Search results for: learning environments
1283 The SAFRS System : A Case-Based Reasoning Training Tool for Capturing and Re-Using Knowledge
Authors: Souad Demigha
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The paper aims to specify and build a system, a learning support in radiology-senology (breast radiology) dedicated to help assist junior radiologists-senologists in their radiologysenology- related activity based on experience of expert radiologistssenologists. This system is named SAFRS (i.e. system supporting the training of radiologists-senologists). It is based on the exploitation of radiologic-senologic images (primarily mammograms but also echographic images or MRI) and their related clinical files. The aim of such a system is to help breast cancer screening in education. In order to acquire this expert radiologist-senologist knowledge, we have used the CBR (case-based reasoning) approach. The SAFRS system will promote the evolution of teaching in radiology-senology by offering the “junior radiologist" trainees an advanced pedagogical product. It will permit a strengthening of knowledge together with a very elaborate presentation of results. At last, the know-how will derive from all these factors.
Keywords: Learning support, radiology-senology, training, education, CBR, accumulated experience.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16681282 Bayesian Online Learning of Corresponding Points of Objects with Sequential Monte Carlo
Authors: Miika Toivanen, Jouko Lampinen
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This paper presents an online method that learns the corresponding points of an object from un-annotated grayscale images containing instances of the object. In the first image being processed, an ensemble of node points is automatically selected which is matched in the subsequent images. A Bayesian posterior distribution for the locations of the nodes in the images is formed. The likelihood is formed from Gabor responses and the prior assumes the mean shape of the node ensemble to be similar in a translation and scale free space. An association model is applied for separating the object nodes and background nodes. The posterior distribution is sampled with Sequential Monte Carlo method. The matched object nodes are inferred to be the corresponding points of the object instances. The results show that our system matches the object nodes as accurately as other methods that train the model with annotated training images.Keywords: Bayesian modeling, Gabor filters, Online learning, Sequential Monte Carlo.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15811281 Emotion Detection in Twitter Messages Using Combination of Long Short-Term Memory and Convolutional Deep Neural Networks
Authors: B. Golchin, N. Riahi
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One of the most significant issues as attended a lot in recent years is that of recognizing the sentiments and emotions in social media texts. The analysis of sentiments and emotions is intended to recognize the conceptual information such as the opinions, feelings, attitudes and emotions of people towards the products, services, organizations, people, topics, events and features in the written text. These indicate the greatness of the problem space. In the real world, businesses and organizations are always looking for tools to gather ideas, emotions, and directions of people about their products, services, or events related to their own. This article uses the Twitter social network, one of the most popular social networks with about 420 million active users, to extract data. Using this social network, users can share their information and opinions about personal issues, policies, products, events, etc. It can be used with appropriate classification of emotional states due to the availability of its data. In this study, supervised learning and deep neural network algorithms are used to classify the emotional states of Twitter users. The use of deep learning methods to increase the learning capacity of the model is an advantage due to the large amount of available data. Tweets collected on various topics are classified into four classes using a combination of two Bidirectional Long Short Term Memory network and a Convolutional network. The results obtained from this study with an average accuracy of 93%, show good results extracted from the proposed framework and improved accuracy compared to previous work.
Keywords: emotion classification, sentiment analysis, social networks, deep neural networks
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 6641280 Delineating Students’ Speaking Anxieties and Assessment Gaps in Online Speech Performances
Authors: Mary Jane B. Suarez
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Speech anxiety is innumerable in any traditional communication classes especially for ESL students. The speech anxiety intensifies when communication skills assessments have taken its toll in an online mode of learning due to the perils of the COVID-19 virus. Teachers and students have experienced vast ambiguity on how to realize a still effective way to teach and learn various speaking skills amidst the pandemic. This mixed method study determined the factors that affected the public speaking skills of students in online performances, delineated the assessment gaps in assessing speaking skills in an online setup, and recommended ways to address students’ speech anxieties. Using convergent parallel design, quantitative data were gathered by examining the desired learning competencies of the English course including a review of the teacher’s class record to analyze how students’ performances reflected a significantly high level of anxiety in online speech delivery. Focus group discussion was also conducted for qualitative data describing students’ public speaking anxiety and assessment gaps. Results showed a significantly high level of students’ speech anxiety affected by time constraints, use of technology, lack of audience response, being conscious of making mistakes, and the use of English as a second language. The study presented recommendations to redesign curricular assessments of English teachers and to have a robust diagnosis of students’ speaking anxiety to better cater to the needs of learners in attempt to bridge any gaps in cultivating public speaking skills of students as educational institutions segue from the pandemic to the post-pandemic milieu.
