positions along the chain. Protein structure prediction is one of the crucial goals worked towards by the members of bioinformatics and theoretical chemistry backgrounds. Among the four different structure levels in proteins, we emphasize mainly the secondary level structure. Generally, the secondary protein basically comprises alpha-helix and beta-sheets. Multi-class classification problem of data with disparity is truly a challenge to overcome and has to be addressed for the beta strands. Imbalanced data distribution constitutes a couple of the classes of data having very limited training samples collated with other classes. The secondary structure data is extracted from the protein primary sequence, and the beta-strands are predicted using suitable machine learning algorithms.Keywords: proteins, secondary structure elements, beta-sheets, beta-strands, alpha-helices, machine learning algorithms
Procedia PDF Downloads 967752 Use of Generative Adversarial Networks (GANs) in Neuroimaging and Clinical Neuroscience Applications
Authors: Niloufar Yadgari
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GANs are a potent form of deep learning models that have found success in various fields. They are part of the larger group of generative techniques, which aim to produce authentic data using a probabilistic model that learns distributions from actual samples. In clinical settings, GANs have demonstrated improved abilities in capturing spatially intricate, nonlinear, and possibly subtle disease impacts in contrast to conventional generative techniques. This review critically evaluates the current research on how GANs are being used in imaging studies of different neurological conditions like Alzheimer's disease, brain tumors, aging of the brain, and multiple sclerosis. We offer a clear explanation of different GAN techniques for each use case in neuroimaging and delve into the key hurdles, unanswered queries, and potential advancements in utilizing GANs in this field. Our goal is to connect advanced deep learning techniques with neurology studies, showcasing how GANs can assist in clinical decision-making and enhance our comprehension of the structural and functional aspects of brain disorders.Keywords: GAN, pathology, generative adversarial network, neuro imaging
Procedia PDF Downloads 407751 An Assessment of the Extent and Impact of Motor Insurance Fraud Claims in Nigeria
Authors: Olatokunbo Shoyemi, Mario Brito, Ian Dawson
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In recent times, the Nigerian motor insurers have experienced high volume of motor insurance claim pay-outs and insignificant contribution to the net premium income of the Nigerian insurance market, which has been a major concern for the shareholders/stakeholders. It has been argued that there are many factors that have brought about these concerns. However, anecdotal evidence (ongoing debates among industry practitioners) suggests prevalence of fraud due to poor practices in motor insurance business in Nigeria. This study is therefore aimed to carry out an assessment of fraud in motor insurance claims as perceived by experts in the Nigerian insurance market. This study adopted a descriptive research design, and the analysis was built on a survey among insurance experts in Nigeria using a designed questionnaire. A purposive and snowball sampling were used to select our sample (N = 120) - representing a selection of all professionally qualified insurance experts in Nigeria insurance industry. The study found that Nigerian insurance experts (i) largely agree that there is a problematic level of fraud in the Nigerian motor insurance industry; (ii) perceive soft fraud to be about 3 times more common than hard fraud in the Nigerian motor insurance industry, and (iii) strongly agree there are problematic impacts from fraud on the solvency of the Nigerian motor insurers. This paper has provided an empirical understanding of the existence, extent, and impact of fraud risks within the Nigerian insurance market based on expert knowledge and insights rather than, as has often been the case, a reliance on individual anecdotes.Keywords: claims, net premium income, motor insurance, soft fraud, hard fraud
Procedia PDF Downloads 1127750 Strategic Analysis of Energy and Impact Assessment of Microalgae Based Biodiesel and Biogas Production in Outdoor Raceway Pond: A Life Cycle Perspective
Authors: T. Sarat Chandra, M. Maneesh Kumar, S. N. Mudliar, V. S. Chauhan, S. Mukherji, R. Sarada
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The life cycle assessment (LCA) of biodiesel production from freshwater microalgae Scenedesmus dimorphus cultivated in open raceway pond is performed. Various scenarios for biodiesel production were simulated using primary and secondary data. The parameters varied in the modelled scenarios were related to biomass productivity, mode of culture mixing and type of energy source. The process steps included algae cultivation in open raceway ponds, harvesting by chemical flocculation, dewatering by mechanical drying option (MDO) followed by extraction, reaction and purification. Anaerobic digestion of defatted algal biomass (DAB) for biogas generation is considered as a co-product allocation and the energy derived from DAB was thereby used in the upstream of the process. The scenarios were analysed for energy demand, emissions and environmental impacts within the boundary conditions grounded on "cradle to gate" inventory. Across all the Scenarios, cultivation via raceway pond was observed to be energy intensive process. The mode of culture mixing and biomass productivity determined the energy requirements of