Search results for: supports vectors machine

Authors: Vasantha Gouri Prathapagiri

Abstract:

Innovations in ICT sector facilitate qualitative life style for citizens across the globe. Countries that facilitate usage of new techniques in ICT, i.e., big data analytics find it easier to fulfil the needs of their citizens. Big data is characterised by its volume, variety, and speed. Analytics involves its processing in a cost effective way in order to draw conclusion for their useful application. Big data also involves into the field of machine learning, artificial intelligence all leading to accuracy in data presentation useful for public policy making. Hence using data analytics in public policy making is a proper way to march towards all round development of any country. The data driven insights can help the government to take important strategic decisions with regard to socio-economic development of her country. Developed nations like UK and USA are already far ahead on the path of digitization with the support of Big Data analytics. India is a huge country and is currently on the path of massive digitization being realised through Digital India Mission. Internet connection per household is on the rise every year. This transforms into a massive data set that has the potential to improvise the public services delivery system into an effective service mechanism for Indian citizens. In fact, when compared to developed nations, this capacity is being underutilized in India. This is particularly true for administrative system in rural areas. The present paper focuses on the need for big data analytics adaptation in Indian rural administration and its contribution towards development of the country on a faster pace. Results of the research focussed on the need for increasing awareness and serious capacity building of the government personnel working for rural development with regard to big data analytics and its utility for development of the country. Multiple public policies are framed and implemented for rural development yet the results are not as effective as they should be. Big data has a major role to play in this context as can assist in improving both policy making and implementation aiming at all round development of the country.

Keywords: Digital India Mission, public service delivery system, public policy, Indian administration

Procedia PDF Downloads 138

Authors: M. S. Nandana, K. Udaya Bhat, C. M. Manjunatha

Abstract:

In this study aluminum alloy 7010 was subjected to three different ageing treatments i.e., peak ageing (T6), over-ageing (T7451) and retrogression and re ageing (RRA) to study the influence of precipitate microstructure on the fatigue crack growth rate behavior. The microstructural modification was studied by using transmission electron microscope (TEM) to examine the change in the size and morphology of precipitates in the matrix and on the grain boundaries. The standard compact tension (CT) specimens were fabricated and tested under constant amplitude fatigue crack growth tests to evaluate the influence of heat treatment on the fatigue crack growth rate properties. The tests were performed in a computer-controlled servo-hydraulic test machine applying a load ratio, R = 0.1 at a loading frequency of 10 Hz as per ASTM E647. The fatigue crack growth was measured by adopting compliance technique using a CMOD gauge attached to the CT specimen. The average size of the matrix precipitates were found to be of 16-20 nm in T7451, 5-6 nm in RRA and 2-3 nm in T6 conditions respectively. The grain boundary precipitate which was continuous in T6, was disintegrated in RRA and T7451 condition. The PFZ width was lower in RRA compared to T7451 condition. The crack growth rate was higher in T7451 and lowest in RRA treated alloy. The RRA treated alloy also exhibits an increase in threshold stress intensity factor range (∆Kₜₕ). The ∆Kₜₕ measured was 11.1, 10.3 and 5.7 MPam¹/² in RRA, T6 and T7451 alloys respectively. The fatigue crack growth rate in RRA treated alloy was nearly 2-3 times lower than that in T6 and was one order lower than that observed in T7451 condition. The surface roughness of RRA treated alloy was more pronounced when compared to the other conditions. The reduction in fatigue crack growth rate in RRA alloy was majorly due to the increase in roughness and partially due to increase in spacing between the matrix precipitates. The reduction in crack growth rate and increase in threshold stress intensity range is expected to benefit the damage tolerant capability of aircraft structural components under service loads.

Keywords: damage tolerance, fatigue, heat treatment, PFZ, RRA

Procedia PDF Downloads 138

Authors: Nahid Hassanshahi, Ayoub Karimi-Jashni, Nasser Talebbeydokhti

Abstract:

Due to the economic and environmental benefits of producing less waste, the US Environmental Protection Agency (EPA) introduces source reduction as one of the most important means to deal with the problems caused by increased landfills and pollution. Waste reduction involves all waste management methods, including source reduction, recycling, and composting, which reduce waste flow to landfills or other disposal facilities. Source reduction of waste can be studied from two perspectives: avoiding waste production, or reducing per capita waste production, and waste deviation that indicates the reduction of waste transfer to landfills. The present paper has investigated home composting as a managerial solution for reduction of waste transfer to landfills. Home composting has many benefits. The use of household waste for the production of compost will result in a much smaller amount of waste being sent to landfills, which in turn will reduce the costs of waste collection, transportation and burial. Reducing the volume of waste for disposal and using them for the production of compost and plant fertilizer might help to recycle the material in a shorter time and to use them effectively in order to preserve the environment and reduce contamination. Producing compost in a home-based manner requires very small piece of land for preparation and recycling compared with other methods. The final product of home-made compost is valuable and helps to grow crops and garden plants. It is also used for modifying the soil structure and maintaining its moisture. The food that is transferred to landfills will spoil and produce leachate after a while. It will also release methane and greenhouse gases. But, composting these materials at home is the best way to manage degradable materials, use them efficiently and reduce environmental pollution. Studies have shown that the benefits of the sale of produced compost and the reduced costs of collecting, transporting, and burying waste can well be responsive to the costs of purchasing home compost machine and the cost of related trainings. Moreover, the process of producing home compost may be profitable within 4 to 5 years and as a result, it will have a major role in reducing waste management.

Keywords: compost, home compost, reducing waste, waste management

Procedia PDF Downloads 405

Authors: Abbas Ali Husseini, Ali Mohammad Yazdani, Fatemeh Ghadiri, Alper Şişman

Abstract:

We developed a microchip device that uses surface acoustic waves for rapid lysis of low level of cell samples. The device incorporates sharp-edge glass microparticles for improved performance. We optimized the lysis conditions for high efficiency and evaluated the device's feasibility for point-of-care applications. The microchip contains a 13-finger pair interdigital transducer with a 30-degree focused angle. It generates high-intensity acoustic beams that converge 6 mm away. The microchip operates at a frequency of 16 MHz, exciting Rayleigh waves with a 250 µm wavelength on the LiNbO3 substrate. Cell lysis occurs when Candida albicans cells and glass particles are placed within the focal area. The high-intensity surface acoustic waves induce centrifugal forces on the cells and glass particles, resulting in cell lysis through lateral forces from the sharp-edge glass particles. We conducted 42 pilot cell lysis experiments to optimize the surface acoustic wave-induced streaming. We varied electrical power, droplet volume, glass particle size, concentration, and lysis time. A regression machine-learning model determined the impact of each parameter on lysis efficiency. Based on these findings, we predicted optimal conditions: electrical signal of 2.5 W, sample volume of 20 µl, glass particle size below 10 µm, concentration of 0.2 µg, and a 5-minute lysis period. Downstream analysis successfully amplified a DNA target fragment directly from the lysate. The study presents an efficient microchip-based cell lysis method employing acoustic streaming and microparticle collisions within microdroplets. Integration of a surface acoustic wave-based lysis chip with an isothermal amplification method enables swift point-of-care applications.