Keywords: Blended learning, communication skills assessment, online speech delivery, public speaking anxiety, speech anxiety.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1761279 Computer Assisted Learning in a Less Resource Region
Authors: Hamidullah Sokout, Samiullah Paracha, Abdul Rashid Ahmadi
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Passing the entrance exam to a university is a major step in one's life. University entrance exam commonly known as Kankor is the nationwide entrance exam in Afghanistan. This examination is prerequisite for all public and private higher education institutions at undergraduate level. It is usually taken by students who are graduated from high schools. In this paper, we reflect the major educational school graduates issues and propose ICT-based test preparation environment, known as ‘Online Kankor Exam Prep System’ to give students the tools to help them pass the university entrance exam on the first try. The system is based on Intelligent Tutoring System (ITS), which introduced an essential package of educational technology for learners that features: (I) exam-focused questions and content; (ii) self-assessment environment; and (iii) test preparation strategies in order to help students to acquire the necessary skills in their carrier and keep them up-to-date with instruction.
Keywords: Web-based test prep systems, Learner-centered design, E-Learning, Intelligent tutoring system.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19511278 Open Source Software in Higher Education: Oman SQU Case Study
Authors: Amal S. Al-Badi, Ali H. Al-Badi
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Many organizations are opting to adopt Open Source Software (OSS) as it is the current trend to rely on each other rather than on companies (Software vendors). It is a clear shift from organizations to individuals, the concept being to rely on collective participation rather than companies/vendors.
The main objectives of this research are 1) to identify the current level of OSS usage in Sultan Qaboos University; 2) to identify the potential benefits of using OSS in educational institutes; 3) to identify the OSS applications that are most likely to be used within an educational institute; 4) to identify the existing and potential barriers to the successful adoption of OSS in education.
To achieve these objectives a two-stage research method was conducted. First a rigorous literature review of previously published material was performed (interpretive/descriptive approach), and then a set of interviews were conducted with the IT professionals at Sultan Qaboos University in Oman in order to explore the extent and nature of their usage of OSS.
Keywords: Open source software; social software, e-learning 2.0, Web 2.0, connectivism, personal learning environment (PLE), OpenID, OpenSocial and OpenCourseWare.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 36441277 Machine Learning Methods for Flood Hazard Mapping
Authors: S. Zappacosta, C. Bove, M. Carmela Marinelli, P. di Lauro, K. Spasenovic, L. Ostano, G. Aiello, M. Pietrosanto
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This paper proposes a neural network approach for assessing flood hazard mapping. The core of the model is a machine learning component fed by frequency ratios, namely statistical correlations between flood event occurrences and a selected number of topographic properties. The classification capability was compared with the flood hazard mapping River Basin Plans (Piani Assetto Idrogeologico, acronimed as PAI) designed by the Italian Institute for Environmental Research and Defence, ISPRA (Istituto Superiore per la Protezione e la Ricerca Ambientale), encoding four different increasing flood hazard levels. The study area of Piemonte, an Italian region, has been considered without loss of generality. The frequency ratios may be used as a standalone block to model the flood hazard mapping. Nevertheless, the mixture with a neural network improves the classification power of several percentage points, and may be proposed as a basic tool to model the flood hazard map in a wider scope.
Keywords: flood modeling, hazard map, neural networks, hydrogeological risk, flood risk assessment
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 7231276 What the Future Holds for Social Media Data Analysis
Authors: P. Wlodarczak, J. Soar, M. Ally
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The dramatic rise in the use of Social Media (SM) platforms such as Facebook and Twitter provide access to an unprecedented amount of user data. Users may post reviews on products and services they bought, write about their interests, share ideas or give their opinions and views on political issues. There is a growing interest in the analysis of SM data from organisations for detecting new trends, obtaining user opinions on their products and services or finding out about their online reputations. A recent research trend in SM analysis is making predictions based on sentiment analysis of SM. Often indicators of historic SM data are represented as time series and correlated with a variety of real world phenomena like the outcome of elections, the development of financial indicators, box office revenue and disease outbreaks. This paper examines the current state of research in the area of SM mining and predictive analysis and gives an overview of the analysis methods using opinion mining and machine learning techniques.