the cultivation step. Emissions to Freshwater were found to be maximum contributing to 93-97% of total emissions in all the scenarios. Global warming potential (GWP) was the found to be major environmental impact accounting to about 99% of total environmental impacts in all the modelled scenarios. It was noticed that overall emissions and impacts were directly related to energy demand and an inverse relationship was observed with biomass productivity. The geographic location of an energy source affected the environmental impact of a given process. The integration of defatted algal remnants derived electricity with the cultivation system resulted in a 2% reduction in overall energy demand. Direct biogas generation from microalgae post harvesting is also analysed. Energy surplus was observed after using part of the energy in upstream for biomass production. Results suggest biogas production from microalgae post harvesting as an environmentally viable and sustainable option compared to biodiesel production.Keywords: biomass productivity, energy demand, energy source, Lifecycle Assessment (LCA), microalgae, open raceway pond
Procedia PDF Downloads 2917749 An Ecological Approach to Understanding Student Absenteeism in a Suburban, Kansas School
Authors: Andrew Kipp
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Student absenteeism is harmful to both the school and the absentee student. One approach to improving student absenteeism is targeting contextual factors within the students’ learning environment. However, contemporary literature has not taken an ecological agency approach to understanding student absenteeism. Ecological agency is a theoretical framework that magnifies the interplay between the environment and the actions of people within the environment. To elaborate, the person’s personal history and aspirations and the environmental conditions provide potential outlets or restrictions to their intended action. The framework provides the unique perspective of understanding absentee students’ decision-making through the affordances and constraints found in their learning environment. To that effect, the study was guided by the question, “Why do absentee students decide to engage in absenteeism in a suburban Kansas school?” A case study methodology was used to answer the research question. Four suburban, Kansas high school absentee students in the 2020-2021 school year were selected for the study. The fall 2020 semester was in a remote learning setting, and the spring 2021 semester was in an in-person learning setting. The study captured their decision-making with respect to school attendance throughsemi-structured interviews, prolonged observations, drawings, and concept maps. The data was analyzed through thematic analysis. The findings revealed that peer socialization opportunities, methods of instruction, shifts in cultural beliefs due to COVID-19, manifestations of anxiety and lack of space to escape their anxiety, social media bullying, and the inability to receive academic tutoring motivated the participants’ daily decision to either attend or miss school. The findings provided a basis to improve several institutional and classroom practices. These practices included more student-led instruction and less teacher-led instruction in both in-person and remote learning environments, promoting socialization through classroom collaboration and clubs based on emerging student interests, reducing instances of bullying through prosocial education, safe spaces for students to escape the classroom to manage their anxiety, and more opportunities for one-on-one tutoring to improve grades. The study provides an example of using the ecological agency approach to better understand the personal and environmental factors that lead to absenteeism. The study also informs educational policies and classroom practices to better promote student attendance. Further research should investigate other school contexts using the ecological agency theoretical framework to better understand the influence of the school environment on student absenteeism.Keywords: student absenteeism, ecological agency, classroom practices, educational policy, student decision-making
Procedia PDF Downloads 1497748 Rapid Flood Damage Assessment of Population and Crops Using Remotely Sensed Data
Authors: Urooj Saeed, Sajid Rashid Ahmad, Iqra Khalid, Sahar Mirza, Imtiaz Younas
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Pakistan, a flood-prone country, has experienced worst floods in the recent past which have caused extensive damage to the urban and rural areas by loss of lives, damage to infrastructure and agricultural fields. Poor flood management system in the country has projected the risks of damages as the increasing frequency and magnitude of floods are felt as a consequence of climate change; affecting national economy directly or indirectly. To combat the needs of flood emergency, this paper focuses on remotely sensed data based approach for rapid mapping and monitoring of flood extent and its damages so that fast dissemination of information can be done, from local to national level. In this research study, spatial extent of the flooding caused by heavy rains of 2014 has been mapped by using space borne data to assess the crop damages and affected population in sixteen districts of Punjab. For this purpose, moderate resolution imaging spectroradiometer (MODIS) was used to daily mark the flood extent by using Normalised Difference Water Index (NDWI). The highest flood value data was integrated with the LandScan 2014, 1km x 1km grid based population, to calculate the affected population in flood hazard zone. It was estimated that the floods covered an area of 16,870 square kilometers, with 3.0 million population affected. Moreover, to assess the flood damages, Object Based Image Analysis (OBIA) aided with spectral signatures was applied on Landsat image to attain the thematic layers of healthy (0.54 million acre) and damaged crops (0.43 million acre). The study yields that the population of Jhang district (28% of 2.5 million population) was affected the most. Whereas, in terms of crops, Jhang and Muzzafargarh are the ‘highest damaged’ ranked district of floods 2014 in Punjab. This study was completed within 24 hours of the peak flood time, and proves to be an effective methodology for rapid assessment of damages due to flood hazardKeywords: flood hazard, space borne data, object based image analysis, rapid damage assessment
