Search results for: embedded learning support

Authors: D. I. George Amalarethinam, A. Emima

Abstract:

Educational Data Mining (EDM) is one of the newest topics to emerge in recent years, and it is concerned with developing methods for analyzing various types of data gathered from the educational circle. EDM methods and techniques with machine learning algorithms are used to extract meaningful and usable information from huge databases. For scientists and researchers, realistic applications of Machine Learning in the EDM sectors offer new frontiers and present new problems. One of the most important research areas in EDM is predicting student success. The prediction algorithms and techniques must be developed to forecast students' performance, which aids the tutor, institution to boost the level of student’s performance. This paper examines various classification techniques in prediction methods and data mining tools used in EDM.

Keywords: classification technique, data mining, EDM methods, prediction methods

Procedia PDF Downloads 107

Authors: A. Biran, P. Sobhe Bidari, A. Almazroe, V. Lakshminarayanan, K. Raahemifar

Abstract:

Diabetic Retinopathy (DR) is a severe retinal disease which is caused by diabetes mellitus. It leads to blindness when it progress to proliferative level. Early indications of DR are the appearance of microaneurysms, hemorrhages and hard exudates. In this paper, an automatic algorithm for detection of DR has been proposed. The algorithm is based on combination of several image processing techniques including Circular Hough Transform (CHT), Contrast Limited Adaptive Histogram Equalization (CLAHE), Gabor filter and thresholding. Also, Support Vector Machine (SVM) Classifier is used to classify retinal images to normal or abnormal cases including non-proliferative or proliferative DR. The proposed method has been tested on images selected from Structured Analysis of the Retinal (STARE) database using MATLAB code. The method is perfectly able to detect DR. The sensitivity specificity and accuracy of this approach are 90%, 87.5%, and 91.4% respectively.

Keywords: diabetic retinopathy, fundus images, STARE, Gabor filter, support vector machine

Procedia PDF Downloads 279

Authors: Syed Atif Hassan, Luv Mehta, Syed Asif Hassan

Abstract:

Hit song science is a field of investigation wherein machine learning techniques are applied to music tracks in order to extract such features from audio signals which can capture information that could explain the popularity of respective tracks. Record companies invest huge amounts of money into recruiting fresh talents and churning out new music each year. Gaining insight into the basis of why a song becomes popular will result in tremendous benefits for the music industry. This paper aims to extract basic musical and more advanced, acoustic features from songs while also taking into account external factors that play a role in making a particular song popular. We use a dataset derived from popular Spotify playlists divided by genre. We use ten genres (blues, classical, country, disco, hip-hop, jazz, metal, pop, reggae, rock), chosen on the basis of clear to ambiguous delineation in the typical sound of their genres. We feed these features into three different classifiers, namely, SVM with RBF kernel, a deep neural network, and a recurring neural network, to build separate predictive models and choosing the best performing model at the end. Predicting song popularity is particularly important for the music industry as it would allow record companies to produce better content for the masses resulting in a more competitive market.

Keywords: classifier, machine learning, music tracks, popularity, prediction

Procedia PDF Downloads 637

Authors: Nguyen Thi Kim Thoa

Abstract:

Vietnam currently has about two million five hundred deaf/hard of hearing people. Although the issue of Vietnamese Sign Language (VSL) education has received attention from the State, there are still many issues that need to be resolved, such as policies, teacher training in both knowledge and teaching methods, education programs, and textbook compilation. Furthermore, the issue of research on VSL has not yet attracted the attention of linguists. Using the quantitative description method, the article will analyze, synthesize, and compare to find methods to create signed words in VSL, such as based on external shape characteristics, operational characteristics, operating methods, and basic meanings, from which we can see the special nature of signed words, the division of word types and the morphological meaning of creating new words through sign methods. From the results of this research, the aspect of ‘visual culture’ will be clarified in Vietnamese Deaf Culture. Through that, we also develop a number of vocabulary teaching methods (such as teaching vocabulary through a group of methods of forming signed words, teaching vocabulary using mind maps, and teaching vocabulary through culture...), with the aim of further improving the effectiveness of teaching and learning VSL in Vietnam. The research results also provide deaf people in Vietnam with a scientific and effective method of learning vocabulary, helping them quickly integrate into the community. The article will be a useful reference for linguists who want to research VSL.

Keywords: Vietnamese sign language (VSL), signed word, teaching, method

Procedia PDF Downloads 17

Authors: Ken Hampshire, Thomas Mazzuchi, Shahram Sarkani

Abstract:

As a subset of metaheuristics, nature-inspired optimization algorithms such as particle swarm optimization (PSO) have shown promise both in solving intractable problems and in their extensibility to novel problem formulations due to their general approach requiring few assumptions. Unfortunately, single instantiations of algorithms require detailed tuning of parameters and cannot be proven to be best suited to a particular illustrative problem on account of the “no free lunch” (NFL) theorem. Using these algorithms in real-world problems requires exquisite knowledge of the many techniques and is not conducive to reconciling the various approaches to given classes of problems. This research aims to present a unified view of PSO-based approaches from the perspective of relevant systems engineering problems, with the express purpose of then eliciting the best solution for any problem formulation in an ensemble learning bucket of models approach. The central hypothesis of the research is that extending the PSO algorithms found in the literature to real-world optimization problems requires a general ensemble-based method for all problem formulations but a specific implementation and solution for any instance. The main results are a problem-based literature survey and a general method to find more globally optimal solutions for any systems engineering optimization problem.

