Search results for: deep learning models

Authors: Erhan Eroğlu

Abstract:

This paper presents a new method called Mentor and Mentee Based Learning. This new method is becoming more and more common especially at workplaces. This study is significant as it clearly underlines how it works well. Education has always aimed at equipping people with the necessary knowledge and information. For many decades it went on teachers’ talk and chalk methods. In the second half of the nineteenth century educators felt the need for some changes in delivery systems. Some new terms like self- discovery, learner engagement, student centered learning, hands on learning have become more and more popular for such a long time. However, some educators believe that there is much room for better learning methods in many fields as they think the learners still cannot fulfill their potential capacities. Thus, new systems and methods are still being developed and applied at education centers and work places. One of the latest methods is assigning some mentors for the newly recruited employees and training them within a mentor and mentee program which allows both parties to see their strengths and weaknesses and the areas which can be improved. This paper aims at finding out the perceptions of the mentors and mentees on the programs they are offered at their workplaces and suggests some betterment alternatives. The study has been conducted via a qualitative method whereby some interviews have been done with both mentors and mentees separately and together. Results show that it is a great way to train inexperienced one and also to refresh the older ones. Some points to be improved have also been underlined. The paper shows that education is not a one way path to follow.

Keywords: learning, mentor, mentee, training

Procedia PDF Downloads 228

Authors: Milica Ž. Karadžić, Lidija R. Jevrić, Sanja Podunavac-Kuzmanović, Strahinja Z. Kovačević, Anamarija I. Mandić, Katarina Penov-Gaši, Andrea R. Nikolić, Aleksandar M. Oklješa

Abstract:

This study considered selection of the in silico molecular descriptors and the models for newly synthesized steroid derivatives description and their characterization using chemometric techniques. Multiple linear regression (MLR) models were established and gave the best molecular descriptors for quantitative structure-retention relationship (QSRR) modeling of the retention of the investigated molecules. MLR models were without multicollinearity among the selected molecular descriptors according to the variance inflation factor (VIF) values. Used molecular descriptors were ranked using generalized pair correlation method (GPCM). In this method, the significant difference between independent variables can be noticed regardless almost equal correlation between dependent variable. Generated MLR models were statistically and cross-validated and the best models were kept. Models were ranked using sum of ranking differences (SRD) method. According to this method, the most consistent QSRR model can be found and similarity or dissimilarity between the models could be noticed. In this study, SRD was performed using average values of experimentally observed data as a golden standard. Chemometric analysis was conducted in order to characterize newly synthesized steroid derivatives for further investigation regarding their potential biological activity and further synthesis. This article is based upon work from COST Action (CM1105), supported by COST (European Cooperation in Science and Technology).

Keywords: generalized pair correlation method, molecular descriptors, regression analysis, steroids, sum of ranking differences

Procedia PDF Downloads 347

Authors: Manuela Nayantara Jeyaraj

Abstract:

Having moved into the 21^st century, it is way past being arguable that innovative technology needs to be incorporated into conventional classroom teaching. Though the Western world has found presumable success in achieving this, it is still a concept under battle in developing countries such as Sri Lanka. Reaching the acme of implementing interactive virtual learning within classrooms is a struggling idealistic fascination within the island. In order to overcome this problem, this study is set to reveal facts that limit the implementation of virtual, interactive learning within the school classrooms and provide hacks that could prove the augmented use of the Virtual World to enhance teaching and learning experiences. As each classroom moves along with the usage of technology to fulfill its functionalities, a few intense hacks provided will build the administrative onuses on a virtual system. These hacks may divulge barriers based on social conventions, financial boundaries, digital literacy, intellectual capacity of the staff, and highlight the impediments in introducing students to an interactive virtual learning environment and thereby provide the necessary actions or changes to be made to succeed and march along in creating an intellectual society built on virtual learning and lifestyle. This digital learning environment will be composed of multimedia presentations, trivia and pop quizzes conducted on a GUI, assessments conducted via a virtual system, records maintained on a database, etc. The ultimate objective of this study could enhance every child's basic learning environment; hence, diminishing the digital divide that exists in certain communities.

Keywords: digital divide, digital learning, digitization, Sri Lanka, teaching methodologies

Procedia PDF Downloads 353

Authors: Navid Daryasafar, Nima Farshidfar

Abstract:

In this article, we make attempt to hide error in video with an emphasis on the time-wise use of autoregressive (AR) models. To resolve this problem, we assume that all information in one or more video frames is lost. Then, lost frames are estimated using analogous Pixels time information in successive frames. Accordingly, after presenting autoregressive models and how they are applied to estimate lost frames, two general methods are presented for using these models. The first method which is the same standard method of autoregressive models estimates lost frame in unidirectional form. Usually, in such condition, previous frames information is used for estimating lost frame. Yet, in the second method, information from the previous and next frames is used for estimating the lost frame. As a result, this method is known as bidirectional estimation. Then, carrying out a series of tests, performance of each method is assessed in different modes. And, results are compared.