Procedia PDF Downloads 3317747 Hybrid Feature Selection Method for Sentiment Classification of Movie Reviews
Authors: Vishnu Goyal, Basant Agarwal
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Sentiment analysis research provides methods for identifying the people’s opinion written in blogs, reviews, social networking websites etc. Sentiment analysis is to understand what opinion people have about any given entity, object or thing. Sentiment analysis research can be broadly categorised into three types of approaches i.e. semantic orientation, machine learning and lexicon based approaches. Feature selection methods improve the performance of the machine learning algorithms by eliminating the irrelevant features. Information gain feature selection method has been considered best method for sentiment analysis; however, it has the drawback of selection of threshold. Therefore, in this paper, we propose a hybrid feature selection methods comprising of information gain and proposed feature selection method. Initially, features are selected using Information Gain (IG) and further more noisy features are eliminated using the proposed feature selection method. Experimental results show the efficiency of the proposed feature selection methods.Keywords: feature selection, sentiment analysis, hybrid feature selection
Procedia PDF Downloads 3427746 Resident-Aware Green Home
Authors: Ahlam Elkilani, Bayan Elsheikh Ali, Rasha Abu Romman, Amjed Al-mousa, Belal Sababha
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The amount of energy the world uses doubles every 20 years. Green homes play an important role in reducing the residential energy demand. This paper presents a platform that is intended to learn the behavior of home residents and build a profile about their habits and actions. The proposed resident aware home controller intervenes in the operation of home appliances in order to save energy without compromising the convenience of the residents. The presented platform can be used to simulate the actions and movements happening inside a home. The paper includes several optimization techniques that are meant to save energy in the home. In addition, several test scenarios are presented that show how the controller works. Moreover, this paper shows the computed actual savings when each of the presented techniques is implemented in a typical home. The test scenarios have validated that the techniques developed are capable of effectively saving energy at homes.Keywords: green home, resident aware, resident profile, activity learning, machine learning
Procedia PDF Downloads 3937745 Teachers' Beliefs and Practices in Designing Negotiated English Lesson Plans
Authors: Joko Nurkamto
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A lesson plan is a part of the planning phase in a learning and teaching system framing the scenario of pedagogical activities in the classroom. It informs a decision on what to teach and how to landscape classroom interaction. Regardless of these benefits, the writer has witnessed the fact that lesson plans are viewed merely as a teaching document. Therefore, this paper will explore teachers’ beliefs and practices in designing lesson plans. It focuses primarily on how both teachers and students negotiate lesson plans in which the students are deemed to be the agents of instructional innovations. Additionally, the paper will talk about how such lesson plans are enacted. To investigate these issues, document analysis, in-depth interviews, participant classroom observation, and focus group discussion will be deployed as data collection methods in this explorative case study. The benefits of the paper are to show different roles of lesson plans and to discover different ways to design and enact such plans from a socio-interactional perspective.Keywords: instructional innovation, learning and teaching system, lesson plan, pedagogical activities, teachers' beliefs and practices
Procedia PDF Downloads 1577744 Chinese Students’ Use of Corpus Tools in an English for Academic Purposes Writing Course: Influence on Learning Behaviour, Performance Outcomes and Perceptions
Authors: Jingwen Ou
