Search results for: state support
11915 Machine Learning for Disease Prediction Using Symptoms and X-Ray Images
Authors: Ravija Gunawardana, Banuka Athuraliya
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Machine learning has emerged as a powerful tool for disease diagnosis and prediction. The use of machine learning algorithms has the potential to improve the accuracy of disease prediction, thereby enabling medical professionals to provide more effective and personalized treatments. This study focuses on developing a machine-learning model for disease prediction using symptoms and X-ray images. The importance of this study lies in its potential to assist medical professionals in accurately diagnosing diseases, thereby improving patient outcomes. Respiratory diseases are a significant cause of morbidity and mortality worldwide, and chest X-rays are commonly used in the diagnosis of these diseases. However, accurately interpreting X-ray images requires significant expertise and can be time-consuming, making it difficult to diagnose respiratory diseases in a timely manner. By incorporating machine learning algorithms, we can significantly enhance disease prediction accuracy, ultimately leading to better patient care. The study utilized the Mask R-CNN algorithm, which is a state-of-the-art method for object detection and segmentation in images, to process chest X-ray images. The model was trained and tested on a large dataset of patient information, which included both symptom data and X-ray images. The performance of the model was evaluated using a range of metrics, including accuracy, precision, recall, and F1-score. The results showed that the model achieved an accuracy rate of over 90%, indicating that it was able to accurately detect and segment regions of interest in the X-ray images. In addition to X-ray images, the study also incorporated symptoms as input data for disease prediction. The study used three different classifiers, namely Random Forest, K-Nearest Neighbor and Support Vector Machine, to predict diseases based on symptoms. These classifiers were trained and tested using the same dataset of patient information as the X-ray model. The results showed promising accuracy rates for predicting diseases using symptoms, with the ensemble learning techniques significantly improving the accuracy of disease prediction. The study's findings indicate that the use of machine learning algorithms can significantly enhance disease prediction accuracy, ultimately leading to better patient care. The model developed in this study has the potential to assist medical professionals in diagnosing respiratory diseases more accurately and efficiently. However, it is important to note that the accuracy of the model can be affected by several factors, including the quality of the X-ray images, the size of the dataset used for training, and the complexity of the disease being diagnosed. In conclusion, the study demonstrated the potential of machine learning algorithms for disease prediction using symptoms and X-ray images. The use of these algorithms can improve the accuracy of disease diagnosis, ultimately leading to better patient care. Further research is needed to validate the model's accuracy and effectiveness in a clinical setting and to expand its application to other diseases.Keywords: K-nearest neighbor, mask R-CNN, random forest, support vector machine
Procedia PDF Downloads 15411914 Indigenizing the Curriculum: Teaching at the Ifugao State University, Philippines
Authors: Nancy Ann P. Gonzales, Serafin L. Ngohayon
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The Nurturing Indigenous Knowledge Experts (NIKE) among the young generation in Ifugao was a project in Ifugao, Philippines spearheaded by the Ifugao State University (IFSU) and was sponsored by the UNESCO Association in Japan. Through the project, he Ifugao Indigenous Knowledge Workbook was developed. It contains nine chapters. The workbook was pilot-tested to students who had IK classes. The descriptive survey method of research was used. A questionnaire was used to gather data from first year Bachelor of Elementary Education and Bachelor of Political Science students. Frequency count, percentage and mean were computed. T-test was used to determine if there exists significant difference on knowledge gained before and after IK was taught to the students. Results revealed that the respondents have an increased level of IK in all the areas covered in the NIKE workbook after they enrolled in their classes. It is alarming to note that the students are knowledgeable about IK but they are not practicing it. However, according to the respondents, they will apply their IK through teaching after graduation.Keywords: curriculum, elders, Indigenous knowledge, and students
Procedia PDF Downloads 35711913 Poverty Reduction in European Cities: Local Governments’ Strategies and Programmes to Reduce Poverty; Interview Results from Austria
Authors: Melanie Schinnerl, Dorothea Greiling
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In the context of the 2020 strategy, poverty and its fight returned to the center of national political efforts. This served as motivation for an Austrian research grant-funded project to focus on the under-researched local government level with the aim to identify municipal best-practice cases and to derive policy implications for Austria. Designing effective poverty reduction strategies is a complex challenge which calls for an integrated multi-actor in approach. Cities are increasingly confronted to combat poverty, even in rich EU-member states. By doing so cities face substantial demographic, cultural, economic and social challenges as well as changing welfare state regimes. Furthermore, there is a low willingness of (right-wing) governments to support the poor. Against this background, the research questions are: 1. How do local governments define poverty? 2. Who are the main risk groups and what are the most pressing problems when fighting urban poverty? 3. What is regarded as successful anti-poverty initiatives? 4. What is the underlying welfare state concept? To address the research questions a multi-method approach was chosen, consisting of a systematic literature analysis, a comprehensive document analysis, and expert interviews. For interpreting the data the project follows the qualitative-interpretive paradigm. Municipal approaches for reducing poverty are compared based on deductive, as well as inductive identified criteria. In addition to an intensive literature analysis, interviews (40) were conducted in Austria since the project started in March 2018. From the other countries, 14 responses have been collected, providing a first insight. Regarding the definition of poverty the EU SILC-definition as well as counting the persons who receive need-based minimum social benefits, the Austrian form of social welfare, are the predominant approaches in Austria. In addition to homeless people, single-parent families, un-skilled persons, long-term unemployed persons, migrants (first and second generation), refugees and families with at least 3 children were frequently mentioned. The most pressing challenges