Keywords: error steganography, unidirectional estimation, bidirectional estimation, AR linear estimation

Procedia PDF Downloads 540

Authors: Jaeseo Lim, Jooyong Park

Abstract:

Although there is ample evidence that student involvement enhances learning, college education is still mainly centered on lectures. However, in recent years, the effectiveness of discussions and the use of collective intelligence have attracted considerable attention. This study intends to examine the empirical effects of discussions on learning outcomes in various conditions. Eighty eight college students participated in the study and were randomly assigned to three groups. Group 1 was told to review material after a lecture, as in a traditional lecture-centered class. Students were given time to review the material for themselves after watching the lecture in a video clip. Group 2 participated in a discussion in groups of three or four after watching the lecture. Group 3 participated in a discussion after studying on their own. Unlike the previous two groups, students in Group 3 did not watch the lecture. The participants in the three groups were tested after studying. The test questions consisted of memorization problems, comprehension problems, and application problems. The results showed that the groups where students participated in discussions had significantly higher test scores. Moreover, the group where students studied on their own did better than that where students watched a lecture. Thus discussions are shown to be effective for enhancing learning. In particular, discussions seem to play a role in preparing students to solve application problems. This is a preliminary study and other age groups and various academic subjects need to be examined in order to generalize these findings. We also plan to investigate what kind of support is needed to facilitate discussions.

Keywords: discussions, education, learning, lecture, test

Procedia PDF Downloads 176

Authors: Michael Stewart

Abstract:

Mutation testing is a type of software testing proposed in the 1970s where program statements are deliberately changed to introduce simple errors so that test cases can be validated to determine if they can detect the errors. Test cases are executed against the mutant code to determine if one fails, detects the error and ensures the program is correct. One major issue with this type of testing was it became intensive computationally to generate and test all possible mutations for complex programs. This paper used reinforcement learning and parallel processing within the context of mutation testing for the selection of mutation operators and test cases that reduced the computational cost of testing and improved test suite effectiveness. Experiments were conducted using sample programs to determine how well the reinforcement learning-based algorithm performed with one live mutation, multiple live mutations and no live mutations. The experiments, measured by mutation score, were used to update the algorithm and improved accuracy for predictions. The performance was then evaluated on multiple processor computers. With reinforcement learning, the mutation operators utilized were reduced by 50 – 100%.

Keywords: automated-testing, machine learning, mutation testing, parallel processing, reinforcement learning, software engineering, software testing

Procedia PDF Downloads 198

Authors: Helga Mayr

Abstract:

In our ongoing effort to address urgent global challenges related to sustainability, higher education institutions play a central role in raising a generation of informed and empowered citizens committed to sustainable development. This paper presents the preliminary results of the so far realized evaluation of a compulsory module on education for sustainable development (ESD) offered to students in the bachelor's program in elementary education at the University College of Teacher Education Tyrol (PH Tirol), Austria. The module includes a lecture on sustainability and education as well as a project-based seminar that aims to foster a deep understanding of ESD and its application in pedagogical practice. The study examines various dimensions related to the module's impact on participating students, focusing on prevalent sustainability concepts, intentions, actions, general and sustainability-related self-efficacy, perceived competence related to ESD, and ESD-related self-efficacy. In addition, the research addresses assessment of the learning process. To obtain a comprehensive overview of the effectiveness of the module, a mixed methods approach was/is used in the evaluation. Quantitative data was/is collected through surveys and self-assessment instruments, while qualitative findings were/will be obtained through focus group interviews and reflective analysis. The PH Tirol is collaborating with another University College of Teacher Education (Styria) and a university of applied sciences in Switzerland (UAS of the Grisons) to broaden the scope of the analysis and allow for comparative findings. Preliminary results indicate that students have a relatively rudimentary understanding of sustainability. The extent to which completion of the module influences understanding of sustainability, awareness, intentions, and actions, as well as self-efficacy, is currently under investigation. The results will be available at the time of the conference and will be presented there. In terms of learning, the project-based seminar, which promotes hands-on engagement with ESD, was evaluated for its effectiveness in fostering key sustainability competencies as well as sustainability-related and ESD-related self-efficacy. The research not only provides insights into the effectiveness of the compulsory module ESD at the PH Tirol but also contributes to the broader discourse on integrating ESD into teacher education.

