Search results for: Deep learning

Authors: Ebert Brea

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We propose a novel direct search algorithm for identifying at least a local minimum of mixed integer nonlinear unconstrained optimization problems. The Mixed Integer Randomized Pattern Search Algorithm (MIRPSA), so-called by the author, is based on a randomized pattern search, which is modified by the MIRPSA for finding at least a local minimum of our problem. The MIRPSA has two main operations over the randomized pattern search: moving operation and shrinking operation. Each operation is carried out by the algorithm when a set of conditions is held. The convergence properties of the MIRPSA is analyzed using a Markov chain approach, which is represented by an infinite countable set of state space λ, where each state d(q) is defined by a measure of the qth randomized pattern search Hq, for all q in N. According to the algorithm, when a moving operation is carried out on the qth randomized pattern search Hq, the MIRPSA holds its state. Meanwhile, if the MIRPSA carries out a shrinking operation over the qth randomized pattern search Hq, the algorithm will visit the next state, this is, a shrinking operation at the qth state causes a changing of the qth state into (q+1)th state. It is worthwhile pointing out that the MIRPSA never goes back to any visited states because the MIRPSA only visits any qth by shrinking operations. In this article, we describe the MIRPSA for mixed integer nonlinear unconstrained optimization problems for doing a deep study of its convergence properties using Markov chain viewpoint. We herein include a low dimension case for showing more details of the MIRPSA, when the algorithm is used for identifying the minimum of a mixed integer quadratic function. Besides, numerical examples are also shown in order to measure the performance of the MIRPSA.

Keywords: direct search, mixed integer optimization, random search, convergence, Markov chain

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Authors: A. Giannakopoulos, S. B. Buckley

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Problem solving in any field is recognised as a prerequisite for any advancement in knowledge. For example in South Africa it is one of the seven critical outcomes of education together with critical thinking. As a systematic way to problem solving was initiated in mathematics by the great mathematician George Polya (the father of problem solving), more detailed and comprehensive ways in problem solving have been developed. This paper is based on the findings by the author and subsequent recommendations for further research in problem solving and critical thinking. Although the study was done in mathematics, there is no doubt by now in almost anyone’s mind that mathematics is involved to a greater or a lesser extent in all fields, from symbols, to variables, to equations, to logic, to critical thinking. Therefore it stands to reason that mathematical principles and learning cannot be divorced from any field. In management of knowledge situations, the types of problems are similar to mathematics problems varying from simple to analogical to complex; from well-structured to ill-structured problems. While simple problems could be solved by employees by adhering to prescribed sequential steps (the process), analogical and complex problems cannot be proceduralised and that diminishes the capacity of the organisation of knowledge creation and innovation. The low efficiency in some organisations and the low pass rates in mathematics prompted the author to view problem solving as a product. The authors argue that using mathematical approaches to knowledge management problem solving and treating problem solving as a product will empower the employee through further training to tackle analogical and complex problems. The question the authors asked was: If it is true that problem solving and critical thinking are indeed basic skills necessary for advancement of knowledge why is there so little literature of knowledge management (KM) about them and how they are connected and advance KM?This paper concludes with a conceptual model which is based on general accepted principles of knowledge acquisition (developing a learning organisation), knowledge creation, sharing, disseminating and storing thereof, the five pillars of knowledge management (KM). This model, also expands on Gray’s framework on KM practices and problem solving and opens the doors to a new approach to training employees in general and domain specific areas problems which can be adapted in any type of organisation.

Keywords: critical thinking, knowledge management, mathematics, problem solving

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Authors: Fadlan Atmaja Nursiwan, Ugi Kurnia Gusti

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Garba Hill, located in Tekana Village, South Sumatera Province is comprised to South Sumatra Basin and classified as back arc basin. This area is entered as an active margin of Sundaland which experiences subduction several times since Mesozoic to recent time. The traces of Mesozoic subduction in the southern part of Sumatra island are exposed in Garba Hill area. The aim of this investigation is to study the tectonic changes in the first phase in Mesozoic era at the active margin of Sundaland which causes the rocks assemblage in Garba hill consist of continental and oceanic plate rocks which the correlation between those rocks show indistinct relation. This investigation is conducted by field observation in Tekana village and Lubar Village, Muara Dua, South Sumatra along with laboratory analysis included fossil and geochemistry analysis of radiolarian chert, petrography analysis of granite and basalt, and structural modelling. Fossil and geochemistry analysis of radiolarian chert and geochemistry of granite rocks shown the relation between the two rocks and Mesozoic subduction of Woyla terrane on western margin of Sundaland. Petrography analysis from granite and basalt depict the tectonic affinity of rocks. Moreover, structural analysis showed the changes of lineation direction from N-S to WNW-ESE.

Keywords: granite, mesozoic, radiolarian, subduction traces

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Authors: Ugochukwu Ejike Akpudo, Jank-Wook Hur

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The increasing demand for improved productivity, maintainability, and reliability has prompted rapidly increasing research studies on the emerging condition-based maintenance concept- Prognostics and health management (PHM). Varieties of fuel pumps serve critical functions in several hydraulic systems; hence, their failure can have daunting effects on productivity, safety, etc. The need for condition monitoring and assessment of these pumps cannot be overemphasized, and this has led to the uproar in research studies on standard feature extraction techniques for optimized condition assessment of fuel pumps. By extracting time-based, frequency-based and the more robust time-frequency based features from these vibrational signals, a more comprehensive feature assessment (and selection) can be achieved for a more accurate and reliable condition assessment of these pumps. With the aid of emerging deep classification and regression algorithms like the locally linear embedding (LLE), we propose a method for comprehensive condition assessment of electromagnetic fuel pumps (EMFPs). Results show that the LLE as a comprehensive feature extraction technique yields better feature fusion/dimensionality reduction results for condition assessment of EMFPs against the use of single features. Also, unlike other feature fusion techniques, its capabilities as a fault classification technique were explored, and the results show an acceptable accuracy level using standard performance metrics for evaluation.