Keywords: particle swarm optimization, nature-inspired optimization, metaheuristics, systems engineering, ensemble learning

Procedia PDF Downloads 75

Authors: Lisseth Rojas Barreto, Carlos Muñoz Hernández

Abstract:

The COVID-19 pandemic led to many abrupt changes, including a prolonged lockdown, which brought about work and personal challenges to the population worldwide. Among the most affected populations are women who are workers and housewives at the same time, and especially those who are also parenting. These women were faced with the challenge to perform their usual varied roles during the lockdown from the same physical space, which inevitably had strong repercussions for each of them. This paper will present some results of a research study whose main objective was to examine the possible effects that the COVID-19 pandemic lockdown may have caused in the work, social, family, and personal environments of female English teachers who are also housewives and, by extension in the teaching and learning processes that they lead. Participants included five female English language teachers of a public foreign language school, they are all married, and two of them have children. Similarly, we examined some of the coping strategies these teachers used to tackle the pandemic-related challenges in their different roles, especially those used for their language teaching role; coping strategies are understood as a repertoire of behaviors in response to incidents that can be stressful for the subject, possible challenging events or situations that involve emotions with behaviors and decision-making of people which are used in order to find a meaning or positive result (Lazarus &Folkman, 1986) Following a qualitative-case study design, we gathered the data through a survey and a focus group interview with the participant teachers who work at a public language school in southern Colombia. Preliminary findings indicate that the circumstances that emerged as a result of the pandemic lockdown affected the participants in different ways, including financial, personal, family, health, and work-related issues. Among the strategies that participants found valuable to deal with the novel circumstances, we can highlight the reorganization of the household and work tasks and the increased awareness of time management for the household, work, and leisure. Additionally, we were able to evidence that the participants faced the circumstances with a positive view. Finally, in order to cope with their teaching duties, some participants acknowledged their lack of computer or technology literacy in order to deliver their classes online, which made them find support from their students or more knowledgeable peers to cope with it. Others indicated that they used strategies such as self-learning in order to get acquainted and be able to use the different technological tools and web-based platforms available.

Keywords: coping strategies, language teaching, female teachers, pandemic lockdown

Procedia PDF Downloads 91

Authors: T. Heiman, D. Olenik-Shemesh

Abstract:

Over the past decade, with the rapid growth of electronic communication, the internet and, in particular, social networking has become an inseparable part of people's daily lives. Along with its benefits, a new type of online aggression has emerged, defined as cyber bullying, a form of interpersonal aggressive behavior that takes place through electronic means. Cyber-bullying is characterized by repetitive behavior over time of maladaptive authority and power usage using computers and cell phones via sending insulting messages and hurtful pictures. Preliminary findings suggest that the prevalence of involvement in cyber-bullying among higher education students varies between 10 and 35%. As to date, universities are facing an uphill effort in trying to restrain online misbehavior. As no studies examined the relationships between cyber-bullying involvement with personal aspects, and its impacts on academic achievement and work functioning, this present study examined the nature of cyber-bullying involvement among 1,052 undergraduate students (mean age = 27.25, S.D = 4.81; 66.2% female), coping with, as well as the effects of social support, perceived self-efficacy, well-being, and body-perception, in relation to cyber-victimization. We assume that students in higher education are a vulnerable population and at high risk of being cyber-victims. We hypothesize that social support might serve as a protective factor and will moderate the relationships between the socio-emotional variables and the occurrence of cyber- victimization. The findings of this study will present the relationships between cyber-victimization and the social-emotional aspects, which constitute risk and protective factors. After receiving approval from the Ethics Committee of the University, a Google Drive questionnaire was sent to a random sample of students, studying in the various University study centers. Students' participation was voluntary, and they completed the five questionnaires anonymously: Cyber-bullying, perceived self-efficacy, subjective well-being, social support and body perception. Results revealed that 11.6% of the students reported being cyber-victims during last year. Examining the emotional and behavioral reactions to cyber-victimization revealed that female emotional and behavioral reactions were significantly greater than the male reactions (p < .001). Moreover, females reported on a significant higher social support compared to men; male reported significantly on a lower social capability than female; and men's body perception was significantly more positive than women's scores. No gender differences were observed for subjective well-being scale. Significant positive correlations were found between cyber-victimization and fewer friends, lower grades, and work ineffectiveness (r = 0.37- .40, p < 0 .001). The results of the Hierarchical regression indicated significantly that cyber-victimization can be predicted by lower social support, lower body perception, and gender (female), that explained 5.6% of the variance (R2 = 0.056, F(5,1047) = 12.47, p < 0.001). The findings deepen our understanding of the students' involvement in cyber-bullying, and present the relationships of the social-emotional and academic aspects on cyber-victim students. In view of our findings, higher education policy could help facilitate coping with cyber-bullying incidents, and student support units could develop intervention programs aimed at reducing cyber-bullying and its impacts.

Keywords: academic and personal factors, cyber-victimization, social support, higher education

Procedia PDF Downloads 276

Authors: Young-Min Ko, Seung-Jun Yu, Seongjoo Lee, Hyoung-Kyu Song

Abstract:

The Internet of things (IoT) system has attracted attention. IoT is a technology to connect all the objects to the internet as well as computer. IoT makes it possible for providing more data interoperability methods for an application purpose. Among the IoT technology, the research of devices so that they can communicate without power supply has been actively conducted. Batteryless system permits us to communicate without power supply devices. In this paper, batteryless backscatter system is used as a tag. And mobile devices which are embedded wireless fidelity (Wi-Fi) chipset are used as a reader. The backscatter tag can be obtained Internet connectivity from the reader. Conventional Wi-Fi backscatter system has limitation in the transmission range. In this paper, the proposed algorithm can be obtained improved reliability as well as overcoming the limitation about transmission range.

