Miracle-dz/UniFAR-FTUs huggingface dataset:
Audio pattern discovery and retrieval

This thesis explores unsupervised algorithms for pattern discovery and retrieval in audio and speech data. In this work, audio pattern is defined as repeating audio content such as repeating music segments or words/short phrases in speech recordings. The meanings of “pattern” will be defined separately for different types of data, for example, repeating pattern discovery in music will extract segments with similar melody in music piece; In human speech, the same words/short phrases spoken by single or multiple speakers are also defined as speech patterns; In broadcast audio, repeated commercials/logo music are also considered as patterns. Previous work on audio pattern discovery focuses on either symbolizing the audio signal into token sequences followed by text-based search or using Brute-Force search techniques such as self-similarity matrix and Dynamic Time Warping. Symbolization process that relies on Vector Quantization or other modeling techniques may suffer from misclassification errors, and the exhaustive search requires high computation cost and can also be affected by channel distortion and speaker variation in audio data. Such limitations motivate me to explore more efficient and robust approaches to automatically detect repeating information in audio data. In this thesis, different unsupervised techniques are examined to analyze music and speech separately. For music, an efficient approach which extends Ukkonon’s suffix tree construction algorithm is proposed to detect repeating segments. For speech data, an iterative merging approach which is based on Acoustic Segment Model (ASM) is proposed to discover recurrent phrases/words in speech. This thesis also explores the techniques of searching audio pattern in broadcast audio which consists of diverse content such as speech, music/songs, commercials, sound effects and background noise. Existing audio pattern retrieval techniques focus only on specific
3-D Path Planning With Multiple Motions for a Gliding Robotic Dolphin

This paper presents a three-dimensional (3-D) path planning method that combines the gliding with dolphin-like motions for the gliding robotic dolphin. A specific task that the robot uses the gliding motion for long-distance cruise and the dolphin-like motion for maneuverable obstacle avoidance is employed. The results of simulations and aquatic experiments validate the full-state dynamic model and the specific task, further offer some theoretical supports for 3-D path planning. Further, the 3-D path planning method is composed of three main components: 1) gliding path generation; 2) improved Astar (A*) algorithm; and 3) segmented Bezier curve smoothing. First, the gliding path is generated autonomously with the kinematic constraints that are obtained via the simulations of dynamic model. Furthermore, when the obstacles are detected by the sonar, an improved A* algorithm is employed to avoid the obstacles. Afterward, considering the path planned by A* is unsmoothed, a segmented Bezier curve method is presented. Simulation results demonstrate the effectiveness of the method, offering valuable insight into the utilization of hybrid underwater robots in the context of real-time task execution.
Analysis of channels for Software Defined Radio using LabVIEW

The role of radio in wireless communication has been extended to a much extent from few decades. The basic concept of software defined radio is that the radio can be configured from software hence reducing the need of hardware. In this paper software defined radio (SDR) 32-QAM modem is implemented using LabVIEW software. LabVIEW is a graphically based programming language developed by National Instruments. It has built in functionality for test and measurement automation, instrument control, data acquisition, and data analysis applications. The aim of this paper is to simulate SDR for next generation wireless communication having Gaussian and time varying channel. The simulation is done to analyze the performance of hamming coding in Gaussian channel and convolution coding in time varying channel is compared Adaptive filter is used to minimize the effect of noise. It is obvious from the simulation results that the SNR and BER values are analyzed using hamming coding & convolution coding depending upon applications & thus gives better results.
Efficient segmentation and positioning of 3D fluorescent spherical beads in confocal microscopy

Particle estimation is a classical problem arising in many science fields, such as biophysics, fluid mechanics, bio-medical imaging. Many interesting applications in these areas involve 3D data: this work presents a technique to estimate the 3D coordinates of the center of spherical particles. This procedure provides an estimation of both the center and the profile of the 2D intersections of the particles with the frames, by coupling the usage of Total Variation functional and of a regularized weighted Least Square fit. The 2D information is used to retrieve the 3D coordinates using geometrical properties. The performance of this procedure strongly depends on the quality of the acquisition, hence a particularly tailored denoising technique is applied for Poisson noise: this leads to a better estimation of the particle positions.
Calibration and the Expert Problem