Keywords: cell lysis, surface acoustic wave, micro-glass particle, droplet

Procedia PDF Downloads 64

Authors: R. Fardid, R. Coppes

Abstract:

Introduction: In mediastinal radiotherapy and to a lesser extend also in total-body irradiation (TBI) radiation exposure may lead to development of cardiac diseases. Radiation-induced heart disease is dose-dependent and it is characterized by a loss of cardiac function, associated with progressive heart cells degeneration. We aimed to determine the in-vivo radiation effects on fibronectin, ColaA1, ColaA2, galectin and TGFb1 gene expression levels in left ventricle heart tissues of rats after irradiation. Material and method: Four non-treatment adult Wistar rats as control group (group A) were selected. In group B, 4 adult Wistar rats irradiated to 20 Gy single dose of 150 Mev proton beam locally in heart only. In heart plus lung irradiate group (group C) 4 adult rats was irradiated by 50% of lung laterally plus heart radiation that mentioned in before group. At 8 weeks after radiation animals sacrificed and left ventricle heart dropped in liquid nitrogen for RNA extraction by Absolutely RNA® Miniprep Kit (Stratagen, Cat no. 400800). cDNA was synthesized using M-MLV reverse transcriptase (Life Technologies, Cat no. 28025-013). We used Bio-Rad machine (Bio Rad iQ5 Real Time PCR) for QPCR testing by relative standard curve method. Results: We found that gene expression of fibronectin in group C significantly increased compared to control group, but it was not showed significant change in group B compared to group A. The levels of gene expressions of Cola1 and Cola2 in mRNA did not show any significant changes between normal and radiation groups. Changes of expression of galectin target significantly increased only in group C compared to group A. TGFb1 expressions in group C more than group B showed significant enhancement compared to group A. Conclusion: In summary we can say that 20 Gy of proton exposure of heart tissue may lead to detectable damages in heart cells and may distribute function of them as a component of heart tissue structure in molecular level.

Keywords: gene expression, heart damage, proton irradiation, radiotherapy

Procedia PDF Downloads 472

Authors: Baladitya Swaika, Rahul Khatry

Abstract:

Computer Adaptive Tests (CATs) is one of the most efficient ways for testing the cognitive abilities of students. CATs are based on Item Response Theory (IRT) which is based on item selection and ability estimation using statistical methods of maximum information selection/selection from posterior and maximum-likelihood (ML)/maximum a posteriori (MAP) estimators respectively. This study aims at combining both classical and Bayesian approaches to IRT to create a dataset which is then fed to a neural network which automates the process of ability estimation and then comparing it to traditional CAT models designed using IRT. This study uses python as the base coding language, pymc for statistical modelling of the IRT and scikit-learn for neural network implementations. On creation of the model and on comparison, it is found that the Neural Network based model performs 7-10% worse than the IRT model for score estimations. Although performing poorly, compared to the IRT model, the neural network model can be beneficially used in back-ends for reducing time complexity as the IRT model would have to re-calculate the ability every-time it gets a request whereas the prediction from a neural network could be done in a single step for an existing trained Regressor. This study also proposes a new kind of framework whereby the neural network model could be used to incorporate feature sets, other than the normal IRT feature set and use a neural network’s capacity of learning unknown functions to give rise to better CAT models. Categorical features like test type, etc. could be learnt and incorporated in IRT functions with the help of techniques like logistic regression and can be used to learn functions and expressed as models which may not be trivial to be expressed via equations. This kind of a framework, when implemented would be highly advantageous in psychometrics and cognitive assessments. This study gives a brief overview as to how neural networks can be used in adaptive testing, not only by reducing time-complexity but also by being able to incorporate newer and better datasets which would eventually lead to higher quality testing.

Keywords: computer adaptive tests, item response theory, machine learning, neural networks

Procedia PDF Downloads 160

Authors: Corrado Grassi, Achim Schröter, Yves Gloy, Thomas Gries

Abstract:

Air jet weaving is the most productive, but also the most energy consuming weaving method. Increasing energy costs and environmental impact are constantly a challenge for the manufacturers of weaving machines. Current technological developments concern with low energy costs, low environmental impact, high productivity, and constant product quality. The high degree of energy consumption of the method can be ascribed to the high need of compressed air. An energy efficiency method is applied to the air jet weaving technology. Such method identifies and classifies the main relevant energy consumers and processes from the exergy point of view and it leads to the identification of energy efficiency potentials during the weft insertion process. Starting from the design phase, energy efficiency is considered as the central requirement to be satisfied. The initial phase of the method consists of an analysis of the state of the art of the main weft insertion components in order to point out a prioritization of the high demanding energy components and processes. The identified major components are investigated to reduce the high demand of energy of the weft insertion process. During the interaction of the flow field coming from the relay nozzles within the profiled reed, only a minor part of the stream is really accelerating the weft yarn, hence resulting in large energy inefficiency. Different tools such as FEM analysis, CFD simulation models and experimental analysis are used in order to design a more energy efficient design of the involved components in the filling insertion. A different concept for the metal strip of the profiled reed is developed. The developed metal strip allows a reduction of the machine energy consumption. Based on a parametric and aerodynamic study, the designed reed transmits higher values of the flow power to the filling yarn. The innovative reed fulfills both the requirement of raising energy efficiency and the compliance with the weaving constraints.