for Austrian cities are: expected reductions of social budgets, a great insecurity of the central government's social policy reform plans, the growing number of homeless people and a lack of affordable housing. Together with affordable housing, old-age poverty will gain more importance in the future. The Austrian best practice examples, suggested by interviewees, focused primarily on homeless, children and young people (till 25). Central government’s policy changes have already negative effects on programs for refugees and elderly unemployed. Social Housing in Vienna was frequently mentioned as an international best practice case, other growing cities can learn from. The results from Austria indicate a change towards the social investment state, which primarily focuses on children and labour market integration. The first insights from the other countries indicate that affordable housing and labor market integration are cross-cutting issues. Inherited poverty and old-age poverty seems to be more pressing outside Austria.Keywords: anti-poverty policies, European cities, empirical study, social investment
Procedia PDF Downloads 11711912 Health Trajectory Clustering Using Deep Belief Networks
Authors: Farshid Hajati, Federico Girosi, Shima Ghassempour
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We present a Deep Belief Network (DBN) method for clustering health trajectories. Deep Belief Network (DBN) is a deep architecture that consists of a stack of Restricted Boltzmann Machines (RBM). In a deep architecture, each layer learns more complex features than the past layers. The proposed method depends on DBN in clustering without using back propagation learning algorithm. The proposed DBN has a better a performance compared to the deep neural network due the initialization of the connecting weights. We use Contrastive Divergence (CD) method for training the RBMs which increases the performance of the network. The performance of the proposed method is evaluated extensively on the Health and Retirement Study (HRS) database. The University of Michigan Health and Retirement Study (HRS) is a nationally representative longitudinal study that has surveyed more than 27,000 elderly and near-elderly Americans since its inception in 1992. Participants are interviewed every two years and they collect data on physical and mental health, insurance coverage, financial status, family support systems, labor market status, and retirement planning. The dataset is publicly available and we use the RAND HRS version L, which is easy to use and cleaned up version of the data. The size of sample data set is 268 and the length of the trajectories is equal to 10. The trajectories do not stop when the patient dies and represent 10 different interviews of live patients. Compared to the state-of-the-art benchmarks, the experimental results show the effectiveness and superiority of the proposed method in clustering health trajectories.Keywords: health trajectory, clustering, deep learning, DBN
Procedia PDF Downloads 36911911 Hip and Valley Support Location in Wood Framing
Authors: P. Hajyalikhani, B. Hudson, D. Boll, L. Boren, Z. Sparks, M. Ward
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Wood Light frame construction is one of the most common types of construction methods for residential and light commercial building in North America and parts of Europe. The typical roof framing for wood framed building is sloped and consists of several structural members such as rafters, hips, and valleys which are connected to the ridge and ceiling joists. The common slopes for roofs are 3/12, 8/12, and 12/12. Wood framed residential roof failure is most commonly caused by wind damage in such buildings. In the recent study, one of the weaknesses of wood framed roofs is long unsupported structural member lengths, such as hips and valleys. The purpose of this research is to find the critical support location for long hips and valleys with different slopes. ForteWeb software is used to find the critical location. The analysis results demonstrating the maximum unbraced hip and valley length are from 8.5 to 10.25 ft. dependent on the slope and roof type.Keywords: wood frame, stick framing, hip, valley
Procedia PDF Downloads 11711910 Post Disaster Community Support with Family Manga Exhibition as a Tool for Intervention and Outreach: Reflection on the past Five Years from a Narrative Perspective
Authors: Kuniko Muramoto, Tadashi Nakamura, Shiro Dan
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On March 11, 2011 the Great East Japan Disaster caused widespread damage. In the aftermath, we searched for ways to provide long-term support and enhanced resilience to affected areas, arriving at the Family Manga Exhibition: an art collection portraying family life. It became a tool for community outreach and intervention, and we implemented support programs by collaborating with local support agencies. This 10-year project has been touring through four prefectures in Tohoku since the disaster struck, bearing witness to the effects of disaster and recovery alike. At this five-year mark, we use a narrative perspective to present our findings and reflect on post-disaster community support. It is important to note that the exhibition’s art does not directly depict the disaster; it portrays stories of anonymous families instead. They stimulate viewers’ memories and remind them of their own family stories. We analyzed viewers' oral and written responses to the exhibition and discovered that family manga as an art form enhances the viewer’s sense of connection to people close to them. We also discovered that the viewers gained more universal perspective on their own situations by viewing the exhibition. Manga, we found, offered a certain safety by enabling the viewers to control how they would interact with the exhibition's content and themes. In addition, the purpose of the project was for us to become witnesses of the disaster and recovery. Supporters of the project became active listeners, functioning as interactive agents who helped forming stories. Voices of the story tellers and the listeners layered upon each other and, as a result, converged into brand new narratives. The essence of traumatic experience is ‘the sense of overwhelming powerlessness and isolation’. When we redefine trauma as ‘broken relationships’, we can say that ‘enhancing relationships’ and ‘weaving relationships’ are what strengthen our resilience. This project used narrative as a modality to fortify the resilience of people involved by enhancing the social capital of bonding, bridging, and linking. The manga exhibition functioned as a tool to achieve this end, suggesting that similar applications are possible. Programs we held in-between manga exhibitions also served to enhance narratives of resiliency in the regions. However, we will save that story for another time. We hope to continue collecting the precious and polyphonic voices of people to present as stories born out of the Great East Japan Disaster. This effort extends beyond the immediately affected area by helping us prepare our resilience for future disasters.Keywords: community, manga, narrative, resilience
