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Experiments on Kaldi-Based Forced Phonetic Alignment for Brazilian Portuguese 1

10th Brazilian Conference on Intelligent Systems, BRACIS 2021

作者： Batista, Cassio Neto, Nelson Computer Science Graduate Program FalaBrasil Group Federal University of Pará Augusto Corrêa 1 Belém66075–110 Brazil

ISBN: (数字)9783030916992

ISBN: (纸本)9783030916985

Forced phonetic alignment (FPA) is the task of associating a given phonetic unit to a timestamp interval in the speech waveform. Phoneticians are able mark the boundaries with precision, but as the corpus grows it becomes infeasible to do it by hand. For Brazilian Portuguese (BP) in particular, only three tools appear to perform FPA: EasyAlign, Montreal Forced Aligner (MFA), and UFPAlign. Therefore, this work aims to develop resources based on Kaldi toolkit for UFPAlign, including their release alongside all scripts under open licenses;and to bring forth a comparison to the other two aforementioned aligners. Evaluation took place in terms of the phone boundary metric over a dataset of 385 hand-aligned utterances, and results show that Kaldi-based aligners perform better overall, and that UFPAlign models are more accurate than MFA’s. Furthermore, complex deep-learning-based approaches did not seem to improve performance compared to simpler models. © 2021, Springer Nature Switzerland AG.

关键词： Acoustic Modeling

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Multi-Resonant Class-E2 DC-DC Converter based on Voltage-Controlled Oscillator

Multi-Resonant Class-E2 DC-DC Converter based on Voltage-Con...

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IEEE Kansas Power and Energy Conference

作者： Lucas Sangoi Mendonça Valmir de Oliveira Academic Department of Electronics Federal University of Technology-Paraná Curitiba Brazil Academic Department of Electronics Graduate Program in Electrical and Computer Engineering Federal University of Technology-Paraná Curitiba Brazil

ISBN: (数字)9798350372403

ISBN: (纸本)9798350372410

This paper shows the design and implementation of a multi-resonant Class-E 2 DC-DC converter based on voltage- controlled oscillator. By cascading a Class-E inverter to a Class-E rectifier, a double soft-switching converter is obtained, in which, the active switch turns-on with zero voltage switching and the diode turns-off with zero derivative voltage switching. This work relies on design equations based on normalized charts that relate the resonant frequency to the current transfer function, quality factor and peak values for the switch variables. In order to activate the switch, a circuit scheme is proposed based on a voltage-controlled oscillator connected to a low-side gate-driver. Therefore, it is not necessary to use a microcontroller neither auxiliary power sources. Experimental results are presented to show the feasibility of the proposed converter.

关键词： Q-factor Voltage-controlled oscillators Transfer functions Resonant frequency Rectifiers Switches DC-DC power converters

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Delayed Matching to Sample by Adolescents With and Without Intellectual Disabilities: Memory and Intellectual Disability

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Trends in Psychology 2023年第2期31卷 286-306页

作者： de Oliveira Teixeira, Isabela Postalli, Lidia Maria Marson Aggio, Natalia M. Federal University of Sao Carlos (UFSCar) Washington Luis Highway Km 235 SP Sao Carlos Brazil Department of Psychology Graduate Program in Special Education Federal University of Sao Carlos (UFSCar) Washington Luis Highway Km 235 SP Sao Carlos Brazil National Institute of Science and Technology On Behavior Cognition and Teaching (INCT-ECCE) MG Belo Horizonte Brazil Department of Psychological Basic Process Graduate Program in Behavior Sciences Universidade de Brasília (UnB) Brasília Brazil

This study investigated the effect of different delay intervals, in identity and arbitrary conditional discrimination tasks with unfamiliar stimuli on adolescents with and without intellectual disabilities and described their problem-solving strategies. The procedure consisted of pretraining, identity training, and arbitrary relations through a matching-to-sample (MTS) task and delayed matching-to-sample (DMTS) tests (0, 2, 4, 6, and 8 s). The results showed that all participants learned identity and arbitrary MTS relations, although two of them required additional procedures. In the DMTS tests, results showed that increasing delays led to a more accentuated decrease in participants’ performances for those with intellectual disabilities, and that performance was worse for arbitrary relations than for identity conditional relations. Naming the stimuli was the main strategy used to complete the tasks. Overall, all participants without intellectual disabilities reported the strategies used, and participants with intellectual disabilities were not able to report the strategy or needed specific questions to describe it. © 2023, Associação Brasileira de Psicologia.