Keywords: education for sustainable development, teacher education, project-based learning, effectiveness measurements

Procedia PDF Downloads 68

Authors: Noriyuki Suyama

Abstract:

The progress and spread of digitalization have led to the provision of a variety of new services. The recent progress in digitization can be attributed to rapid developments in science and technology. First, the research and diffusion of artificial intelligence (AI) has made dramatic progress. Around 2000, the third wave of AI research, which had been underway for about 50 years, arrived. Specifically, machine learning and deep learning were made possible in AI, and the ability of AI to acquire knowledge, define the knowledge, and update its own knowledge in a quantitative manner made the use of big data practical even for commercial PCs. On the other hand, with the spread of social media, information exchange has become more common in our daily lives, and the lending and borrowing of goods and services, in other words, the sharing economy, has become widespread. The scope of this trend is not limited to any industry, and its momentum is growing as the SDGs take root. In addition, the Social Network Service (SNS), a part of social media, has brought about the evolution of the retail business. In the past few years, social network services (SNS) involving users or companies have especially flourished. The People's Republic of China (hereinafter referred to as "China") is a country that is stimulating enormous consumption through its own unique SNS, which is different from the SNS used in developed countries around the world. This paper focuses on the effectiveness and challenges of influencer marketing by focusing on the influence of influencers on users' behavior and satisfaction with Chinese SNSs. Specifically, Conducted was the quantitative survey of Tik Tok users living in China, with the aim of gaining new insights from the analysis and discussions. As a result, we found several important findings and knowledge.

Keywords: customer satisfaction, social networking services, influencer marketing, Chinese consumers’ behavior

Procedia PDF Downloads 89

Authors: Lise P. Labéjof, Krisnayne S. Ribeiro, Nicolle P. dos Santos

Abstract:

An unrecorded experiment of use of the smartphone as a tool for practical classes of histology is presented in this article. Behavior, learning of the students of three science courses at the University were analyzed and compared as well as the mode of teaching of this discipline and the appreciation of the students, using either digital photographs taken by phone or drawings for record microscopic observations, analyze and interpret histological sections of human or animal tissues.

Keywords: cell phone, digital micrographies, learning of sciences, teaching practices

Procedia PDF Downloads 596

Authors: Stephen L. Green, Alexander N. Gorban, Ivan Y. Tyukin

Abstract:

Within the past decade, using Convolutional Neural Networks (CNN)’s to create Deep Learning systems capable of translating Sign Language into text has been a breakthrough in breaking the communication barrier for deaf-mute people. Conventional research on this subject has been concerned with training the network to recognize the fingerspelling gestures of a given language and produce their corresponding alphanumerics. One of the problems with the current developing technology is that images are scarce, with little variations in the gestures being presented to the recognition program, often skewed towards single skin tones and hand sizes that makes a percentage of the population’s fingerspelling harder to detect. Along with this, current gesture detection programs are only trained on one finger spelling language despite there being one hundred and forty-two known variants so far. All of this presents a limitation for traditional exploitation for the state of current technologies such as CNN’s, due to their large number of required parameters. This work aims to present a technology that aims to resolve this issue by combining a pretrained legacy AI system for a generic object recognition task with a corrector method to uptrain the legacy network. This is a computationally efficient procedure that does not require large volumes of data even when covering a broad range of sign languages such as American Sign Language, British Sign Language and Chinese Sign Language (Pinyin). Implementing recent results on method concentration, namely the stochastic separation theorem, an AI system is supposed as an operate mapping an input present in the set of images u ∈ U to an output that exists in a set of predicted class labels q ∈ Q of the alphanumeric that q represents and the language it comes from. These inputs and outputs, along with the interval variables z ∈ Z represent the system’s current state which implies a mapping that assigns an element x ∈ ℝⁿ to the triple (u, z, q). As all xi are i.i.d vectors drawn from a product mean distribution, over a period of time the AI generates a large set of measurements xi called S that are grouped into two categories: the correct predictions M and the incorrect predictions Y. Once the network has made its predictions, a corrector can then be applied through centering S and Y by subtracting their means. The data is then regularized by applying the Kaiser rule to the resulting eigenmatrix and then whitened before being split into pairwise, positively correlated clusters. Each of these clusters produces a unique hyperplane and if any element x falls outside the region bounded by these lines then it is reported as an error. As a result of this methodology, a self-correcting recognition process is created that can identify fingerspelling from a variety of sign language and successfully identify the corresponding alphanumeric and what language the gesture originates from which no other neural network has been able to replicate.

Keywords: convolutional neural networks, deep learning, shallow correctors, sign language

Procedia PDF Downloads 100

Authors: Ramorola Mmankoko Ziphorah

Abstract:

Videoconference technology represents a recent experiment of technology integration into teaching and learning in South Africa. Increasingly, videoconference technology is commonly used as a substitute for the traditional face-to-face approaches to teaching and learning in helping tutors to reshape and change their teaching practices. Interestingly, though, some studies point out that videoconference technology is commonly used for knowledge dissemination by tutors and not so much for the actual teaching of course content in Open and Distance Learning context. Though videoconference technology has become one of the dominating technologies available among Open and Distance Learning institutions, it is not clear that it has been used as effectively to bridge the learning distance in time, geography, and economy. While tutors are prepared theoretically, in most tutor preparation programs, on the use of videoconference technology, there are still no practical guidelines on how they should go about integrating this technology into their course teaching. Therefore, there is an urgent need to focus on tutor development, specifically on their capacities and skills to use videoconference technology. The assumption is that if tutors become competent in the use of the videoconference technology for course teaching, then their use in Open and Distance Learning environment will become more commonplace. This is the imperative of the 4th Industrial Revolution (4IR) on education generally. Against the current vacuum in the practice of using videoconference technology for course teaching, the current study proposes a qualitative phenomenological approach to investigate the efficacy of videoconferencing as an approach to student learning. Using interviews and observation data from ten participants in Open and Distance Learning institution, the author discusses how dialogue and structure interacted to provide the participating tutors with a rich set of opportunities to deliver course content. The findings to this study highlight various challenges experienced by tutors when using videoconference technology. The study suggests tutor development programs on their capacity and skills and on how to integrate this technology with various teaching strategies in order to enhance student learning. The author argues that it is not merely the existence of the structure, namely the videoconference technology, that provides the opportunity for effective teaching, but that is the interactions, namely, the dialogue amongst tutors and learners that make videoconference technology an attractive vehicle for challenging and changing tutors practice.

Keywords: open distance learning, transactional distance, tutor, videoconference

Procedia PDF Downloads 128

Authors: S. Chee Choy, Daljeet Singh Sedhu

Abstract:

This study examines the relationships between how and why students learned and academic achievement for 2646 university students from various faculties. The LALQ, a self-report measure of student approaches to learning was administered and academic achievement data were obtained from student CGPA. The results showed significant differences in the approach to learning of male and female students. How and why students learned can influence their achievement and efficacy as well. High and low achievers have different learning behaviours. High female achievers were more likely to learn for a better future and be persistent in it. Meanwhile high male achievers were more likely to seek approval from their peers and be more confident about graduating on time from their university. The implications of individual differences and limitations of the study are discussed.

Keywords: student learning, learner awareness, student achievement, LALQ

Procedia PDF Downloads 346

Authors: Francimar Alves, Marcos Castro, Marllus Lustosa

Abstract:

In the context of the teaching of computer programming, the choice of tool to use is very important in the initiation and continuity of learning a programming language. The literature tools do not always provide usability and pedagogical dynamism clearly and accurately for effective learning. This hypothesis implies fall in productivity and difficulty of learning a particular programming language by students. The integrated development environments (IDEs) Dev-C ++ and Code :: Blocks are widely used in introductory courses for undergraduate courses in Computer Science for learning C and C ++ languages. However, after several years of discontinuity maintaining the source code of Dev-C ++ tool, the continued use of the same in the teaching and learning process of the students of these institutions has led to difficulties, mainly due to the lack of update by the official developers, which resulted in a sequence of problems in using it on educational settings. Much of the users, dissatisfied with the IDE Dev-C ++, migrated to Code :: Blocks platform targeting the more dynamic range in the learning process of the C and C ++ languages. Nevertheless, there is still the need to create a tool that can provide the resources of most IDE's software development literature, however, more interactive, simple, accurate and efficient. This motivation led to the creation of Falcon C ++ tool, IDE that brings with features that turn it into an educational platform, which focuses primarily on increasing student learning index in the early disciplines of programming and algorithms that use the languages ​​C and C ++ . As a working methodology, a field research to prove the truth of the proposed tool was used. The test results and interviews with entry-level students and intermediate in a postsecondary institution gave basis for the composition of this work, demonstrating a positive impact on the use of the tool in teaching programming, showing that the use of Falcon C ++ software is beneficial in the teaching process of the C and C ++ programming languages.

Keywords: ide, education, learning, development, language

Procedia PDF Downloads 443

Authors: Lynette Nickleberry Stewart

Abstract:

The present presentation seeks to explore distinction across disciplines in the appropriateness of accelerated courses and suggestions for implementing accelerated courses in various disciplines. Grounded in a review of research on accelerated learning (AL), this presentation will discuss the intradisciplinary appropriateness of accelerated courses for various topics and student types, and make suggestions for implementing augmented courses. Meant to inform an emerging ‘handbook’ of accelerated course development, facilitators will lead participants in a discussion of personal challenges and triumphs in their attempts at accelerated course design.

Keywords: adult learning, abbreviated courses, accelerated learning, course design

Procedia PDF Downloads 120

Authors: Bahman Gorjian

Abstract:

This study investigated the effects of closed-captioning on vocabulary learning and listening comprehension of English-language movies. Captioning is thus an effective language-learning tool for persons learning English as a second language. Because students may learn a foreign language "passively," utilizing subtitles on television could make learning English enjoyable for them. Closed captioning is an electrical technique that converts spoken words from a television program's audio into written text that mimics subtitles in another language. The findings of this study showed the importance of using closed-captioning software when learning a foreign language. As a result, these must be considered when teaching EFL/ESL. The influence of watching movies with closed captions on vocabulary and hearing is compared in this study. This goal can be reached by employing a closed-captioned movie as a teaching tool in the classroom. This research was critical because it demonstrates the advantages of closed-captioning programs in EFL classrooms for both teachers and students. The study's findings assisted teachers in better understanding how to employ closed captioning as a teaching tool in the classroom. The effects will be seen as even more significant for language learners who use the method.

