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Artykuły w czasopismach na temat "Learning assistance units"
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Amalia Zubaedah, Putri. "E-learning Implementation Assistance is Fun for Paud Teachers in Argasunya Village, Cirebon City". Devotion Journal of Community Service 2, nr 2 (14.01.2021): 79–87. http://dx.doi.org/10.36418/dev.v2i2.71.
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The impact of the Covid-19 pandemic is felt by all levels of society and all aspects of life, including early childhood education. Educational units must have the readiness of human resources in the form of educators and education staff as well as the readiness of technology facilities so that the learning process can be carried out effectively and efficiently. However, not all PAUD units are able to carry out internet-based learning which is called e-learning. This study aims to provide assistance in implementing a fun E-Learning for PAUD teachers in Argasunya Village, Cirebon City. This study uses a qualitative method. The community service steps taken are through webinars, question and answer and discussion. The results of this study can be concluded that the understanding of participants in implementing e-learning increases through examples of fun activities that parents can do at home so that they can stimulate all aspects of child development
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Rachman, Ali, Muhammad Andri Setiawan i Hendro Yulius Suryo Putro. "The Implementation of Independent Learning-Independent Campus in the Guidance and Counseling Study Program". Bisma The Journal of Counseling 6, nr 1 (29.05.2022): 56–65. http://dx.doi.org/10.23887/bisma.v6i1.42384.
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The Minister of Education and Culture of the Republic of Indonesia has issued a policy of independent learning on independent campuses. This policy aims to improve the competence of graduates, both soft skills and hard skills, encourage students to master various sciences, students are better prepared to enter the world of work. The purpose of this study was to determine the implementation of the independent campus learning program in the Guidance and Counseling Study Program FKIP ULM. This type of research is descriptive qualitative. The data is taken in research through literature study. The results of the analysis show that the concept of independent learning in independent campuses is manifested in the form of activities, namely student exchanges, internships or work practices, teaching assistance in education units, research, humanitarian projects, entrepreneurial activities, independence projects, and real work lectures on village development. The implementation of the independent campus learning program in the Guidance and Counseling Study Program FKIP ULM is carried out through three learning activities, namely teaching assistance in education units, internships or work practices, and student exchanges.
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Su, Binbin, Christian Smith i Elena Gutierrez Farewik. "Gait Phase Recognition Using Deep Convolutional Neural Network with Inertial Measurement Units". Biosensors 10, nr 9 (27.08.2020): 109. http://dx.doi.org/10.3390/bios10090109.
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Gait phase recognition is of great importance in the development of assistance-as-needed robotic devices, such as exoskeletons. In order for a powered exoskeleton with phase-based control to determine and provide proper assistance to the wearer during gait, the user’s current gait phase must first be identified accurately. Gait phase recognition can potentially be achieved through input from wearable sensors. Deep convolutional neural networks (DCNN) is a machine learning approach that is widely used in image recognition. User kinematics, measured from inertial measurement unit (IMU) output, can be considered as an ‘image’ since it exhibits some local ‘spatial’ pattern when the sensor data is arranged in sequence. We propose a specialized DCNN to distinguish five phases in a gait cycle, based on IMU data and classified with foot switch information. The DCNN showed approximately 97% accuracy during an offline evaluation of gait phase recognition. Accuracy was highest in the swing phase and lowest in terminal stance.
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Zhou, Zijun, Shuqin Yang, Zhisen Ni, Weixing Qian, Cuihong Gu i Zekun Cao. "Pedestrian Navigation Method Based on Machine Learning and Gait Feature Assistance". Sensors 20, nr 5 (10.03.2020): 1530. http://dx.doi.org/10.3390/s20051530.
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In recent years, as the mechanical structure of humanoid robots increasingly resembles the human form, research on pedestrian navigation technology has become of great significance for the development of humanoid robot navigation systems. To solve the problem that the wearable inertial navigation system based on micro-inertial measurement units (MIMUs) installed on feet cannot effectively realize its positioning function when the body movement is too drastic to be measured correctly by commercial grade inertial sensors, a pedestrian navigation method based on construction of a virtual inertial measurement unit (VIMU) and gait feature assistance is proposed. The inertial data from different positions of pedestrians’ lower limbs are collected synchronously via actual IMUs as training samples. The nonlinear mapping relationship between inertial information from the human foot and leg is established by a visual geometry group-long short term memory (VGG-LSTM) neural network model, based on which the foot VIMU and virtual inertial navigation system (VINS) are constructed. The VINS experimental results show that, combined with zero-velocity update (ZUPT), the integrated method of error modification proposed in this paper can effectively reduce the accumulation of positioning errors in situations where the gait type exceeds the measurement range of the inertial sensors. The positioning performance of the proposed method is more accurate and stable in complex gait types than that merely using ZUPT.
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Tulchinskii, V. V., V. I. Tulchinskii, S. I. Kondratyev i A. L. Boran-Keshishian. "Automatic assistance system for visual control of targets". Journal of Physics: Conference Series 2061, nr 1 (1.10.2021): 012076. http://dx.doi.org/10.1088/1742-6596/2061/1/012076.