Keywords: electromagnetic fuel pumps, comprehensive feature extraction, condition assessment, locally linear embedding, feature fusion

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Authors: Tommy Krieger, Klaus Gruendler

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We present a novel approach for measuring democracy, which enables a very detailed and sensitive index. This method is based on Support Vector Machines, a mathematical algorithm for pattern recognition. Our implementation evaluates 188 countries in the period between 1981 and 2011. The Support Vector Machines Democracy Index (SVMDI) is continuously on the 0-1-Interval and robust to variations in the numerical process parameters. The algorithm introduced here can be used for every concept of democracy without additional adjustments, and due to its flexibility it is also a valuable tool for comparison studies.

Keywords: democracy, democracy index, machine learning, support vector machines

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Authors: Volker Koch

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This paper deals with the education of purchasing professionals in Austria. In this education, equivalent and measurable criteria are collected in order to create a comparison. The comparison shows the problem. To make the aforementioned comparison possible, methodologies such as KODE-Competence Atlas or presentations in a matrix form are used. The result shows the content taught and whether there are any similarities or interesting differences in the current Austrian purchasers’ formations. Purchasing professionals learning competencies are also illustrated in the study result.

Keywords: competencies, education, purchasing professional, technological-oriented

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Authors: Sereen Itani

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As the world aspires for technological innovation, Innovative Robotics Technology-Supported Pedagogic Models in STEAM Education (Science, Technology, Engineering, Arts, and Mathematics) are critical in our global education system to build and enhance the next generation 21st century skills. Thus, diverse international schools endeavor in attempts to construct an integrated robotics and technology enhanced curriculum based on interdisciplinary subjects. Accordingly, it is vital that the globe remains resilient in STEAM fields by equipping the future learners and educators with Innovative Technology Experiences through robotics to support such fields. A variety of advanced teaching methods is employed to learn about Robotics Technology-integrated pedagogic models. Therefore, it is only when STEAM and innovations in Robotic Technology becomes integrated with real-world applications that transformational learning can occur. Robotics STEAM education implementation faces major challenges globally. Moreover, STEAM skills and concepts are communicated in separation from the real world. Instilling the passion for robotics and STEAM subjects and educators’ preparation could lead to the students’ majoring in such fields by acquiring enough knowledge to make vital contributions to the global STEAM industries. Thus, this necessitates the establishment of Pedagogic models such as Innovative Robotics Technologies to enhance STEAM education and develop students’ 21st-century skills. Moreover, an ICT innovative supported robotics classroom will help educators empower and assess students academically. Globally, the Robotics Design System and platforms are developing in schools and university labs creating a suitable environment for the robotics cross-discipline STEAM learning. Accordingly, the research aims at raising awareness about the importance of robotics design systems and methodologies of effective employment of robotics innovative technology-supported pedagogic models to enhance and develop (STEAM) education globally and enhance the next generation 21st century skills.

Keywords: education, robotics, STEAM (Science, Technology, Engineering, Arts and Mathematics Education), challenges

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Authors: Yichao Liu, Peter Fransson, Julian Heidecke, Jonas Wallin, Joacim Rockloev

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Dengue, a mosquito-borne viral disease, poses a significant public health challenge in endemic tropical or subtropical countries, including Sri Lanka. To reveal insights into the complexity of the dynamics of this disease and study the drivers, a comprehensive model capable of both robust forecasting and insightful inference of drivers while capturing the co-circulating of several virus strains is essential. However, existing studies mostly focus on only one aspect at a time and do not integrate and carry insights across the siloed approach. While mechanistic models are developed to capture immunity dynamics, they are often oversimplified and lack integration of all the diverse drivers of disease transmission. On the other hand, purely data-driven methods lack constraints imposed by immuno-epidemiological processes, making them prone to overfitting and inference bias. This research presents a hybrid model that combines machine learning techniques with mechanistic modelling to overcome the limitations of existing approaches. Leveraging eight years of newly reported dengue case data, along with socioeconomic factors, such as human mobility, weekly climate data from 2011 to 2018, genetic data detecting the introduction and presence of new strains, and estimates of seropositivity for different districts in Sri Lanka, we derive a data-driven vector (SEI) to human (SEIR) model across 16 regions in Sri Lanka at the weekly time scale. By conducting ablation studies, the lag effects allowing delays up to 12 weeks of time-varying climate factors were determined. The model demonstrates superior predictive performance over a pure machine learning approach when considering lead times of 5 and 10 weeks on data withheld from model fitting. It further reveals several interesting interpretable findings of drivers while adjusting for the dynamics and influences of immunity and introduction of a new strain. The study uncovers strong influences of socioeconomic variables: population density, mobility, household income and rural vs. urban population. The study reveals substantial sensitivity to the diurnal temperature range and precipitation, while mean temperature and humidity appear less important in the study location. Additionally, the model indicated sensitivity to vegetation index, both max and average. Predictions on testing data reveal high model accuracy. Overall, this study advances the knowledge of dengue transmission in Sri Lanka and demonstrates the importance of incorporating hybrid modelling techniques to use biologically informed model structures with flexible data-driven estimates of model parameters. The findings show the potential to both inference of drivers in situations of complex disease dynamics and robust forecasting models.

