1,720,979 research outputs found
A new distributed application and network layer protocol for voip in mobile ad hoc networks
No full textIn this work a new protocol for Voice over IP (VoIP) transmissions in wireless ad-hoc networks is proposed. Distributed architecture is necessary when dealing with dynamic environments, such as ports or battlefields, where creating infrastructures becomes expensive or impossible. Mobile ad-hoc networks (MANETs) are based on a peer-to-peer approach and each node participates in the organization of the whole network. VoIP over MANETs is a challenging issue due to the intrinsic distributed nature of the existing peer-to-peer paradigm. This paper proposes a new protocol, capable of ensuring a quality of service (QoS) level for VoIP calls over a MANET and to manage a large number of calls in the system. Novel metric and utility functions are proposed to perform the best path selection from source to destination nodes, respecting the QoS parameters for VoIP quality. In particular, an objective metric such as R-factor is considered, and a flexibility index is defined in order to maximize the number of acceptable VoIP calls. Performance evaluation shows that the proposed approach led to better network management in terms of admitted calls and respected QoS constraints. © 2012 IEEE
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
Multi-Stream 1D CNN for EEG Motor Imagery Classification of Limbs Activation
Full text linkDetermining the motor intentions of an individual through the analysis of electroencephalograms (EEGs) is a challenging task that concurrently holds considerable potential in aiding subjects with motor dysfunctions. Moreover, thanks to the recent advances in artificial intelligence models and EEG acquisition devices, such analyses can be carried out with ever higher accuracy. The latter aspect covers great importance, since the EEG analysis of subjects whose mental efforts are focused on moving limbs is frequently used for crucial tasks, including the control of interactive interfaces and prosthetic devices. In this paper, a novel multi-stream 1D Convolutional Neural Network (CNN) architecture is proposed. The input EEG signal is processed by four convolutional streams, which differ in the size of convolutional kernels, thus allowing the extraction of information at different time scales. The resulting 1D feature maps are then fused together and provided to a dense classifier to identify which limb the subject intended to move. Comprehensive experiments conducted on PhysioNet EEG motor movement/imagery dataset, which remains the reference collection of data in this application context, have demonstrated that the proposed model surpasses the key works in the current state-of-the-art in both cross-subject and intra-subject settings
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
A Novel Transformer-Based IMU Self-Calibration Approach through On-Board RGB Camera for UAV Flight Stabilization
Full text linkDuring flight, unmanned aerial vehicles (UAVs) need several sensors to follow a predefined path and reach a specific destination. To this aim, they generally exploit an inertial measurement unit (IMU) for pose estimation. Usually, in the UAV context, an IMU entails a three-axis accelerometer and a three-axis gyroscope. However, as happens for many physical devices, they can present some misalignment between the real value and the registered one. These systematic or occasional errors can derive from different sources and could be related to the sensor itself or to external noise due to the place where it is located. Hardware calibration requires special equipment, which is not always available. In any case, even if possible, it can be used to solve the physical problem and sometimes requires removing the sensor from its location, which is not always feasible. At the same time, solving the problem of external noise usually requires software procedures. Moreover, as reported in the literature, even two IMUs from the same brand and the same production chain could produce different measurements under identical conditions. This paper proposes a soft calibration procedure to reduce the misalignment created by systematic errors and noise based on the grayscale or RGB camera built-in on the drone. Based on the transformer neural network architecture trained in a supervised learning fashion on pairs of short videos shot by the UAV’s camera and the correspondent UAV measurements, the strategy does not require any special equipment. It is easily reproducible and could be used to increase the trajectory accuracy of the UAV during the flight
Distilled Gradual Pruning with Pruned Fine-tuning
No full textNeural Networks (NNs) have been driving machine learning progress in recent years, but their larger models present challenges in resource-limited environments. Weight pruning reduces the computational demand, often with performance degradation and long training procedures. This work introduces Distilled Gradual Pruning with Pruned Fine-tuning (DG2PF), a comprehensive algorithm that iteratively prunes pre-trained neural networks using knowledge distillation. We employ a magnitude-based unstructured pruning function that selectively removes a specified proportion of unimportant weights from the network. This function also leads to an efficient compression of the model size while minimizing classification accuracy loss. Additionally, we introduce a simulated pruning strategy with the same effects of weight recovery but while maintaining stable convergence. Furthermore, we propose a multi-step self-knowledge distillation strategy to effectively transfer the knowledge of the full, unpruned network to the pruned counterpart. We validate the performance of our algorithm through extensive experimentation on diverse benchmark datasets, including CIFAR-10 and ImageNet, as well as a set of model architectures. The results highlight how our algorithm prunes and optimizes pre-trained neural networks without substantially degrading their classification accuracy while delivering significantly faster and more compact models
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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