Keywords: Ambient RF, Backscatter, Batteryless communication, Energy-harvesting, IoT, RFID, Tag, Wi-Fi

Procedia PDF Downloads 373

Authors: Eugenia Vomvoridi-Ivanovic

Abstract:

It is broadly assumed that participation in field experiences will help pre-service teachers (PSTs) bridge theory to practice. However, this is often not the case since PSTs who are placed in classrooms with large numbers of students from diverse linguistic, cultural, racial, and ethnic backgrounds (culturally diverse students (CDS)) usually observe ineffective mathematics teaching practices that are in contrast to those discussed in their teacher preparation program. Over the past decades, the educational research community has paid increasing attention to investigating out-of-school learning contexts and how participation in such contexts can contribute to the achievement of underrepresented groups in Science, Technology, Engineering, and mathematics (STEM) education and their expanded participation in STEM fields. In addition, several research studies have shown that students display different kinds of mathematical behaviors and discourse practices in out-of-school contexts than they do in the typical mathematics classroom since they draw from a variety of linguistic and cultural resources to negotiate meanings and participate in joint problem solving. However, almost no attention has been given to exploring these contexts as field experiences for pre-service mathematics teachers. The purpose of this study was to explore how participation in a community based after-school field experience promotes understanding of the content pedagogy concepts introduced in elementary mathematics methods courses, particularly as they apply to teaching mathematics to CDS. This study draws upon a situated, socio-cultural theory of teacher learning that centers on the concept of learning as situated social practice, which includes discourse, social interaction, and participation structures. Consistent with exploratory case study methodology, qualitative methods were employed to investigate how a cohort of twelve participating pre-service teacher's approach to pedagogy and their conversations around teaching and learning mathematics to CDS evolved through their participation in the after-school field experience, and how they connected the content discussed in their mathematics methods course with their interactions with the CDS in the after-school. Data were collected over a period of one academic year from the following sources: (a) audio recordings of the PSTs' interactions with the students during the after-school sessions, (b) PSTs' after-school field-notes, (c) audio-recordings of weekly methods course meetings, and (d) other document data (e.g., PST and student generated artifacts, PSTs' written course assignments). The findings of this study reveal that the PSTs benefitted greatly through their participation in the after-school field experience. Specifically, after-school participation promoted a deeper understanding of the content pedagogy concepts introduced in the mathematics methods course and gained a greater appreciation for how students learn mathematics with understanding. Further, even though many of PSTs' assumptions about the mathematical abilities of CDS were challenged and PSTs began to view CDSs' cultural and linguistic backgrounds as resources (rather than obstacles) for learning, some PSTs still held negative stereotypes about CDS and teaching and learning mathematics to CDS in particular. Insights gained through this study contribute to a better understanding of how informal mathematics learning contexts may provide a valuable context for pre-service teacher's learning to teach mathematics to CDS.

Keywords: after-school mathematics program, pre-service mathematical education of teachers, qualitative methods, situated socio-cultural theory, teaching culturally diverse students

Procedia PDF Downloads 119

Authors: Zhikal Qadir Salih, Hanife Bensen

Abstract:

As the advent of modern technology continues to make towering impacts on everything, its relevance permeates to all spheres, language learning, and writing skills in particular not an exception. This study aimed at finding out how EFL learners perceive online tools to improve their writing skills. The study was carried out at Tishk University. Copies of the questionnaire were distributed to the participants, in order to elicit their perceptions. The collected data were subjected to descriptive and inferential statistics. The outcome revealed that the participants have positive perceptions about online tools in using them to enhance their writing skills. The study however found out that both gender and the class level of the participants do not make any significant difference in their perceptions about the use of online tools, as far as writing skill is concerned. Based on these outcomes, relevant recommendations were made.

Keywords: online tools, writing skills, EFL learners, language learning

Procedia PDF Downloads 87

Authors: Kishor T. Zingre, Seshadhri Srinivasan

Abstract:

Energy consumption by the building sector is increasing at an alarming rate throughout the world and leading to more building-related CO₂ emissions into the environment. In buildings, the main contributors to energy consumption are heating, ventilation, and air-conditioning (HVAC) systems, lighting, and electrical appliances. It is hypothesised that the energy efficiency in buildings can be achieved by implementing sustainable technologies such as i) enhancing the thermal resistance of fabric materials for reducing heat gain (in hotter climates) and heat loss (in colder climates), ii) enhancing daylight and lighting system, iii) HVAC system and iv) occupant localization. Energy performance of various sustainable technologies is highly dependent on climatic conditions. This paper investigated the use of machine learning techniques for accurate prediction of air-conditioning energy in seasonal climates. The data required to train the machine learning techniques is obtained using the computational simulations performed on a 3-story commercial building using EnergyPlus program plugged-in with OpenStudio and Google SketchUp. The EnergyPlus model was calibrated against experimental measurements of surface temperatures and heat flux prior to employing for the simulations. It has been observed from the simulations that the performance of sustainable fabric materials (for walls, roof, and windows) such as phase change materials, insulation, cool roof, etc. vary with the climate conditions. Various renewable technologies were also used for the building flat roofs in various climates to investigate the potential for electricity generation. It has been observed that the proposed technique overcomes the shortcomings of existing approaches, such as local linearization or over-simplifying assumptions. In addition, the proposed method can be used for real-time estimation of building air-conditioning energy.