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Abstract The article discusses the possibility of creating a system for automating the process of searching and assessing the danger of targets using machine vision and existing ship systems. The technologies for processing images from the ship’s camera system are analyzed: object recognition by a ready-made convolutional neural retrained network, as well as object detection by SURF algorithms. The parameters of the danger of goals within the framework of the problem to be solved have been analyzed and developed, and a structural analysis has been elaborated. The functionality of the automatic operation of the system as a closed circuit has been considered. To achieve the technical result in the system as an integrated part of the ship’s equipment based on cognitive information processing, a composite information object from the ship’s sensors and control systems was introduced. It is decomposed into blocks in which the associated logical information processing takes place using basic modules consisting of adaptive cells-approximators as learning elements capable of independently processing information. The following units are included in the local area network: an information support unit (ISU), a decision making unit (DMU), a command-organizational unit (COU) with an operator’s workstation. The ISU is connected by a two-way communication output with aggregate LAN units, the other output is connected in series with a situation determination unit and the “model of the surrounding space” block. The survey was carried out on board a modern LNG gas carrier using ship systems.
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Saehana, Sahrul, Muhammad Ali, Darsikin Darsikin, Nurgan Nurgan i Delthawati Is Ratnaningtyas. "Pelatihan Penggunaan Learning Management System (LMS) bagi Guru Sebagai Mitra Asistensi Mengajar Program MBKM Prodi Pendidikan Fisika FKIP Universitas Tadulako". Bubungan Tinggi: Jurnal Pengabdian Masyarakat 3, nr 4 (12.12.2021): 441. http://dx.doi.org/10.20527/btjpm.v3i4.4333.
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Program Merdeka Belajar Kampus Merdeka (MBKM) merupakan program nasional bertujuan untuk meningkatkan kualitas output pendidikan dengan melakukan sejumlah aktivitas seperti asistensi mengajar di satuan pendidikan oleh mahasiswa. Learning management system (LMS) sangat dibutuhkan untuk melaksanakan program asistensi mengajar khususnya dalam melakukan evaluasi. Tujuan program ini adalah untuk melatih guru di sekolah mitra dalam menggunakan LMS sehingga dapat mendampingi mahasiswa dalam program asistensi mengajar. Kegiatan ini dilakukan dalam bentuk pelatihan dimana guru dilatih menggunakan LMS. Mitra kegiatan ini adalah SMP dan SMA di Propinsi Sulawesi Tengah. Instrumen yang digunakan adalah lembar observasi dan wawancara. Dari hasil pengamatan diketahui bahwa guru dapat memanfaatkan dengan baik aplikasi evaluasi berbasis LMS yang dirancang oleh tim pengabdi. Hasil wawancara memperkuat hal ini, dimana guru tidak mengalami kesulitan dalam menggunakan aplikasi penilaian bagi mahasiswa program asistensi mengajar karena dilengkapi petunjuk yang jelas. The Independent Learning Campus Independent Program is a national program that improves scholarly output quality by carrying out activities such as teaching assistants in academic units by students. A learning management system (LMS) is needed to carry out teaching assistance programs, especially evaluations. This program aims to train teachers at partner schools in using the LMS so that they can assist students in teaching assistance programs. This activity is carried out in training where teachers are trained to use LMS. Partners of this activity are junior and senior high schools in Central Sulawesi Province. The instruments used are observation sheets and interviews. From the observations, it is known that teachers can make good use of the LMS-based evaluation application designed by the service team. The results of the interviews reinforce this, where the teacher does not experience difficulties in using the assessment application for students in the teaching assistant program because it is equipped with clear instructions.
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Zhao, Sikai, Jie Zhao, Dongbao Sui, Tianshuo Wang, Tianjiao Zheng, Chuanwu Zhao i Yanhe Zhu. "Modular Robotic Limbs for Astronaut Activities Assistance". Sensors 21, nr 18 (21.09.2021): 6305. http://dx.doi.org/10.3390/s21186305.
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In order to meet the assist requirements of extravehicular activity (EVA) for astronauts, such as moving outside the international space station (ISS) or performing on-orbit tasks by a single astronaut, this paper proposes an astronaut robotic limbs system (AstroLimbs) for extravehicular activities assistance. This system has two robotic limbs that can be fixed on the backpack of the astronaut. Each limb is composed of several basic module units with identical structure and function, which makes it modularized and reconfigurable. The robotic limbs can work as extra arms of the astronaut to assist them outside the space station cabin. In this paper, the robotic limbs are designed and developed. The reinforcement learning method is introduced to achieve autonomous motion planning capacity for the robot, which makes the robot intelligent enough to assist the astronaut in unstructured environment. In the meantime, the movement of the robot is also planned to make it move smoothly. The structure scene of the ISS for extravehicular activities is modeled in a simulation environment, which verified the effectiveness of the proposed method.
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Chamisijatin, Lise, Yuni Pantiwati i Siti Zaenab. "Pendampingan Peningkatan Mutu Satuan Pendidikan Melalui Penyusunan Tiga Instrumen Utama Di SMP Muhammadiyah 02 Kota Batu". Sasambo: Jurnal Abdimas (Journal of Community Service) 4, nr 2 (19.05.2022): 249–60. http://dx.doi.org/10.36312/sasambo.v4i2.673.