Keywords: compartmental model, climate, dengue, machine learning, social-economic

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Authors: Beier Zhu, Rui Zhang, Qi Song

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Text contained within fixed-layout documents can be of great semantic value and so requires a high localization accuracy, such as ID cards, invoices, cheques, and passports. Recently, algorithms based on deep convolutional networks achieve high performance on text detection tasks. However, for text localization in fixed-layout documents, such algorithms detect word bounding boxes individually, which ignores the layout information. This paper presents a novel architecture built on convolutional neural networks (CNNs). A global text localization network and a regional bounding-box regression network are introduced to tackle the problem in a coarse-to-fine manner. The text localization network simultaneously locates word bounding points, which takes the layout information into account. The bounding-box regression network inputs the features pooled from arbitrarily sized RoIs and refine the localizations. These two networks share their convolutional features and are trained jointly. A typical type of fixed-layout documents: ID cards, is selected to evaluate the effectiveness of the proposed system. These networks are trained on data cropped from nature scene images, and synthetic data produced by a synthetic text generation engine. Experiments show that our approach locates high accuracy word bounding boxes and achieves state-of-the-art performance.

Keywords: bounding box regression, convolutional networks, fixed-layout documents, text localization

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Authors: Asma Ameur, Dhafer Malouche

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Nowadays, user comments on the Internet have an important impact on hotel bookings. This confirms that the e-reputation issue can influence the likelihood of customer loyalty to a hotel. In this way, e-reputation has become a real differentiator between hotels. For this reason, we have a unique opportunity in the opinion mining field to analyze the comments. In fact, this field provides the possibility of extracting information related to the polarity of user reviews. This sentimental study (Opinion Mining) represents a new line of research for analyzing the unstructured textual data. Knowing the score of e-reputation helps the hotelier to better manage his marketing strategy. The score we then obtain is translated into the image of hotels to differentiate between them. Therefore, this present research highlights the importance of hotel satisfaction ‘scoring. To calculate the satisfaction score, the sentimental analysis can be manipulated by several techniques of machine learning. In fact, this study treats the extracted textual data by using the Artificial Neural Networks Approach (ANNs). In this context, we adopt the aforementioned technique to extract information from the comments available in the ‘Trip Advisor’ website. This actual paper details the description and the modeling of the ANNs approach for the scoring of online hotel reviews. In summary, the validation of this used method provides a significant model for hotel sentiment analysis. So, it provides the possibility to determine precisely the polarity of the hotel users reviews. The empirical results show that the ANNs are an accurate approach for sentiment analysis. The obtained results show also that this proposed approach serves to the dimensionality reduction for textual data’ clustering. Thus, this study provides researchers with a useful exploration of this technique. Finally, we outline guidelines for future research in the hotel e-reputation field as comparing the ANNs with other technique.

Keywords: clustering, consumer behavior, data mining, e-reputation, machine learning, neural network, online hotel ‘reviews, opinion mining, scoring

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Authors: Mohammad Hossein Badamchi

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As Leo Strauss demonstrates in his works, Political Philosophy in the western tradition is an epistemic-naturalistic tradition insofar Hanna Arendt mentioning the deep conflict between philosophy and politics, opposed to be named “political philosopher” prefer the title “political thinker” for herself. In fact, the Western political philosophy’s tendency to derive politics from natural law and epistemic argumentations makes a paradox between the actual “the political” and the theoretical “natural politics” in the western tradition. In this paper, we want to show that Hanna Arendt, in her exploration to find a new realm of the non-naturalistic way of thinking about the political is walking on a completely different tradition of political philosophy which was first established by Al-Farabi, the founder of Islamic political philosophy around thousand years after Greek Philosophy. Despite Aristotelian Polis which is a Natural community based on true natural rationality to reach the natural purposes of mankind, Al-Farabi’s Madine (his reconstructed concept of Aristotelian Polis) is completely constructed against natural cities, which are formulated by necessity logic of natural arguments and natural deception of humanity. In fact, Farabi considers the natural understanding of politics as Ignorant ideologies used by governments to suppress people. Madine in Farabi’s work is not a natural institution but is a collaborative constitution founded by citizens. So despite Aristotelian thinking, here we don’t have just A Polis that is the one true polis, but we have various multiple Madines among one, is virtuous not by definition but by real action of citizens and civil relations. Al-Farabi’s political philosophy is not a Naturalistic-epistemic Political Philosophy but is a Phronetic Political Philosophy which Hanna Arendt wants to establish outside of western contemplative anti-active political philosophy tradition.

Keywords: al-farabi, hanna arendt, natural politics, the political, political philosophy

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Authors: Carly Nesvat, Dominic Jarrett, Colin Thomson, Wilma Coltart, Thelma Bowers, Jan Thomson

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Introduction: Within Scotland, the Same As You strategy committed to moving people with learning disabilities out of long-stay hospital accommodation into homes in the community. Much of the focus of this movement was on the placement of people within individual homes. In order to achieve this, potentially excessive supports were put in place which created dependence, and carried significant ongoing cost primarily for local authorities. The greater focus on empowerment and community participation which has been evident in more recent learning disability strategy, along with the financial pressures being experienced across the public sector, created an imperative to re-examine that provision, particularly in relation to the use of expensive sleepover supports to individuals, and the potential for this to be appropriately scaled back through the use of telecare. Method: As part of a broader programme of redesigning overnight supports within North Ayrshire, a cluster of individuals living in close proximity were identified, who were in receipt of overnight supports, but who were identified as having the capacity to potentially benefit from their removal. In their place, a responder service was established (an individual staying overnight in a nearby service user’s home), and a variety of telecare solutions were placed within individual’s homes. Active and passive technology was connected to an Alarm Receiving Centre, which would alert the local responder service when necessary. Individuals and their families were prepared for the change, and continued to be informed about progress with the pilot. Results: 4 individuals, 2 of whom shared a tenancy, had their sleepover supports removed as part of the pilot. Extensive data collection in relation to alarm activation was combined with feedback from the 4 individuals, their families, and staff involved in their support. Varying perspectives emerged within the feedback. 3 of the individuals were clearly described as benefitting from the change, and the greater sense of independence it brought, while more concerns were evident in relation to the fourth. Some family members expressed a need for greater preparation in relation to the change and ongoing information provision. Some support staff also expressed a need for more information, to help them understand the new support arrangements for an individual, as well as noting concerns in relation to the outcomes for one participant. Conclusion: Developing a telecare response in relation to a cluster of individuals was facilitated by them all being supported by the same care provider. The number of similar clusters of individuals being identified within North Ayrshire is limited. Developing other solutions such as a response service for redesign will potentially require greater collaboration between different providers of home support, as well as continuing to explore the full range of telecare, including digital options. The pilot has highlighted the need for effective preparatory and ongoing engagement with staff and families, as well as the challenges which can accompany making changes to long-standing packages of support.