Keywords: closed-captions, listening, comprehension, vcabulary

Procedia PDF Downloads 89

Authors: Mohamed Ahmed Khalil

Abstract:

The number of deep well anode ground beds (GBs) have been retrieved due to unoperated anode chains. New identical magnetite anode chains (MAC) have been installed at Raslanuf complex impressed current Cathodic protection (ICCP) system, distributed at different plants (Utility, ethylene and polyethylene). All problems associated with retrieving and installation of MACs have been discussed, rectified and presented. All GB-associated severely corroded wellhead casings were well maintained and/or replaced by new fabricated and modified ones. The main cause of the wellhead casing's severe internal corrosion was discussed and the conducted remedy action to overcome future corrosion problems is presented. All GB-connected anode junction boxes (AJBs) and shunts were closely inspected, maintained and necessary replacement and/or modifications were carried out on shunts. All damaged GB concrete foundations (CF) have been inspected and completely replaced. All GB-associated Transformer-Rectifiers Units (TRU) were subjected to thorough inspection and necessary maintenance was performed on each individual TRU. After completion of all MACs and TRU maintenance activities, each cathodic protection station (CPS) has been re-operated, alternative current (AC), direct current (DC), voltage and structure to soil potential (S/P) measurements have been conducted, recorded and all obtained test results are presented. DC current outputs have been adjusted and DC current outputs of each MAC have been recorded for each GB AJB.

Keywords: magnetite anodes, deep well, ground beds, cathodic protection, transformer rectifier, impressed current, junction boxes

Procedia PDF Downloads 119

Authors: Mehmet Halkaci, Ekrem Öztürk, Mevlüt Türköz, H. Selçuk Halkacı

Abstract:

Hydromechanical deep drawing (HMD) process is an advanced manufacturing process used to form deep parts with only one forming step. In this process, sheet metal blank can be drawn deeper by means of fluid pressure acting on sheet surface in the opposite direction of punch movement. High limiting drawing ratio, good surface quality, less springback characteristic and high dimensional accuracy are some of the advantages of this process. The performance of the HMD process is affected by various process parameters such as fluid pressure, blank holder force, punch-die radius, pre-bulging pressure and height, punch diameter, friction between sheet-die and sheet-punch. The fluid pressure and bank older force are the main loading parameters and affect the formability of HMD process significantly. The punch diameter also influences the limiting drawing ratio (the ratio of initial sheet diameter to punch diameter) of the sheet metal blank. In this research, optimal loading (fluid pressure and blank holder force) profiles were determined for AA 5754-O sheet material through fuzzy control algorithm developed in previous study using LS-DYNA finite element analysis (FEA) software. In the preceding study, the fuzzy control algorithm was developed utilizing geometrical criteria such as thinning and wrinkling. In order to obtain the final desired part with the developed algorithm in terms of the punch diameter requested, the effect of punch diameter, which is the one of the process parameters, on loading profiles was investigated separately using blank thickness of 1 mm. Thus, the practicality of the previously developed fuzzy control algorithm with different punch diameters was clarified. Also, thickness distributions of the sheet metal blank along a curvilinear distance were compared for the FEA in which different punch diameters were used. Consequently, it was found that the use of different punch diameters did not affect the optimal loading profiles too much.

Keywords: Finite Element Analysis (FEA), fuzzy control, hydromechanical deep drawing, optimal loading profiles, punch diameter

Procedia PDF Downloads 431

Authors: Tsai-Pei Liu, Zhi-Rou Zheng, Tzu-Tzu Wen

Abstract:

Innovative logistics system simulation teaching is to extract the characteristics of the system through simulation methodology. The system has randomness and interaction problems in the execution time. Therefore, the simulation model can usually deal with more complex logistics process problems, giving students different learning modes. Students have more autonomy in learning time and learning progress. System simulation has become a new educational tool, but it still needs to accept many tests to use it in the teaching field. Although many business management departments in Taiwan have started to promote, this kind of simulation system teaching is still not popular, and the prerequisite for popularization is to be supported by students. This research uses an extension of Integration Unified Theory of Acceptance and Use of Technology (UTAUT2) to explore the acceptance of students in universities of science and technology to use system simulation as a learning tool. At the same time, it is hoped that this innovation can explore the effectiveness of the logistics system simulation after the introduction of teaching. The results indicated the significant influence of performance expectancy, social influence and learning value on students’ intention towards confirmed the influence of facilitating conditions and behavioral intention. The extended UTAUT2 framework helps in understanding students’ perceived value in the innovative logistics system teaching context.