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Kemampuan guru dalam menyusun instrument Asesmen Kompetensi Minimum (AKM) belum dimiliki oleh guru SMP Muhammadiyah 2 Batu. Untuk itu perlu pendampingan tentang penyusunan instrumen soal berbasis AKM. Kegiatan ini bertujuan untuk melakukan pendampingan peningkatan mutu satuan pendidikan melalui penyusunan instrumen utama di SMP Muhammadiyah 02 Kota Batu. Metode pelaksanaan kegiatan yang dilakukan adalah: (1) Pelatihan tentang pengembangan instrumen AKM, Survei Karakter, dan Survei Lingkungan Belajar, dan (2) Pendampingan tentang pengembangan instrumen AKM. Adapun rincian kegiatan adalah sebagai berikut. Berdasarkan serangkaian kegiatan pengabdian kepada masyarakat melalui pendampingan pengembangan instrumen AKM, Survei Karakter, dan Survei Lingkungan Belajar pada guru SMP Muhammadiyah 2 Batu, telah dilaksanakan dengan baik. Kegiatan ini meliputi pelatihan instrumen AKM, Survei Karakter, dan Survei Lingkungan Belajar dan pendampingan penyusunan instrumen AKM berciri literasi membaca dan literasi numerasi. Guru SMP Muhammadiyah 02 Batu dapat mengembangkan instrumen dalam bentuk kumpulan soal berciri literasi membaca dan numerasi, yang selanjutnya instrumen ini dapat digunakan sebagai panduan pemberian tugas pada siswa dalam proses pembelajaran guna menyiapkan AKM. Produk instrumen yang dihasilkan memuat soal literasi membaca dan literasi numerasi pada matapelajaran IPA, Matematika, IPS, Bahasa Indonesia, Bahasa Inggris, Bahasa Indonesia dan Pendidikan Agama Islam Assistance in improving the quality of education units through the preparation of three main instruments at SMP Muhammadiyah 02 Batu City The teacher's ability to develop the Minimum Competency Assessment (AKM) instrument is not yet owned by the teachers of SMP Muhammadiyah 2 Batu. For this reason, assistance is needed in the preparation of AKM-based question instruments. This activity aims to provide assistance to improve the quality of education units through the preparation of the main instrument at SMP Muhammadiyah 02 Batu City. The methods of implementing the activities carried out are (1) Training on the development of AKM instruments, Character Surveys, and Learning Environment Surveys, and (2) Assistance in the development of AKM instruments. The details of the activities are as follows. Based on a series of community service activities through assistance in developing AKM instruments, Character Surveys, and Learning Environment Surveys for SMP Muhammadiyah 2 Batu teachers, have been carried out well. These activities include training on AKM instruments, Character Surveys, and Learning Environment Surveys, and assistance in the preparation of AKM instruments characterized by reading literacy and numeracy literacy. Teachers of SMP Muhammadiyah 02 Batu can develop instruments in the form of a collection of questions characterized by reading literacy and numeracy, which then can be used as a guide for giving assignments to students in the learning process to prepare AKM. The resulting instrument product contains reading literacy and numeracy literacy questions in science, mathematics, social studies, Indonesian, English, Indonesian, and Islamic religious education subjects
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Nuryadi, Achmad, Mulyono, Shandy Pieter Pelamonia, I. Gede Dharma U, Ramadhany Hananto P i Riga Mardika. "Learning Innovation With The Theme Of Online-Based Learning Innovation". GANDRUNG: Jurnal Pengabdian Kepada Masyarakat 3, nr 1 (28.02.2022): 399–403. http://dx.doi.org/10.36526/gandrung.v3i1.1598.
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To implement based on the results of the rapid survey analysis of learning from home during the COVID-19 prevention period, Ministry of Education and Culture April 2020, the obstacles faced by teachers in learning from home include the percentage of teachers' ability to operate digital devices of 67.11%, the availability of facilities and infrastructure owned by students. by 29.45%. Difficulty in understanding lessons is a complaint of the majority of students in almost all types of education units. There are difficulties in understanding related to subjects that are almost the same experienced by every level of our education, of course there needs to be a way how to need student assistance. In preparation for offline learning, SMPN 1 Tegalampel Bondowoso requires many references on how to innovate online learning. Therefore, it is necessary to hold counseling about Online Learning Innovation at SMPN 1 Tegalampel Bondowoso. The implementation of the Community Service Program activities by the Physical Education Lecturer Team at PGRI University Adi Buana Surabaya went smoothly. The teachers of SMPN 1 Tegalampel Bondowoso were very enthusiastic about participating in every scheduled activity. In order to prepare for offline learning, SMPN 1 Tegalampel Bondowoso needs many references on how to innovate online learning. Starting from knowledge of other innovations that can benefit all
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Grafnetterova, Nikola, Hilda Cecilia Contreras Aguirre i Rosa M. Banda. "Teamwork Makes the Dream Work: Experiences of Student-Athletes in STEM with Dual Advising". NACADA Journal 41, nr 1 (1.01.2021): 47–63. http://dx.doi.org/10.12930/nacada-20-06.
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Despite the nation's critical need for science, technology, engineering, and mathematics (STEM) college graduates, the National Collegiate Athletic Association's Division I student-athletes represent a small portion of STEM majors. Student-athletes pursuing STEM disciplines benefit from the assistance of academic and athletic advisors; this study explored student-athletes' experiences with such dual advising. Building on Terenzini and Reason's (2005) comprehensive model of influences on student learning and persistence, our findings highlighted STEM athletes' need for individualized advising, support engagement in STEM, and options and flexibility in the curriculum. The study also exposed uncertainty about the different roles of academic and athletic advising units and the ways limited communication diminishes the effectiveness of the advising units' collaborative efforts.
Rozprawy doktorskie na temat "Learning assistance units"
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Peach, Deborah. "Improving the Provision of Learning Assistance Services in Higher Education". Thesis, Griffith University, 2004. http://hdl.handle.net/10072/365399.