Procedia PDF Downloads 22411909 An Inverse Approach for Determining Creep Properties from a Miniature Thin Plate Specimen under Bending
Authors: Yang Zheng, Wei Sun
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This paper describes a new approach which can be used to interpret the experimental creep deformation data obtained from miniaturized thin plate bending specimen test to the corresponding uniaxial data based on an inversed application of the reference stress method. The geometry of the thin plate is fully defined by the span of the support, l, the width, b, and the thickness, d. Firstly, analytical solutions for the steady-state, load-line creep deformation rate of the thin plates for a Norton’s power law under plane stress (b → 0) and plane strain (b → ∞) conditions were obtained, from which it can be seen that the load-line deformation rate of the thin plate under plane-stress conditions is much higher than that under the plane-strain conditions. Since analytical solution is not available for the plates with random b-values, finite element (FE) analyses are used to obtain the solutions. Based on the FE results obtained for various b/l ratios and creep exponent, n, as well as the analytical solutions under plane stress and plane strain conditions, an approximate, numerical solutions for the deformation rate are obtained by curve fitting. Using these solutions, a reference stress method is utilised to establish the conversion relationships between the applied load and the equivalent uniaxial stress and between the creep deformations of thin plate and the equivalent uniaxial creep strains. Finally, the accuracy of the empirical solution was assessed by using a set of “theoretical” experimental data.Keywords: bending, creep, thin plate, materials engineering
Procedia PDF Downloads 47411908 Computing Machinery and Legal Intelligence: Towards a Reflexive Model for Computer Automated Decision Support in Public Administration
Authors: Jacob Livingston Slosser, Naja Holten Moller, Thomas Troels Hildebrandt, Henrik Palmer Olsen
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In this paper, we propose a model for human-AI interaction in public administration that involves legal decision-making. Inspired by Alan Turing’s test for machine intelligence, we propose a way of institutionalizing a continuous working relationship between man and machine that aims at ensuring both good legal quality and higher efficiency in decision-making processes in public administration. We also suggest that our model enhances the legitimacy of using AI in public legal decision-making. We suggest that case loads in public administration could be divided between a manual and an automated decision track. The automated decision track will be an algorithmic recommender system trained on former cases. To avoid unwanted feedback loops and biases, part of the case load will be dealt with by both a human case worker and the automated recommender system. In those cases an experienced human case worker will have the role of an evaluator, choosing between the two decisions. This model will ensure that the algorithmic recommender system is not compromising the quality of the legal decision making in the institution. It also enhances the legitimacy of using algorithmic decision support because it provides justification for its use by being seen as superior to human decisions when the algorithmic recommendations are preferred by experienced case workers. The paper outlines in some detail the process through which such a model could be implemented. It also addresses the important issue that legal decision making is subject to legislative and judicial changes and that legal interpretation is context sensitive. Both of these issues requires continuous supervision and adjustments to algorithmic recommender systems when used for legal decision making purposes.Keywords: administrative law, algorithmic decision-making, decision support, public law
Procedia PDF Downloads 21711907 Using Machine Learning to Monitor the Condition of the Cutting Edge during Milling Hardened Steel
Authors: Pawel Twardowski, Maciej Tabaszewski, Jakub Czyżycki
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The main goal of the work was to use machine learning to predict cutting-edge wear. The research was carried out while milling hardened steel with sintered carbide cutters at various cutting speeds. During the tests, cutting-edge wear was measured, and vibration acceleration signals were also measured. Appropriate measures were determined from the vibration signals and served as input data in the machine-learning process. Two approaches were used in this work. The first one involved a two-state classification of the cutting edge - suitable and unfit for further work. In the second approach, prediction of the cutting-edge state based on vibration signals was used. The obtained research results show that the appropriate use of machine learning algorithms gives excellent results related to monitoring cutting edge during the process.Keywords: milling of hardened steel, tool wear, vibrations, machine learning
Procedia PDF Downloads 5911906 Bearing Capacity Improvement in a Silty Clay Soil with Crushed Polyethylene Terephthalate
Authors: Renzo Palomino, Alessandra Trujillo, Lidia Pacheco
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The document presents a study based on the incremental bearing capacity of silty clay soil with the incorporation of crushed PET fibers. For a better understanding of the behavior of soil, it is necessary to know its origin. The analyzed samples came from the subgrade layer of a highway that connects the cities of Muniches and Yurimaguas in Loreto, Peru. The material in this area usually has properties such as low support index, medium to high plasticity, and other characteristics that make it considered a ‘problematic’ soil due to factors such as climate, humidity, and geographical location. In addition, PET fibers are obtained from the decomposition of plastic bottles that are polluting agents with a high production rate in our country; in that sense, their use in a construction process represents a considerable reduction in environmental impact. Moreover, to perform a precise analysis of the behavior of this soil mixed with PET, tests such as the hydrometer test, Proctor and CBR with 15%, 10%, 5%, 4%, 3%, and 1% of PET with respect to the mass of the sample of natural soil were carried out. The results show that when a low percentage of PET is used, the support index increases.Keywords: environmental impact, geotechnics, PET, silty clay soil
Procedia PDF Downloads 23711905 Active Disturbance Rejection Control for Maximization of Generated Power from Wind Energy Conversion Systems using a Doubly Fed Induction Generator
Authors: Tamou Nasser, Ahmed Essadki, Ali Boukhriss