Keywords: Social Media, text mining, knowledge discovery, predictive analysis, machine learning.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 38471275 Web 2.0 in Higher Education: The Instructors’ Acceptance in Higher Educational Institutes in Kingdom of Bahrain
Authors: Amal M. Alrayes, Hayat M. Ali
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Since the beginning of distance education with the rapid evolution of technology, the social network plays a vital role in the educational process to enforce the interaction been the learners and teachers. There are many Web 2.0 technologies, services and tools designed for educational purposes. This research aims to investigate instructors’ acceptance towards web-based learning systems in higher educational institutes in Kingdom of Bahrain. Questionnaire is used to investigate the instructors’ usage of Web 2.0 and the factors affecting their acceptance. The results confirm that instructors had high accessibility to such technologies. However, patterns of use were complex. Whilst most expressed interest in using online technologies to support learning activities, learners seemed cautious about other values associated with web-based system, such as the shared construction of knowledge in a public format. The research concludes that there are main factors that affect instructors’ adoption which are security, performance expectation, perceived benefits, subjective norm, and perceived usefulness.
Keywords: Web 2.0, Higher education, Acceptance, Students’ perception.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13081274 Teaching Project of Architecture in Portugal: Future Perspectives and the Revolution of New Generations
Authors: Patricia Diogo
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As teachers and researchers, we often find ourselves grappling with a central question about what it truly means to teach project in architecture in Portugal in the 21st century. It is a question that transcends the simple transmission of technical knowledge or even the sharing of our personal experiences. Rather, it is about developing a teaching pedagogy that responds to and reflects the profound social, environmental, and technological shifts we are currently navigating. Teaching architecture in Portugal today is not a mere continuation of tradition; it is, in essence, a living laboratory of innovation. Each new generation of students enters our classrooms with a hunger not just for design techniques, but for meaning—seeking to understand the role they can play in reshaping our physical and cultural environments. They are not passive recipients of knowledge, but active participants in the creation of a more sustainable, ethical, and thoughtful architecture.
Keywords: Architecture, heritage, memories, project studio, teaching.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 191273 Prediction of Research Topics Using Ensemble of Best Predictors from Similar Dataset
Authors: Indra Budi, Rizal Fathoni Aji, Agus Widodo
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Prediction of future research topics by using time series analysis either statistical or machine learning has been conducted previously by several researchers. Several methods have been proposed to combine the forecasting results into single forecast. These methods use fixed combination of individual forecast to get the final forecast result. In this paper, quite different approach is employed to select the forecasting methods, in which every point to forecast is calculated by using the best methods used by similar validation dataset. The dataset used in the experiment is time series derived from research report in Garuda, which is an online sites belongs to the Ministry of Education in Indonesia, over the past 20 years. The experimental result demonstrates that the proposed method may perform better compared to the fix combination of predictors. In addition, based on the prediction result, we can forecast emerging research topics for the next few years.
Keywords: Combination, emerging topics, ensemble, forecasting, machine learning, prediction, research topics, similarity measure, time series.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21221272 Experimental Study of Hyperparameter Tuning a Deep Learning Convolutional Recurrent Network for Text Classification
Authors: Bharatendra Rai
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Sequences of words in text data have long-term dependencies and are known to suffer from vanishing gradient problem when developing deep learning models. Although recurrent networks such as long short-term memory networks help overcome this problem, achieving high text classification performance is a challenging problem. Convolutional recurrent networks that combine advantages of long short-term memory networks and convolutional neural networks, can be useful for text classification performance improvements. However, arriving at suitable hyperparameter values for convolutional recurrent networks is still a challenging task where fitting of a model requires significant computing resources. This paper illustrates the advantages of using convolutional recurrent networks for text classification with the help of statistically planned computer experiments for hyperparameter tuning.
