Using Generic Summarization to Improve Music Information Retrieval Tasks

In order to satisfy processing time constraints, many MIR tasks process only a segment of the whole music signal. This practice may lead to decreasing performance, since the most important information for the tasks may not be in those processed segments. In this paper, we leverage generic summarization algorithms, previously applied to text and speech summarization, to summarize items in music datasets. These algorithms build summaries, that are both concise and diverse, by selecting appropriate segments from the input signal which makes them good candidates to summarize music as well. We evaluate the summarization process on binary and multiclass music genre classification tasks, by comparing the performance obtained using summarized datasets against the performances obtained using continuous segments (which is the traditional method used for addressing the previously mentioned time constraints) and full songs of the same original dataset. We show that GRASSHOPPER, LexRank, LSA, MMR, and a Support Sets-based Centrality model improve classification performance when compared to selected 30-second baselines. We also show that summarized datasets lead to a classification performance whose difference is not statistically significant from using full songs. Furthermore, we make an argument stating the advantages of sharing summarized datasets for future MIR research.Comment: 24 pages, 10 tables; Submitted to IEEE/ACM Transactions on Audio, Speech and Language Processin

On the Application of Generic Summarization Algorithms to Music

Several generic summarization algorithms were developed in the past and successfully applied in fields such as text and speech summarization. In this paper, we review and apply these algorithms to music. To evaluate this summarization's performance, we adopt an extrinsic approach: we compare a Fado Genre Classifier's performance using truncated contiguous clips against the summaries extracted with those algorithms on 2 different datasets. We show that Maximal Marginal Relevance (MMR), LexRank and Latent Semantic Analysis (LSA) all improve classification performance in both datasets used for testing.Comment: 12 pages, 1 table; Submitted to IEEE Signal Processing Letter

Urban regeneration economics: The case of Lisbon's old downtown

Buildings are one of the biggest assets of Lisbon's central downtown accumulated over a period of several centuries. The efficient use and optimization of the value of these assets are a challenge for both the owners of individual buildings and for society as a whole. Recently, a new regeneration initiative was announced for old urban Lisbon's downtown, covering three fields of intervention: the economic, social and physical fields. This paper presents a case study of the regeneration program for the Lisbon's old downtown including an analysis of the framework used to assess the costs and benefits. Santrauka Pastatai – tai vienas pagrindinių Lisabonos centrinio komercinio rajono turtų, sukauptų per keletą amžių. Efektyvus šio turto naudojimas ir vertės optimizavimas – tai iššūkis ir atskirų pastatų savininkams, ir visai visuomenei. Neseniai paskelbta nauja senojo Lisabonos komercinio rajono atgaivinimo iniciatyva, apimanti tris intervencijos sritis: ekonominę, socialinę ir fi zinę. Šiame darbe pristatomas senojo Lisabonos komercinio rajono atgaivinimo programos atvejo tyrimas, pateikiama sąnaudų bei naudingumo įvertinimo sistemos analizė. First published online: 18 Oct 201

Chitosan Nanoparticles as Drug Delivery Systems

The goal of the present work is to synthesize chitosan-coated superparamagnetic iron oxide nanoparticles (CS SPIONs) for doxorubicin (DOX) delivery for cancer theranostics. The CS SPIONs will be loaded with the anticancer drug DOX because it is largely used clinically for different cancers types. In this work chitosan nanoparticles (CS NPs) and iron oxide nanoparticles were synthetized by ionic gelation and thermal decomposition techniques, respectively. Chitosan depolymerization was performed to be used different molecular weights (474 – 39 kDa) to produce CS NPs with different diameters. Magnetic stirring and pH influence were also studied. Dynamic Light Scattering (DLS) measurements indicate that was obtained different nanoparticles diameters, approximately the lowest diameters were around 100 nm and 9 nm for CS NPS and iron NPs respectively. Then, CS SPIONs were formed. Synthetized nanoparticles were characterized by (DLS), UV-Visible (UV-Vis), Fourier Transform Infrared Spectroscopy (FTIR) and Transmission Electrons Microscopy (TEM). Superconducting Quantum Interference Device (SQUID) and magnetic hyperthermia studies indicate that this nanoparticles show a superparamagnetic behavior and the ability to generate heat. These characteristics are essential to be possible to use these nanoparticles in biomedical applications such as contrast agents for MRI, magnetic drug delivery, cancer diagnostics and treatment. The DOX delivery studies indicate that the drug release depends on pH and in the first 10-20 hours the majority of drug is released. Finally, the in vitro cell viability and proliferation studies were conducted using the Vero cell line. These studies indicate that the CS SPIONs synthetized in the present work are non-toxic up to the CS SPIONs concentration of 1.25 mg/ml. Considering all the studies conducted in this work, it can be concluded that the nanoparticles synthetized possess the necessary characteristics to be used in biomedical applications

Modeling Worldwide Highway Networks

This letter addresses the problem of modeling the highway systems of different countries by using complex networks formalism. More specifically, we compare two traditional geographical models with a modified geometrical network model where paths, rather than edges, are incorporated at each step between the origin and destination nodes. Optimal configurations of parameters are obtained for each model and used in the comparison. The highway networks of Brazil, the US and England are considered and shown to be properly modeled by the modified geographical model. The Brazilian highway network yielded small deviations that are potentially accountable by specific developing and sociogeographic features of that country.Comment: 5 pages, 3 figures, 1 tabl