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This paper presents the control of doubly fed induction generator (DFIG) used in the wind energy conversion systems. Maximum power point tracking (MPPT) strategy is used to extract the maximum of power during the conversion and taking care that the system does not exceed the operating limits. This is done by acting on the pitch angle to control the orientation of the turbine's blades. Having regard to its robustness and performance, active disturbance rejection control (ADRC) based on the extended state observer (ESO) is employed to achieve the control of both rotor and grid side converters. Simulations are carried out using matlab simulink.Keywords: active disturbance rejection control, extended state observer, doubly fed induction generator, maximum power point tracking
Procedia PDF Downloads 56411904 Maximization of Generated Power from Wind Energy Conversion Systems Using a Doubly Fed Induction Generator with Active Disturbance Rejection Control
Authors: Tamou Nasser, Ahmed Essadki, Ali Boukhriss
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This paper presents the control of doubly fed induction generator (DFIG) used in the wind energy conversion systems. Maximum power point tracking (MPPT) strategy is used to extract the maximum of power during the conversion and taking care that the system does not exceed the operating limits. This is done by acting on the pitch angle to control the orientation of the turbine's blades. Having regard to its robustness and performance, active disturbance rejection control (ADRC) based on the extended state observer (ESO) is employed to achieve the control of both rotor and grid side converters. Simulations are carried out using matlab simulink.Keywords: active disturbance rejection control, extended state observer, doubly fed induction generator, maximum power point tracking
Procedia PDF Downloads 49911903 A Dose Distribution Approach Using Monte Carlo Simulation in Dosimetric Accuracy Calculation for Treating the Lung Tumor
Authors: Md Abdullah Al Mashud, M. Tariquzzaman, M. Jahangir Alam, Tapan Kumar Godder, M. Mahbubur Rahman
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This paper presents a Monte Carlo (MC) method-based dose distributions on lung tumor for 6 MV photon beam to improve the dosimetric accuracy for cancer treatment. The polystyrene which is tissue equivalent material to the lung tumor density is used in this research. In the empirical calculations, TRS-398 formalism of IAEA has been used, and the setup was made according to the ICRU recommendations. The research outcomes were compared with the state-of-the-art experimental results. From the experimental results, it is observed that the proposed based approach provides more accurate results and improves the accuracy than the existing approaches. The average %variation between measured and TPS simulated values was obtained 1.337±0.531, which shows a substantial improvement comparing with the state-of-the-art technology.Keywords: lung tumour, Monte Carlo, polystyrene, Elekta synergy, Monaco planning system
Procedia PDF Downloads 44511902 Inducing Cryptobiosis State of Tardigrades in Cyanobacteria Synechococcus elongatus for Effective Preservation
Authors: Nilesh Bandekar, Sumita Dasgupta, Luis Alberto Allcahuaman Huaya, Souvik Manna
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Cryptobiosis is a dormant state where all measurable metabolic activities are at a halt, allowing an organism to survive in extreme conditions like low temperature (cryobiosis), extreme drought (anhydrobiosis), etc. This phenomenon is observed especially in tardigrades that can retain this state for decades depending on the abiotic environmental conditions. On returning to favorable conditions, tardigrades re-attain a metabolically active state. In this study, cyanobacteria as a model organism are being chosen to induce cryptobiosis for its effective preservation over a long period of time. Preserving cyanobacteria using this strategy will have multiple space applications because of its ability to produce oxygen. In addition, research has shown the survivability of this organism in space for a certain period of time. Few species of cyanobacterial residents of the soil such as Microcoleus, are able to survive in extreme drought as well. This work specifically focuses on Synechococcus elongatus, an endolith cyanobacteria with multiple benefits. It has the capability to produce 25% oxygen in water bodies. It utilizes carbon dioxide to produce oxygen via photosynthesis and also uses carbon dioxide as an energy source to form glucose via the Calvin cycle. There is a fair possibility of initiating cryptobiosis in such an organism by inducing certain proteins extracted from tardigrades such as Heat Shock Proteins (Hsp27 and Hsp30c) and/or hydrophilic Late Embryogenesis Abundant proteins (LEA). Existing methods like cryopreservation are difficult to execute in space keeping in mind their cost and heavy instrumentation. Also, extensive freezing may cause cellular damage. Therefore, cryptobiosis-induced cyanobacteria for its transportation from Earth to Mars as a part of future terraforming missions on Mars will save resources and increase the effectiveness of preservation. Finally, Cyanobacteria species like Synechococcus elongatus can also produce oxygen and glucose on Mars in favorable conditions and holds the key to terraforming Mars.Keywords: cryptobiosis, cyanobacteria, glucose, mars, Synechococcus elongatus, tardigrades
Procedia PDF Downloads 22711901 Opportunities and Challenges: Tracing the Evolution of India's First State-led Curriculum-based Media Literacy Intervention
Authors: Ayush Aditya
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In today's digitised world, the extent of an individual’s social involvement is largely determined by their interaction over the internet. The Internet has emerged as a primary source of information consumption and a reliable medium for receiving updates on everyday activities. Owing to this change in the information consumption pattern, the internet has also emerged as a hotbed of misinformation. Experts are of the view that media literacy has emerged as one of the most effective strategies for addressing the issue of misinformation. This paper aims to study the evolution of the Kerala government's media literacy policy, its implementation strategy, challenges and opportunities. The objective of this paper is to create a conceptual framework containing details of the implementation strategy based on the Kerala model. Extensive secondary research of literature, newspaper articles, and other online sources was carried out to locate the timeline of this policy. This was followed by semi-structured interview discussions with government officials from Kerala to trace the origin and evolution of this policy. Preliminary findings based on the collected data suggest that this policy is a case of policy by chance, as the officer who headed this policy during the state level implementation was the one who has already piloted a media literacy program in a district called Kannur as the district collector. Through this paper, an attempt is made to trace the history of the media literacy policy starting from the Kannur intervention in 2018, which was started to address the issue of vaccine hesitancy around measles rubella(MR) vaccination. If not for the vaccine hesitancy, this program would not have been rolled out in Kannur. Interviews with government