Keywords: Convolutional recurrent networks, hyperparameter tuning, long short-term memory networks, Tukey honest significant differences
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1131271 Throughput Analysis over Power Line Communication Channel in an Electric Noisy Scenario
Authors: Edward P. Guillen, Julián J. López, Cesar Y. Barahona
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Powerline Communications –PLC– as an alternative method for broadband networking, has the advantage of transmitting over channels already used for electrical distribution or even transmission. But these channels have been not designed with usual wired channels requirements for broadband applications such as stable impedance or known attenuation, and the network have to reject noises caused by electrical appliances that share the same channel. Noise control standards are difficult to complain or simply do not exist on Latin-American environments. This paper analyzes PLC throughput for home connectivity by probing noisy channel scenarios in a PLC network and the statistical results are shown.Keywords: Power Line Communications, OFDM, Noise Analysis, Throughput Analysis, PLC, Home Network.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 23061270 Scientific Methods in Educational Management: The Metasystems Perspective
Authors: Elena A. Railean
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Although scientific methods have been the subject of a large number of papers, the term ‘scientific methods in educational management’ is still not well defined. In this paper, it is adopted the metasystems perspective to define the mentioned term and distinguish them from methods used in time of the scientific management and knowledge management paradigms. In our opinion, scientific methods in educational management rely on global phenomena, events, and processes and their influence on the educational organization. Currently, scientific methods in educational management are integrated with the phenomenon of globalization, cognitivisation, and openness, etc. of educational systems and with global events like the COVID-19 pandemic. Concrete scientific methods are nested in a hierarchy of more and more abstract models of educational management, which form the context of the global impact on education, in general, and learning outcomes, in particular. However, scientific methods can be assigned to a specific mission, strategy, or tactics of educational management of the concrete organization, either by the global management, local development of school organization, or/and development of the life-long successful learner. By accepting this assignment, the scientific method becomes a personal goal of each individual with the educational organization or the option to develop the educational organization at the global standards. In our opinion, in educational management, the scientific methods need to confine the scope to the deep analysis of concrete tasks of the educational system (i.e., teaching, learning, assessment, development), which result in concrete strategies of organizational development. More important are seeking the ways for dynamic equilibrium between the strategy and tactic of the planetary tasks in the field of global education, which result in a need for ecological methods of learning and communication. In sum, distinction between local and global scientific methods is dependent on the subjective conception of the task assignment, measurement, and appraisal. Finally, we conclude that scientific methods are not holistic scientific methods, but the strategy and tactics implemented in the global context by an effective educational/academic manager.
Keywords: Educational management, scientific management, educational leadership, scientific method in educational management.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13921269 Developing Student Teachers to Be Professional Teachers
Authors: Suttipong Boonphadung
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Practicum placements are an critical factor for student teachers on Education Programs. How can student teachers become professionals? This study was to investigate problems, weakness and obstacles of practicum placements and develop guidelines for partnership in the practicum placements. In response to this issue, a partnership concept was implemented for developing student teachers into professionals. Data were collected through questionnaires on attitude toward problems, weaknesses, and obstacles of practicum placements of student teachers in Rajabhat universities and included focus group interviews. The research revealed that learning management, classroom management, curriculum, assessment and evaluation, classroom action research, and teacher demeanor are the important factors affecting the professional development of Education Program student teachers. Learning management plan and classroom management concerning instructional design, teaching technique, instructional media, and student behavior management are another important aspects influencing the professional development for student teachers.
Keywords: Developing student teacher, Partnership concepts, Professional teachers.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20431268 Simulating Drilling Using a CAD System
Authors: Panagiotis Kyratsis, Konstantinos Kakoulis
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Nowadays, the rapid development of CAD systems’ programming environments results in the creation of multiple downstream applications, which are developed and becoming increasingly available. CAD based manufacturing simulations is gradually following the same trend. Drilling is the most popular holemaking process used in a variety of industries. A specially built piece of software that deals with the drilling kinematics is presented. The cutting forces are calculated based on the tool geometry, the cutting conditions and the tool/work-piece materials. The results are verified by experimental work. Finally, the response surface methodology (RSM) is applied and mathematical models of the total thrust force and the thrust force developed because of the main cutting edges are proposed.Keywords: Application programming interface, CAD, drilling, response surface methodology, RSM.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18081267 The Creative Unfolding of “Reduced Descriptive Structures” in Musical Cognition: Technical and Theoretical Insights Based on the OpenMusic and PWGL Long-Term Feedback
Authors: Jacopo Baboni Schilingi
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We here describe the theoretical and philosophical understanding of a long term use and development of algorithmic computer-based tools applied to music composition. The findings of our research lead us to interrogate some specific processes and systems of communication engaged in the discovery of specific cultural artworks: artistic creation in the sono-musical domain. Our hypothesis is that the patterns of auditory learning cannot be only understood in terms of social transmission but would gain to be questioned in the way they rely on various ranges of acoustic stimuli modes of consciousness and how the different types of memories engaged in the percept-action expressive systems of our cultural communities also relies on these shadowy conscious entities we named “Reduced Descriptive Structures”.