Keywords: challenges, change, engagement, telecare

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Authors: Piotr A. Kowalski, Kasper Sapala, Wiktor Warchalowski

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PM10 is a suspended dust that primarily has a negative effect on the respiratory system. PM10 is responsible for attacks of coughing and wheezing, asthma or acute, violent bronchitis. Indirectly, PM10 also negatively affects the rest of the body, including increasing the risk of heart attack and stroke. Unfortunately, Poland is a country that cannot boast of good air quality, in particular, due to large PM concentration levels. Therefore, based on the dense network of Airly sensors, it was decided to deal with the problem of prediction of suspended particulate matter concentration. Due to the very complicated nature of this issue, the Machine Learning approach was used. For this purpose, Convolution Neural Network (CNN) neural networks have been adopted, these currently being the leading information processing methods in the field of computational intelligence. The aim of this research is to show the influence of particular CNN network parameters on the quality of the obtained forecast. The forecast itself is made on the basis of parameters measured by Airly sensors and is carried out for the subsequent day, hour after hour. The evaluation of learning process for the investigated models was mostly based upon the mean square error criterion; however, during the model validation, a number of other methods of quantitative evaluation were taken into account. The presented model of pollution prediction has been verified by way of real weather and air pollution data taken from the Airly sensor network. The dense and distributed network of Airly measurement devices enables access to current and archival data on air pollution, temperature, suspended particulate matter PM1.0, PM2.5, and PM10, CAQI levels, as well as atmospheric pressure and air humidity. In this investigation, PM2.5, and PM10, temperature and wind information, as well as external forecasts of temperature and wind for next 24h served as inputted data. Due to the specificity of the CNN type network, this data is transformed into tensors and then processed. This network consists of an input layer, an output layer, and many hidden layers. In the hidden layers, convolutional and pooling operations are performed. The output of this system is a vector containing 24 elements that contain prediction of PM10 concentration for the upcoming 24 hour period. Over 1000 models based on CNN methodology were tested during the study. During the research, several were selected out that give the best results, and then a comparison was made with the other models based on linear regression. The numerical tests carried out fully confirmed the positive properties of the presented method. These were carried out using real ‘big’ data. Models based on the CNN technique allow prediction of PM10 dust concentration with a much smaller mean square error than currently used methods based on linear regression. What's more, the use of neural networks increased Pearson's correlation coefficient (R²) by about 5 percent compared to the linear model. During the simulation, the R² coefficient was 0.92, 0.76, 0.75, 0.73, and 0.73 for 1st, 6th, 12th, 18th, and 24th hour of prediction respectively.

Keywords: air pollution prediction (forecasting), machine learning, regression task, convolution neural networks

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Authors: Forouzan Salehi Fergeni

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Converting the movement intents of a person into commands for action employing brain signals like electroencephalogram signals is a brain-computer interface (BCI) system. When left or right-hand motions are imagined, different patterns of brain activity appear, which can be employed as BCI signals for control. To make better the brain-computer interface (BCI) structures, effective and accurate techniques for increasing the classifying precision of motor imagery (MI) based on electroencephalography (EEG) are greatly needed. Subject dependency and non-stationary are two features of EEG signals. So, EEG signals must be effectively processed before being used in BCI applications. In the present study, after applying an 8 to 30 band-pass filter, a car spatial filter is rendered for the purpose of denoising, and then, a method of analysis of variance is used to select more appropriate and informative channels from a category of a large number of different channels. After ordering channels based on their efficiencies, a sequential forward channel selection is employed to choose just a few reliable ones. Features from two domains of time and wavelet are extracted and shortlisted with the help of a statistical technique, namely the t-test. Finally, the selected features are classified with different machine learning and neural network classifiers being k-nearest neighbor, Probabilistic neural network, support-vector-machine, Extreme learning machine, decision tree, Multi-layer perceptron, and linear discriminant analysis with the purpose of comparing their performance in this application. Utilizing a ten-fold cross-validation approach, tests are performed on a motor imagery dataset found in the BCI competition III. Outcomes demonstrated that the SVM classifier got the greatest classification precision of 97% when compared to the other available approaches. The entire investigative findings confirm that the suggested framework is reliable and computationally effective for the construction of BCI systems and surpasses the existing methods.