Keywords: air jet weaving, aerodynamic simulation, energy efficiency, experimental validation, weft insertion

Procedia PDF Downloads 179

Authors: Hoai Nam Huynh, Edouard Rivière-Lorphèvre, Olivier Verlinden

Abstract:

Manufacturing technologies are becoming continuously more diversified over the years. The increasing use of robots for various applications such as assembling, painting, welding has also affected the field of machining. Machining robots can deal with larger workspaces than conventional machine-tools at a lower cost and thus represent a very promising alternative for machining applications. Furthermore, their inherent structure ensures them a great flexibility of motion to reach any location on the workpiece with the desired orientation. Nevertheless, machining robots suffer from a lack of stiffness at their joints restricting their use to applications involving low cutting forces especially finishing operations. Vibratory instabilities may also happen while machining and deteriorate the precision leading to scrap parts. Some researchers are therefore concerned with the identification of optimal parameters in robotic machining. This paper continues the development of a virtual robotic machining simulator in order to find optimized cutting parameters in terms of depth of cut or feed per tooth for example. The simulation environment combines an in-house milling routine (DyStaMill) achieving the computation of cutting forces and material removal with an in-house multibody library (EasyDyn) which is used to build a dynamic model of a 3-DOF planar robot with flexible links. The position of the robot end-effector submitted to milling forces is controlled through an inverse kinematics scheme while controlling the position of its joints separately. Each joint is actuated through a servomotor for which the transfer function has been computed in order to tune the corresponding controller. The output results feature the evolution of the cutting forces when the robot structure is deformable or not and the tracking errors of the end-effector. Illustrations of the resulting machined surfaces are also presented. The consideration of the links flexibility has highlighted an increase of the cutting forces magnitude. This proof of concept will aim to enrich the database of results in robotic machining for potential improvements in production.

Keywords: control, milling, multibody, robotic, simulation

Procedia PDF Downloads 231

Authors: Nathenal Thomas

Abstract:

In the food chain and in many other agricultural products, corn, also known as maize, which goes by the scientific name Zea mays subsp, is a widely produced agricultural product. Corn has the highest adaptability. It comes in many different types, is employed in many different industrial processes, and is more adaptable to different agro-climatic situations. In Ethiopia, maize is among the most widely grown crop. Small-scale corn farming may be a household's only source of food in developing nations like Ethiopia. The aforementioned data demonstrates that the country's requirement for this crop is excessively high, and conversely, the crop's productivity is very low for a variety of reasons. The most damaging disease that greatly contributes to this imbalance between the crop's supply and demand is the corn disease. The failure to diagnose diseases in maize plant until they are too late is one of the most important factors influencing crop output in Ethiopia. This study will aid in the early detection of such diseases and support farmers during the cultivation process, directly affecting the amount of maize produced. The diseases in maize plants, such as northern leaf blight and cercospora leaf spot, have distinct symptoms that are visible. This study aims to detect the most frequent and degrading maize diseases using the most efficiently used subset of machine learning technology, deep learning so, called Image Processing. Deep learning uses networks that can be trained from unlabeled data without supervision (unsupervised). It is a feature that simulates the exercises the human brain goes through when digesting data. Its applications include speech recognition, language translation, object classification, and decision-making. Convolutional Neural Network (CNN) for Image Processing, also known as convent, is a deep learning class that is widely used for image classification, image detection, face recognition, and other problems. it will also use this algorithm as the state-of-the-art for my research to detect maize diseases by photographing maize leaves using a mobile phone.

Keywords: CNN, zea mays subsp, leaf blight, cercospora leaf spot

Procedia PDF Downloads 59

Authors: Pranay Mathur, Carlo Michelassi, Simi Karatha, Gilda Pedoto

Abstract:

Industrial plant uptime is top most importance for reliable, profitable & sustainable operation. Trip and failed start has major impact on plant reliability and all plant operators focussed on efforts required to minimise the trips & failed starts. The performance of these CTQs are measured with 2 metrics, MTBT(Mean time between trips) and SR (Starting reliability). These metrics helps to identify top failure modes and identify units need more effort to improve plant reliability. Baker Hughes Trip reduction program structured to reduce these unwanted trip 1. Real time machine operational parameters remotely available and capturing the signature of malfunction including related boundary condition. 2. Real time alerting system based on analytics available remotely. 3. Remote access to trip logs and alarms from control system to identify the cause of events. 4. Continuous support to field engineers by remotely connecting with subject matter expert. 5. Live tracking of key CTQs 6. Benchmark against fleet 7. Break down to the cause of failure to component level 8. Investigate top contributor, identify design and operational root cause 9. Implement corrective and preventive action 10. Assessing effectiveness of implemented solution using reliability growth models. 11. Develop analytics for predictive maintenance With this approach , Baker Hughes team is able to support customer in achieving their Reliability Key performance Indicators for monitored units, huge cost savings for plant operators. This Presentation explains these approach while providing successful case studies, in particular where 12nos. of LNG and Pipeline operators with about 140 gas compressing line-ups has adopted these techniques and significantly reduce the number of trips and improved MTBT

Keywords: reliability, availability, sustainability, digital infrastructure, weibull, effectiveness, automation, trips, fail start

Procedia PDF Downloads 57

Authors: Tomiwa, Akinyemi Clement

Abstract:

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

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

Procedia PDF Downloads 10

Authors: Weber-Lewerenz Bianca

Abstract:

Digitization is developing fast and has become a powerful tool for digital planning, construction, and operations. Its transformation bears high potentials for companies, is critical for success, and thus, requires responsible handling. This study provides an assessment of calls made in the sustainable development goals by the United Nations (SDGs), White Papers on AI by international institutions, EU-Commission and German Government requesting for the consideration and protection of values and fundamental rights, the careful demarcation between machine (artificial) and human intelligence and the careful use of such technologies. The study discusses digitization and the impacts of artificial intelligence (AI) in construction engineering from an ethical perspective by generating data via conducting case studies and interviewing experts as part of the qualitative method. This research evaluates critically opportunities and risks revolving around corporate digital responsibility (CDR) in the construction industry. To the author's knowledge, no study has set out to investigate how CDR in construction could be conceptualized, especially in relation to the digitization and AI, to mitigate digital transformation both in large, medium-sized, and small companies. No study addressed the key research question: Where can CDR be allocated, how shall its adequate ethical framework be designed to support digital innovations in order to make full use of the potentials of digitization and AI? Now is the right timing for constructive approaches and apply ethics-by-design in order to develop and implement a safe and efficient AI. This represents the first study in construction engineering applying a holistic, interdisciplinary, inclusive approach to provide guidelines for orientation, examine benefits of AI and define ethical principles as the key driver for success, resources-cost-time efficiency, and sustainability using digital technologies and AI in construction engineering to enhance digital transformation. Innovative corporate organizations starting new business models are more likely to succeed than those dominated by conservative, traditional attitudes.