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This study is motivated by the need to look continually for ways to improve Griffith University’s learning assistance services so that they meet the changing needs of stakeholders and are at the same time cost-effective and efficient. This study uses the conceptual tools of cultural-historical activity theory and expansive visibilisation to investigate the development and transformation of learning assistance services at Griffith University, one of Australia's largest multi-campus universities. Cultural-historical activity is a powerful theoretical framework that acknowledges the importance of dimensions such as cultural context, local setting, collective understanding, and the influence of historical variables on interactions in settings. Expansive visibilisation is a practical four-stage process that was used in this study to make visible and analysable the work context of the Learning Assistance Unit. The study uses these conceptual tools to illustrate how learning assistance services at the University have moved through several stages of historical development and that historical variables, such as the political setting and physical location of services continue to influence current work practices. The investigation involved gathering data through interviews and focus group discussions with key stakeholders in order to map the University's Learning Assistance Unit as an activity system that appears to have separated out from the overall activity system of the University. It involved making visible problems and tensions in the activity system, and identifying ways of improving future practice. The study reveals problem clusters and underlying tensions amongst the interacting activity systems of the Learning Assistance Unit, faculty, library and student. These problem clusters relate to different understandings about the purpose of the Learning Assistance Unit and the role of the learning adviser, the difficulties in offering a quality service on a restricted budget, and tensions between contextualised and de-contextualised learning assistance. The study suggests that resolving these tensions depends on staff taking an active role in critically examining their practice, in particular the way that they collaborate with key stakeholders in the learning environment. The dissertation concludes by suggesting that one way forward is to expand the activity system on its socio-spatial, temporal, moral-ideological, and systemic-developmental dimensions (Engeström, 1999c).Thesis (Professional Doctorate)
Doctor of Education (EdD)
School of Cognition, Language and Special Education
Full Text
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Peach, Deborah, i n/a. "Improving the Provision of Learning Assistance Services in Higher Education". Griffith University. School of Cognition, Language and Special Education, 2004. http://www4.gu.edu.au:8080/adt-root/public/adt-QGU20040319.163140.
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This study is motivated by the need to look continually for ways to improve Griffith Universitys learning assistance services so that they meet the changing needs of stakeholders and are at the same time cost-effective and efficient. This study uses the conceptual tools of cultural-historical activity theory and expansive visibilisation to investigate the development and transformation of learning assistance services at Griffith University, one of Australia's largest multi-campus universities. Cultural-historical activity is a powerful theoretical framework that acknowledges the importance of dimensions such as cultural context, local setting, collective understanding, and the influence of historical variables on interactions in settings. Expansive visibilisation is a practical four-stage process that was used in this study to make visible and analysable the work context of the Learning Assistance Unit. The study uses these conceptual tools to illustrate how learning assistance services at the University have moved through several stages of historical development and that historical variables, such as the political setting and physical location of services continue to influence current work practices. The investigation involved gathering data through interviews and focus group discussions with key stakeholders in order to map the University's Learning Assistance Unit as an activity system that appears to have separated out from the overall activity system of the University. It involved making visible problems and tensions in the activity system, and identifying ways of improving future practice. The study reveals problem clusters and underlying tensions amongst the interacting activity systems of the Learning Assistance Unit, faculty, library and student. These problem clusters relate to different understandings about the purpose of the Learning Assistance Unit and the role of the learning adviser, the difficulties in offering a quality service on a restricted budget, and tensions between contextualised and de-contextualised learning assistance. The study suggests that resolving these tensions depends on staff taking an active role in critically examining their practice, in particular the way that they collaborate with key stakeholders in the learning environment. The dissertation concludes by suggesting that one way forward is to expand the activity system on its socio-spatial, temporal, moral-ideological, and systemic-developmental dimensions (Engeström, 1999c).
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Mollitor, Hannah. "A qualitative analysis of the experience of therapeutic relationships between patients and nursing assistants within a medium secure unit for men with learning disabilities". Thesis, University of East London, 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.532698.
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Howard, Shaun Michael. "Deep Learning for Sensor Fusion". Case Western Reserve University School of Graduate Studies / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=case1495751146601099.
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Wentzel, Zurina. "The effectiveness of senior students as tutor assistants in the English special project for academic development at UWC". University of the Western Cape, 1992. http://hdl.handle.net/11394/8477.
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Magister Educationis - MEdSince the inception of the University in 1960 under the Apartheid regime and up until a few years ago Afrikaans had dominated both as educational and as communication medium. However, political change - at the University and in South Africa - has brought about a change in language patterns. According to the HSRC Work Committee on Languages and Language Instruction (1981), a high percentage (40%) of Afrikaans-speaking people classified as coloured and living in the Cape Peninsula choose English as the medium of instruction and also regard it as the most important language to be learnt at schools (also 40%). As a result of this, and the enrolment of a large percentage of Xhosa speaking students, who generally prefer English to Afrikaans as an educational medium, English has become the language most commonly used both inside and outside the classroom. The homogeneity of preference has, however, not been matched by mastery of the language. For approximately 70% of all first-year students English is a second or even a third language. Though University entry is based on at least ten years of the study of English, standards of proficiency differ quite considerably as a result of inequalities in education. Because students need to improve their level of English proficiency I investigated the effectiveness of using senior students as tutor assistants in an academic development programme, the English Special Project, at UWC. This study aims at revealing that the tutor assistantships in the English Special Project can alleviate problems that occur with annual increases in student numbers under certain conditions. These are that: 1 prospective tutor assistants undergo proper tutor assistant training; 2 tutor assistants are committed to the course of academic development; 3 tutor assistants have the time available that is necessary for the task. In Chapter 1 give an insight into what this study is about, the reasons for conducting it and what my personal involvement with the ESP has been. In Chapter 2 I review some of the overseas and local literature on TA systems. In Chapter 3 I describe a case-study to evaluate the success of the TA system in the ESP with reference to academic development. I emphasize the intensive, individual care of and attention to first-year students. In an attempt to address the problem, the effectiveness of senior students as tutor assistants to assist in tutorial sessions is described. In Chapter 4 I discuss the value of TA intervention in the ESP at personal and social levels. Chapter 5 contains the general conclusions and my recommendations to improve the ESP.