Keywords: Algorithmic sonic computation, corrected and self-correcting learning patterns in acoustic perception, morphological derivations in sensorial patterns, social unconscious modes of communication.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 6081266 Interactive Methods of Design Education as the Principles of Social Implications of Modern Communities
Authors: Pelin Yildiz
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The term interactive education indicates the meaning related with multidisciplinary aspects of distance education following contemporary means around a common basis with different functional requirements. The aim of this paper is to reflect the new techniques in education with the new methods and inventions. These methods are better supplied by interactivity. The integration of interactive facilities in the discipline of education with distance learning is not a new concept but in addition the usage of these methods on design issue is newly being adapted to design education. In this paper the general approach of this method and after the analysis of different samples, the advantages and disadvantages of these approaches are being identified. The method of this paper is to evaluate the related samples and then analyzing the main hypothesis. The main focus is to mention the formation processes of this education. Technological developments in education should be filtered around the necessities of the design education and the structure of the system could then be formed or renewed. The conclusion indicates that interactive methods of education in design issue is a meaning capturing not only technical and computational intelligence aspects but also aesthetical and artistic approaches coming together around the same purpose.Keywords: Interactive education, distance learning, designeducation, computational intelligence.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16401265 Detecting and Secluding Route Modifiers by Neural Network Approach in Wireless Sensor Networks
Authors: C. N. Vanitha, M. Usha
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In a real world scenario, the viability of the sensor networks has been proved by standardizing the technologies. Wireless sensor networks are vulnerable to both electronic and physical security breaches because of their deployment in remote, distributed, and inaccessible locations. The compromised sensor nodes send malicious data to the base station, and thus, the total network effectiveness will possibly be compromised. To detect and seclude the Route modifiers, a neural network based Pattern Learning predictor (PLP) is presented. This algorithm senses data at any node on present and previous patterns obtained from the en-route nodes. The eminence of any node is upgraded by their predicted and reported patterns. This paper propounds a solution not only to detect the route modifiers, but also to seclude the malevolent nodes from the network. The simulation result proves the effective performance of the network by the presented methodology in terms of energy level, routing and various network conditions.
Keywords: Neural networks, pattern learning, security, wireless sensor networks.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13011264 Evaluation of Classification Algorithms for Road Environment Detection
Authors: T. Anbu, K. Aravind Kumar
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The road environment information is needed accurately for applications such as road maintenance and virtual 3D city modeling. Mobile laser scanning (MLS) produces dense point clouds from huge areas efficiently from which the road and its environment can be modeled in detail. Objects such as buildings, cars and trees are an important part of road environments. Different methods have been developed for detection of above such objects, but still there is a lack of accuracy due to the problems of illumination, environmental changes, and multiple objects with same features. In this work the comparison between different classifiers such as Multiclass SVM, kNN and Multiclass LDA for the road environment detection is analyzed. Finally the classification accuracy for kNN with LBP feature improved the classification accuracy as 93.3% than the other classifiers.Keywords: Classifiers, feature extraction, mobile-based laser scanning, object location estimation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 7731263 Machine Learning Techniques for COVID-19 Detection: A Comparative Analysis
Authors: Abeer Aljohani
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The COVID-19 virus spread has been one of the extreme pandemics across the globe. It is also referred as corona virus which is a contagious disease that continuously mutates into numerous variants. Currently, the B.1.1.529 variant labeled as Omicron is detected in South Africa. The huge spread of COVID-19 disease has affected several lives and has surged exceptional pressure on the healthcare systems worldwide. Also, everyday life and the global economy have been at stake. Numerous COVID-19 cases have produced a huge burden on hospitals as well as health workers. To reduce this burden, this paper predicts COVID-19 disease based on the symptoms and medical history of the patient. As machine learning is a widely accepted area and gives promising results for healthcare, this research presents an architecture for COVID-19 detection using ML techniques integrated with feature dimensionality reduction. This paper uses a standard University of California Irvine (UCI) dataset for predicting COVID-19 disease. This dataset comprises symptoms of 5434 patients. This paper also compares several supervised ML techniques on the presented architecture. The architecture has also utilized 10-fold cross validation process for generalization and Principal Component Analysis (PCA) technique for feature reduction. Standard parameters are used to evaluate the proposed architecture including F1-Score, precision, accuracy, recall, Receiver Operating Characteristic (ROC) and Area under Curve (AUC). The results depict that Decision tree, Random Forest and neural networks outperform all other state-of-the-art ML techniques. This result can be used to effectively identify COVID-19 infection cases.
