Search results for "ARN"
showing 10 items of 8344 documents
MARL-Ped+Hitmap: Towards Improving Agent-Based Simulations with Distributed Arrays
2016
Multi-agent systems allow the modelling of complex, heterogeneous, and distributed systems in a realistic way. MARL-Ped is a multi-agent system tool, based on the MPI standard, for the simulation of different scenarios of pedestrians who autonomously learn the best behavior by Reinforcement Learning. MARL-Ped uses one MPI process for each agent by design, with a fixed fine-grain granularity. This requirement limits the performance of the simulations for a restricted number of processors that is lesser than the number of agents. On the other hand, Hitmap is a library to ease the programming of parallel applications based on distributed arrays. It includes abstractions for the automatic parti…
Massively Parallel Huffman Decoding on GPUs
2018
Data compression is a fundamental building block in a wide range of applications. Besides its intended purpose to save valuable storage on hard disks, compression can be utilized to increase the effective bandwidth to attached storage as realized by state-of-the-art file systems. In the foreseeing future, on-the-fly compression and decompression will gain utmost importance for the processing of data-intensive applications such as streamed Deep Learning tasks or Next Generation Sequencing pipelines, which establishes the need for fast parallel implementations. Huffman coding is an integral part of a number of compression methods. However, efficient parallel implementation of Huffman decompre…
FeatherCNN: Fast Inference Computation with TensorGEMM on ARM Architectures
2020
Deep Learning is ubiquitous in a wide field of applications ranging from research to industry. In comparison to time-consuming iterative training of convolutional neural networks (CNNs), inference is a relatively lightweight operation making it amenable to execution on mobile devices. Nevertheless, lower latency and higher computation efficiency are crucial to allow for complex models and prolonged battery life. Addressing the aforementioned challenges, we propose FeatherCNN – a fast inference library for ARM CPUs – targeting the performance ceiling of mobile devices. FeatherCNN employs three key techniques: 1) A highly efficient TensorGEMM (generalized matrix multiplication) routine is app…
Catalogue of Interactive Learning Objectives to improve an Integrated Medical and Dental Curriculum.
2016
ABSTRACT Introduction Online learning media are increasingly being incorporated into medical and dental education. However, the coordination between obligatory and facultative teaching domains still remains unsatisfying. The Catalogue of Interactive Learning Objectives of the University Clinic of Mainz (ILKUM), aims to offer knowledge transfer for students while being mindful of their individual qualifications. Its hierarchical structure is designed according to the Association for Dental Education in Europe (ADEE) levels of competence. Materials and methods The ILKUM was designed to establish a stronger interconnection between already existing and prospective learning strategies. All conte…
Empowering education professionals with twenty-first century skills through master's of education dissertation/thesis work
2021
This paper aims to explore the potential role of Master’s of Education dissertation/thesis work in developing twenty-first century skills. A total of 600 education professionals studying Master’s of Education programmes in five countries – Poland, Portugal, England, Latvia, and Romania – were surveyed. The findings have revealed that participants recognise the usefulness of twenty-first century skills for their (future) professional practice, and perceive dissertation/thesis work as a valuable foundation for developing these skills. This study offers practical implications for designers of Master’s of Education programmes and contributes to our understanding that this assignment is not only…
ULearn: Personalized Medical Learning on the Web for Patient Empowerment
2019
Abstract. Health literacy constitutes an important step towards patient empowerment and the Web is presently the biggest repository of medical information and, thus, the biggest medical resource to be used in the learning process. However, at present web medical information is mainly accessed through generic search engines that do not take into account the user specific needs and starting knowledge and so are not able to support learning activities tailored to the specific user requirements. This work presents “ULearn” a meta engine that supports access, understanding and learning on the Web in the medical domain based on specific user requirements and knowledge levels towards what we call …
How do we assess in Clinical Legal Education? A 'reflection' about reflective learning
2016
I suggest this hypothesis and these premises from the perspective of my experience in Clinical Legal Education and the use of experiential learning methods in other 'traditional' courses. Firstly, institutional assessment must be distinguished from the assessment of learning. Traditionally, assessment is reduced to institutional assessment: that is, to give a mark depending on the achievement of knowledge instead of focusing in the student's learning. However, I propose (to remember) that: 1) (Formative) assessment is part of learning; 2) Reflective learning (and reflective skills) is/are a part of assessment. This implies a process of continuous evaluation instead of summative evaluation, …
Teaching clinical reasoning and decision-making skills to nursing students: Design, development, and usability evaluation of a serious game
2016
Background\ud \ud Serious games (SGs) are a type of simulation technology that may provide nursing students with the opportunity to practice their clinical reasoning and decision-making skills in a safe and authentic environment. Despite the growing number of SGs developed for healthcare professionals, few SGs are video based or address the domain of home health care.\ud \ud Aims\ud \ud This paper aims to describe the design, development, and usability evaluation of a video based SG for teaching clinical reasoning and decision-making skills to nursing students who care for patients with chronic obstructive pulmonary disease (COPD) in home healthcare settings.\ud \ud Methods\ud \ud A prototy…
Developing a Serious Game for Nurse Education.
2018
Future nursing education is challenged to develop innovative and effective programs that align with current changes in health care and to educate nurses with a high level of clinical reasoning skills, evidence-based knowledge, and professional autonomy. Serious games (SGs) are computer-based simulations that combine knowledge and skills development with video game–playing aspects to enable active, experiential, situated, and problem-based learning. In a PhD project, a video-based SG was developed to teach nursing students nursing care for patients with chronic obstructive pulmonary disease in home health care and hospital settings. The current article summarizes the process of the SG devel…
Hybrid Deep Shallow Network for Assessment of Depression Using Electroencephalogram Signals
2020
Depression is a mental health disorder characterised by persistently depressed mood or loss of interest in activities resulting impairment in daily life significantly. Electroencephalography (EEG) can assist with the accurate diagnosis of depression. In this paper, we present two different hybrid deep learning models for classification and assessment of patient suffering with depression. We have combined convolutional neural network with Gated recurrent units (RGUs), thus the proposed network is shallow and much smaller in size in comparison to its counter LSTM network. In addition to this, proposed approach is less sensitive to parameter settings. Extensive experiments on EEG dataset shows…