Keywords: UTAUT2, logistics system simulation, learning value, Taiwan

Procedia PDF Downloads 115

Authors: Mamadou Dione, Eric Matzner-lober, Philippe Alexandre

Abstract:

The Energy Transition Act defined by the French State has precise implications on Renewable Energies, in particular on its remuneration mechanism. Until then, a purchase obligation contract permitted the sale of wind-generated electricity at a fixed rate. Tomorrow, it will be necessary to sell this electricity on the Market (at variable rates) before obtaining additional compensation intended to reduce the risk. This sale on the market requires to announce in advance (about 48 hours before) the production that will be delivered on the network, so to be able to predict (in the short term) this production. The fundamental problem remains the variability of the Wind accentuated by the geographical situation. The objective of the project is to provide, every day, short-term forecasts (48-hour horizon) of wind production using weather data. The predictions of the GFS model and those of the ECMWF model are used as explanatory variables. The variable to be predicted is the production of a wind farm. We do two approaches: a direct approach that predicts wind generation directly from weather data, and an integrated approach that estimâtes wind from weather data and converts it into wind power by power curves. We used machine learning techniques to predict this production. The models tested are random forests, CART + Bagging, CART + Boosting, SVM (Support Vector Machine). The application is made on a wind farm of 22MW (11 wind turbines) of the Compagnie du Vent (that became Engie Green France). Our results are very conclusive compared to the literature.

Keywords: forecast aggregation, machine learning, spatio-temporal dynamics modeling, wind power forcast

Procedia PDF Downloads 217

Authors: Zachary Blanks, Solomon Sonya

Abstract:

Poaching presents a serious threat to endangered animal species, environment conservations, and human life. Additionally, some poaching activity has even been linked to supplying funds to support terrorist networks elsewhere around the world. Consequently, agencies dedicated to protecting wildlife habitats have a near intractable task of adequately patrolling an entire area (spanning several thousand kilometers) given limited resources, funds, and personnel at their disposal. Thus, agencies need predictive tools that are both high-performing and easily implementable by the user to help in learning how the significant features (e.g. animal population densities, topography, behavior patterns of the criminals within the area, etc) interact with each other in hopes of abating poaching. This research develops a classification model using machine learning algorithms to aid in forecasting future attacks that is both easy to train and performs well when compared to other models. In this research, we demonstrate how data imputation methods (specifically predictive mean matching, gradient boosting, and random forest multiple imputation) can be applied to analyze data and create significant predictions across a varied data set. Specifically, we apply these methods to improve the accuracy of adopted prediction models (Logistic Regression, Support Vector Machine, etc). Finally, we assess the performance of the model and the accuracy of our data imputation methods by learning on a real-world data set constituting four years of imputed data and testing on one year of non-imputed data. This paper provides three main contributions. First, we extend work done by the Teamcore and CREATE (Center for Risk and Economic Analysis of Terrorism Events) research group at the University of Southern California (USC) working in conjunction with the Department of Homeland Security to apply game theory and machine learning algorithms to develop more efficient ways of reducing poaching. This research introduces ensemble methods (Random Forests and Stochastic Gradient Boosting) and applies it to real-world poaching data gathered from the Ugandan rain forest park rangers. Next, we consider the effect of data imputation on both the performance of various algorithms and the general accuracy of the method itself when applied to a dependent variable where a large number of observations are missing. Third, we provide an alternate approach to predict the probability of observing poaching both by season and by month. The results from this research are very promising. We conclude that by using Stochastic Gradient Boosting to predict observations for non-commercial poaching by season, we are able to produce statistically equivalent results while being orders of magnitude faster in computation time and complexity. Additionally, when predicting potential poaching incidents by individual month vice entire seasons, boosting techniques produce a mean area under the curve increase of approximately 3% relative to previous prediction schedules by entire seasons.

Keywords: ensemble methods, imputation, machine learning, random forests, statistical analysis, stochastic gradient boosting, wildlife protection

Procedia PDF Downloads 292

Authors: Nahla H. Alaswadko, Rayya A. Hassan, Bayar N. Mohammed

Abstract:

Empirical deterministic models have been developed to predict roughness progression of heavy duty spray sealed pavements for a dataset representing rural arterial roads. The dataset provides a good representation of the relevant network and covers a wide range of operating and environmental conditions. A sample with a large size of historical time series data for many pavement sections has been collected and prepared for use in multilevel regression analysis. The modelling parameters include road roughness as performance parameter and traffic loading, time, initial pavement strength, reactivity level of subgrade soil, climate condition, and condition of drainage system as predictor parameters. The purpose of this paper is to report the approaches adopted for models development and validation. The study presents multilevel models that can account for the correlation among time series data of the same section and to capture the effect of unobserved variables. Study results show that the models fit the data very well. The contribution and significance of relevant influencing factors in predicting roughness progression are presented and explained. The paper concludes that the analysis approach used for developing the models confirmed their accuracy and reliability by well-fitting to the validation data.