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Writing for academic purposes in a second or foreign language poses a significant challenge for non-native speakers, particularly at the tertiary level, where English academic writing for L2 students is often hindered by difficulties in academic discourse, including vocabulary, academic register, and organization. The past two decades have witnessed a rising popularity in the application of the data-driven learning (DDL) approach in EAP writing instruction. In light of such a trend, this study aims to enhance the integration of DDL into English for academic purposes (EAP) writing classrooms by investigating the perception of Chinese college students regarding the use of corpus tools for improving EAP writing. Additionally, the research explores their corpus consultation behaviors during training to provide insights into corpus-assisted EAP instruction for DDL practitioners. Given the uprising popularity of DDL, this research aims to investigate Chinese university students’ use of corpus tools with three main foci: 1) the influence of corpus tools on learning behaviours, 2) the influence of corpus tools on students’ academic writing performance outcomes, and 3) students’ perceptions and potential perceptional changes towards the use of such tools. Three corpus tools, CQPWeb, Sketch Engine, and LancsBox X, are selected for investigation due to the scarcity of empirical research on patterns of learners’ engagement with a combination of multiple corpora. The research adopts a pre-test / post-test design for the evaluation of students’ academic writing performance before and after the intervention. Twenty participants will be divided into two groups: an intervention and a non-intervention group. Three corpus training workshops will be delivered at the beginning, middle, and end of a semester. An online survey and three separate focus group interviews are designed to investigate students’ perceptions of the use of corpus tools for improving academic writing skills, particularly the rhetorical functions in different essay sections. Insights from students’ consultation sessions indicated difficulties with DDL practice, including insufficiency of time to complete all tasks, struggle with technical set-up, unfamiliarity with the DDL approach and difficulty with some advanced corpus functions. Findings from the main study aim to provide pedagogical insights and training resources for EAP practitioners and learners.Keywords: corpus linguistics, data-driven learning, English for academic purposes, tertiary education in China
Procedia PDF Downloads 677743 Digital Dialogue Game, Epistemic Beliefs, Argumentation and Learning
Authors: Omid Noroozi, Martin Mulder
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The motivational potential of educational games is undeniable especially for teaching topics and skills that are difficult to deal with in traditional educational situations such as argumentation competence. Willingness to argue has an association with student epistemic beliefs, which can influence whether, and the way in which students engage in argumentative discourse activities and critical discussion. The goal of this study was to explore how undergraduate students engage with argumentative discourse activities which have been designed to intensify debate, and whether epistemic beliefs are significant to the outcomes. A pre-test, post-test design was used with students who were assigned to groups of four. They were asked to argue a controversial topic with the aim of exploring various perspectives, and the 'pros and cons' on the topic of 'Genetically Modified Organisms (GMOs)'. The results show that the game facilitated argumentative discourse and a willingness to argue and challenged peers, regardless of students’ epistemic beliefs. Furthermore, the game was evaluated positively in terms of students’ motivation and satisfaction with the learning experience.Keywords: argumentation, attitudinal change, epistemic beliefs, dialogue, digital game objectives and theoretical
Procedia PDF Downloads 4097742 Cyberstalking as an Online Sexual Harassment: Evidence from Experience from Female University Students in Tanzanian Institutions of Higher Learning
Authors: Angela Mathias Kavishe
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Sexual harassment directed at women is reported in many societies, including in Tanzania. The advent of ICT technology, especially in universities, seems to aggravate the situation by extending harassment to cyberspace in various forms, including cyberstalking. Evidence shows that online violence is more dangerous than physical one due to the ability to access multiple private information, attack many victims, mask the perpetrator's identity, suspend the threat for a long time and spread over time and space. The study aimed to measure the magnitude of cyber harassment in Tanzanian higher learning institutions and to assess institutional sensitivity to ICT-mediated gender-based violence. It was carried out in 4 higher learning institutions in Tanzania: Mwalimu Nyerere Memorial Academy and Institute of Finance Management in Dar es Salaam and SAUT, and the University of Dodoma, where a survey questionnaire was distributed to 400 students and 40 key informants were interviewed. It was found that in each institution, the majority of female students experienced online harassment on social media perpetrated by ex-partners, male students, and university male teaching staff. The perpetrators compelled the female students to post nude pictures, have sexual relations with them, or utilize the posted private photographs to force female students to practice online or offline sexual relations. These threats seem to emanate from social-cultural beliefs about the subordinate position of women in society and that women's bodies are perceived as sex objects. It is therefore concluded that cyberspace provides an alternative space for perpetrators to exercise violence towards women.Keywords: cyberstalking, embodiment, gender-based violence, internet
Procedia PDF Downloads 557741 Fostering Creativity in Education Exploring Leadership Perspectives on Systemic Barriers to Innovative Pedagogy
Authors: David Crighton, Kelly Smith
