3,004 research outputs found
An Approach for Sentiment Classification of Music
No full textIn recent years, the music recommendation systems and dynamic generation of playlists have become extremely promising research areas. Thanks to the widespread use of the Internet, users can store a consistent set of music data and use them in the everyday context thanks to portable music players. The problem of modern music recommendation systems is how to process this large amount of data and extract meaningful content descriptors. The aim of this paper is to compare different approaches to decode the content within the mood of a song and to propose a new set of features to be considered for classification
“Magic Mirror in my Hand, what is the Sentiment in the Lens?”: an Action Unit based Approach for Mining Sentiments from Multimedia Contents
No full textEmotions are an increasingly important factor in Human-Computer Interaction. So, extracting emotions from multimedia contents is becoming one of the most challenging research topics in Computer Science. Facial expressions, posture, gestures, speech, emotive changes of physical parameter (e.g. body temperature, blush and changes in the tone of the voice) can reflect changes in the user's emotional state. All this kind of parameters can be detected and interpreted by a computer leading to the so-called “affective computing”. Through affective computing, client's posture, gestures, and facial expressions could be used, along with words, for a more accurate evaluation of their psychological state. In this paper an approach for the extraction of emotions from images will be introduced. The proposed framework involves the adoption of action units’ extraction from facial expression according to the Ekman theory. The proposed approach has been tested on standard datasets and the results are interesting and promising
Sentiment detection in social networks and in collaborative learning environments
No full textDaily millions of messages appear on the web, which is becoming a rich source of data for opinion mining and sentiment analysis. The computational study of opinions, feelings and emotions expressed in a text often relates to the identification of agreement or disagreement with statements, contained in comments or reviews, that convey positive or negative feelings. The detection and analysis of sentiment in textual communication is a topic attracting attention also in the context of collaborative learning in social networks, being learners actively engaged in presenting and defending ideas and opinions, as well as exchanging moods about courses with peers. In this paper, we investigate the adoption of a probabilistic approach based on the Latent Dirichlet Allocation (LDA) as Sentiment Grabber. Through this approach, for a set of documents belonging to a same knowledge domain, a graph, the Mixed Graph of Terms, can be automatically extracted. The paper shows how this graph contains a set of weighted word pairs, which are discriminative for sentiment classification. The proposed method has been tested in different context: a standard dataset containing movie reviews; a real-time analysis of social networks posts; a collaborative learning scenario. The experimental evaluation shows how the proposed approach is effective and satisfactory
An assessment of the impact of possible CAP reform scenarios on Romanian agriculture
No full textUsing a simplified model, with key-variable the prices of two different possible scenarios of CAP reform after 2013 (moderate and radical), this paper present a comparison between the price effects of implementation of each reform scenario at 2015 horizon on Romanian agriculture. This short analysis shows that, under the presented hypotheses, the net welfare effect, due to the price changes, for the selected products, is positive in both reform scenarios, yet greater in the case of the radical reform. Integrated in the large context of Romanian development, it seems that the influence of CAP reform upon agriculture and rural areas will be most likely a gradual one: an interpenetration between the two scenarios is foreseeable, starting with the moderate reform that will dominate the period around 2013, the reform measures acquiring a more radical character afterwards.CAP reform, Romania, welfare effects, Agricultural and Food Policy,
Rich, Sturmian, and trapezoidal words
No full textIn this paper we explore various interconnections between rich words, Sturmian words, and trapezoidal words. Rich words, first introduced by the second and third authors together with J. Justin and S. Widmer, constitute a new class of finite and infinite words characterized by having the maximal number of palindromic factors. Every finite Sturmian word is rich, but not conversely. Trapezoidal words were first introduced by the first author in studying the behavior of the subword complexity of finite Sturmian words. Unfortunately this property does not characterize finite Sturmian words. In this note we show that the only trapezoidal palindromes are Sturmian. More generally we show that Sturmian palindromes can be characterized either in terms of their subword complexity (the trapezoidal property) or in terms of their palindromic complexity. We also obtain a similar characterization of rich palindromes in terms of a relation between palindromic complexity and subword complexity
Characterization Results for the Poset Based Representation of Topological Relations - I: Introduction and Models
No full text@article{DBLP:journals/informaticaSI/ForlizziN99,
author = {Luca Forlizzi and
Enrico Nardelli},
title = {Characterization Results for the Poset Based Representation
of Topological Relations - I: Introduction and Models.},
journal = {Informatica (Slovenia)},
volume = {23},
number = {2},
year = {1999},
bibsource = {DBLP, http://dblp.uni-trier.de}
Characterization Results for the Poset Based Representation of Topological Relations - II: Intersection and Union
No full text@article{DBLP:journals/informaticaSI/ForlizziN00,
author = {Luca Forlizzi and
Enrico Nardelli},
title = {Characterization Results for the Poset Based Representation
of Topological Relations - II: Intersection and Union.},
journal = {Informatica (Slovenia)},
volume = {24},
number = {1},
year = {2000},
bibsource = {DBLP, http://dblp.uni-trier.de}
System-on-chip Computing and Interconnection Architectures for Telecommunications and Signal Processing
No full textThis dissertation proposes novel architectures and design techniques targeting SoC building blocks for telecommunications and signal processing applications.