Keywords: brain-computer interface, channel selection, motor imagery, support-vector-machine

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Authors: Irene Capecchi, Tommaso Borghini, Iacopo Bernetti

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An important tool for the enhancement of cultural sites is serious games (SG), i.e., games designed for educational purposes; SG is applied in cultural sites through trivia, puzzles, and mini-games for participation in interactive exhibitions, mobile applications, and simulations of past events. The combination of Augmented Reality (AR) and digital cultural content has also produced examples of cultural heritage recovery and revitalization around the world. Through AR, the user perceives the information of the visited place in a more real and interactive way. Another interesting technological development for the revitalization of cultural sites is the combination of AR and Global Positioning System (GPS), which integrated have the ability to enhance the user's perception of reality by providing historical and architectural information linked to specific locations organized on a route. To the author’s best knowledge, there are currently no applications that combine GPS AR and SG for cultural heritage revitalization. The present research focused on the development of an SG based on GPS and AR. The study area is the village of Caldana in Tuscany, Italy. Caldana is a fortified Renaissance village; the most important architectures are the walls, the church of San Biagio, the rectory, and the marquis' palace. The historical information is derived from extensive research by the Department of Architecture at the University of Florence. The storyboard of the SG is based on the history of the three characters who built the village: marquis Marcello Agostini, who was commissioned by Cosimo I de Medici, Grand Duke of Tuscany, to build the village, his son Ippolito and his architect Lorenzo Pomarelli. The three historical characters were modeled in 3D using the freeware MakeHuman and imported into Blender and Mixamo to associate a skeleton and blend shapes to have gestural animations and reproduce lip movement during speech. The Unity Rhubarb Lip Syncer plugin was used for the lip sync animation. The historical costumes were created by Marvelous Designer. The application was developed using the Unity 3D graphics and game engine. The AR+GPS Location plugin was used to position the 3D historical characters based on GPS coordinates. The ARFoundation library was used to display AR content. The SG is available in two versions: for children and adults. the children's version consists of finding a digital treasure consisting of valuable items and historical rarities. Players must find 9 village locations where 3D AR models of historical figures explaining the history of the village provide clues. To stimulate players, there are 3 levels of rewards for every 3 clues discovered. The rewards consist of AR masks for archaeologist, professor, and explorer. At the adult level, the SG consists of finding the 16 historical landmarks in the village, and learning historical and architectural information interactively and engagingly. The application is being tested on a sample of adults and children. Test subjects will be surveyed on a Likert scale to find out their perceptions of using the app and the learning experience between the guided tour and interaction with the app.

Keywords: augmented reality, cultural heritage, GPS, serious game

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Authors: Michal Pachocki

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This study investigates the effects of mobility in the context of a different environment and work culture through analysing the learners perception of their international work experience. Since this kind of professional training abroad is becoming more popular in Europe, mainly due to the EU funding opportunities, it is of paramount importance to assess its long-term impact on educational and career paths of former students. Moreover, the tracer study aimed at defining what professional, social and intercultural competencies were gained or developed by the interns and to which extent those competences proved to be useful meeting the labor market requirements. Being a populous EU member state which actively modernizes its vocational education system (also with European funds), Poland can serve as an illustrative case study to investigate the above described research problems. However, the examined processes are most certainly universal, wherever mobility is included in the learning process. The target group of this research was the former mobility participants and the study was conducted using quantitative and qualitative methods, such as the online survey with over 2 600 questionnaires completed by the former mobility participants; -individual in-depth interviews (IDIs) with 20 Polish graduates already present in the labour market; - 5 focus group interviews (FGIs) with 60 current students of the Polish vocational schools, who have recently returned from the training abroad. As the adopted methodology included a data triangulation, the collected findings have also been supplemented with data obtained by the desk research (mainly contextual information and statistical summary of mobility implementation). The results of this research – to be presented in full scope within the conference presentation – include the participants’ perception of their work mobility. The vast majority of graduates agrees that such an experience has had a significant impact on their professional careers and claims that they would recommend training abroad to persons who are about to enter the labor market. Moreover, in their view, such form of practical training going beyond formal education provided them with an opportunity to try their hand in the world of work. This allowed them – as they accounted for them – to get acquainted with a work system and context different from the ones experienced in Poland. Although the work mobility becomes an important element of the learning process in the growing number of Polish schools, this study reveals that many sending institutions suffer from a lack of the coherent strategy for planning domestic and foreign training programmes. Nevertheless, the significant number of graduates claims that such a synergy improves the quality of provided training. Despite that, the research proved that the transnational mobilities exert an impact on their future careers and personal development. However, such impact is, in their opinion, dependant on other factors, such as length of the training period, the nature and extent of work, recruitment criteria and the quality of organizational arrangement and mentoring provided to learners. This may indicate the salience of the sending and receiving institutions organizational capacity to deal with mobility.

Keywords: learning mobility, transnational training, vocational education and training graduates, tracer study

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Authors: Ankit Sinha, Soham Banerjee, Pratik Chattopadhyay

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Automated product recognition in retail stores is an important real-world application in the domain of Computer Vision and Pattern Recognition. In this paper, we consider the problem of automatically identifying the classes of the products placed on racks in retail stores from an image of the rack and information about the query/product images. We improve upon the existing approaches in terms of effectiveness and memory requirement by developing a two-stage object detection and recognition pipeline comprising of a Faster-RCNN-based object localizer that detects the object regions in the rack image and a ResNet-18-based image encoder that classifies the detected regions into the appropriate classes. Each of the models is fine-tuned using appropriate data sets for better prediction and data augmentation is performed on each query image to prepare an extensive gallery set for fine-tuning the ResNet-18-based product recognition model. This encoder is trained using a triplet loss function following the strategy of online-hard-negative-mining for improved prediction. The proposed models are lightweight and can be connected in an end-to-end manner during deployment to automatically identify each product object placed in a rack image. Extensive experiments using Grozi-32k and GP-180 data sets verify the effectiveness of the proposed model.