officials suggest that when authorities decided to take up this initiative in 2020, a huge amount of misinformation emerging during the COVID-19 pandemic was the trigger. There was misinformation regarding government orders, healthcare facilities, vaccination, and lockdown regulations, which affected everyone, unlike the case of Kannur, where it was only a certain age group of kids. As a solution to this problem, the state government decided to create a media literacy curriculum to be taught in all government schools of the state starting from standard 8 till graduation. This was a tricky task, as a new course had to be immediately introduced in the school curriculum amid all the disruptions in the education system caused by the pandemic. It was revealed during the interview that in the case of the state-wide implementation, every step involved multiple checks and balances, unlike the earlier program where stakeholders were roped-in as and when the need emerged. On the pedagogy, while the training during the pilot could be managed through PowerPoint presentation, designing a state-wide curriculum involved multiple iterations and expert approvals. The reason for this is COVID-19 related misinformation has lost its significance. In the next phase of the research, an attempt will be made to compare other aspects of the pilot implementation with the state-wide implementation.Keywords: media literacy, digital media literacy, curriculum based media literacy intervention, misinformation
Procedia PDF Downloads 9311900 Overcoming Reading Barriers in an Inclusive Mathematics Classroom with Linguistic and Visual Support
Authors: A. Noll, J. Roth, M. Scholz
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The importance of written language in a democratic society is non-controversial. Students with physical, learning, cognitive or developmental disabilities often have difficulties in understanding information which is presented in written language only. These students suffer from obstacles in diverse domains. In order to reduce such barriers in educational as well as in out-of-school areas, access to written information must be facilitated. Readability can be enhanced by linguistic simplifications like the application of easy-to-read language. Easy-to-read language shall help people with disabilities to participate socially and politically in society. The authors state, for example, that only short simple words should be used, whereas the occurrence of complex sentences should be avoided. So far, these guidelines were not empirically proved. Another way to reduce reading barriers is the use of visual support, for example, symbols. A symbol conveys, in contrast to a photo, a single idea or concept. Little empirical data about the use of symbols to foster the readability of texts exist. Nevertheless, a positive influence can be assumed, e.g., because of the multimedia principle. It indicates that people learn better from words and pictures than from words alone. A qualitative Interview and Eye-Tracking-Study, which was conducted by the authors, gives cause for the assumption that besides the illustration of single words, the visualization of complete sentences may be helpful. Thus, the effect of photos, which illustrate the content of complete sentences, is also investigated in this study. This leads us to the main research question which was focused on: Does the use of easy-to-read language and/or enriching text with symbols or photos facilitate pupils’ comprehension of learning tasks? The sample consisted of students with learning difficulties (N = 144) and students without SEN (N = 159). The students worked on the tasks, which dealt with introducing fractions, individually. While experimental group 1 received a linguistically simplified version of the tasks, experimental group 2 worked with a variation which was linguistically simplified and furthermore, the keywords of the tasks were visualized by symbols. Experimental group 3 worked on exercises which were simplified by easy-to-read-language and the content of the whole sentences was illustrated by photos. Experimental group 4 received a not simplified version. The participants’ reading ability and their IQ was elevated beforehand to build four comparable groups. There is a significant effect of the different setting on the students’ results F(3,140) = 2,932; p = 0,036*. A post-hoc-analyses with multiple comparisons shows that this significance results from the difference between experimental group 3 and 4. The students in the group easy-to-read language plus photos worked on the exercises significantly more successfully than the students who worked in the group with no simplifications. Further results which refer, among others, to the influence of the students reading ability will be presented at the ICERI 2018.Keywords: inclusive education, mathematics education, easy-to-read language, photos, symbols, special educational needs
Procedia PDF Downloads 15411899 Funding Innovative Activities in Firms: The Ownership Structure and Governance Linkage - Evidence from Mongolia
Authors: Ernest Nweke, Enkhtuya Bavuudorj
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The harsh realities of the scandalous failure of several notable corporations in the past two decades have inextricably resulted in a surge in corporate governance studies. Nevertheless, little or no attention has been paid to corporate governance studies in Mongolian firms and much less to the comprehension of the correlation among ownership structure, corporate governance mechanisms and trend of innovative activities. Innovation is the bed rock of enterprise success. However, the funding and support for innovative activities in many firms are to a great extent determined by the incentives provided by the firm’s internal and external governance mechanisms. Mongolia is an East Asian country currently undergoing a fast-paced transition from socialist to democratic system and it is a widely held view that private ownership as against public ownership fosters innovation. Hence, following the privatization policy of Mongolian Government which has led to the transfer of the ownership of hitherto state controlled and state directed firms to private individuals and organizations, expectations are high that sufficient motivation would be provided for firm managers to engage in innovative activities. This research focuses on the relationship between ownership structure, corporate governance on one hand and the level of innovation on the hand. The paper is empirical in nature and derives data from both reliable secondary and primary sources. Secondary data for the study was in respect of ownership structure of Mongolian listed firms and innovation trend in Mongolia generally. These were analyzed using tables, charts, bars and percentages. Personal interviews and surveys were held to collect primary data. Primary data was in respect of corporate governance practices in Mongolian firms and were collected using structured questionnaire. Out of a population of three hundred and twenty (320) companies listed on the Mongolian Stock Exchange (MSE), a sample size of thirty (30) randomly selected companies was utilized for the study. Five (5) management level employees were surveyed in each selected firm giving a total of one hundred and fifty (150) respondents. Data collected were analyzed and research hypotheses tested using Chi-Square test statistic. Research results showed that corporate governance mechanisms were better and have significantly improved overtime in privately held as opposed to publicly owned firms. Consequently, the levels of innovation in privately held firms were considerably higher. It was concluded that a significant and positive relationship exists between private ownership and good corporate governance on one hand and the level of funding provided for innovative activities in Mongolian firms on the other hand.Keywords: corporate governance, innovation, ownership structure, stock exchange