Hardware implementation of Low-Density Parity-Check decoders is approached at both the algorithmic and the architecture level. Low-Density Parity-Check codes are a promising coding scheme for future communication standards due to their outstanding error correction performance.
This work proposes a methodology for analyzing effects of finite precision arithmetic on error correction performance and hardware complexity. The methodology is throughout employed for co-designing the decoder. First, a low-complexity check node based on the P-output decoding principle is designed and characterized on a CMOS standard-cells library. Results demonstrate implementation loss below 0.2 dB down to BER of 10^{-8} and a saving in complexity up to 59% with respect to other works in recent literature. High-throughput and low-latency issues are addressed with modified single-phase decoding schedules. A new "memory-aware" schedule is proposed requiring down to 20% of memory with respect to the traditional two-phase flooding decoding. Additionally, throughput is doubled and logic complexity reduced of 12%. These advantages are traded-off with error correction performance, thus making the solution attractive only for long codes, as those adopted in the DVB-S2 standard. The "layered decoding" principle is extended to those codes not specifically conceived for this technique. Proposed architectures exhibit complexity savings in the order of 40% for both area and power consumption figures, while implementation loss is smaller than 0.05 dB.
Most modern communication standards employ Orthogonal Frequency Division Multiplexing as part of their physical layer. The core of OFDM is the Fast Fourier Transform and its inverse in charge of symbols (de)modulation. Requirements on throughput and energy efficiency call for FFT hardware implementation, while ubiquity of FFT suggests the design of parametric, re-configurable and re-usable IP hardware macrocells. In this context, this thesis describes an FFT/IFFT core compiler particularly suited for implementation of OFDM communication systems. The tool employs an accuracy-driven configuration engine which automatically profiles the internal arithmetic and generates a core with minimum operands bit-width and thus minimum circuit complexity. The engine performs a closed-loop optimization over three different internal arithmetic models (fixed-point, block floating-point and convergent block floating-point) using the numerical accuracy budget given by the user as a reference point. The flexibility and re-usability of the proposed macrocell are illustrated through several case studies which encompass all current state-of-the-art OFDM communications standards (WLAN, WMAN, xDSL, DVB-T/H, DAB and UWB). Implementations results are presented for two deep sub-micron standard-cells libraries (65 and 90 nm) and commercially available FPGA devices. Compared with other FFT core compilers, the proposed environment produces macrocells with lower circuit complexity and same system level performance (throughput, transform size and numerical accuracy).
The final part of this dissertation focuses on the Network-on-Chip design paradigm whose goal is building scalable communication infrastructures connecting hundreds of core. A low-complexity link architecture for mesochronous on-chip communication is discussed. The link enables skew constraint looseness in the clock tree synthesis, frequency speed-up, power consumption reduction and faster back-end turnarounds. The proposed architecture reaches a maximum clock frequency of 1 GHz on 65 nm low-leakage CMOS standard-cells library. In a complex test case with a full-blown NoC infrastructure, the link overhead is only 3% of chip area and 0.5% of leakage power consumption.
Finally, a new methodology, named metacoding, is proposed. Metacoding generates correct-by-construction technology independent RTL codebases for NoC building blocks. The RTL coding phase is abstracted and modeled with an Object Oriented framework, integrated within a commercial tool for IP packaging (Synopsys CoreTools suite). Compared with traditional coding styles based on pre-processor directives, metacoding produces 65% smaller codebases and reduces the configurations to verify up to three orders of magnitude
To Kick or Not to Kick: An Affective Computing Question
No full textWith the Web 2.0 and its services, the users are able to express their own emotions through the production and sharing of multimedia contents. In this context, we can interpret the flood of selfies that everyday invades the web as the will to overcome the limits of the textual communication. Therefore, it becomes particularly interesting the possibility to extract in an automatic way information about the emotional state of the people present in the multimedia content. The knowledge of a person’s emotional state gives useful information for the personalization of many online services. Some examples of the areas where such an approach can be adopted are the services for the content recommendation, for the entertainment and for the distance training. In this paper, the techniques of sentiment extraction from multimedia contents will be applied to the sports world. In particular, the aim is to verify the possibility to predict the result of a penalty kick analyzing the player’s face. The objective is to investigate the possibility to evaluate in real time the psychic conditions of an athlete during a competition. The system has been tested on an opportunely built dataset and the results are more than satisfying
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