Keywords: retail stores, faster-RCNN, object localization, ResNet-18, triplet loss, data augmentation, product recognition

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Authors: E. Oliver, A. Cebolla, A. Dominguez, A. Gonzalez-Segura, E. de la Cruz, S. Albertini, L. Ferrini, K. Kronika, T. Nilsen, R. Baños

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The main objective of MEAL is to develop a pedagogical tool aimed to help teachers and nutritionists (students and professionals) to acquire, train, promote and deliver to children basic nutritional education and healthy eating behaviours competencies. MEAL is focused on eating behaviours and not only in nutritional literacy, and will use new technologies like Information and Communication Technologies (ICTs) and serious games (SG) platforms to consolidate the nutritional competences and habits.

Keywords: nutritional education, pedagogical ICT platform, serious games, training course

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Authors: Antonio M. Oliveira, Patricia Oliveira-Silva, Jose Matias Alves, Gary McPherson

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The music teaching is oriented towards offering formal music training. Due to its specificities, this vocational program starts at a very young age. Although provided by the State, the offer is limited to 6 schools throughout the country, which means that the vacancies for prospective students are very limited every year. It is therefore crucial that these vacancies be taken by especially motivated children grown within households that offer the ideal setting for success. Some of the instruments used to evaluate musical performance are highly sensitive to specific previous training, what represents a severe validity problem for testing children who have had restricted opportunities for formal training. Moreover, these practices may be unfair because, for instance, they may not reflect the candidates’ music aptitudes. Based on what constitutes a prerequisite for making an excellent music student, researchers in this field have long argued that motivation, task commitment, and parents’ support are as important as ability. Thus, the aim of this study is: (1) to prepare an inventory of admission requirements in Australia, Portugal and Ireland; (2) to examine whether the candidates to music conservatories and parents’ level of motivation, assessed at three evaluation points (i.e., admission, at the end of the first year, and at the end of the second year), correlates positively with the candidates’ progress in learning a musical instrument (i.e., whether motivation at the admission may predict student musicianship); (3) an adaptation of an existing instrument to assess the motivation (i.e., to adapt the items to the music setting, focusing on the motivation for playing a musical instrument). The inclusion criteria are: only children registered in the administrative services to be evaluated for entrance to the conservatory will be accepted for this study. The expected number of participants is fifty (5-6 years old) in all the three frequency schemes: integrated, articulated and supplementary. Revisiting musical admission procedures is of particular importance and relevance to musical education because this debate may bring guidance and assistance about the needed improvement to make the process of admission fairer and more transparent.

Keywords: music learning, music admission requirements, student’s motivation, parent’s motivation

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Authors: Elham Shirvani-Ghadikolaei

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In this paper, we examine the connection between the human mind and body within the framework of Merleau-Ponty's phenomenology. We study the role of this connection in designing more efficient learning environments, alongside the findings in physical recognition and educational neuroscience. Our research shows the interplay between the mind and the body in the external world and discusses its implications. Based on these observations, we make suggestions as to how the educational system can benefit from taking into account the interaction between the mind and the body in educational affairs.

Keywords: educational neurosciences, embodied cognition, pedagogical neurosciences, phenomenology

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Authors: Ricardo Avila, Gabriel Lopes, Vania Vidal, Jose Macedo

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This article offers a approach to the automatic discovery of semantic concepts and links in the domain of Oil Exploration and Production (E&P). Machine learning methods combined with textual pre-processing techniques were used to detect local patterns in texts and, thus, generate new concepts and new semantic links. Even using more specific vocabularies within the oil domain, our approach has achieved satisfactory results, suggesting that the proposal can be applied in other domains and languages, requiring only minor adjustments.

Keywords: semantic links, data mining, linked data, SKOS

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Authors: Kuo-Kai Lin, Po-Lun Chang

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Research Background and Purpose: Following the development of the Internet and multimedia, the Internet and information technology have become crucial avenues of modern communication and knowledge acquisition. The advantages of using mobile devices for learning include making learning borderless and accessible. Mobile learning has become a trend in disease management and health promotion in recent years. End-stage renal disease (ESRD) is an irreversible chronic disease, and patients who do not receive kidney transplants can only rely on hemodialysis or peritoneal dialysis to survive. Due to the complexities in caregiving for patients with ESRD that stem from their advanced age and other comorbidities, the patients’ incapacity of self-care leads to an increase in the need to rely on their families or primary caregivers, although whether the primary caregivers adequately understand and implement patient care is a topic of concern. Therefore, this study explored whether primary caregivers’ health care provisions can be improved through the intervention of an automatic speech intelligent system, thereby improving the objective health outcomes of patients undergoing long-term dialysis. Method: This study developed an automatic speech intelligent system with healthcare functions such as health information voice prompt, two-way feedback, real-time push notification, and health information delivery. Convenience sampling was adopted to recruit eligible patients from a hemodialysis center at a regional teaching hospital as research participants. A one-group pretest-posttest design was adopted. Descriptive and inferential statistics were calculated from the demographic information collected from questionnaires answered by patients and primary caregivers, and from a medical record review, a health care scale (recorded six months before and after the implementation of intervention measures), a subjective health assessment, and a report of objective physiological indicators. The changes in health care behaviors, subjective health status, and physiological indicators before and after the intervention of the proposed automatic speech intelligent system were then compared. Conclusion and Discussion: The preliminary automatic speech intelligent system developed in this study was tested with 20 pretest patients at the recruitment location, and their health care capacity scores improved from 59.1 to 72.8; comparisons through a nonparametric test indicated a significant difference (p < .01). The average score for their subjective health assessment rose from 2.8 to 3.3. A survey of their objective physiological indicators discovered that the compliance rate for the blood potassium level was the most significant indicator; its average compliance rate increased from 81% to 94%. The results demonstrated that this automatic speech intelligent system yielded a higher efficacy for chronic disease care than did conventional health education delivered by nurses. Therefore, future efforts will continue to increase the number of recruited patients and to refine the intelligent system. Future improvements to the intelligent system can be expected to enhance its effectiveness even further.