Procedia PDF Downloads 19511898 Parent’s Preferences about Technology-Based Therapy for Children and Young People on the Autism Spectrum – a UK Survey
Authors: Athanasia Kouroupa, Karen Irvine, Sivana Mengoni, Shivani Sharma
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Exploring parents’ preferences towards technology-based interventions for children on the autism spectrum can inform future research and support technology design. The study aimed to provide a comprehensive description of parents’ knowledge and preferences about innovative technology to support children on the autism spectrum. Survey data were collected from parents (n = 267) internationally. The survey included information about the use of conventional (e.g., smartphone, iPod, tablets) and non-conventional (e.g., virtual reality, robot) technologies. Parents appeared to prefer conventional technologies such as tablets and dislike non-conventional ones. They highlighted the positive contribution technology brought to the children’s lives during the pandemic. A few parents were equally concerned that the compulsory introduction of technology during the pandemic was associated with elongated time on devices. The data suggested that technology-based interventions are not widely known, need to be financially approachable and achieve a high standard of design to engage users.Keywords: autism, intervention, preferences, technology
Procedia PDF Downloads 13311897 Assessment of Solid Waste Management in General Mohammed Inuwa Wushishi Housing Estate, Minna, Niger State, Nigeria
Authors: Garba Inuwa Kuta, Mohammed, Adamu, Mohammed Ahmed Emigilati, Ibrahim Ishiaku, Kudu Dangana
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The study sought to identify the problems of solid waste management in General Mohammed InuwaWushishi Housing Estate. The two broad types of data, the secondary and primary data were used in the study. Questionnaires and personal observations were also used to collect some of the data. Factors impeding the effective and efficient solid waste management were identified. The study revealed that sacks disposal method and open dumping are the most commonly used method of disposal, about 30.0% of the respondent use sacks disposal method in the estate while 24.9% dump their refuse on the floor. Wrong attitudes and perceptions of the people about sanitation issues contributed to solid waste management problems of General Mohammed InuwaWushishi Housing Estate. Majority of the households did not educate their members on the need to clean their surroundings and refuse to buy drum for waste disposal from Niger State Environmental Protection Agency (NISEPA) on the basis that the drums are expensive. Virtually, all the people depended on Niger State Environmental Protection Agency (NISEPA) facilities for the disposal of their household refuse. Solid waste management problems were partly the results of NISEPA’s inability to cope with the situation because of lack of equipment. It was recommended that there should be an increase in enlightenment to the people on domestic waste disposal to keep the surroundings clean.Keywords: housing estate, assessment, solid waste, disposal, management
Procedia PDF Downloads 65011896 Machine Vision System for Measuring the Quality of Bulk Sun-dried Organic Raisins
Authors: Navab Karimi, Tohid Alizadeh
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An intelligent vision-based system was designed to measure the quality and purity of raisins. A machine vision setup was utilized to capture the images of bulk raisins in ranges of 5-50% mixed pure-impure berries. The textural features of bulk raisins were extracted using Grey-level Histograms, Co-occurrence Matrix, and Local Binary Pattern (a total of 108 features). Genetic Algorithm and neural network regression were used for selecting and ranking the best features (21 features). As a result, the GLCM features set was found to have the highest accuracy (92.4%) among the other sets. Followingly, multiple feature combinations of the previous stage were fed into the second regression (linear regression) to increase accuracy, wherein a combination of 16 features was found to be the optimum. Finally, a Support Vector Machine (SVM) classifier was used to differentiate the mixtures, producing the best efficiency and accuracy of 96.2% and 97.35%, respectively.Keywords: sun-dried organic raisin, genetic algorithm, feature extraction, ann regression, linear regression, support vector machine, south azerbaijan.
Procedia PDF Downloads 7311895 Child Feeding Practices Among Mothers in Urban Areas of Akure, Ondo State, Nigeria
Authors: Olufemi Samuel Shola, Oladapo Adenike Adesola
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Inadequate dietary intake has increased the susceptibility of under five children to malnutrition and infections. This study, therefore, assessed the feeding practices of children of 0-23 months of age among mothers in urban areas of Akure, Ondo State, Nigeria. Simple random sampling technique was used to select four hundred (400) mothers out of 710 mothers from 7 primary health care centres in Akure metropolis for the study. Data were collected using modified WHO 2003 Questionnaire on child feeding practices. Data were analyzed using descriptive statistics, while chi-square was used to determine the association between variables. Results showed that 52.0% of the children were males, with 47.5% in the 6-8 months age group. More than half (57.0%) of the mothers were between the ages of 20-29 years, and 45.0% had secondary education. Majority (94.3%) of the mothers breastfed their children in the last 24 hours preceding the survey. The feeding practices history of mothers showed that 28.0% and 53.7% of the mothers initiated breastfeeding less than 30 minutes and between 30 minutes to 1 hour after delivery, respectively. Also, 52.0% of mothers practiced exclusive breastfeeding for six months, while 26.2% breastfed from 6 months up to 2 years of age. Dietary diversity of the children age 6-23 months revealed that 68.7% of the children attained the minimum dietary diversity by consuming 4 or more food groups in the last 24 hours. There was a significant association (P < 0.05) between mothers’ education (n=180), occupation(n=41) and dietary diversity (n= 150) and meal frequency (n=209). Therefore, the study concluded that the duration of breastfeeding and time of introduction of complementary food did not meet WHO recommended guidelines. There is urgent need to launching more programmes.Keywords: breastfeeding, mothers, child feeding, urban areas, ondo state, nigeria