A decision maker needs to give his subjective probability for a single event of interest, A. Being aware that he has little substantive knowledge of the factors affecting A, the decision maker asks an expert for advice. The expert gives his subjective probability for A. In the light of this information, how should the decision maker form his subjective probability? In particular, does it matter to the decision maker whether the expert is a well-calibrated probability assessor? In this paper these questions are explored and it is suggested that concepts such as calibration and refinement cannot usefully be defined independently of the decision maker.
MINIATURIZED MULTISTUBS LOADED RECTANGULAR MONOPOLE ANTENNA FOR MULTIBAND APPLICATIONS BASED ON THEORY OF CHARACTERISTICS MODES

A miniaturized rectangular monopole antenna (RMA) integrated with a T-shaped stub, inverted long and short L-shaped stub resonators based on application of the theory of characteristic modes (CMs) is investigated for multiband operation. CMs of embedded multistubs resonators on the RMA are examined and perceived that the entire structure is able to excite magnetic and electric CMs, in which three valuable CMs at 2.69/3.68/5.35 GHz are attained to cover WiMAX and WLAN bands. Based on CM analysis, the design formulation of multistubs resonators loaded antenna is presented. The proposed multiband antenna has been fabricated, tested, and experimentally characterized. The measured fractional bandwidths (FBWs) are 7.03% (180 MHz, 2.47–2.65 GHz), 10.43% (360 MHz, 3.27– 3.63 GHz), and 11.42% (630 MHz, 5.20–5.83 GHz). The antenna exhibits isolated multiple frequency bands, stable monopole-like radiation patterns, and flat realized gains over the operating resonance bands while maintaining the small antenna size.
Neighbourhood Liveability Assessment of Shepparton: The application of indicators as evidence to plan for a healthy and liveable regional city.

The primary objective of the Neighbourhood Liveability Assessment was to gain a better understanding of liveability within neighbourhoods across Shepparton. The secondary objective was to provide evidence of liveability that could be applied to inform and evaluate major long term policy and planning initiatives planned within and across Council, DHHS and key partners.
Grammar rule based cross language information retrieval for Telugu

The rapid spread of the World Wide Web and improvements in information retrieval (IR) techniques have allowed people to access huge amount of information. However, majority of the web content is in English. While content in languages like Telugu and Tamil are growing every day, a huge gap remains. This gap is what this research work will be addressing. In general information retrieval systems, the relevant information retrieved for the user query, only if the information is available in that query language. For example a Telugu search engine will retrieve only results for content in Telugu. It is not considering the relevant information that is available in the other languages for the given user query. Cross Language Information Retrieval (CLIR) systems seek to overcome this gap. A CLIR system retrieves information from a language that is different from the user’s query language. The goal of this research work is to develop a new framework for Telugu English Cross Language Information Retrieval using Language Grammar Rules. The major challenges addressed are query ambiguity and the linguistic differences between the query and content language. The steps in this research are as follows: a) The user query is tokenized into keywords using tokenizer. The language grammar rules are applied to the tokenized query terms to identify the subject, verb, object and inflection in tokenized keywords. b) The query processor searches the English equivalent terms in the ontology for the terms identified using language grammar rules. The terms which are not available in ontology are considered as Out-OfVocabulary terms and literally transliterated into the English language.
Dynamic risk management of assets susceptible to pitting corrosion

This paper presents a methodology to assess and dynamically update the risk of process components affected by pitting corrosion. The proposed framework considers the time-dependent growth of pits and uses the non-homogenous Markov process to model the maximum pit depth. The developed pit depth model is incorporated into a limit state function to estimate the failure probability of affected components. Economic consequences are estimated considering both business and accidental losses due to failure. The estimated risk is updated using Bayesian analysis as new inspection data become available. Different risk management strategies including prevention, control and mitigation measures are also studied.
Tailoring the magnetic properties of cobalt ferrite nanoparticles using the polyol process