Keywords: building energy efficiency, energyplus, machine learning techniques, seasonal climates

Procedia PDF Downloads 103

Authors: Susana Barreto

Abstract:

This paper explores a pedagogical exercise that employs family photos as catalysts for teaching visual analysis and inspiring academic writing among MA students. The study aimed to achieve two primary objectives: to impart students with the skills of analyzing images or artifacts and to ignite their writing for research purposes. Conducted at Viana Polytechnic in Portugal, the exercise involved two classes on Arts Management and Art Education Master course comprising approximately twenty students from diverse academic backgrounds, including Economics, Design, Fine Arts, and Sociology, among others. The exploratory exercise involved selecting an old family photo, analyzing its content and context, and deconstructing the chosen images in an intuitive and systematic manner. Students were encouraged to engage in photo elicitation, seeking insights from family/friends to gain multigenerational perspectives on the images. The feedback received from this exercise was consistently positive, largely due to the personal connection students felt with the objects of analysis. Family photos, with their emotional significance, fostered deeper engagement and motivation in the learning process. Furthermore, visual analysing family photos stimulated critical thinking as students interpreted the composition, subject matter, and potential meanings embedded in the images. This practice enhanced their ability to comprehend complex visual representations and construct compelling visual narratives, thereby facilitating the writing process. The exercise also facilitated the identification of patterns, similarities, and differences by comparing different family photos, leading to a more comprehensive analysis of visual elements and themes. Throughout the exercise, students found analyzing their own photographs both enjoyable and insightful. They progressed through preliminary analysis, explored content and context, and artfully interwove these components. Additionally, students experimented with various techniques such as converting photos to black and white, altering framing angles, and adjusting sizes to unveil hidden meanings.The methodology employed included observation, documental analysis of written reports, and student interviews. By including students from diverse academic backgrounds, the study enhanced its external validity, enabling a broader range of perspectives and insights during the exercise. Furthermore, encouraging students to seek multigenerational perspectives from family and friends added depth to the analysis, enriching the learning experience and broadening the understanding of the cultural and historical context associated with the family photos Highlighting the emotional significance of these family photos and the personal connection students felt with the objects of analysis fosters a deeper connection to the subject matter. Moreover, the emphasis on stimulating critical thinking through the analysis of composition, subject matter, and potential meanings in family photos suggests a targeted approach to developing analytical skills. This improvement focuses specifically on critical thinking and visual analysis, enhancing the overall quality of the exercise. Additionally, the inclusion of a step where students compare different family photos to identify patterns, similarities, and differences further enhances the depth of the analysis. This comparative approach adds a layer of complexity to the exercise, ultimately leading to a more comprehensive understanding of visual elements and themes. The expected results of this study will culminate in a set of practical recommendations for implementing this exercise in academic settings.

Keywords: visual analysis, academic writing, pedagogical exercise, family photos

Procedia PDF Downloads 44

Authors: Carlos Ferreira, Paulo Freitas, Valentim Freitas

Abstract:

Creative industries’ workers are becoming more prominent as countries move towards intellectual-based economies. Consequently, the nature and essence of the workplace needs to be reconfigured so that creativity and productivity can be better promoted at these spaces. Using a multidisciplinary approach and a user-centered methodology, combining product design, electronic engineering, software and human-computer interaction, we have designed and developed a new seat that uses embedded sensors and actuators to increase the overall well-being of its users, their productivity and their creativity. Our contribution focuses on the parameters that most affect the user’s work on these kinds of spaces, which are, according to our study, noise and temperature. We describe the design process for a new interactive seat targeted at improving workspace productivity.

Keywords: human-computer interaction, usability, user interface, creativity, ergonomics

Procedia PDF Downloads 206

Authors: Ali Kirkbas

Abstract:

R peaks in an electrocardiogram (ECG) are signs of cardiac activity in individuals that reveal valuable information about cardiac abnormalities, which can lead to mortalities in some cases. This paper examines the problem of detecting R-peaks in ECG signals, which is a two-class pattern classification problem in fact. To handle this problem with a reliable high accuracy, we propose to use the common vector approach which is a successful machine learning algorithm. The dataset used in the proposed method is obtained from MIT-BIH, which is publicly available. The results are compared with the other popular methods under the performance metrics. The obtained results show that the proposed method shows good performance than that of the other. methods compared in the meaning of diagnosis accuracy and simplicity which can be operated on wearable devices.

Keywords: ECG, R-peak classification, common vector approach, machine learning

Procedia PDF Downloads 44

Authors: Julio Jesus Salazar, Julio Jesus De Lama

Abstract:

the fundamental objective of hydrological studies applied to the engineering field is to determine the statistically consistent volumes or water flows that, in each case, allow us to size or design a series of elements or structures to effectively manage and develop a river basin. To determine these values, there are several ways of working within the framework of traditional hydrology: (1) Study each of the factors that influence the hydrological cycle, (2) Study the historical behavior of the hydrology of the area, (3) Study the historical behavior of hydrologically similar zones, and (4) Other studies (rain simulators or experimental basins). Of course, this range of studies in a certain basin is very varied and complex and presents the difficulty of collecting the data in real time. In this complex space, the study of variables can only be overcome by collecting and transmitting data to decision centers through the Internet of things and artificial intelligence. Thus, this research work implemented the learning project of the sub-basin of the Shullcas river in the Andean basin of the Mantaro river in Peru. The sensor firmware to collect and communicate hydrological parameter data was programmed and tested in similar basins of the European Union. The Machine Learning applications was programmed to choose the algorithms that direct the best solution to the determination of the rainfall-runoff relationship captured in the different polygons of the sub-basin. Tests were carried out in the mountains of Europe, and in the sub-basins of the Shullcas river (Huancayo) and the Yauli river (Jauja) with heights close to 5000 m.a.s.l., giving the following conclusions: to guarantee a correct communication, the distance between devices should not pass the 15 km. It is advisable to minimize the energy consumption of the devices and avoid collisions between packages, the distances oscillate between 5 and 10 km, in this way the transmission power can be reduced and a higher bitrate can be used. In case the communication elements of the devices of the network (internet of things) installed in the basin do not have good visibility between them, the distance should be reduced to the range of 1-3 km. The energy efficiency of the Atmel microcontrollers present in Arduino is not adequate to meet the requirements of system autonomy. To increase the autonomy of the system, it is recommended to use low consumption systems, such as the Ashton Raggatt McDougall or ARM Cortex L (Ultra Low Power) microcontrollers or even the Cortex M; and high-performance direct current (DC) to direct current (DC) converters. The Machine Learning System has initiated the learning of the Shullcas system to generate the best hydrology of the sub-basin. This will improve as machine learning and the data entered in the big data coincide every second. This will provide services to each of the applications of the complex system to return the best data of determined flows.

Keywords: hydrology, internet of things, machine learning, river basin

Procedia PDF Downloads 146

Authors: Hajer Chaker Ben Hadj Kacem, Thouraya Slama, Néjiba El Yetim Zribi

Abstract:

This paper analyzes the effects of gender, affiliation, prior work experience, social work, and vicarious learning through family role models on entrepreneurial skills development by students when they have learned through the entrepreneurship method in Tunisia. Authors suggest that these variables enhance the development of students’ entrepreneurial skills when combined with teaching through entrepreneurship. The article assesses the impact of these combinations by comparing their effects on the development of thirteen students’ entrepreneurial competencies, namely entrepreneurial mindset, core self-evaluation, entrepreneurial attitude, entrepreneurial knowledge, creativity, financial literacy, managing ambiguity, marshaling of resources, planning, teaching methods, entrepreneurial teachers, innovative employee, and Entrepreneurial intention. Authors use a two-sample independent t-test to make the comparison, and the results indicate that, when combined with teaching through the entrepreneurship method, students with prior work experience developed better six entrepreneurial skills; students with social work developed better three entrepreneurial skills, men developed better four entrepreneurial skills than women. However, all students developed their entrepreneurial skills through this practical method regardless of their affiliation and their vicarious learning through family role models.

Keywords: affiliation, entrepreneurial skills, gender, role models, social work, teaching through entrepreneurship, vicarious learning, work experience

Procedia PDF Downloads 86

Authors: Shiuh-Jer Huang, Chen-Zon Yan, C. K. Huang, Chun-Chien Ting

Abstract:

Since the vision system application in industrial environment for autonomous purposes is required intensely, the image recognition technique becomes an important research topic. Here, deep learning algorithm is employed in image system to recognize the industrial object and integrate with a 7A6 Series Manipulator for object automatic gripping task. PC and Graphic Processing Unit (GPU) are chosen to construct the 3D Vision Recognition System. Depth Camera (Intel RealSense SR300) is employed to extract the image for object recognition and coordinate derivation. The YOLOv2 scheme is adopted in Convolution neural network (CNN) structure for object classification and center point prediction. Additionally, image processing strategy is used to find the object contour for calculating the object orientation angle. Then, the specified object location and orientation information are sent to robotic controller. Finally, a six-axis manipulator can grasp the specific object in a random environment based on the user command and the extracted image information. The experimental results show that YOLOv2 has been successfully employed to detect the object location and category with confidence near 0.9 and 3D position error less than 0.4 mm. It is useful for future intelligent robotic application in industrial 4.0 environment.

Keywords: deep learning, image processing, convolution neural network, YOLOv2, 7A6 series manipulator

Procedia PDF Downloads 223

Authors: A. U. Ugwu

Abstract:

Post-Apartheid South African education system had witnessed waves of curriculum reforms. Accordingly, there have been evidences of responsiveness towards local and global challenges of sustainable development over the past decade. In other words, the curriculum shows sensitivity towards issues of Sustainable Development (SD). Moreover, the paradigm of Sustainable Development Goals (SDGs) was introduced by the UNESCO in year 2015. The SDGs paradigm is essentially a vision towards actualizing sustainability in all aspects of the global society. Education for Sustainable Development (ESD) in retrospect entails teaching and learning to actualize the intended UNESCO 2030 SDGs. This paper explores how teaching and learning of ESD can be improved, by drawing from local context of the South African schooling system. Preservice natural sciences and technology teachers in their 2nd to 4th years of study at a university’s college of education in South Africa were contacted as participants of the study. Using qualitative case study research design, the study drew from the views and experiences of five (5) purposively selected participants from a broader study, aiming to closely understating how ESD is implemented pedagogically in teaching and learning. The inquiry employed questionnaires and a focus group discussion as qualitative data generation tools. A qualitative data analysis of generated data was carried out using content and thematic analysis, underpinned by interpretive paradigm. The result of analyzed data, suggests that ESD pedagogy at the location where this research was conducted is largely influenced by contextual factors. Furthermore, the result of the study shows that there is a critical need to employ/adopt local experiences or occurrences while teaching sustainable development. Certain pedagogical approaches such as the use of videos relative to local context should also be considered in order to achieve a more realistic application. The paper recommends that educational institutions through teaching and learning should implement ESD by drawing on local contexts and problems, thereby foregrounding constructivism, appreciating and fostering students' prior knowledge and lived experiences.