Keywords: roughness progression, empirical model, pavement performance, heavy duty pavement

Procedia PDF Downloads 168

Authors: Ivan Traina, Luigi Sangalli, Fabio Tognon, Angelo Lascioli

Abstract:

Currently, challenges regarding preschooler children are mainly focused on a sedentary lifestyle. Also, motor activity in infancy is seen as a tool for the separate acquisition of cognitive and socio-emotional skills rather than considering neuromotor development as a tool for improving learning abilities. The paper utilized an observational research method to shed light on the results of practicing neuromotor exercises in preschool children with disability as well as provide implications for practice.

Keywords: children with disability, learning abilities, inclusion, neuromotor development

Procedia PDF Downloads 155

Authors: Geraldine O’Neill

Abstract:

Work-integrated learning is a valuable learning experience for students in higher education. However, the fairness of the assessment process has been identified as a challenge. This study explored solutions to this challenge through interviews with expert authors in the field and workshops across nine different disciplines in Ireland. In keeping with the use of a participatory and action research methodology, the key stakeholders in the process, the students, educators, and practitioners, identified some solutions. The solutions included the need to: clarify the assessments’ expectations; enhance the flexibility of the competencies, reduce the number of competencies; use grading scales with lower specificity; support practitioner training, and empower students in the assessment process. The results are discussed as they relate to interactional, procedural, and distributive fairness.

Keywords: competencies, fairness, grading scales, work-integrated learning

Procedia PDF Downloads 125

Authors: Sanjay Patil, Shakil A. Kagzi, Harit K. Raval

Abstract:

Tailor Welded Blanks (TWB) are utilized in automotive industries widely because of their advantage of weight and cost reduction and maintaining required strength and structural integrity. TWB consist of two or more sheet having dissimilar or similar material and thickness; welded together to form a single sheet before forming it to desired shape. Forming of the tailor welded blank is affected by ratio of thickness of blanks, ratio of their strength, etc. mainly due to in-homogeneity of material. In the present work the relative effect of these parameters on weld line movement is studied during deep drawing of TWB using FE simulation using HYPERWORKS. The simulation is validated with results from the literature. Simulations were than performed based on Taguchi orthogonal array followed by the ANOVA analysis to determine the significance of these parameters on forming of TWB.

Keywords: ANOVA, deep drawing, Tailor Welded Blank (TWB), weld line movement

Procedia PDF Downloads 312

Authors: Ahmed T. Alahmar

Abstract:

There is an increasing trend toward student-centred interactive e-learning methods and students’ feedback is a valuable tool for improving learning methods. The aim of this study was to explore the attitude of second year pharmacy students at the University of Babylon, Iraq, towards lectures, exams and e-learning. Materials and methods: Ninety pharmacy students were surveyed by paper questionnaire about their preference for lecture format, use of e-files, theoretical lectures versus practical experiments, lecture and lab time. Students were also asked about their predilection for Moodle-based online exams, different types of exam questions, exam time and other extra academic activities. Results: Students prefer to read lectures on paper (73.3%), use of PowerPoint file (76.7%), short lectures of less than 10 pages (94.5%), practical experiments (66.7%), lectures and lab time of less than two hours (89.9% and 96.6 respectively) and intra-lecture discussions (68.9%). Students also like to have paper-based exam (73.3%), short essay (40%) or MCQ (34.4%) questions and also prefer to do extra activities like reports (22.2%), seminars (18.6%) and posters (10.8%). Conclusion: Second year pharmacy students have different attitudes toward traditional and electronic leaning and assessment methods. Using multimedia, e-learning and Moodle are increasingly preferred methods among some students.

Keywords: pharmacy, students, lecture, exam, e-learning, Moodle

Procedia PDF Downloads 164

Authors: Meiju Chen, Chaoyu Guo, Chia Wei Tang

Abstract:

The present study's purpose is twofold: first, to construct indicators for learning-oriented school education and, second, to conduct a survey to examine how learning-oriented education has been implemented in junior high schools after the launch of the 12-year compulsory curriculum. For indicator system construction, we compiled relevant literature to develop a preliminary indicator list model and then conducted two rounds of a questionnaire survey to gain comprehensive feedback from experts to finalize our indicator model. In the survey's first round, 12 experts were invited to evaluate the indicators' appropriateness. Based on the experts' consensus, we determined our final indicator list and used it to develop the Fuzzy Delphi questionnaire to finalize the indicator system and each indicator's relative value. For the fact-finding survey, we collected 454 valid samples to examine how the concept of learning-oriented education is adopted and implemented in the junior high school context. We also used this data in our importance-performance analysis to explore the strengths and weaknesses of school education in Taiwan. The results suggest that the indicator system for learning-oriented school education must consist of seven dimensions and 34 indicators. Among the seven dimensions, 'student learning' and 'curriculum planning and implementation' are the most important yet underperforming dimensions that need immediate improvement. We anticipate that the indicator system will be a useful tool for other countries' evaluation of schools' performance in learning-oriented education.