Keywords: construction engineering, digitization, digital transformation, artificial intelligence, ethics, corporate digital responsibility, digital innovation

Procedia PDF Downloads 215

Authors: Peiming Li

Abstract:

This paper presents an innovative blockchain-based approach to enhance the reliability and efficiency of federated learning systems. By integrating a decentralized oracle consensus mechanism into the federated learning framework, we address key challenges of data and model integrity. Our approach utilizes a network of redundant oracles, functioning as independent validators within an epoch-based training system in the federated learning model. In federated learning, data is decentralized, residing on various participants' devices. This scenario often leads to concerns about data integrity and model quality. Our solution employs blockchain technology to establish a transparent and tamper-proof environment, ensuring secure data sharing and aggregation. The decentralized oracles, a concept borrowed from blockchain systems, act as unbiased validators. They assess the contributions of each participant using a Hidden Markov Model (HMM), which is crucial for evaluating the consistency of participant inputs and safeguarding against model poisoning and malicious activities. Our methodology's distinct feature is its epoch-based training. An epoch here refers to a specific training phase where data is updated and assessed for quality and relevance. The redundant oracles work in concert to validate data updates during these epochs, enhancing the system's resilience to security threats and data corruption. The effectiveness of this system was tested using the Mnist dataset, a standard in machine learning for benchmarking. Results demonstrate that our blockchain-oriented federated learning approach significantly boosts system resilience, addressing the common challenges of federated environments. This paper aims to make these advanced concepts accessible, even to those with a limited background in blockchain or federated learning. We provide a foundational understanding of how blockchain technology can revolutionize data integrity in decentralized systems and explain the role of oracles in maintaining model accuracy and reliability.

Keywords: federated learning system, block chain, decentralized oracles, hidden markov model

Procedia PDF Downloads 43

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

Abstract:

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

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

Procedia PDF Downloads 87

Authors: Annalise Weckesser, Alex Wade, Clara Joergensen, Jerome Turner

Abstract:

Introduction: Digital mobile technologies afford Generation M a number of opportunities in terms of communication, creativity and connectivity in their social interactions. Yet these young people’s use of such technologies is often the source of moral panic with accordant social anxiety especially prevalent in media representations of teen ‘sexting,’ or the sending of sexually explicit images via smartphones. Thus far, most responses to youth sexting have largely been ineffective or unjust with adult authorities sometimes blaming victims of non-consensual sexting, using child pornography laws to paradoxically criminalise those they are designed to protect, and/or advising teenagers to simply abstain from the practice. Prevention strategies are further skewed, with sex education initiatives often targeted at girls, implying that they shoulder the responsibility of minimising the risks associated with sexting (e.g. revenge porn and sexual predation). Purpose of Study: Despite increasing public interest and concern about ‘teen sexting,’ there remains a dearth of research with young people regarding their experiences of navigating sex and relationships in the current digital media landscape. Furthermore, young people's views on sexting are rarely solicited in the policy and educational strategies aimed at them. To address this research-policy-education gap, an interdisciplinary team of four researchers (from anthropology, media, sociology and education) have undertaken a peer-to-peer research project to co-create a sexual health intervention. Methods: In the winter of 2015-2016, the research team conducted serial group interviews with four cohorts of students (aged 13 to 15) from a secondary school in the West Midlands, UK. To facilitate open dialogue, girls and boys were interviewed separately, and each group consisted of no more than four pupils. The team employed a range of participatory techniques to elicit young people’s views on sexting, its consequences, and its interventions. A final focus group session was conducted with all 14 male and female participants to explore developing a peer-to-peer ‘safe sexting’ education intervention. Findings: This presentation will highlight the ongoing, ‘old school’ sexual double standards at work within this new digital frontier. In the sharing of ‘nudes’ (teens’ preferred term to ‘sexting’) via social media apps (e.g. Snapchat and WhatsApp), girls felt sharing images was inherently risky and feared being blamed and ‘slut-shamed.’ In contrast, boys were seen to gain in social status if they accumulated nudes of female peers. Further, if boys had nudes of themselves shared without consent, they felt they were expected to simply ‘tough it out.’ The presentation will also explore what forms of supports teens desire to help them in their day-to-day navigation of these digitally mediated, heteronormative performances of teen femininity and masculinity expected of them. Conclusion: This is the first research project, within UK, conducted with rather than about teens and the phenomenon of sexting. It marks a timely and important contribution to the nascent, but growing body of knowledge on gender, sexual politics and the digital mobility of sexual images created by and circulated amongst young people.

Keywords: teens, sexting, gender, sexual politics

Procedia PDF Downloads 213

Authors: Vishal Raj, Noorhan Abbas

Abstract:

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

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

Procedia PDF Downloads 87

Authors: Nuran Öze

Abstract:

People always want to be aware of what is happening around them. The nature of man constantly triggers the need for gathering information because of curiosity. The media has emerged to save people the need for information. It is known that the media has changed with the technological developments over time, diversified and, people's information needs are provided in different ways. Today, the Internet has become an integral part of everyday life. The invasion of the Internet into everyday life practices at this level affects every aspect of life. These effects cause people to change their life practices. Technological developments have always influenced of people, the way they reach information. Looking at the history of the media, the breaking point about the dissemination of information is seen as the invention of the machine of the printing press. This adventure that started with written media has now become a multi-dimensional structure. Written, audio, visual media has now changed shape with new technologies. Especially emerging of the internet to everyday life, of course, has effects on media field. 'New media' has appeared which contains most of traditional media features in its'. While in the one hand this transformation enables captures a harmony between traditional and new media, on the other hand, new media and traditional media are rivaling each other. The purpose of this study is to examine the problematic relationship between traditional media and new media through the news reading practices of individuals. This study can be evaluated as a kind of media sociology. To reach this aim, two different field researches will be done besides literature review. The research will be conducted in Northern Cyprus. Northern Cyprus Northern Cyprus is located in the Mediterranean Sea. North Cyprus is a country which is not recognized by any country except Turkey. Despite this, takes its share from all technological developments take place in the world. One of the field researches will consist of the questionnaires to be applied on media readers' news reading practices. This survey will be conducted in a social media environment. The second field survey will be conducted in the form of interviews with general editorials or news directors in traditional media. In the second field survey, in-depth interview method will be applied. As a result of these investigations, supporting sides between the new media and the traditional media and directions which contrast with each other will be revealed. In addition to that, it will try to understand the attitudes and perceptions of readers about the traditional media and the new media in this study.