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The ability to adopt creative pedagogical approaches is increasingly vital in today’s educational landscape. This study examines the institutional barriers that hinder educators, in the UK, from embracing such innovation, focusing specifically on the experiences and perspectives of educational leaders. Current literature primarily focuses on the challenges that academics and teachers encounter, particularly highlighting how management culture and audit processes negatively affect their ability to be creative in classrooms and lecture theatres. However, this focus leaves a gap in understanding management perspectives, which is crucial for providing a more holistic insight into the challenges encountered in educational settings. To explore this gap, we are conducting semi-structured interviews with senior leaders across various educational contexts, including universities, schools, and further education colleges. This qualitative methodology, combined with thematic analysis, aims to uncover the managerial, financial, and administrative pressures these leaders face in fostering creativity in teaching and supporting professional learning opportunities. Preliminary insights indicate that educational leaders face significant barriers, such as institutional policies, resource limitations, and external performance indicators. These challenges create a restrictive environment that stifles educators' creativity and innovation. Addressing these barriers is essential for empowering staff to adopt more creative pedagogical approaches, ultimately enhancing student engagement and learning outcomes. By alleviating these constraints, educational leaders can cultivate a culture that fosters creativity and flexibility in the classroom. These insights will inform practical recommendations to support institutional change and enhance professional learning opportunities, contributing to a more dynamic educational environment. In conclusion, this study offers a timely exploration of how leadership can influence the pedagogical landscape in a rapidly evolving educational context. The research seeks to highlight the crucial role that educational leaders play in shaping a culture of creativity and adaptability, ensuring that institutions are better equipped to respond to the challenges of contemporary education.Keywords: educational leadership, professional learning, creative pedagogy, marketisation
Procedia PDF Downloads 217740 An Anthropometric and Postural Risk Assessment of Students in Computer Laboratories of a State University
Authors: Sarah Louise Cruz, Jemille Venturina
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Ergonomics considers the capabilities and limitations of a person as they interact with tools, equipment, facilities and tasks in their work environment. Workplace is one example of physical work environment, be it a workbench or a desk. In school laboratories, sitting is the most common working posture of the students. Students maintain static sitting posture as they perform different computer-aided activities. The College of Engineering and College of Information and Communication Technology of a State University consist of twenty-two computer laboratories. Normally, students aren’t usually aware of the importance of sustaining proper sitting posture while doing their long hour computer laboratory activities. The study evaluates the perceived discomfort and working postures of students as they are exposed on current workplace design of computer laboratories. The current study utilizes Rapid Upper Limb Assessment (RULA), Body Discomfort Chart using Borg’s CR-10 Scale Rating and Quick Exposure Checklist in order to assess the posture and the current working condition. The result of the study may possibly minimize the body discomfort experienced by the students. The researchers redesign the individual workstations which includes working desk, sitting stool and other workplace design components. Also, the economic variability of each alternative was considered given that the study focused on improvement of facilities of a state university.Keywords: computer workstation, ergonomics, posture, students, workplace
Procedia PDF Downloads 3157739 Detection and Classification of Rubber Tree Leaf Diseases Using Machine Learning
Authors: Kavyadevi N., Kaviya G., Gowsalya P., Janani M., Mohanraj S.
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Hevea brasiliensis, also known as the rubber tree, is one of the foremost assets of crops in the world. One of the most significant advantages of the Rubber Plant in terms of air oxygenation is its capacity to reduce the likelihood of an individual developing respiratory allergies like asthma. To construct such a system that can properly identify crop diseases and pests and then create a database of insecticides for each pest and disease, we must first give treatment for the illness that has been detected. We shall primarily examine three major leaf diseases since they are economically deficient in this article, which is Bird's eye spot, algal spot and powdery mildew. And the recommended work focuses on disease identification on rubber tree leaves. It will be accomplished by employing one of the superior algorithms. Input, Preprocessing, Image Segmentation, Extraction Feature, and Classification will be followed by the processing technique. We will use time-consuming procedures that they use to detect the sickness. As a consequence, the main ailments, underlying causes, and signs and symptoms of diseases that harm the rubber tree are covered in this study.Keywords: image processing, python, convolution neural network (CNN), machine learning
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