Keywords: learning-oriented education, school education, fuzzy Delphi method, importance-performance analysis

Procedia PDF Downloads 142

Authors: Yi-Chuan Cheng, Li-Chi Huang, Yu-Shan Chang

Abstract:

Introduction: The main purpose of this study was to explore the relationship between the learning number, care knowledge, care skills and maternal confidence in preterm infant care in Taiwan. Background: Preterm infants care has been stressful for mother caring at home. Many programs have been applied for improving the infant care maternal confident. But less to know the learning behavior in mothers of preterm infant. Methods: The sample consisted of 55 mothers with preterm infants were recruited in a neonatal intermediate unit at a medical center in central Taiwan. The self-reported questionnaires including knowledge and skills of preterm infant care scales and maternal confidence scale were used to evaluation, which were conducted during hospitalization, before hospital discharge, and one month after discharge. We performed by using Pearson correlation of the collected data using SPSS 18. Results: The study showed that the learning number and knowledge in preterm infant care was a significant positive correlation (r = .40), and the skills and confidence preterm infant care was positively correlated (r = .89). Conclusions: Study results showed the mother had more learning number in preterm infant care will be stronger knowledge, and the skills and confidence in preterm infant care were also positively correlated. Thus, we found the learning behavior change significant care knowledge. And the maternal confidence change significant with skill on preterm infant’s care. But bondage still needs further study and develop the participation in hospital-based instructional programs, which could lead to greater long-term retention of learning.

Keywords: learning behavior, care knowledge, care skills, maternal confidence

Procedia PDF Downloads 260

Authors: Josip Vasilj, Petar Sarajcev, Damir Jakus

Abstract:

One of the major difficulties introduced with wind power penetration is the inherent uncertainty in production originating from uncertain wind conditions. This uncertainty impacts many different aspects of power system operation, especially the balancing power requirements. For this reason, in power system development planing, it is necessary to evaluate the potential uncertainty in future wind power generation. For this purpose, simulation models are required, reproducing the performance of wind power forecasts. This paper presents a wind power forecast error simulation models which are based on the stochastic process simulation. Proposed models capture the most important statistical parameters recognized in wind power forecast error time series. Furthermore, two distinct models are presented based on data availability. First model uses wind speed measurements on potential or existing wind power plant locations, while the seconds model uses statistical distribution of wind speeds.

Keywords: wind power, uncertainty, stochastic process, Monte Carlo simulation

Procedia PDF Downloads 483

Authors: Ameer A. Jebur, William Atherton, Rafid M. Alkhaddar, Edward Loffill

Abstract:

Understanding the behaviour of the piles under the action of the independent lateral loads and the precise prediction of the capacity of piles subjected to different lateral loads are vital topics in foundation design and analysis. Moreover, the laterally loaded behaviour of deep foundations penetrated in cohesive and non-cohesive soils is basically analysed by the Winkler Model (beam on elastic foundation), in which the interaction between the pile embedded depth and contacted soil is simulated by nonlinear p–y curves. The presence of many approaches to interpret the behaviour of soil-pile interaction has resulted in numerous outputs and indicates that no general approach has yet been adopted. The current study presents the result of numerical modelling of the behaviour of steel tubular piles (25.4mm) outside diameter with various embedment depth-to-diameter ratios (L/d) embedded in a sand calibrated chamber of known relative density. The study revealed that the shear strength parameters of the sand specimens and the (L/d) ratios are the most significant factor influencing the response of the pile and its capacity while taking into consideration the complex interaction between the pile and soil. Good agreement has been achieved when comparing the application of this modelling approach with experimental physical modelling carried out by another researcher.

Keywords: deep foundations, slenderness ratio, soil-pile interaction, winkler model (beam on elastic foundation), non-cohesive soil

Procedia PDF Downloads 299

Authors: Deborah Asibu Abu

Abstract:

Motivation is the process that initiates, guides, and maintains goal-oriented behaviors. It is one of the most important ingredients in teaching and learning yet it does not come by chance; it involves necessary strategies appropriate to achieve a common goal. In learning, the psychological attention of the student is very important. This helps them to imagine whatever is being taught for a simple understanding, nonetheless, many students will be able to imagine how the environment is in social studies or how the bones or plant is, in integrated Science but will find it difficult to imagine what subject-verb agreement or phrases and clauses actually looks like until they are motivated or with the use of TLM’s to stir their interest to learn and forever remember. For students to be able to receive the motivation they need, there must be an effective relationship between the teacher and the student as well as the use of strategies for effectual execution of achievable goals. Every teacher must understand the importance of motivation by applying various kinds of teaching methodology, especially in the English Language as a subject. Hence this paper suggests some important factors necessary for student’s motivation in teaching and learning English Language, it handles what teaching method is, types of motivation, educational curriculum structure of many, what suitable teaching methods can achieve, appropriate teachers’ disposition, learning environment as tool for motivation and some other domestic factors that can also influence student motivation.

Keywords: english language, teacher-student relationship, curriculum structure, learning environment

Procedia PDF Downloads 50