Keywords: automatic speech intelligent system for health care, primary caregiver, long-term hemodialysis, health care capabilities, health outcomes

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Authors: Peter Akayuure

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One key determinant of the quality of mathematics learning is the teacher’s ability to assess students adequately and effectively and make assessment an integral part of the instructional practices. If the mathematics teacher lacks the required literacy to perform classroom assessment roles, the true trajectory of learning success and attainment of curriculum expectations might be indeterminate. It is therefore important that educators and policymakers understand and seek ways to improve the literacy level of mathematics teachers to implement classroom assessments that would meet curriculum demands. This study employed a descriptive survey design to explore perceived levels of assessment literacy of mathematics teachers to implement classroom assessment with the school based assessment framework in Ghana. A 25-item classroom assessment inventory on teachers’ assessment scenarios was adopted, modified, and administered to a purposive sample of 48 mathematics teachers from eleven Senior High Schools. Seven other items were included to further collect data on their self-efficacy towards assessment literacy. Data were analyzed using descriptive and bivariate correlation statistics. The result shows that, on average, 48.6% of the mathematics teachers attained standard levels of assessment literacy. Specifically, 50.0% met standard one in choosing appropriate assessment methods, 68.3% reached standard two in developing appropriate assessment tasks, 36.6% reached standard three in administering, scoring, and interpreting assessment results, 58.3% reached standard four in making appropriate assessment decisions, 41.7% reached standard five in developing valid grading procedures, 45.8% reached standard six in communicating assessment results, and 36.2 % reached standard seven by identifying unethical, illegal and inappropriate use of assessment results. Participants rated their self-efficacy belief in performing assessments high, making the relationships between participants’ assessment literacy scores and self-efficacy scores weak and statistically insignificant. The study recommends that institutions training mathematics teachers or providing professional developments should accentuate assessment literacy development to ensure standard assessment practices and quality instruction in mathematics education at senior high schools.

Keywords: assessment literacy, mathematics teacher, senior high schools, Ghana

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Authors: Andrei Nosov

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This paper discusses the development directions of dialogue systems within the digitalisation of the railway industry, where technologies based on conversational AI are already potentially applied or will be applied. Conversational AI is one of the popular natural language processing (NLP) tasks, as it has great prospects for real-world applications today. At the same time, it is a challenging task as it involves many areas of NLP based on complex computations and deep insights from linguistics and psychology. In this review, we focus on dialogue systems and their implementation in the railway domain. We comprehensively review the state-of-the-art research results on dialogue systems and analyse them from three perspectives: type of problem to be solved, type of model, and type of system. In particular, from the perspective of the type of tasks to be solved, we discuss characteristics and applications. This will help to understand how to prioritise tasks. In terms of the type of models, we give an overview that will allow researchers to become familiar with how to apply them in dialogue systems. By analysing the types of dialogue systems, we propose an unconventional approach in contrast to colleagues who traditionally contrast goal-oriented dialogue systems with open-domain systems. Our view focuses on considering retrieval and generative approaches. Furthermore, the work comprehensively presents evaluation methods and datasets for dialogue systems in the railway domain to pave the way for future research. Finally, some possible directions for future research are identified based on recent research results.

Keywords: digitalisation, railway, dialogue systems, conversational AI, natural language processing, natural language understanding, natural language generation

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Authors: R. Ziaie Moayed, E. Ghanbari Alamouty

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Deep soil mixing is one of the improvement methods in geotechnical engineering which is widely used in soft soils. This article investigates the consolidation behavior of a soft clay soil which is improved by soil-cement column (SCC) by numerical modeling using Plaxis2D program. This behavior is simulated under vertical static and cyclic load which is applied on the soil surface. The static load problem is the simulation of a physical model test in an axisymmetric condition which uses a single SCC in the model center. The results of numerical modeling consist of settlement of soft soil composite, stress on soft soil and column, and excessive pore water pressure in the soil show a good correspondence with the test results. The response of soft soil composite to the cyclic load in vertical direction also compared with the static results. Also the effects of two variables namely the cement content used in a SCC and the area ratio (the ratio of the diameter of SCC to the diameter of composite soil model, a) is investigated. The results show that the stress on the column with the higher value of a, is lesser compared with the stress on other columns. Different rate of consolidation and excessive pore pressure distribution is observed in cyclic load problem. Also comparing the results of settlement of soil shows higher compressibility in the cyclic load problem.

Keywords: area ratio, consolidation behavior, cyclic load, numerical modeling, soil-cement column

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Authors: Rodolfo Alfonso, David Alonso, Albin Garcia, Jose Luis Alonso

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Recently a new kilovoltage radiotherapy unit model Xstrahl 200 - donated to the INOR´s Department of Radiotherapy (DR-INOR) in the framework of a IAEA's technical cooperation project- has been commissioned. This unit is able to treat shallow and low deep laying lesions, as it provides 8 discrete beam qualities, from 40 to 200 kV. As part of the patient-specific quality assurance program established at DR-INOR for external beam radiotherapy, it has been recommended to implement in vivo dose measurements (IVD), as they allow effectively discovering eventual errors or failures in the radiotherapy process. For that purpose a radio-photoluminescence (RPL) dosimetry system, model XXX, -also donated to DR-INOR by the same IAEA project- has been studied and commissioned. Main dosimetric parameters of the RPL system, such as reproducibility, linearity, and filed size influence were assessed. In a similar way, the response of radiochromic EBT3 type film was investigated for purposes of IVD. Both systems were calibrated in terms of entrance surface dose. Results of the dosimetric commissioning of RPL and EBT3 for IVD, and their pre-clinical implementation through end-to-end test cases are presented. The RPL dosimetry seems more recommendable for hyper-fractionated schemes with larger fields and curved patient contours, as those in chest wall irradiations, where the use of more than one dosimeter could be required. The radiochromic system involves smaller corrections with field size, but it sensibility is lower; hence it is more adequate for hypo-fractionated treatments with smaller fields.