Keywords: Supervised machine learning, COVID-19 prediction, healthcare analytics, Random Forest, Neural Network.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3841262 Conception of a Reliable, Low Cost and Autonomous Explorative Hovercraft
Authors: S. Burgalat, L. Teilhac, A. Brand, E. Chastel, M. Jumeline
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The paper presents actual benefits and drawbacks of a multidirectional autonomous hovercraft conceived with limited resources and designed for indoor exploration. Recent developments in the field have led to the apparition of very powerful automotive systems capable of very high calculation and exploration in complex unknown environments. They usually propose very complex algorithms, high precision/cost sensors and sometimes have heavy calculation consumption with complex data fusion. These systems are usually powerful but have a certain price, and the benefits may not be worth the cost, especially considering their hardware limitations and their power consumption. The present approach is to build a compromise between cost, power consumption and results preciseness.
Keywords: Hovercraft, Indoor Exploration, Autonomous, Multidirectional, Wireless Control.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22231261 CScheme in Traditional Concurrency Problems
Authors: Nathar Shah, Visham Cheerkoot
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CScheme, a concurrent programming paradigm based on scheme concept enables concurrency schemes to be constructed from smaller synchronization units through a GUI based composer and latter be reused on other concurrency problems of a similar nature. This paradigm is particularly important in the multi-core environment prevalent nowadays. In this paper, we demonstrate techniques to separate concurrency from functional code using the CScheme paradigm. Then we illustrate how the CScheme methodology can be used to solve some of the traditional concurrency problems – critical section problem, and readers-writers problem - using synchronization schemes such as Single Threaded Execution Scheme, and Readers Writers Scheme.Keywords: Concurrent Programming, Object Oriented Programming, Environments for multiple-processor systems, Programming paradigms.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16921260 Localization for Indoor Service Robot Using Natural Landmark on the Ceiling
Authors: Seung-Hun Kim, Changwoo Park
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In this paper, we present a localization of a mobile robot with localization modules which have two ceiling-view cameras in indoor environments. We propose two kinds of localization method. The one is the localization in the local space; we use the line feature and the corner feature between the ceiling and wall. The other is the localization in the large space; we use the natural features such as bulbs, structures on the ceiling. These methods are installed on the embedded module able to mount on the robot. The embedded module has two cameras to be able to localize in both the local space and the large spaces. The experiment is practiced in our indoor test-bed and a government office. The proposed method is proved by the experimental results.
Keywords: Robot, Localization, Indoor, Ceiling vision, Local space, Large space, Complex space.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21761259 Using Design Sprint for Software Engineering Undergraduate Student Projects: A Method Paper
Authors: Sobhani U. Pilapitiya, Tharanga Peiris
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Software engineering curriculums generally consist of industry-based practices such as project-based learning (PBL) which mainly focuses on efficient and innovative product development. These approaches can be tailored and used in project-based modules in software engineering curriculums. However, there are very limited attempts in the area especially related to Sri Lankan context. This paper describes a tailored pedagogical approach and its results of using design sprint which can be used for project-based modules in software engineering (SE) curriculums. A controlled group of second year software engineering students was selected for the study. The study results indicate that all of the students agreed that the design sprint approach is effective in group-based projects and 83% of students stated that it minimized the re-work compared to traditional project approaches. The tailored process was effective, easy to implement and produced desired results at the end of the session while providing students an enjoyable experience.
Keywords: design sprint, project-based learning, software engineering, curriculum
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 7321258 A Hypermap for Supply Chain Management
Authors: James K. Ho
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We present a prototype interactive (hyper) map of strategic, tactical, and logistic options for Supply Chain Management. The map comprises an anthology of options, broadly classified within the strategic spectrum of efficiency versus responsiveness, and according to logistic and cross-functional drivers. They are exemplified by cases in diverse industries. We seek to get all these information and ideas organized to help supply chain managers identify effective choices for specific business environments. The key and innovative linkage we introduce is the configuration of competitive forces. Instead of going through seemingly endless and isolated cases and wondering how one can borrow from them, we aim to provide a guide by force comparisons. The premise is that best practices in a different industry facing similar forces may be a most productive resource in supply chain design and planning. A prototype template is demonstrated.
