1,720,961 research outputs found
Soil Moisture Estimation based on the RSSI of RFID Modules
No full textNowadays the RFID technology and Internet of Things are becoming empowering and enabling tools in various fields, including smart and precision agriculture. The aim of this research is to propose an innovative system for the detection of soil moisture based on the use of standard UHF RFID tags and on the measurement of the received signal strength detected by a reader that can be hosted on board drones or farm vehicles. The reader detects the RSSI received from tags placed below the ground level and according to the measured value is able to discriminate if the ground is dry or wet. Microwave propagation is, in fact, strongly influenced by the presence of water in the soil and by exploiting the instantaneous and average RSSI values it is possible to discriminate the conditions of dry and wet soil and, thus, optimize irrigation in a wide area. The results obtained by using a first prototype show that the approach is suitable for any type of soil: sandy, clayey or loamy; further studies must be conducted in order to identify different levels of soil moisture and to determine the moisture levels at different depths
Rate adaptation control protocol for variable packet size sources: Modelling and simulation
No full textFPGA Implementation of a BPSK Modulator with Frequency Hopping
Full text linkPSK modulations are very widespread in communication due to their robustness to the noise. In order to avoid interference or for anti-jamming purposes, frequency hopping may be applied. In this work we present an FPGA implementation of a BPSK modulator based on frequency hopping. The results shows good performance, more than 300 MHz of clock system, low area occupation and low power dissipation (about 100 mW)
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
Reducing interferences in wireless communication systems by mobile agents with recurrent neural networks-based adaptive channel equalization
No full textSolving channel equalization problem in communication systems is based on adaptive filtering algorithms. Today, Mobile Agents (MAs) with Recurrent Neural Networks (RNNs) can be also adopted for effective interference reduction in modern wireless communication systems (WCSs). In this paper MAs with RNNs are proposed as novel computing algorithms for reducing interferences in WCSs performing an adaptive channel equalization. The method to provide it is so called MAs-RNNs. We perform the implementation of this new paradigm for interferences reduction. Simulations results and evaluations demonstrates the effectiveness of this approach and as better transmission performance in wireless communication network can be achieved by using the MAs-RNNs based adaptive filtering algorithm
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
Techniques for Recognising and Classifying Environmental Noise Using Deep Learning
No full textIncreasing urbanisation poses new challenges in mitigating noise pollution and preserving quality of life. In this study, we present an innovative approach for the classification of environmental noise, exploiting advanced Deep Learning (DL) techniques. By merging three different public datasets, we created a unified corpus to train and test a convolutional neural network (CNN), with the aim of efficiently recognising and classifying various noise events. The proposed approach overcomes the limitations of conventional methodologies, avoiding the need for data pre-processing that could alter sound characteristics. The experimental results demonstrate a significant improvement in classification accuracy, reaching 96.93% with the test set and 100% by applying a post-processing filter. These results emphasise the potential of DL in the treatment of environmental noise, offering new perspectives for signal processing and telecommunications
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