Keywords: new media, news, North Cyprus, traditional media

Procedia PDF Downloads 214

Authors: Elena Bellini, Daniele Mugnaini, Michele Boschetto

Abstract:

People with an Autistic Spectrum Disorder and an Intellectual Disability who need to attend a Hospital Emergency Waiting Room frequently present high levels of discomfort and challenging behaviors due to stress-related hyperarousal, sensory sensitivity, novelty-anxiety, communication and self-regulation difficulties. Increased agitation and acting out also disturb the diagnostic and therapeutic processes, and the emergency room climate. Architectural design disciplines aimed at reducing distress in hospitals or creating autism-friendly environments are called for to find effective answers to this particular need. A growing number of researchers are considering the physical environment as an important point of intervention for people with autism. It has been shown that providing the right setting can help enhance confidence and self-esteem and can have a profound impact on their health and wellbeing. Environmental psychology has evaluated the perceived quality of care, looking at the design of hospital rooms, paths and circulation, waiting rooms, services and devices. Furthermore, many studies have investigated the influence of the hospital environment on patients, in terms of stress-reduction and therapeutic intervention’ speed, but also on health professionals and their work. Several services around the world are organizing autism-friendly hospital environments which involve the architecture and the specific staff training. In Italy, the association Spes contra spem has promoted and published, in 2013, the ‘Chart of disabled people in the hospital’. It stipulates that disabled people should have equal rights to accessible and high-quality care. There are a few Italian examples of therapeutic programmes for autistic people as the Dama project in Milan and the recent experience of Children and Autism Foundation in Pordenone. Careggi’s Emergency Waiting Room in Florence has been built to satisfy this challenge. This project of research comes from a collaboration between the technical staff of Careggi Hospital, the Center for autism PAMAPI and some architects expert in the sensory environment. The methodology of focus group involved architects, psychologists and professionals through a transdisciplinary research, centered on the links between the spatial characteristics and clinical state of people with ASD. The relationship between architectural space and quality of life is studied to pay maximum attention to users’ needs and to support the medical staff in their work by a specific program of training. The result of this research is a sum of criteria used to design the emergency waiting room, that will be illustrated. A protected room, with a clear space design, maximizes comprehension and predictability. The multisensory environment is thought to help sensory integration and relaxation. Visual communication through Ipad allows an anticipated understanding of medical procedures, and a specific technological system supports requests, choices and self-determination in order to fit sensory stimulation to personal preferences, especially for hypo and hypersensitive people. All these characteristics should ensure a better regulation of the arousal, less behavior problems, improving treatment accessibility, safety, and effectiveness. First results about patient-satisfaction levels will be presented.

Keywords: accessibility of care, autism-friendly architecture, personalized therapeutic process, sensory environment

Procedia PDF Downloads 244

Authors: Insaf Ajili, Malik Mallem, Jean-Yves Didier

Abstract:

Human motion recognition has been extensively increased in recent years due to its importance in a wide range of applications, such as human-computer interaction, intelligent surveillance, augmented reality, content-based video compression and retrieval, etc. However, it is still regarded as a challenging task especially in realistic scenarios. It can be seen as a general machine learning problem which requires an effective human motion representation and an efficient learning method. In this work, we introduce a descriptor based on Laban Movement Analysis technique, a formal and universal language for human movement, to capture both quantitative and qualitative aspects of movement. We use Discrete Hidden Markov Model (DHMM) for training and classification motions. We improve the classification algorithm by proposing two DHMMs for each motion class to process the motion sequence in two different directions, forward and backward. Such modification allows avoiding the misclassification that can happen when recognizing similar motions. Two experiments are conducted. In the first one, we evaluate our method on a public dataset, the Microsoft Research Cambridge-12 Kinect gesture data set (MSRC-12) which is a widely used dataset for evaluating action/gesture recognition methods. In the second experiment, we build a dataset composed of 10 gestures(Introduce yourself, waving, Dance, move, turn left, turn right, stop, sit down, increase velocity, decrease velocity) performed by 20 persons. The evaluation of the system includes testing the efficiency of our descriptor vector based on LMA with basic DHMM method and comparing the recognition results of the modified DHMM with the original one. Experiment results demonstrate that our method outperforms most of existing methods that used the MSRC-12 dataset, and a near perfect classification rate in our dataset.

Keywords: human motion recognition, motion representation, Laban Movement Analysis, Discrete Hidden Markov Model

Procedia PDF Downloads 187

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

Abstract:

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

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

Procedia PDF Downloads 161

Authors: Mohammadjavad Sotoudeheian, Soroush Nematollahi

Abstract:

Crohn’s disease (CD) is a chronic gastrointestinal segment inflammation encompassing immune dysregulation in a genetically susceptible individual in response to the environmental triggers and interaction between the microbiome and immune system. Uncontrolled inflammation leads to long-term complications, including fibrotic strictures and enteric fistulae. Increased production of Th1 and Th17-cell cytokines and defects in T-regulatory cells have been associated with CD. Th17-cells are essential for protection against extracellular pathogens, but their atypical activity can cause autoimmunity. Intrinsic defects in the control of programmed cell death in the mucosal T-cell compartment are strongly implicated in the pathogenesis of CD. The apoptosis defect in mucosal T-cells in CD has been endorsed as an imbalance of the Bcl-2 and the Bax. The immune system encounters foreign antigens through microbial colonization of mucosal surfaces or infections. In addition, FOSL downregulated IL-26 expression, a cytokine that marks inflammatory Th17-populations in patients suffering from CD. Furthermore, the expression of IL-23 is associated with the transcription factor primary leucine zipper transcription factor ATF-like (Batf). Batf-deficiency demonstrated the crucial role of Batf in colitis development. Batf and IL-23 mediate their effects by inducing IL-6 production. Strong association of IL-23R, Stat3, and Stat4 with IBD susceptibility point to a critical involvement of T-cells. IL-23R levels in transfer fistula were dependent on the AP-1 transcription factor JunB that additionally controlled levels of RORγt by facilitating DNA binding of Batf. T lymphocytes lacking JunB failed to induce IL-23- and Th17-mediated experimental colitis highlighting the relevance of JunB for the IL-23/ Th17 pathway. The absence of T-bet causes unrestrained Th17-cell differentiation. T-cells are central parts of immune-mediated colon fistula. Especially Th17-cells were highly prevalent in inflamed IBD tissues, as RORγt is effective in preventing colitis. Intraepithelial lymphocytes (IEL) contain unique T-cell subsets, including cells expressing RORγt. Increased activated Th17 and decreased T-regulatory cells in inflamed intestinal tissues had been seen. T-cells differentiate in response to many cytokines, including IL-1β, IL-6, IL-23, and TGF-β, into Th17-cells, a process which is critically dependent on the Batf. IL-23 promotes Th17-cell in the colon. Batf manages the generation of IL-23 induced IL-23R+ Th17-cells. Batf is necessary for TGF-β/IL-6-induced Th17-polarization. Batf-expressing T-cells are the core of T-cell-mediated colitis. The human-specific parts of three AP-1 transcription factors, FOSL1, FOSL2, and BATF, are essential during the early stages of Th17 differentiation. BATF supports the Th17 lineage. FOSL1, FOSL2, and BATF make possession of regulatory loci of genes in the Th17 lineage cascade. The AP1 transcription factor Batf is identified to control intestinal inflammation and seems to regulate pathways within lymphocytes, which could theoretically control the expression of several genes. It shows central regulatory properties over Th17-cell development and is intensely upregulated within IBD-affected tissues. Here, we demonstrated that targeting Batf in IBD appears as a therapeutic approach that reduces colitogenic T-cell activities during fistula formation while aiming to affect inflammation in the gut epithelial cells.