Procedia PDF Downloads 12711894 Artificial Intelligent-Based Approaches for Task Offloading, Resource Allocation and Service Placement of Internet of Things Applications: State of the Art
Authors: Fatima Z. Cherhabil, Mammar Sedrati, Sonia-Sabrina Bendib
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In order to support the continued growth, critical latency of IoT applications, and various obstacles of traditional data centers, mobile edge computing (MEC) has emerged as a promising solution that extends cloud data-processing and decision-making to edge devices. By adopting a MEC structure, IoT applications could be executed locally, on an edge server, different fog nodes, or distant cloud data centers. However, we are often faced with wanting to optimize conflicting criteria such as minimizing energy consumption of limited local capabilities (in terms of CPU, RAM, storage, bandwidth) of mobile edge devices and trying to keep high performance (reducing response time, increasing throughput and service availability) at the same time. Achieving one goal may affect the other, making task offloading (TO), resource allocation (RA), and service placement (SP) complex processes. It is a nontrivial multi-objective optimization problem to study the trade-off between conflicting criteria. The paper provides a survey on different TO, SP, and RA recent multi-objective optimization (MOO) approaches used in edge computing environments, particularly artificial intelligent (AI) ones, to satisfy various objectives, constraints, and dynamic conditions related to IoT applications.Keywords: mobile edge computing, multi-objective optimization, artificial intelligence approaches, task offloading, resource allocation, service placement
Procedia PDF Downloads 11511893 The Combined Methodology To Detect Onboard Driver Fatigue
Authors: K. Senthil Nathan, P. Rajasekaran
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Fatigue is a feeling of extreme physical or mental tiredness. Almost everyone becomes fatigued at some time, but driver’s fatigue is a serious problem that leads to thousands of automobile crashes each year. Fatigue process is often a change from the alertness and vigor state to the tiredness and weakness state. It is not only accompanied by drowsiness but also has a negative impact on mood. There have been studies to detect and quantify fatigue from the measurement of physiology variables such as electroencephalogram (EEG), electrooculogram (EOG), and electromyogram (EMG). This project involves a multimodal sensing of driver’s drowsiness. The first method is to count the eye blinking rate. In the second level, we authenticate the results of eye blink module with a grip sensor. The Flexiforce sensor is placed over the steering wheel. In the third level, the activities are sensed, the time elapsed from the driver’s last activity is counted here. The activities in the sense: Changing gear, applying brake, pressing sound horns, and turning the steering wheel. Absence of these activities is also an indicator of fatigue.Keywords: eye blink sensor, Flexiforce sensor, EEG, EOG, EMG
Procedia PDF Downloads 48311892 Selection of Solid Waste Landfill Site Using Geographical Information System (GIS)
Authors: Fatih Iscan, Ceren Yagci
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Rapid population growth, urbanization and industrialization are known as the most important factors of environment problems. Elimination and management of solid wastes are also within the most important environment problems. One of the main problems in solid waste management is the selection of the best site for elimination of solid wastes. Lately, Geographical Information System (GIS) has been used for easing selection of landfill area. GIS has the ability of imitating necessary economical, environmental and political limitations. They play an important role for the site selection of landfill area as a decision support tool. In this study; map layers will be studied for minimum effect of environmental, social and cultural factors and maximum effect for engineering/economical factors for site selection of landfill areas and using GIS for an decision support mechanism in solid waste landfill areas site selection will be presented in Aksaray/TURKEY city, Güzelyurt district practice.Keywords: GIS, landfill, solid waste, spatial analysis
Procedia PDF Downloads 35911891 The Traveling Behavior and Needs for Tourist Support Facilities of Inbound Tourists Visiting Ratanakosin Island
Authors: Sakul Jariyachamsit
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The objectives of this research were to study the behaviour of inbound tourist who visited Ratanakosin Island and to study their needs concerning support facilities. The independent variables included gender, age, levels of education, occupation, and income while the dependent variables were classified into two groups: tourists’ behaviour variables and tourists’ need of supporting facilities. A simple random sampling method was utilized to get 225 respondents. The majority of respondents were both male and female in the same proportion but most were between 21-30 years old. Most were married with a graduated degree. The average income of the respondents was between $20,000-30,000. The findings revealed that the majority of respondents came to Thailand for the first time and spent about 8 days in Thailand and preferred to travel in small groups. Their decision to come to Thailand was influenced by word of mouth. When they first thought of Thailand, they thought of Thai food. In terms of the needs for tourists around the Ratanakosin Island, and ranked in importance, are as follows: a tourist centre, somebody who can speak English, a trustable agency, police patrol, and the availability of maps and brochures.Keywords: Rattanakosin Island, tourist, travelling behaviour, media engineering
Procedia PDF Downloads 35711890 A Linear Active Disturbance Rejection Control for Maximization of Generated Power from Wind Energy Conversion Systems Using a Doubly Fed Induction Generator
Authors: Tamou Nasser, Ahmed Essadki, Ali Boukhriss
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This paper presents the control of doubly fed induction generator (DFIG) used in the wind energy conversion systems. Maximum power point tracking (MPPT) strategy is used to extract the maximum of power during the conversion and taking care that the system does not exceed the operating limits. This is done by acting on the pitch angle to control the orientation of the turbine's blades. Having regard to its robustness and performance, active disturbance rejection control (ADRC) based on the extended state observer (ESO) is employed to achieve the control of both rotor and grid side converters. Simulations are carried out using MATLAB simulink.Keywords: active disturbance rejection control, extended state observer, doubly fed induction generator, maximum power point tracking