Keywords: context, education for sustainable development, natural sciences and technology preservice teachers, qualitative research, sustainable development goals

Procedia PDF Downloads 152

Authors: Semanur Savruk, Onur Akbatı

Abstract:

Integration of various communication protocols into an automation system causes a rise in setup and maintenance cost and make to control network devices in difficulty. The gateway becomes necessary for reducing complexity in network topology. In this study, Modbus RTU/Modbus TCP industrial ethernet gateway design and implementation are presented with ARM embedded system and FreeRTOS real-time operating system. The Modbus gateway can perform communication with Modbus RTU and Modbus TCP devices over itself. Moreover, the gateway can be adjustable with the user-interface application or messaging interface. Conducted experiments and the results are presented in the paper. Eventually, the proposed system is a complete, low-cost, real-time, and user-friendly design for monitoring and setting devices and useful for meeting remote control purposes.

Keywords: gateway, industrial communication, modbus, network

Procedia PDF Downloads 123

Authors: Wei Li, Tuo Yang

Abstract:

In order to satisfy the real-time and accurate requirements of cigarette smoke detection in complex scenes, a cigarette smoke detection technology based on the combination of deep learning and color features was proposed. Firstly, based on the color features of cigarette smoke, the suspicious cigarette smoke area in the image is extracted. Secondly, combined with the efficiency of cigarette smoke detection and the problem of network overfitting, a network model for cigarette smoke detection was designed according to YOLOV3 algorithm to reduce the false detection rate. The experimental results show that the method is feasible and effective, and the accuracy of cigarette smoke detection is up to 99.13%, which satisfies the requirements of real-time cigarette smoke detection in complex scenes.

Keywords: deep learning, computer vision, cigarette smoke detection, YOLOV3, color feature extraction

Procedia PDF Downloads 71

Authors: Fatihin Khoirul, Muhammad Muqorrobin Ist

Abstract:

Bojonegoro Regency is one of the districts that use the concept Agropolitan as the Territorial Development Policy. Three sub-district designated as Area Development District of Agropolitan are Kapas, Dander, and Kalitidu or commonly called KADEKA. Current policy has been shown results, but there was an inequality of results in some areas. One of them occurred in the Ngringinrejo village with the main commodities is Starfruit and Wedi village with the main commodities is Salak fruit. Therefore, a comparative study is used to search for causal factors of inequality result of the policy by using the 5 aspects compared, namely: (1) Management Development Agropolitan; (2) Physical Condition agropolitan Region; (3) Implementing Agency at the Village Level; (4) Village Government Support; and (5) Community support. Based on the discussion of qualitative analysis, it was found that five aspects have their respective roles in creating inequality of outcomes that occur in both villages. But beyond that, there are conditions where the two villages experienced the same condition that is when the initial implementation of the policy. The condition is referred to as 'the phenomenon of price trap.' The condition is caused by lower commodity prices, causing the village government's commitment in implementing policies too low, followed by public awareness in support of the policy is also low, so care for commodities is also low, and the quality is too low lead and eventually back causing low price. However, the difference is that the village Ngringinrejo able to get out of this condition with 'the new culture of administration' at the end of 2013. While the conditions in the village of Wedi compounded by not respected request assistance by the irrigation district.

Keywords: comparative policy analysis, qualitative comparative, inequallity, price trap, new culture of administration

Procedia PDF Downloads 267

Authors: Anita Setianingrum, Oki S. Jaya, Zuherman Rustam

Abstract:

Forecasting stock price is a challenging task due to the complex time series of the data. The complexity arises from many variables that affect the stock market. Many time series models have been proposed before, but those previous models still have some problems: 1) put the subjectivity of choosing the technical indicators, and 2) rely upon some assumptions about the variables, so it is limited to be applied to all datasets. Therefore, this paper studied a novel Adaptive Neuro-Fuzzy Inference System (ANFIS) time series model based on Support Vector Regression (SVR) for forecasting the stock market. In order to evaluate the performance of proposed models, stock market transaction data of TAIEX and HIS from January to December 2015 is collected as experimental datasets. As a result, the method has outperformed its counterparts in terms of accuracy.

Keywords: ANFIS, fuzzy time series, stock forecasting, SVR

Procedia PDF Downloads 230

Authors: Hanae Ait Hattani, Nohaila Ait Hattani

Abstract:

Globalization, with the rapid technological progress, is affecting every life aspect. The 21st century higher education faces a major challenge in preparing well-rounded and competent graduates to compete in the global marketplace. Worldwide, educational policies work to develop the quality of instruction at all educational levels by focusing on promoting students’ qualifications and skills, considering both academic activities and non-academic attributes. In fact, extracurricular activities (ECAs) complement the academic curriculum and enhance the student experience by improving their interpersonal skills and attitudes. This study comes to examine the potential of extracurricular activities as a vital tool for soft skills’ development. Using empirical research, the study aims to measure and evaluate the extent to which university students’ engagement in extracurricular activities contribute in positively changing their learning experience, fostering their soft skills and fostering their behaviors and attitudes. Findings emanating from a questionnaire and semi-structured interviews add a number of contributions to the literature. They support the assumption suggesting that ECAs can be considered a valuable way to acquire, develop, and demonstrate softs skills that students today need to evidence in a variety of contexts, such as communication skills, team work, leadership, problem-solving, to name but a few.