Keywords: immune system, Crohn’s Disease, BATF, T helper cells, Bcl, interleukin, FOSL

Procedia PDF Downloads 126

Authors: Victor Manuel Alcántara Alza

Abstract:

The way in which the application of the deep cryogenic treatment DCT(-196°C) affects, applied with subsequent aging, was investigated, regarding the mechanical properties of hardness, toughness and microstructure, applied to martensitic stainless steels, with the aim of establishing a different methodology compared to the traditional DCT cryogenic treatment with subsequent tempering. For this experimental study, a muffle furnace was used, first subjecting the specimens to deep cryogenization in a liquid Nitrogen bath/4h, after being previously austenitized at the following temperatures: 1020-1030-1040-1050 (°C) / 1 hour; and then tempered in oil. A first group of cryogenic samples were subjected to subsequent aging at 150°C, with immersion times: 2.5 -5- 10 - 20 - 50 – 100 (h). The next group was subjected to subsequent tempering at temperatures: 480-500-510-520-530-540 (°C)/ 2h. The hardness tests were carried out under standards, using a Universal Durometer, and the readings were made on the HRC scale. The Impact Resistance tests were carried out in a Charpy machine following the ASTM E 23 – 93ª standard. Measurements were taken in joules. Microscopy was performed at the optical level using a 1000X microscope. It was found: For the entire aging interval, the samples austenitized at 1050°C present greater hardness than austenitized at 1040°C, with the maximum peak aged being at 30h. In all cases, the aged samples exceed the hardness of the tempered samples, even in their minimum values. In post-tempered samples, the tempering temperature hardly have effect on the impact strength of material. In the Cryogenic Treatment: DCT + subsequent aging, the maximum hardness value (58.7 HRC) is linked to an impact toughness value (54J) obtained with aging time of 39h, which is considered an optimal condition. The higher hardness of steel after the DCT treatment is attributed to the transformation of retained austenite into martensite. The microstructure is composed mainly of lath martensite; and the original grain size of the austenite can be appreciated. The choice of the combination: Hardness-toughness, is subject to the required service conditions of steel.

Keywords: deep cryogenic treatment; aged precipitation; martensitic steels;, mechanical properties; martensitic steels, hardness, carbides precipitaion

Procedia PDF Downloads 61

Authors: Kwan Hee Han

Abstract:

External environment of enterprise is rapidly changing majorly by global competition, cost reduction pressures, and new technology. In these situations, production scheduling function plays a critical role to meet customer requirements and to attain the goal of operational efficiency. It deals with short-term decision making in the production process of the whole supply chain. The major task of production scheduling is to seek a balance between customer orders and limited resources. In manufacturing companies, this task is so difficult because it should efficiently utilize resource capacity under the careful consideration of many interacting constraints. At present, many computerized software solutions have been utilized in many enterprises to generate a realistic production schedule to overcome the complexity of schedule generation. However, most production scheduling systems do not provide sufficient information about the validity of the generated schedule except limited statistics. Process mining only recently emerged as a sub-discipline of both data mining and business process management. Process mining techniques enable the useful analysis of a wide variety of processes such as process discovery, conformance checking, and bottleneck analysis. In this study, the performance of generated production schedule is evaluated by mining event log data of production scheduling software system by using the process mining techniques since every software system generates event logs for the further use such as security investigation, auditing and error bugging. An application of process mining approach is proposed for the validation of the goodness of production schedule generated by scheduling software systems in this study. By using process mining techniques, major evaluation criteria such as utilization of workstation, existence of bottleneck workstations, critical process route patterns, and work load balance of each machine over time are measured, and finally, the goodness of production schedule is evaluated. By using the proposed process mining approach for evaluating the performance of generated production schedule, the quality of production schedule of manufacturing enterprises can be improved.

Keywords: data mining, event log, process mining, production scheduling

Procedia PDF Downloads 263

Authors: Nattaporn Khanoonkon, Rangrong Yoksan, Amod A. Ogale

Abstract:

Polyethylene (PE) is one of the most petroleum-based thermoplastic materials used in many applications including packaging due to its cheap, light-weight, chemically inert and capable to be converted into various shapes and sizes of products. Although PE is a commercially potential material, its non-biodegradability caused environmental problems. At present, bio-based polymers become more interesting owing to its bio-degradability, non-toxicity, and renewability as well as being eco-friendly. Thermoplastic starch (TPS) is a bio-based and biodegradable plastic produced from the plasticization of starch under applying heat and shear force. In many researches, TPS was blended with petroleum-based polymers including PE in order to reduce the cost and the use of those polymers. However, the phase separation between hydrophobic PE and hydrophilic TPS limited the amount of TPS incorporated. The immiscibility of two different polarity polymers can be diminished by adding compatibilizer. PE-based compatibilizers, e.g. polyethylene-grafted-maleic anhydride, polyethylene-co-vinyl alcohol, etc. have been applied for the PE/TPS blend system in order to improve their miscibility. Until now, there is no report about the utilization of starch-based compatibilizer for PE/TPS blend system. The aims of the present research were therefore to synthesize a new starch-based compatibilizer, i.e. stearic acid-grafted starch (SA-g-starch) and to study the effect of SA-g-starch on chemical interaction, morphological properties, tensile properties and water vapor as well as oxygen barrier properties of the PE/TPS blend films. PE/TPS blends without and with incorporating SA-g-starch with a content of 1, 3 and 5 part(s) per hundred parts of starch (phr) were prepared using a twin screw extruder and then blown into films using a film blowing machine. Incorporating 1 phr and 3 phr of SA-g-starch could improve miscibility of the two polymers as confirmed from the reduction of TPS phase size and the good dispersion of TPS phase in PE matrix. In addition, the blend containing SA-g-starch with contents of 1 phr and 3 phr exhibited higher tensile strength and extensibility, as well as lower water vapor and oxygen permeabilities than the naked blend. The above results suggested that SA-g-starch could be potentially applied as a compatibilizer for the PE/TPS blend system.