Background: In extrinsically magnetoelectric materials made of two components, the direct magnetoelectric coupling arises from a mechanical strain transmission at the interface due to the shape change of the magnetostrictive component under an external magnetic field. Here, the size of the interface between the two components plays a crucial role. Therefore, the development of nanomaterials exhibiting large surface-to-volume ratios can help to respond to such a requirement. However, the magnetic nanoparticles (NPs) must be highly magnetostrictive and magnetically blocked at room temperature despite their nanometer-size. We describe here the use of the polyol process to synthesize cobalt ferrite (CoxFe3−xO4) nanoparticles with controlled size and composition and the study of the relationship between size and composition and the magnetic behavior. Methods: We used an improved synthesis of magnetostrictive CoxFe3−xO4 NPs based on the forced hydrolysis of metallic salts in a polyol solvent, varying the fraction x. Stoichiometric NPs (x = 1) are expected to be highly magnetostrictive while the sub-stoichiometric NPs (particularly for x ≈ 0.7) are expected to be less magnetostrictive but to present a higher magnetocrystalline anisotropy constant, as previously observed in bulk cobalt ferrites. To control the size of the NPs, in order to overcome the superparamagnetic limit, as well as their chemical composition, in order to get the desired magnetomechanic properties, we carried out the reactions for two nominal precursor contents (x = 1 and 0.67), using two different solvents, i.e., triethylene glycol (TriEG) and tetraethylene glycol (TetEG), and three different durations of refluxing (3, 6 and 15 h). The structure, microstructure and composition of the resulting NPs were then investigated by using X-ray diffraction (XRD), transmission electron microscopy (TEM) and X-ray fluorescence spectroscopy (XRF), respectively. The magnetic properties were also evaluated using standard magnetometry. To measure the magnetostrictive response of the particles, the particles were sintered to dense pellets on which strain gauges were bonded, measuring the size variation radially, as a function of a dc magnetic field. Findings: We found two samples, the first one being stoichiometric and magnetostrictive, and the second one being sub-stoichiometric and presenting a higher magnetization, that are appropriate to be used as ferromagnetic building blocks in nanostructured magnetoelectric materials, particularly materials based on polymers. We show that the polyol solvent and the reaction time are two key parameters to control the size and the magnetic properties of the resulting nanoparticles. We believe that these results provide relevant insights to the design of efficient magnetic and magnetostrictive nanoparticles that can be further functionalized by coupling agents, to be contacted with piezoelectric polymers.
Detection of botnets mounted on the Session Initiation Protocol

A botnet is a group of compromised computers (called bots) controlled by remote attackers to distribute spam emails, launch denial of service attacks, and perform other malicious activities. Botnets can be deployed on top of different protocols, such as the Internet Relay Chat (IRC), the Hyper Text Transfer Protocol (HTTP), and the Session Initiation Protocol (SIP). The SIP is widely used to initiate voice over IP, and it has been recently adopted by the telecommunications standards bodies to be the signaling protocol for mobile telecommunication core networks. Such adoption will introduce a huge number of potential devices to botnets. Therefore, botnets deployed over the SIP present a serious threat for the Internet. We propose a novel approach to detect SIP botnets by looking for users who behave in similar and coordinated patterns. We show through extensive experimental evaluations that the proposed approach achieves low false positive and false negative rates.
Técnicas de simplificação de redes e otimização multiobjetivo para análise de variações de tensão em regime permanente provocadas por parques eólicos integrados ao sistema elétrico

This study presents a description of the development model of a representation of simplified grid applied in hybrid load flow for calculation of the voltage variations in a steady-state caused by the wind farm on power system. Also, it proposes an optimal load-flow able to control power factor on connection bar and to minimize the loss. The analysis process on system, led by the wind producer, it has as base given technician supplied by the grid. So, the propose model to the simplification of the grid that allows the necessity of some knowledge only about the data referring the internal network, that is, the part of the network that interests in the analysis. In this way, it is intended to supply forms for the auxiliary in the systematization of the relations between the sector agents. The model for simplified network proposed identifies the internal network, external network and the buses of boulders from a study of vulnerability of the network, attributing them floating liquid powers attributing slack models. It was opted to apply the presented model in Newton-Raphson and a hybrid load flow, composed by The Gauss-Seidel method Zbarra and Summation Power. Finally, presents the results obtained to a developed computational environment of SCILAB and FORTRAN, with their respective analysis and conclusion, comparing them with the ANAREDE.
Sequential Frequency-Domain Imaging Algorithm for Near-Field MIMO-SAR With Arbitrary Scanning Paths

This paper presents a sequential algorithm for near-field multiple-input multiple-output synthetic aperture radar (MIMO-SAR) imaging. This method can be decomposed into a reconstruction for MIMO array with the range migration technology and a reconstruction for synthesis aperture with the backprojection technology. Different to the range migration algorithm (RMA), the method does not adopt the Fourier transform along the scanning direction; therefore, it can be used for MIMO-SAR systems with arbitrary scanning paths and can perform imaging during the array scanning. In addition, due to its sequential imaging scheme, the proposed method is conducive to parallel processing and reduces the computational memory consumption. Both theoretical analysis and experimental results show that, compared with the RMA and the backprojection algorithm, the proposed method can achieve the same imaging results but with the lowest computational load.
Text Categorization of Indonesian Language Text Documents using Bracewell Algorithm