Części książek na temat "Learning assistance units"
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Muhammad, Wazir, Irfan Ullah i Mohammad Ashfaq. "An Introduction to Deep Convolutional Neural Networks With Keras". W Machine Learning and Deep Learning in Real-Time Applications, 231–72. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-7998-3095-5.ch011.
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Deep learning (DL) is the new buzzword for researchers in the research area of computer vision that unlocked the doors to solving complex problems. With the assistance of Keras library, machine learning (ML)-based DL and various complicated or unresolved issues such as face recognition and voice recognition might be resolved easily. This chapter focuses on the basic concept of Keras-based framework DL library to handle the different real-life problems. The authors discuss the codes of previous libraries and same code run on Keras library and assess the performance on Google Colab Cloud Graphics Processing Units (GPUs). The goal of this chapter is to provide you with the newer concept, algorithm, and technology to solve the real-life problems with the help of Keras framework. Moreover, they discuss how to write the code of standard convolutional neural network (CNN) architectures using Keras libraries. Finally, the codes of validation and training data set to start the training procedure are explored.
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Meeradevi, Pramod Chandrashekhar Sunagar i Anita Kanavalli. "Intrusion Detection System Using Deep Learning". W Advances in Systems Analysis, Software Engineering, and High Performance Computing, 160–81. IGI Global, 2022. http://dx.doi.org/10.4018/978-1-7998-8161-2.ch009.
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With recent advancements in computer network technologies, there has been a growth in the number of security issues in networks. Intrusions like denial of service, exploitation from inside a network, etc. are the most common threat to a network's credibility. The need of the hour is to detect attacks in real time, reduce the impact of the threat, and secure the network. Recent developments in deep learning approaches can be of great assistance in dealing with network interference problems. Deep learning approaches can automatically differentiate between usual and irregular data with high precision and can alert network managers to problems. Deep neural network (DNN) architectures are used with differing numbers of hidden units to solve the limitations of traditional ML models. They also seek to increase predictive accuracy, reduce the rate of false positives, and allow for dynamic changes to the model as new research data is encountered. A thorough comparison of the proposed solution with current models is conducted using different evaluation metrics.
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Outlaw, Veronica, Margaret L. Rice i Vivian H. Wright. "Building Quality Online Courses". W Handbook of Research on Building, Growing, and Sustaining Quality E-Learning Programs, 301–23. IGI Global, 2017. http://dx.doi.org/10.4018/978-1-5225-0877-9.ch015.
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The authors have personally experienced the burdens of creating online courses without the assistance of trained instructional designers. Many faculty are employed in conditions where they develop online courses without the proper knowledge and training of many essential aspects that should accompany the development of an online course (e.g., design, development, learning styles, copyright, design principles, accessibility, incorporating technology, and technical skills) (Singleton et al., 2013; Speck, 2000; Wickersham et al., 2007). The authors propose and describe the use of a detailed online course development and delivery model (Outlaw & Rice, 2015) that was created to provide distance education units with a systematic approach to course development. The proposed model nourishes the partnerships between faculty and designers to improve the quality of online courses, while providing the support faculty need to successfully create online courses. The authors discuss a model that provides consistency in efforts to create efficient workflows to develop online courses.
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Camilleri, Vanessa, Foaad Haddod, Matthew Montebello, Joseph C. Camilleri, Alexiei Dingli i Vince Briffa. "Virtual Reality (VR) Applications in Learning". W Advances in Multimedia and Interactive Technologies, 241–68. IGI Global, 2019. http://dx.doi.org/10.4018/978-1-5225-5912-2.ch011.
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This chapter illustrates the use of VR applications in professional development and introduces an application used to assist teachers, learning support assistants (LSAs), and teaching assistants (TAs) to better understand autistic children's behaviors while in the classroom. One of the challenges faced in classrooms is how to understand the autistic children's behaviors and empathize with them. The proposed VR application repurposes a different form of narrative of the world of a child on the autism spectrum in an immersive environment designed for educators. The VR application in this chapter uses recorded footage through 360-degree cameras and special effects powered by Unity. In a context where integration is a key to today's learning and education, the researchers believe that the use of VR to assist the teachers in empathizing with their learners' traits and conditions may be of great benefit to the learners' school experiences.
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Sahbani, Abdelaziz, i Hela Mahersia. "Advanced Driving Assistance System for an Electric Vehicle Based on Deep Learning". W New Perspectives on Electric Vehicles [Working Title]. IntechOpen, 2021. http://dx.doi.org/10.5772/intechopen.98870.
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This chapter deals with a design of a new speed control method using artificial intelligence techniques applied to an autonomous electric vehicle. In this research, we develop an Advanced Driver Assistance System (ADAS) which aims to enhance the driving manner and the safety, especially when traveling too fast. The proposed model is a complete end-to-end vehicle speed system controller that proceeds from a detected speed limit sign to the regulation of the motor’s speed. It recognizes the speed limit signs before extracting from them, a speed information that will be sent, as reference, to a NARMA-L2 based controller. The study is developped specially for electric vehicle using Brushless Direct Current (BLDC) motor. The simulation results, implemented using Matlab-Simulink, show that the speed of the electric vehicle is controlled successfully with different speed references coming from the image processing unit.