Keywords: Competitive forces, strategic innovation, supplychain management.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18451257 Resident-Aware Green Home
Authors: Ahlam Elkilani, Bayan Elsheikh Ali, Rasha Abu Romman, Amjed Al-mousa, Belal Sababha
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The amount of energy the world uses doubles every 20 years. Green homes play an important role in reducing the residential energy demand. This paper presents a platform that is intended to learn the behavior of home residents and build a profile about their habits and actions. The proposed resident aware home controller intervenes in the operation of home appliances in order to save energy without compromising the convenience of the residents. The presented platform can be used to simulate the actions and movements happening inside a home. The paper includes several optimization techniques that are meant to save energy in the home. In addition, several test scenarios are presented that show how the controller works. Moreover, this paper shows the computed actual savings when each of the presented techniques is implemented in a typical home. The test scenarios have validated that the techniques developed are capable of effectively saving energy at homes.
Keywords: Green Home, Resident Aware, Resident Profile, Activity Learning, Machine Learning.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21581256 Comparison of Finite-Element and IEC Methods for Cable Thermal Analysis under Various Operating Environments
Authors: M. S. Baazzim, M. S. Al-Saud, M. A. El-Kady
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In this paper, steady-state ampacity (current carrying capacity) evaluation of underground power cable system by using analytical and numerical methods for different conditions (depth of cable, spacing between phases, soil thermal resistivity, ambient temperature, wind speed), for two system voltage level were used 132 and 380 kV. The analytical method or traditional method that was used is based on the thermal analysis method developed by Neher-McGrath and further enhanced by International Electrotechnical Commission (IEC) and published in standard IEC 60287. The numerical method that was used is finite element method and it was recourse commercial software based on finite element method.
Keywords: Cable ampacity, Finite element method, underground cable, thermal rating.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 58581255 Exploration of Influential Factors on First Year Architecture Students’ Productivity
Authors: Shima Nikanjam, Badiossadat Hassanpour, Adi Irfan Che Ani
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The design process in architecture education is based upon the Learning-by-Doing method, which leads students to understand how to design by practicing rather than studying. First-year design studios, as starting educational stage, provide integrated knowledge and skills of design for newly jointed architecture students. Within the basic design studio environment, students are guided to transfer their abstract thoughts into visual concrete decisions under the supervision of design educators for the first time. Therefore, introductory design studios have predominant impacts on students’ operational thinking and designing. Architectural design thinking is quite different from students’ educational backgrounds and learning habits. This educational challenge at basic design studios creates a severe need to study the reality of design education at foundation year and define appropriate educational methods with convenient project types with the intention of enhancing architecture education quality. Material for this study has been gathered through long-term direct observation at a first year second semester design studio at the faculty of architecture at EMU (known as FARC 102), fall and spring academic semester 2014-15. Distribution of a questionnaire among case study students and interviews with third and fourth design studio students who passed through the same methods of education in the past 2 years and conducting interviews with instructors are other methodologies used in this research. The results of this study reveal a risk of a mismatch between the implemented teaching method, project type and scale in this particular level and students’ learning styles. Although the existence of such risk due to varieties in students’ profiles could be expected to some extent, recommendations can support educators to reach maximum compatibility.
Keywords: Architecture education, basic design studio, educational method, forms creation skill.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16221254 AINA: Disney Animation Information as Educational Resources
Authors: Piedad Garrido, Fernando Repulles, Andy Bloor, Julio A. Sanguesa, Jesus Gallardo, Vicente Torres, Jesus Tramullas
Abstract:
With the emergence and development of Information and Communications Technologies (ICTs), Higher Education is experiencing rapid changes, not only in its teaching strategies but also in student’s learning skills. However, we have noticed that students often have difficulty when seeking innovative, useful, and interesting learning resources for their work. This is due to the lack of supervision in the selection of good query tools. This paper presents AINA, an Information Retrieval (IR) computer system aimed at providing motivating and stimulating content to both students and teachers working on different areas and at different educational levels. In particular, our proposal consists of an open virtual resource environment oriented to the vast universe of Disney comics and cartoons. Our test suite includes Disney’s long and shorts films, and we have performed some activities based on the Just In Time Teaching (JiTT) methodology. More specifically, it has been tested by groups of university and secondary school students.Keywords: Information retrieval, animation, educational resources, JiTT.
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