Keywords: glass dosimetry, in vivo dosimetry, kilovotage radiotherapy, radiochromic dosimetry

Procedia PDF Downloads 382

Authors: Essam Almuhsin, Ben Soh, Alice Li, Azmat Ullah

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It is widely accepted that university students must acquire new knowledge, skills, awareness, and understanding to increase opportunities for professional and personal growth. The study reveals a significant increase in users engaging in e-coaching activities and a growing need for it during the COVID-19 pandemic. The paper proposes an e-coaching methodology for higher education in Saudi Arabia to address the need for effective coaching in the current online learning environment.

Keywords: role of e-coaching, e-coaching in higher education, Saudi higher education environment, e-coaching methodology, the importance of e-coaching

Procedia PDF Downloads 91

Authors: Mohsine Jebbour

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The ultimate aim of this study was to analyze a second-year baccalaureate textbook of English to see to what extent it includes elements of critical thinking. A further purpose was to assess the extent to which the teachers’ teaching practices help students develop some degree of critical thinking. The literature on critical thinking indicated that all the writers agree that critical thinking is skilled and dispositional oriented, and most of the definitions highlight the skill and disposition to select, collect, analyze and evaluate information effectively. In this study, two instruments were used, namely content analysis and questionnaire to ensure validity and reliability. The sample of this study, on the one hand, was a second year textbook of English, namely Ticket to English. The process of collecting data was carried out through designing a checklist to analyze the textbook of English. On the other hand, high school students (second baccalaureate grade) and teachers of English constituted the second sample. Two questionnaires were administered—One was completed by 28 high school teachers (18 males and10 females), and the other was completed by 51 students (26 males and 25 females) from Fez, Morocco. The items of the questionnaire tended to elicit both qualitative and quantitative data. An attempt was made to answer two research questions. One pertained to the extent to which the textbooks of English contain critical thinking elements (Critical thinking skills and dispositions, types of questions, language learning strategies, classroom activities); the second was concerned with whether the teaching practices of teachers of English help improve students’ critical thinking. The results demonstrated that the textbooks of English include elements of critical thinking, and the teachers’ teaching practices help the students develop some degree of critical thinking. Yet, the textbooks do not include problem-solving activities and media analysis and 86% of the teacher-respondents tended to skip activities in the textbooks, mainly the units dealing with Project Work and Study Skills which are necessary for enhancing critical thinking among the students. Therefore, the textbooks need to be designed around additional activities and the teachers are required to cover the units skipped so as to make the teaching of critical thinking effective.

Keywords: critical thinking, language learning strategies, language proficiency, teaching practices

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Authors: Mi-Hyang Lee, Seung-Hoon Han

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Korean traditional residences have been built with deep design issues for various values such as social, cultural, and environmental influences to be started from a few thousand years ago, but its meaning is being vanished due to the different lifestyles these days. It is necessary, therefore, to grasp the meaning of the Korea traditional building called Hanok and to get Korean people understand its real advantages. The purpose of this study is to propose a standardization methodology for evaluating comfort features towards Korean traditional houses. This paper is also trying to build an official standard evaluation system and to integrate aesthetic and psychological values induced from Hanok. Its comfort performance values could be divided into two large categories that are physical and psychological, and fourteen methods have been defined as the Korean Standards (KS). For this research, field survey data from representative Hanok types were collected for each method. This study also contains a qualitative in-depth analysis of the Hanok comfort index by the professions using AHP (Analytical Hierarchy Process) and has examined the effect of the methods. As a result, this paper could define what methods can provide trustful outcomes and how to evaluate the own strengths in aspects of spatial comfort of Hanok using suggested procedures towards the spatial configuration of the traditional dwellings. This study has finally proposed an integrated development of a standardization methodology assessing the comfort performance for Korean traditional residences, and it is expected that they could evaluate inhabitants of the residents and interior environmental conditions especially structured by wood materials like Hanok.

Keywords: Hanok, comfort performance, human condition, analytical hierarchy process

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Authors: Mariem Saadi, Sabri Kanzari, Adel Zghibi

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In semi-arid areas like the Kairouan region, the constant irrigation with saline water and the overuse of groundwater resources, soils and aquifers salinization has become an increasing concern. In this study, a methodology has been developed to evaluate the groundwater contamination risk based on the unsaturated zone hydraulic properties. Two soil profiles with different ranges of salinity, one located in the north of the plain and another one in the south of plain (each 30 m deep) and both characterized by direct recharge of the aquifer were chosen. Simulations were conducted with Hydrus-1D code using measured precipitation data for the period 1998-2003 and calculated evapotranspiration for both chosen profiles. Four combinations of initial conditions of water content and salt concentration were used for the simulation process in order to find the best match between simulated and measured values. The success of the calibration of Hydrus-1D allowed the investigation of some scenarios in order to assess the contamination risk under different natural conditions. The aquifer risk contamination is related to the natural conditions where it increased while facing climate change and temperature increase and decreased in the presence of a clay layer in the unsaturated zone. Hydrus-1D was a useful tool to predict the groundwater level and quality in the case of a direct recharge and in the absence of any information related to the soil layers except for the texture.

Keywords: Hydrus-1D, Kairouan, salinization, semi-arid region, solute transport, unsaturated zone

Procedia PDF Downloads 163