1,721,020 research outputs found
A YOLOv2 convolutional neural network-based Human-Machine Interface for the control of assistive robotic manipulators
Full text linkDuring the last years, the mobility of people with upper limb disabilities and constrained on power wheelchairs is empowered by robotic arms. Nowadays, even though modern manipulators offer a high number of functionalities, some users cannot exploit all those potentialities due to their reduced manual skills, even if capable of driving the wheelchair by means of proper Human-Machine Interface (HMI). Owing to that, this work proposes a low-cost manipulator realizing only simple tasks and controllable by three different graphical HMI. The latter are empowered using a You Only Look Once (YOLO) v2 Convolutional Neural Network that analyzes the video stream generated by a camera placed on the robotic arm end-effector and recognizes the objects with which the user can interact. Such objects are shown to the user in the HMI surrounded by a bounding box. When the user selects one of the recognized objects, the target position information is exploited by an automatic close-feedback algorithm which leads the manipulator to automatically perform the desired task. A test procedure showed that the accuracy in reaching the desired target is 78%. The produced HMIs were appreciated by different user categories, obtaining a mean score of 8.13/10
A high throughput hardware architecture for parallel recursive systematic convolutional encoders
Full text linkDuring the last years, recursive systematic convolutional (RSC) encoders have found application in modern telecommunication systems to reduce the bit error rate (BER). In view of the necessity of increasing the throughput of such applications, several approaches using hardware implementations of RSC encoders were explored. In this paper, we propose a hardware intellectual property (IP) for high throughput RSC encoders. The IP core exploits a methodology based on the ABCD matrices model which permits to increase the number of inputs bits processed in parallel. Through an analysis of the proposed network topology and by exploiting data relative to the implementation on Zynq 7000 xc7z010clg400-1 field programmable gate array (FPGA), an estimation of the dependency of the input data rate and of the source occupation on the parallelism degree is performed. Such analysis, together with the BER curves, provides a description of the principal merit parameters of a RSC encoder
Estimating the Downlink Data-Rate of a CCSDS File Delivery Protocol IP Core
No full textThe Consultative Committee for Space Data Systems File Delivery Protocol (CFDP) is a protocol designed for the transmission of files in space environment, characterized by frequent link disconnections and high transmission delay. This work presents the characterization of the CFDP IP Core included in the European Space Agency (ESA) IP portfolio in terms of downlink data-rate through a custom methodology. For the characterization of the acknowledged/unacknowledged transmission modes, the CFDP IP Core was implemented on board Virtex-5 and Virtex-6 Field Programmable Gate Arrays and tested by using the ESA Ground Segment CFDP reference software, acting as a secondary CFDP entity. The delivered CFDP packets were encapsulated in Unit Datagram Protocol (UDP) packets and transmitted through Ethernet protocol. Wireshark was used to measure the time for a file transmission. The presented methodology provides a way to estimate the IP Core maximum transmission throughput and to identify the architectural bottlenecks
MEM-OPT: A Scheduling and Data Re-Use System to Optimize On-Chip Memory Usage for CNNs On-Board FPGAs
No full textIn the last years, Convolutional Neural networks (CNNs) found applications in many fields from computer vision to speech recognition, showing outstanding results in terms of accuracy. Field Programmable Gate Arrays (FPGAs) proved to be a promising platform for running CNN algorithms because they offer a remarkable trade-off between power consumption and computational power. However, an efficient implementation of CNN models on-board an FPGA represents a complex task since CNN massive parallel processing is often limited by FPGA storage capabilities and design congestion. This article introduces MEM-OPT, a scheduling algorithm and data re-use system that aims to optimize on-chip memory usage on-board FPGAs for what concerns input feature maps storage and Processing Elements multiply and accumulation process. The work presents MEM-OPT implementations results on a Xilinx XC7Z020, including hardware resources, maximum clock frequency and power consumption. MEM-OPT memory requirements are analyzed for LeNet-5, MobileNet, VGG-16 and other state-of-the-art CNNs, showing, a reduction up to 80% of the overall on-chip memory necessary for storing input feature maps and accumulating output results with respect to alternative solutions available in the literature
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Machine learning assistive application for users with speech disorders
No full textThis paper investigates machine learning approaches toward the development of a speaker dependent keywords spotting system intended for users with speech disorders, in particular for those with dysarthria, i.e., a neuromotor speech impairment associated with severe physical disabilities. In the field of assistive technologies, nowadays automatic speech recognition (ASR) is an open challenge since standard voice recognition approaches and voice driven services are ineffective to recognize atypical speech. To address these issues, we focus our attention on keywords spotting task in presence of dysarthria and we exploit deep learning technology in conjunction with an existing convolutional neural network model to build a tailored ASR system for users with such speech disabilities. However, the usage of a machine learning approach requires enough data availability for the training of the model; to this aim, we introduce a mobile software (app) allowing those with speech disorders to collect their audio contribution in order to enrich the speech model. Considering Italian as main language, this approach allows us to build the first database containing speech samples from Italian native users with dysarthria. As discussed in the end of the article, early experiments show promising results and give us interesting perspectives for future research directions
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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