Keywords: extracurricular activities (ECAs), soft skills, education, university, attitude

Procedia PDF Downloads 61

Authors: Tayo P. Ogundunmade, Adedayo A. Adepoju

Abstract:

Terrorist attacks in liberal democracies bring about a few pessimistic results, for example, sabotaged public support in the governments they target, disturbing the peace of a protected environment underwritten by the state, and a limitation of individuals from adding to the advancement of the country, among others. Hence, seeking for techniques to understand the different factors involved in terrorism and how to deal with those factors in order to completely stop or reduce terrorist activities is the topmost priority of the government in every country. This research aim is to develop an efficient deep learning-based predictive model for the prediction of future terrorist activities in Nigeria, addressing low-quality prediction accuracy problems associated with the existing solution methods. The proposed predictive AI-based model as a counterterrorism tool will be useful by governments and law enforcement agencies to protect the lives of individuals in society and to improve the quality of life in general. A Heterogeneous Bayesian Neural Network (HETBNN) model was derived with Gaussian error normal distribution. Three primary transfer functions (HOTTFs), as well as two derived transfer functions (HETTFs) arising from the convolution of the HOTTFs, are namely; Symmetric Saturated Linear transfer function (SATLINS ), Hyperbolic Tangent transfer function (TANH), Hyperbolic Tangent sigmoid transfer function (TANSIG), Symmetric Saturated Linear and Hyperbolic Tangent transfer function (SATLINS-TANH) and Symmetric Saturated Linear and Hyperbolic Tangent Sigmoid transfer function (SATLINS-TANSIG). Data on the Terrorist activities in Nigeria gathered through questionnaires for the purpose of this study were used. Mean Square Error (MSE), Mean Absolute Error (MAE) and Test Error are the forecast prediction criteria. The results showed that the HETFs performed better in terms of prediction and factors associated with terrorist activities in Nigeria were determined. The proposed predictive deep learning-based model will be useful to governments and law enforcement agencies as an effective counterterrorism mechanism to understand the parameters of terrorism and to design strategies to deal with terrorism before an incident actually happens and potentially causes the loss of precious lives. The proposed predictive AI-based model will reduce the chances of terrorist activities and is particularly helpful for security agencies to predict future terrorist activities.

Keywords: activation functions, Bayesian neural network, mean square error, test error, terrorism

Procedia PDF Downloads 148

Authors: Malte Brettel, Niklas Friederichsen, Michael Keller, Marius Rosenberg

Abstract:

The German manufacturing industry has to withstand an increasing global competition on product quality and production costs. As labor costs are high, several industries have suffered severely under the relocation of production facilities towards aspiring countries, which have managed to close the productivity and quality gap substantially. Established manufacturing companies have recognized that customers are not willing to pay large price premiums for incremental quality improvements. As a consequence, many companies from the German manufacturing industry adjust their production focusing on customized products and fast time to market. Leveraging the advantages of novel production strategies such as Agile Manufacturing and Mass Customization, manufacturing companies transform into integrated networks, in which companies unite their core competencies. Hereby, virtualization of the process- and supply-chain ensures smooth inter-company operations providing real-time access to relevant product and production information for all participating entities. Boundaries of companies deteriorate, as autonomous systems exchange data, gained by embedded systems throughout the entire value chain. By including Cyber-Physical-Systems, advanced communication between machines is tantamount to their dialogue with humans. The increasing utilization of information and communication technology allows digital engineering of products and production processes alike. Modular simulation and modeling techniques allow decentralized units to flexibly alter products and thereby enable rapid product innovation. The present article describes the developments of Industry 4.0 within the literature and reviews the associated research streams. Hereby, we analyze eight scientific journals with regards to the following research fields: Individualized production, end-to-end engineering in a virtual process chain and production networks. We employ cluster analysis to assign sub-topics into the respective research field. To assess the practical implications, we conducted face-to-face interviews with managers from the industry as well as from the consulting business using a structured interview guideline. The results reveal reasons for the adaption and refusal of Industry 4.0 practices from a managerial point of view. Our findings contribute to the upcoming research stream of Industry 4.0 and support decision-makers to assess their need for transformation towards Industry 4.0 practices.

Keywords: Industry 4.0., mass customization, production networks, virtual process-chain

Procedia PDF Downloads 259

Authors: Sumit Sen, Sohan Khedekar, Umang Shinde, Shivam Bhargava

Abstract:

This study has been undertaken to investigate whether the deep learning models are able to predict the future stock prices by training the model with the historical stock price data. Since this work required time series analysis, various models are present today to perform time series analysis such as Recurrent Neural Network LSTM, ARIMA and Facebook Prophet. Applying these models the movement of stock price of stocks are predicted and also tried to provide the future prediction of the stock price of a stock. Final product will be a stock price prediction web application that is developed for providing the user the ease of analysis of the stocks and will also provide the predicted stock price for the next seven days.