Keywords: blend, compatibilizer, polyethylene, thermoplastic starch

Procedia PDF Downloads 425

Authors: Rohollah Ghasemi, Arvin Ghorbani

Abstract:

This study investigates the effect of austempering temperature on microstructure and scratch behavior of the austempered heat-treated compacted graphite irons. The as-cast was used as base material for heat treatment practices. The samples were extracted from as-cast ferritic CGI pieces and were heat treated under austenitising temperature of 900°C for 60 minutes which followed by quenching in salt-bath at different austempering temperatures of 275°C, 325°C and 375°C. For all heat treatments, an austempering holding time of 30 minutes was selected for this study. Light optical microscope (LOM) and scanning electron microscope (SEM) and electron back scattered diffraction (EBSD) analysis confirmed the ausferritic matrix formed in all heat-treated samples. Microscratches were performed under the load of 200, 600 and 1000 mN using a sphero-conical diamond indenter with a tip radius of 50 μm and induced cone angle 90° at a speed of 10 μm/s at room temperature ~25°C. An instrumented nanoindentation machine was used for performing nanoindentation hardness measurement and microscratch testing. Hardness measurements and scratch resistance showed a significant increase in Brinell, Vickers, and nanoindentation hardness values as well as microscratch resistance of the heat-treated samples compared to the as-cast ferritic sample. The increase in hardness and improvement in microscratch resistance are associated with the formation of the ausferrite matrix consisted of carbon-saturated retained austenite and acicular ferrite in austempered matrix. The maximum hardness was observed for samples austempered at 275°C which resulted in the formation of very fine acicular ferrite. In addition, nanohardness values showed a quite significant variation in the matrix due to the presence of acicular ferrite and carbon-saturated retained austenite. It was also observed that the increase of austempering temperature resulted in increase of volume of the carbon-saturated retained austenite and decrease of hardness values.

Keywords: austempered CGI, austempering, scratch testing, scratch plastic deformation, scratch hardness

Procedia PDF Downloads 119

Authors: Assem Abdel Hamed Mousa

Abstract:

The Internet of Things probably already influences your life. And if it doesn’t, it soon will, say computer scientists; Ubiquitous computing names the third wave in computing, just now beginning. First were mainframes, each shared by lots of people. Now we are in the personal computing era, person and machine staring uneasily at each other across the desktop. Next comes ubiquitous computing, or the age of calm technology, when technology recedes into the background of our lives. Alan Kay of Apple calls this "Third Paradigm" computing. Ubiquitous computing is essentially the term for human interaction with computers in virtually everything. Ubiquitous computing is roughly the opposite of virtual reality. Where virtual reality puts people inside a computer-generated world, ubiquitous computing forces the computer to live out here in the world with people. Virtual reality is primarily a horse power problem; ubiquitous computing is a very difficult integration of human factors, computer science, engineering, and social sciences. The approach: Activate the world. Provide hundreds of wireless computing devices per person per office, of all scales (from 1" displays to wall sized). This has required new work in operating systems, user interfaces, networks, wireless, displays, and many other areas. We call our work "ubiquitous computing". This is different from PDA's, dynabooks, or information at your fingertips. It is invisible; everywhere computing that does not live on a personal device of any sort, but is in the woodwork everywhere. The initial incarnation of ubiquitous computing was in the form of "tabs", "pads", and "boards" built at Xerox PARC, 1988-1994. Several papers describe this work, and there are web pages for the Tabs and for the Boards (which are a commercial product now): Ubiquitous computing will drastically reduce the cost of digital devices and tasks for the average consumer. With labor intensive components such as processors and hard drives stored in the remote data centers powering the cloud , and with pooled resources giving individual consumers the benefits of economies of scale, monthly fees similar to a cable bill for services that feed into a consumer’s phone.

Keywords: internet, cloud computing, ubiquitous computing, big data

Procedia PDF Downloads 367

Authors: Gail Joseph

Abstract:

In the United States, to advance the quality and education requirements of PreK teachers, there are concerns regarding barriers for existing early childhood educators to access formal degrees and ongoing professional development. Barriers exist related to affordability and access. Affordability is a key factor that impacts teachers access to degree programs. The lack of financial resources makes it difficult for many qualified candidates to begin, and complete, degree programs. Even if funding was not an issue, accessibility remains a pressing issue in higher education. Some common barriers include geography, long work hours, lack of professional community, childcare, and clear articulation agreements. Greater flexibility is needed to allow all early childhood professionals to pursue college coursework that takes into consideration the many competing demands on their schedules. For these busy professionals, it is particularly important that professional development opportunities are available “on demand” and are seen as relevant to their work. Courses that are available during non-traditional hours make attendance more accessible, and professional development that is relevant to what they need to know and be able to do to be effective in their current positions increase access to and the impact of ongoing professional education. EarlyEdU at the University of Washington provides institutes of higher education and state professional development systems with free comprehensive, competency based college courses based on the latest science of how to optimize child learning and outcomes across developmental domains. The coursework embeds an intentional teaching framework which requires teachers to know what to do in the moment, see effective teaching in themselves and others, enact these practices in the classroom, reflect on what works and what does not, and improve with thoughtful practices. Reinforcing the Intentional Teaching Framework in EarlyEdU courses is the Coaching Companion, an open source, web-based video annotation learning tool that supports coaching in higher education by enabling students to view and refine their teaching practices. The tool is integrated throughout EarlyEdU courses. With the Coaching Companion, students see upload teaching interactions on video and then reflect on the degree to which they incorporate evidence-based practices. Coaching Companion eliminates the traditional separation of theory and practice in college-based teacher preparation. Together, the Intentional Teaching Framework and the Coaching Companion transform the course instructor into a job-embedded coach. The instructor watches student interactions with children on video using the Coaching Companion and looks specifically for interactions defined in course assignments, readings, and lectures. Based on these observations, the instructor offers feedback and proposes next steps. Developed on federal and philanthropic funds, all EarlyEdU courses and the Coaching Companion are available for free to 2= and 4-year colleges and universities with early childhood degrees, as well as to state early learning and education departments to increase access to high quality professional development. We studied the impact of the Coaching Companion in two courses and demonstrated a significant increase in the quality of teacher-child interactions as measured by the PreK CLASS quality teaching assessment. Implications are discussed related to policy and practice.