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Hari Priya K i Malathi S. "Efficient Face Mask Recognition System by Using Deep Learning Methodology". W Advances in Parallel Computing. IOS Press, 2021. http://dx.doi.org/10.3233/apc210047.
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In this project, mask Recognition System is presented, that utilizes the prospect of Object Detection, completed the assistance of Deep Learning philosophies. The past work gives the topic of article identification by joining coarse-grained and fine-grained discovery philosophies without precedent for police work the moving items on high goal recordings. Period object location and acknowledgment finds careful applications in various fields like clinical applications, security police examination, and independent vehicles. There unit of estimation a few machine and profound learning procedures that unit utilized for object discovery and acknowledgment. The development of a convolutional neural organization (CNN) has given a major forward leap to protest discovery and acknowledgment. Convolutional Neural Network (CNN) has arrived at the exemplification of picture characterization for different application. Explicitly in 2D-CNN, there’s huge advancement for object discovery, beside 3D-CNN, it’s still toward the start of partner time. Profound CNN’s unit acclimated get extra exact directions and to deal with high goal video outlines. By taking this idea of location on the grounds that the base to our work, the framework includes in perceiving the essence of the individual and checks if the face have mask or not, befittingly guaranteeing the individual complies with the assurance safety measures so as that the unfurl of hepatotoxic infection may be managed. The framework will unpredictably be utilized for future face ID with face mask till the pandemic gets died.
Streszczenia konferencji na temat "Learning assistance units"
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Bragantini, Jordão, i Alexandre Xavier Falcão. "Interactive Image Segmentation: From Graph-based Algorithms to Feature-Space Annotation". W Anais Estendidos da Conference on Graphics, Patterns and Images. Sociedade Brasileira de Computação - SBC, 2022. http://dx.doi.org/10.5753/sibgrapi.est.2022.23260.
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In recent years, machine learning algorithms that solve problems from a collection of examples (i.e. labeled data), have grown to be the predominant approach for solving computer vision and image processing tasks. These algorithms’ performance is highly correlated with the abundance of examples and their quality, especially methods based on neural networks, which are significantly data-hungry. Notably, image segmentation annotation requires extensive effort to produce high-quality labeling due to the fine-scale of the units (pixels) and resorts to interactive methodologies to provide user assistance. Therefore, improving interactive image segmentation methodologies with the goal of improving data labeling problems is of paramount importance to advance applications of computer vision methods. With this in mind, we investigated the existing literature on interactive image segmentation, contributing to it by introducing novel algorithms that perform the segmentation from markers, contours, and finally proposing a new paradigm for image annotation at scale.
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Sanchez-Romaguera, Veronica, i Robert A. Phillips. "A comparison of a first and third year UG enterprise unit: lessons from experiential learning and interdisciplinarity". W Fourth International Conference on Higher Education Advances. Valencia: Universitat Politècnica València, 2018. http://dx.doi.org/10.4995/head18.2018.8110.
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Drawing from several years of experience, this work describes lessons learnt in designing, delivering and assessing two interdisciplinary enterprise units offered undergraduate students from any discipline studing at the University of Manchester (UK). Both units are electives (optional). One unit is delivered to first year undergrdaute students whereas the other unit is delivered to third/fourth year undergraduate students. Experiential learning and interdisciplinary cohorts are core aspects of both units. Students work on ‘real-world’ projects to develop a credible and competitive solution within a tight dead-line. In this paper, findings are drawn from data collected from staff and teaching assistants observations, students’ reflective diaries and students’ feedback. Findings showed that in general, students at both levels, year 1 and year 3/4, regarded the experience challenging at first due to the ‘unusual’ learning environment when compared to the education that most students have experienced prior to the units here discussed. However, most students highly regarded the interdisciplinary experiential learning experience. The paper contributes to the growth of knowledge and aids understanding of how experiential learning and interdisciplinarity have been effectively combined and introduced in the university curriculum. Although this works focused on enterprise education the experience-based guidance here described is also applicable to a much wider range of situations and academic areas of study. Keywords: Enterprise and Entrepreneurship Education; Employability; Experiential learning; Interdisciplinary education;
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Rieg, Claude, Ralf Ahlstrand, Michel Bieth, Luigi Debarberis, Filippo Sevini, Nigel Taylor, Georgy Karzov i in. "Neutron Embrittlement of VVER 1000 and 440/213 RPVs: Learning From EC Projects on RPV Integrity". W ASME/JSME 2004 Pressure Vessels and Piping Conference. ASMEDC, 2004. http://dx.doi.org/10.1115/pvp2004-2970.