Keywords: Autoregressive Integrated Moving Average, Deep Learning, Long Short Term Memory, Time-series

Procedia PDF Downloads 124

Authors: Ezgiamn Abraha Hagos

Abstract:

The primary objective of this study was to assess the existential concerns and related manifestations of higher learning students by investigating their perception of meaningful life and evaluating their purpose in life. In addition, this study was aimed at assessing the manifestations of existential pain among the students. Data was procured using Purpose in Life test (PIL), Well-being Manifestation Measure Scale (WBMMS), and focus group discussion. The total numbers of participants was 478, of which 299 were males and the remaining 179 females. They were selected using a simple random sampling technique. Data was analyzed using two ways. SPSS-version 20 was used to analyze the quantitative part, and narrative modes were utilized to analyze the qualitative data. The research finding revealed that students are involved in risk taking behaviors like alcohol ingestion, drug use, Khat (chat) chewing, and unsafe sex. In line with this it is found out that life in campus was perceived as temporary and as a result the sense of hedonism was prevalent at any cost. Of course, the most important thing for the majority of the students was to know about the purpose of life. Regarding WBMMS, there was no statistically significant difference among males and females and with the exception of the sub-scale of happiness; in all the sub-scales the mean is low. At last, assisting adolescents to develop holistically in terms of body, mind, and spirit is recommended.

Keywords: existential concerns, higher learning institutions, Ethiopia, Aksum University

Procedia PDF Downloads 406

Authors: Wei Zhao

Abstract:

The pandemic crisis disrupted normal classroom practices so that the constraints of the traditional practice became apparent. This turns out to be new opportunities for technology-based learning and teaching. However, how the technology supports the preschool teachers go through this sudden crisis and how preschool teachers conceived of the use of technology, appropriate and design technological artifacts as a mediator of knowledge construction in order to suit young children’s literacy level are rarely explored. This study addresses these issues by looking at the influence of a web-supported teacher community on changes/shifts in preschool teachers’ epistemological beliefs and practices. This teachers’ professional development community was formulated before the pandemic time and developed virtually throughout the home-based learning caused by Covid-19. It served as a virtual and asynchronous community for those teachers to collaboratively plan for and conduct online lessons using the knowledge-building approach for the purpose of sustaining children’s learning curiosity and opening up new learning opportunities during the lock-down period. The knowledge-building approach helps to increase teachers’ collective responsibility to collaboratively work on shared educational goals in the teacher community and awareness of noticing new ideas or innovations in their classroom. Based on the data collected across five months during and after the lock-down period and the activity theory, results show a dynamic interplay between the evolution of the community culture, the growth of teacher community and teachers’ identity transformation and professional development. Technology is useful in this regard not only because it transforms the geographical distance and new gathering guidelines after the outbreak of pandemic into new ways of communal communication and collaboration. More importantly, while teachers selected, monitored and adapted the technology, it acts as a catalyst for changes in teachers’ old teaching practices and epistemological dispositions.

Keywords: activity theory, changes in epistemology and practice, knowledge building, web-based teachers’ professional development community

Procedia PDF Downloads 168

Authors: Aymen Sassi

Abstract:

The equipment of vehicles with wireless communication capabilities is expected to be the key to the evolution to next generation intelligent transportation systems (ITS). The IEEE community has been continuously working on the development of an efficient vehicular communication protocol for the enhancement of Wireless Access in Vehicular Environment (WAVE). Vehicular communication systems, called V2X, support vehicle to vehicle (V2V) and vehicle to infrastructure (V2I) communications. The efficiency of such communication systems depends on several factors, among which the surrounding environment and mobility are prominent. Accordingly, this study focuses on the evaluation of the real performance of vehicular communication with special focus on the effects of the real environment and mobility on V2X communication. It starts by identifying the real maximum range that such communication can support and then evaluates V2I and V2V performances. The Arada LocoMate OBU transmission system was used to test and evaluate the impact of the transmission range in V2X communication. The evaluation of V2I and V2V communication takes the real effects of low and high mobility on transmission into account.

Keywords: IEEE 802.11p, V2I, V2X, mobility, PLR, Arada LocoMate OBU, maximum range

Procedia PDF Downloads 402

Authors: K. Doi, T. Nishimura, H. Fujimoto

Abstract:

The number of people who become visually impaired and do not have sufficient tactile experiences has increased by various disease. Especially, many acquired visually impaired persons due to accidents, disorders, and aging cannot adequately read Braille. It is known that learning Braille requires a great deal of time and the acquisition of various skills. In our previous studies, we reported one of the problems in learning Braille. Concretely, the standard Braille size is too small for Braille beginners. And also we are short of the objective data regarding easily readable Braille size. Therefore, it is necessary to conduct various experiments for evaluating Braille size that would make learning easier for beginners. In this study, for the purpose of investigating easy-to-read conditions of vertical and horizontal dot spacing for beginners, we conducted one Braille reading experiment. In this our experiment, we prepared test pieces by use of our original Braille printer with controlling function of Braille size. We specifically considered Braille beginners with acquired visual impairments who were unfamiliar with Braille. Therefore, ten sighted subjects with no experience of reading Braille participated in this experiment. Size of vertical and horizontal dot spacing was following conditions. Each dot spacing was 2.0, 2.3, 2.5, 2.7, 2.9, 3.1mm. The subjects were asked to read one Braille character with controlled Braille size. The results of this experiment reveal that Braille beginners can read Braille accurately and quickly when both vertical and horizontal dot spacing are 3.1 mm or more. This knowledge will be helpful data in considering Braille size for acquired visually impaired persons.

Keywords: paper-based Braille, vertical and horizontal dot spacing, readability, acquired visual impairment, Braille beginner

Procedia PDF Downloads 164