Keywords: education technology, distance education, early childhood education, professional development

Procedia PDF Downloads 114

Authors: Betül Gelengül Eki̇mci̇, Semra Günay Aktaş

Abstract:

Festive, habitual activities celebrated on the specified date by a local community, are conducive to recognition of the region. The main function of festive events is to help gathering people via an annual celebration to create an atmosphere of understanding and the opportunity to participate in the joy of life. At the same time, festive events may serve as special occasions on which immigrants return home to celebrate with their family and community, reaffirming their identity and link to the community’s traditions. Festivals also support the local economy by bringing in different visitors to the region. The tradition of “Beet Brewing-Molasses Production,” which is held in İdrisyayla Village is an intangible cultural heritage with customs, traditions, and rituals carrying impacts of cuisine culture of Rumelian immigrants in the Ottoman. After the harvest of the beet plant in the autumn season of the year, Beet Brewing Molasses syrup is made by traditional production methods with co-op of the local community. Festive occurring brewing paste made process provided transmission of knowledge and experience to the young generations. Making molasses, which is a laborious process, is accompanied by folk games such as "sayacı," which is vital element of the festive performed in İdrisyayla. Performance provides enjoyable time and supporting motivation. Like other forms of intangible cultural heritage, “Beet Brewing-Molasses Festive in İdrasyayla is threatened by rapid urbanisation, young generation migration, industrialisation and environmental change. The festive events are threatened with gradual disappearance due to changes communities undergo in modern societies because it depends on the broad participation of practitioners. Ensuring the continuity of festive events often requires the mobilization of large numbers of individuals and the social, political and legal institutions and mechanisms of society. In 2015, Intangible cultural heritage research project with the title of "İdrisyayla Molasses Process" managed by the Eskişehir Governorship, City Directorate of Culture and Tourism and Anadolu University, project members took part in the festival organization to promote sustainability, making it visible, to encourage the broadest public participation possible, to ensure public awareness on the cultural importance. To preserve the originality of and encourage participation in the festive İdrisyayla, local associations, researchers and institutions created foundation and supports festive events, such as "sayacı" folk game, which is vital element of the festive performed in İdrisyayla. Practitioners find new opportunity to market İdrisyayla Molasses production. Publicity program through the press and exhibition made it possible to stress the cultural importance of the festive in İdrisyayla Village. The research reported here used a survey analysis to evaluate an affect of the festive after the spirit of the 2015 Festive in İdrisyayla Village. Particular attention was paid to the importance of the cultural aspects of the festival. Based on a survey of more than a hundred festival attendees, several recommendations are made to festival planners. Results indicate that the variety of festive activities and products offered for sale very important to attendees. The local participants care product sales rather than cultural heritage.

Keywords: agritourism, cultural tourism, festival, sustainable cultural heritage

Procedia PDF Downloads 203

Authors: Mehran Asadi, Afrand Agah

Abstract:

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

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

Procedia PDF Downloads 131

Authors: Michael Josef Schwerer

Abstract:

Background: Analyzing any aircraft accident is mandatory based on the regulations of the International Civil Aviation Organization and the respective country’s criminal prosecution authorities. Legal medicine investigations are unavoidable when fatalities involve the flight crew or when doubts arise concerning the pilot’s aeromedical health status before the event. As a result of frequently tremendous blunt and sharp force trauma along with the impact of the aircraft to the ground, consecutive blast or fire exposition of the occupants or putrefaction of the dead bodies in cases of delayed recovery, relevant findings can be masked or destroyed and therefor being inaccessible in standard pathology practice comprising just forensic autopsy and histopathology. Such cases are of considerable risk of remaining unsolved without legal consequences for those responsible. Further, no lessons can be drawn from these scenarios to improve flight safety and prevent future mishaps. Aims and Methods: To learn from previously unsolved aircraft accidents, re-evaluations of the investigation files and modern molecular pathology studies were performed. Genetic testing involved predominantly PCR-based analysis of gene regulation, studying DNA promotor methylations, RNA transcription and posttranscriptional regulation. In addition, the presence or absence of infective agents, particularly DNA- and RNA-viruses, was studied. Technical adjustments of molecular genetic procedures when working with archived sample material were necessary. Standards for the proper interpretation of the respective findings had to be settled. Results and Discussion: Additional molecular genetic testing significantly contributes to the quality of forensic pathology assessment in aviation mishaps. Previously undetected cardiotropic viruses potentially explain e.g., a pilot’s sudden incapacitation resulting from cardiac failure or myocardial arrhythmia. In contrast, negative results for infective agents participate in ruling out concerns about an accident pilot’s fitness to fly and the aeromedical examiner’s precedent decision to issue him or her an aeromedical certificate. Care must be taken in the interpretation of genetic testing for pre-existing diseases such as hypertrophic cardiomyopathy or ischemic heart disease. Molecular markers such as mRNAs or miRNAs, which can establish these diagnoses in clinical patients, might be misleading in-flight crew members because of adaptive changes in their tissues resulting from repeated mild hypoxia during flight, for instance. Military pilots especially demonstrate significant physiological adjustments to their somatic burdens in flight, such as cardiocirculatory stress and air combat maneuvers. Their non-pathogenic alterations in gene regulation and expression will likely be misinterpreted for genuine disease by inexperienced investigators. Conclusions: The growing influence of molecular pathology on legal medicine practice has found its way into aircraft accident investigation. As appropriate quality standards for laboratory work and data interpretation are provided, forensic genetic testing supports the medico-legal analysis of aviation mishaps and potentially reduces the number of unsolved events in the future.

Keywords: aviation medicine, aircraft accident investigation, forensic pathology, molecular pathology

Procedia PDF Downloads 25