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Since 1991 the European Commission has financed a significant number of Technical Assistance Projects to the Commonwealth of Independent States (TACIS) and EURATOM R&D actions addressing the main safety issues on RPV material embrittlement and integrity assessment. Since the VVER 440 reactors of the reference series 213 are made from recognised neutron embrittlement resistant materials and include comprehensive surveillance programmes, a standard plant life management procedure can be applied to address long-term concerns, mostly aiming at reducing uncertainties in the assessment techniques. Therefore, the open issues (flux effect, upgrading of surveillance results, implementation of toughness measurements and relevant acceptance criteria, behaviour of the cladding) are quite universal. The efficiency of late annealing (at fast [E>0.5 MeV] neutron doses over 1020n/cm2) and the re-embrittlement after annealing remain key issues for any final decision for their operational lifetime. The more recently developed VVER 1000 reactors have some well-known features arising from the original design and manufacturing process (high nickel content in the core weld, location of the surveillance specimens), which have to be carefully considered if appropriate mitigation measures are to be implemented during operation. A precise identification of the issues related to the surveillance programme has been achieved thanks to research on dosimetry evaluation, representativeness (temperature and flux effect) of the specimens and optimisation of the evaluation of their results. Nickle, just as copper and phosphorus, is now recognised as having a detrimental effect on neutron embrittlement in synergy with other elements (e.g. manganese). The analyses of available data for CrNiMn steels do not show a significant effect for fast [E>0.5 MeV] neutron doses below 7.1019n/cm2, but their consistency and relevance might be questionable. A way has already been pioneered which shows how valuable results can be obtained using the existing surveillance programmes specimens. A systematic application on the Russian & Ukrainian plants is now planned in order to get updated figures on design end of life (EOL) integrity assessment. This includes updated dosimetry assessment, multiple specimen testing (reconstitution, impact and static toughness tests) and advanced integrity analyses. An optimised database of representative surveillance results (up to the design end of life) is expected, which should provide a sound basis for further understanding and setting up of relevant prediction tools, considering at the same time any other specific R&D results. The global integrity assessment will also provide for preparing and implementing adequate mitigation measures in due time, if necessary. The paper will report about the knowledge on RPV embrittlement effects, providing evidence of recent contributions to solve shortcomings of the VVER 440/213 and 1000 units. The current state-of-the-art and the remaining open issues have been assessed recently by a group of international experts. The planned R&D activities and the detailed scope of the latest TACIS projects are described.
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Syaifudin, Yan Watequlis, Nobuo Funabiki, Devany C. Wijaya i Ikhlaashul Mu'aasyiqiin. "Performance Investigation of Unit Testing in Android Programming Learning Assistance System". W 2021 IEEE 3rd Global Conference on Life Sciences and Technologies (LifeTech). IEEE, 2021. http://dx.doi.org/10.1109/lifetech52111.2021.9391971.
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Jones, Greg, Hazel Jones, Dom Pensiero i Claire Beattie. "Enhancing students’ employability skills and experiential learning through integration of Xero software". W ASCILITE 2021: Back to the Future – ASCILITE ‘21. University of New England, Armidale, 2021. http://dx.doi.org/10.14742/ascilite2021.0116.
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Introducing XERO Accounting software into a core accounting unit can have many benefits for students, including improving their professional skills and enhancing their employability. However, it is important that students gain knowledge and skills in all aspects of the software as well as understanding the accounting processes that underlie the software’s operations. This paper presents an overview of implementation of Xero software, in a core accounting course, at a regional university in Australia. Student numbers ranged from 24-63 across the semesters studied. We highlight and discuss the processes adopted to appropriately scaffold students’ learning and assessment. We assess the effectiveness of the intervention by observing student engagement with specially developed videos and measuring student results in associated assessment tasks over three offerings of the course. The provision of a suite of learning opportunities, (training and use of excel and Xero accounting software) translated to improved student outcomes on the technologyrelated assessment items. Few students who viewed the learning videos contacted the course teaching team for further assistance, suggesting the videos were an effective resource that provided enhanced learning opportunities for students. These findings provide advice and information regarding the issues associated with integrating accounting software for other teaching teams or institutions considering similar applications in their courses or programs.
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Nadkarni, Prajit, i Narendra Varma Dasararaju. "Visually Similar Products Retrieval for Shopsy". W International Conference on Signal Processing and Vision. Academy and Industry Research Collaboration Center (AIRCC), 2022. http://dx.doi.org/10.5121/csit.2022.122203.
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Visual search is of great assistance in reseller commerce, especially for non-tech savvy users with affinity towards regional languages. Product attributes available in e-commerce have potential for building better visual search systems [2, 20, 29]. We design a visual search system for reseller commerce using a multi-task learning approach and address challenges like image compression, cropping, etc, faced in reseller commerce. Our model consists of three tasks: attribute classification, triplet ranking and variational autoencoder (VAE). We introduce an offline triplet mining technique which utilizes information from multiple attributes to capture relative order within data. This technique displays better performance compared to traditional triplet mining [27] baseline. We compare and report incremental gain achieved by our unified multi-task model over each individual task separately. The efsfectiveness of our method is demonstrated using in-house dataset of images from the Lifestyle business-unit of Flipkart. To efficiently retrieve images in production, we use Approximate Nearest Neighbor (ANN) index.
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Melo, Gustavo, Rohit Ravi, Lucas Jauer i Johannes Henrich Schleifenbaum. "Exploring Augmented Reality for Teaching Design for Additive Manufacturing". W 2022 International Additive Manufacturing Conference. American Society of Mechanical Engineers, 2022. http://dx.doi.org/10.1115/iam2022-94406.
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Abstract Additive Manufacturing (AM) has a great potential of disrupting product design and supply chains in many industries by means of its unique capabilities when compared to traditional manufacturing. A wide range of designers would like to take advantage of AM to improve their designs, but they need assistance in learning and breaking out of their conventional manufacturing mindset in the early phases of the design process. Therefore, this study explores the use of Augmented Reality (AR) to enhance the learning experience of the existing Design Heuristics for Additive Manufacturing using Design for Additive Manufacturing (DfAM) cards. In this study, we propose a modification of DfAM cards to include AR markers into the existing card design and hence provide a comprehensive visualization along with the information about heuristics and examples on the DfAM cards. This helps the user to understand the real-world structure of the final printed product before it is printed. The cross-platform game engine Unity is used for developing the AR models for this research. We also investigate the advantages that AR can provide as a visual interface. An expert review is conducted to obtain development feedback and a trial training session with students is carried out. The student evaluated positively the use of the AR app in their DfAM lecture and exercise.