With the Internet fast progressing, the number of news documents increases significantly and the demand for easy navigation around the news becomes pivotal. The online news domain needs a classifier that is able to classify news articles accurately at a low cost computation. Apart from that, because it is always updated, the classifier also needs to be able to detect new topic. This paper presents the topic identification and category classification method which enable categorization of news articles and identification of topic as new news arise. During the training phase, keywords are extracted from each document. Then, a document is classified to a predefined category. Lastly, the topic of the document is identified. Testing was conducted on Indonesian news corpus. The result shows that the classifier was able to classified Indonesian text documents with a satisfactory accuracy level as high as 93.84%.
The discursive portrayals of Indonesian Muslims and Islam in the American press: A corpus-assisted discourse analysis

Numerous studies across disciplines on how western media portray Muslims have been conducted in different geopolitical and cultural contexts. However, we still lack research into media constructions of Muslims from a particular country, including Indonesia, which is the most populous Muslim nation. This study aims to analyse the linguistic representation of Indonesian Muslims and Islam in two corpora of American newspapers published in two different five-year periods (2002-2006 and 2012-2016) by using corpus-assisted discourse analysis framework. Keyword, collocation and concordance analyses were employed to reveal dominant discourses of Indonesian Muslims. It was also enriched by critical discourse studies’ commitment to analysing social and political contexts. Some of the findings corroborate and reinforce the results of previous studies on media depictions of Muslims in general, in that the dominant discourses around Islam and Muslims are related to terrorism, fundamentalism, conflict and violence. However, this study also brings forward additional information, including a shift in the discourse. Dominant discourses around Indonesian Muslims in the American newspapers have witnessed a slight change over the 15 year-period from terrorism and extremism to radicalism only. What might be highlighted is that there are extremely few positive media portrayals of either Muslims in general or Indonesian Muslims.
Artistic Impact: From Casual and Serious Leisure to Professional Career Development in Disability Arts

Abstract All forms of arts participation are likely to lead to positive outcomes, but the nature and reach of these outcomes will differ. While arts programs have increasingly found favor in disability communities, these programs historically have been oriented toward therapeutic outcomes. They have not been taken seriously in terms of artistic outputs, the deeper benefits for participants, or potential wider societal impact. At the same time, there is anecdotal evidence of increasingly sophisticated artistic engagement involving artists with disability that are gaining wider public attention, popularity, and enabling a serious leisure experience for the artist with the opportunity for professional artistic career development. This article demonstrates how disability arts projects enable opportunities for casual leisure, serious leisure, and professional artistic engagement and examines the resultant social impact for each. To do this we investigate the characteristics and outcomes of three projects through an abductive research design involving a comparative qualitative case-based approach.
Proceedings of the 37th annual meeting of the Association for Computational Linguistics on Computational Linguistics

This volume contains the papers accepted for presentation at the 37th Annual Meeting of the Association for Computational Linguistics, held at the University of Maryland from 20th to 26th June 1999. As co-chairs, we had two particular objectives for the program this year. First, we wanted to acknowledge the increasing worldwide interest in computational linguistics, and mirror the move towards true internationalism that is underway within the ACL itself. Second, we wanted to reflect the broader connections that computational linguistics has with other research communities by increasing the scope of the material covered. You will see the results of our pursual of these objectives throughout the program and its organisation: the 80 papers collected here for presentation were drawn from over 320 received, with the authors representing 29 countries and the reviewers drawn from 25 countries. The larger-than-usual size of the conference this year is at least in part due to our incorporation of community-proposed theme sessions. In an iteration prior to the call for papers itself, we issued a call for theme session proposals. This was our attempt to break with the somewhat traditional set of paper topic categories that one tends to think of at ACL conferences. As a way of highlighting real areas of topical interest in the community, we think the experiment worked extremely well, despite the inevitable hiccups that accompany the introduction of any new idea. But you can be the judge of this: the ACL executive committee and next year's program chairs will be interested to hear what you think of this innovation.