Procedia PDF Downloads 52411889 The Pen Is Mightier than the Sword: Kurdish Language Policy in Turkey
Authors: Irene Yi
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This paper analyzes the development of Kurdish language endangerment in Turkey and Kurdish language education over time. It examines the historical context of the Turkish state, as well as reasons for the Turkish language hegemony. From a linguistic standpoint, the Kurdish language is in danger of extinction despite a large number of speakers, lest Kurdish language education is more widely promoted. The paper argues that Kurdish is no longer in a stable diglossic state; if the current trends continue, the language will lose its vitality. This paper recognizes the importance of education in preserving the language while discussing the changing political and institutional regard for Kurdish education. Lastly, the paper outlines solutions to the issue by looking at a variety of proposals, from creating a Kurdistan to merely changing the linguistic landscape in Turkey. After analysis of possible solutions in terms of realistic ability and effectiveness, the paper concludes that changing linguistic landscape and increasing Kurdish language education are the most ideal first steps in a long fight for Kurdish linguistic equality.Keywords: endangered, Kurdish, oppression, policy
Procedia PDF Downloads 15111888 Environment Patterns and Mental Health of Older Adults in Long-Term Care Facilities: The Role of Activity Profiles
Authors: Shiau-Fang Chao, Yu-Chih Chen
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Owing to physical limitations and restrained lifestyle, older long-term care (LTC) residents are more likely to be affected by their environment than their community-dwelling counterparts. They also participate fewer activities and experience worse mental health than healthy older adults. This study adopts the ICF model to determine the extent to which the clustered patterns of LTC environment and activity participation are associated with older residents’ mental health. Method: Data were collected from a stratified equal probability sample of 634 older residents in 155 LTC institutions in Taiwan. Latent profile analysis (LPA) and latent class analysis (LCA) were conducted to explore the profiles for environment and activity participation. Multilevel modeling was performed to elucidate the relationships among environment profiles, activity profiles, and mental health. Results: LPA identified three mutually exclusive environment profiles (Low-, Moderate-, and High-Support Environment) based on the physical, social, and attitudinal environmental domains, consolidated from 12 environmental measures. LCA constructed two distinct activity profiles (Low- and High-Activity Participation) across seven activity domains (outdoor, volunteer-led leisure, spiritual, household chores, interpersonal exchange, social, and sedentary activity) that were factored from 20 activities. Compared to the Low-Support Environment class, older adults in the Moderate- and High-Support Environment classes had better mental health. Older residents in the Moderate- and High-Support Environment classes were more likely to be in the “High Activity” class, which in turn, exhibited better mental health. Conclusion: This study advances the current knowledge through rigorous methods and study design. The study findings lead to several conclusions. First, this study supports the use of ICF framework to institutionalized older individuals with functional limitations and demonstrates that both measures of environment and activity participation can be refined from multiple indicators. Second, environmental measures that encompass the physical, social, and attitudinal domains would provide a more comprehensive assessment on the place where an older individual embeds. Third, simply counting activities in which an older individual participates or considering a certain type of activity may not capture his or her way of life. Practitioners should not only focus on group or leisure activities within the institutions; rather, more efforts should be made to consider residents’ preferences for everyday life and support their remaining ability by encouraging continuous participation in activities they still willing and capable to perform. Fourth, environment and activity participation are modifiable factors which have greater potential to strengthen older LTC residents’ mental health, and activity participation should be considered in the link between environment and mental health. A combination of enhanced physical, social, and attitudinal environments, and continual engagement in various activities may optimize older LTC residents’ mental health.Keywords: activity, environment, mental health, older LTC residents
Procedia PDF Downloads 19711887 A Parallel Poromechanics Finite Element Method (FEM) Model for Reservoir Analyses
Authors: Henrique C. C. Andrade, Ana Beatriz C. G. Silva, Fernando Luiz B. Ribeiro, Samir Maghous, Jose Claudio F. Telles, Eduardo M. R. Fairbairn
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The present paper aims at developing a parallel computational model for numerical simulation of poromechanics analyses of heterogeneous reservoirs. In the context of macroscopic poroelastoplasticity, the hydromechanical coupling between the skeleton deformation and the fluid pressure is addressed by means of two constitutive equations. The first state equation relates the stress to skeleton strain and pore pressure, while the second state equation relates the Lagrangian porosity change to skeleton volume strain and pore pressure. A specific algorithm for local plastic integration using a tangent operator is devised. A modified Cam-clay type yield surface with associated plastic flow rule is adopted to account for both contractive and dilative behavior.Keywords: finite element method, poromechanics, poroplasticity, reservoir analysis
Procedia PDF Downloads 39111886 Modeling of Building a Conceptual Scheme for Multimodal Freight Transportation Information System
Authors: Gia Surguladze, Nino Topuria, Lily Petriashvili, Giorgi Surguladze
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Modeling of building processes of a multimodal freight transportation support information system is discussed based on modern CASE technologies. Functional efficiencies of ports in the eastern part of the Black Sea are analyzed taking into account their ecological, seasonal, resource usage parameters. By resources, we mean capacities of berths, cranes, automotive transport, as well as work crews and neighbouring airports. For the purpose of designing database of computer support system for Managerial (Logistics) function, using Object-Role Modeling (ORM) tool (NORMA – Natural ORM Architecture) is proposed, after which Entity Relationship Model (ERM) is generated in automated process. The software is developed based on Process-Oriented and Service-Oriented architecture, in Visual Studio.NET environment.Keywords: seaport resources, business-processes, multimodal transportation, CASE technology, object-role model, entity relationship model, SOA
Procedia PDF Downloads 431