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He, Qingyun, Bin Li i Sitao Peng. "UTSG Water Level Prediction Model Based on LSTM and GRU Algorithms". W 2022 29th International Conference on Nuclear Engineering. American Society of Mechanical Engineers, 2022. http://dx.doi.org/10.1115/icone29-91798.
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Abstract Steam generator water level is a complex thermal hydraulic system, which in-ludes nonlinearity, time-variant characteristic, non-minimun phase, mechanical limit and mesurement error. Particularly, “false water level” phenomenon caused by nonminimun phase greatly affects the control of steam generator water level. Thus, in order to greatly help PWRs operators control the water level, enhance the safety of PWRs operation and improve the economic of PWRs, it is of importance to study the technology on prediction of steam generator water level variation trend under normal operation condition of PWRs. A predictive model for U-tube steam generator (UTSG) is in need as an assistance for operators to better control the UTSG water level. The training data, i.e., the variation of UTSG water level in uenced by the sudden change of steam ow rate and feedwater rate, were obtained from a differential equation model, i.e., Ivring’s model. Long short-term memory (LSTM) and gated recurrent unit (GRU), as powerful time series prediction algorithms in deep learning eld, were used to train the UTSG prediction model. The result shows that the trained LSTM and GRU based predictive model have good performance on testing data set with both the one-step prediction and multi-step recurrent prediction. It can be used as a prototype of steam generator level prediction without the intervention of automatic control system.
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Dimovski, Mladen, Claudiu Musat, Vladimir Ilievski, Andreea Hossman i Michael Baeriswyl. "Submodularity-Inspired Data Selection for Goal-Oriented Chatbot Training Based on Sentence Embeddings". W Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}. California: International Joint Conferences on Artificial Intelligence Organization, 2018. http://dx.doi.org/10.24963/ijcai.2018/559.
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Spoken language understanding (SLU) systems, such as goal-oriented chatbots or personal assistants, rely on an initial natural language understanding (NLU) module to determine the intent and to extract the relevant information from the user queries they take as input. SLU systems usually help users to solve problems in relatively narrow domains and require a large amount of in-domain training data. This leads to significant data availability issues that inhibit the development of successful systems. To alleviate this problem, we propose a technique of data selection in the low-data regime that enables us to train with fewer labeled sentences, thus smaller labelling costs. We propose a submodularity-inspired data ranking function, the ratio-penalty marginal gain, for selecting data points to label based only on the information extracted from the textual embedding space. We show that the distances in the embedding space are a viable source of information that can be used for data selection. Our method outperforms two known active learning techniques and enables cost-efficient training of the NLU unit. Moreover, our proposed selection technique does not need the model to be retrained in between the selection steps, making it time efficient as well.
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Kessy, Dillon, Jose Ignacio Sierra Castro, Jose Chirinos, Giorgio De Paola i Maria Jose Lopez Perez-Valiente. "How Artificial Intelligence can Guide Marcellus Development". W SPE Eastern Regional Meeting. SPE, 2021. http://dx.doi.org/10.2118/201786-ms.
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Abstract The application of Artificial Intelligence for planning has received increased attention in the energy industry in the past few years, particularly for the increased production efficiency requirements and environmental standards. The objective of this paper is to show the successful integration of production, completion, subsurface and spatial data using machine-learning algorithms to predict production performance for future development wells. The internal Marcellus Business Unit (MBU) well database, populated with data of 500+ historical wells, has been used in this study. Production data, treated as timeseries, has been processed using functional Principal Component Analysis (PCA) to allow removal of outliers and mode detection. Utilizing this data, a suite of machine-learning algorithms has been applied to reconstruct gas production from available and target well data. Uncertainty quantification has been provided for production curves to identify the quality of prediction. During the study, the sensitivity analysis on input variables has been performed iteratively to screen and rank the most important variables for prediction. The workflow, Unconventional Reservoir Assistant (URA), has been implemented in a proprietary cloud-based platform providing the necessary means for data upload, integration, pre-processing, and finally model training and deployment. This allows the user to focus on the evaluation of model output quality, data filter and workspace generation for continuous model testing and improvement. The full well dataset, split into trained and tested data, has been used for prediction as a preliminary guide to where the most prolific areas of development are located. Results were ranked based on production expected by pad and based on normalized performance. The information was then used to compare with type curves and original development order. In parallel, economic evaluation of break-even was performed to rank all future pads. Consequently, integration of the model prediction and breakeven ranking were used to generate the final development order for the MBU. The URA tool has shown preliminary success in predicting production performance for the pilot development area. Multiple case studies have been run achieving blind test results with high accuracy for historical prediction. Results show some dependency of predictor variable ranking on the field development area, providing insight on how subsurface may affect well dynamic behavior. This paper describes how the integration of URA can complement the development workflow for unconventional reservoirs and be used to predict performance based on complex data integration. The methodology used is superior to standard machine learning models providing only production indicators, as it gives the user the possibility to evaluate economics and completion design sensitivity for future well activities. The methodology can be further extended as a proxy model for well schedule optimization in planning or for better insight into well refrac selection.