关键词： Adolescent Conditional discrimination Delayed matching-to-sample (DMTS) Intellectual disabilities Memory

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Automatic Speech Recognition in Indonesian Using the Transformer Model

Automatic Speech Recognition in Indonesian Using the Transfo...

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International Conference on Informatics, Multimedia, Cyber and Information System (ICIMCIS)

作者： Ilvico Sonata Computer Science Department Binus Graduate Program Computer Sciiene Bina Nusantara University Jakarta Indonesia

Automatic Speech Recognition (ASR) is useful for converting speech into text. ASR is needed to display automatic subtitles on movies or when conducting video conferencing. The use of deep learning in ASR applications is currently still dominated by Long Short-Term Memory (LSTM) and Recurrent Neural Network (RNN). Several previous studies used the Transformer deep learning model in building the ASR model. The accuracy results obtained are better than the LSTM or RNN models. However, ASR research using the Transformer model is still very limited. This paper will discuss the use of the Transformer model for ASR in Indonesian. The dataset used is the Indonesian language private speech dataset. The experimental results show that the Word Error Rate (WER) and Character Error Rate (CER) produced by the proposed model using the Indonesian language primary dataset are almost the same as using the English language public dataset where the resulting WER and CER are 27.34 and 7.96 for Indonesian and 25.28 and 6.02 for English.

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Explainable Tree-Based Boosting Algorithms for Smoker Detection Using Bio-Signals

Explainable Tree-Based Boosting Algorithms for Smoker Detect...

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International Seminar on Research of Information Technology and Intelligent Systems (ISRITI)

作者： Jason Sebastian Sulistyawan Kuncahyo Setyo Nugroho Bens Pardamean Computer Science Department BINUS Graduate Program Master of Computer Science Bina Nusantara University Jakarta Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9798331519643

ISBN: (纸本)9798331519650

Many smoking-related diseases are difficult to treat and often fatal. Rather than treating diseased smokers, preventing the diseased is more achievable, though, many of them deny to being smokers, leading to another problem. Thus, this study aims to detect important aspects that can detect that the person is a smoker or not through their bio-signals through using SHAP, along with a comprehensive analysis of the used methods, gradient-boosting algorithms XGBoost, LightGBM, and CatBoost, known for their efficiency in handling complex datasets and non-linear relationships. The study then found that triglyceride, Gtp, hemoglobins significantly affect the body's responses to smoking, based on the CatBoosts’ results, having an AUC score of up to 0.8612 and an accuracy score of up to 0.7776 with the selected features.

关键词： Seminars Measurement Accuracy Predictive models Feature extraction Boosting Physiology Classification algorithms Reliability Diseases

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Larvicidal activity of terpenes and their derivatives against Aedes aegypti: a systematic review and meta-analysis: Larvicidal activity of terpenes and terpenoids

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Environmental science and Pollution Research 2024年第56期31卷 64703-64718页

作者： de Almeida Teles, Ana Cristina dos Santos, Beatriz Oliveira Santana, Elaine Carvalho Durço, Aimée Obolari Conceição, Lino Sérgio Rocha Roman-Campos, Danilo de Holanda Cavalcanti, Sócrates Cabral de Souza Araujo, Adriano Antunes dos Santos, Márcio Roberto Viana Health Science Graduate Program Federal University of Sergipe Hospital Universitário S/N R Cláudio Batista Sanatório SE Aracaju49060-108 Brazil Department of Pharmacy Federal University of Sergipe Marcelo Deda Chagas Avenue S/N Rosa Elze SE Sao Cristovao49107-230 Brazil Department of Physiology Federal University of Sergipe Marcelo Deda Chagas Avenue S/N Rosa Elze SE Sao Cristovao49107-230 Brazil Federal University of Sergipe Marcelo Deda Chagas Avenue S/N Rosa Elze SE Sao Cristovao49107-230 Brazil Department of Physical Therapy Federal University of Sergipe Hospital Universitário S/N R Cláudio Batista Sanatório SE Aracaju49060-108 Brazil Department of Biophysics Federal University of São Paulo Rua Botucatu 740 Vila Clementino SP São Paulo04023-062 Brazil

Aedes aegypti (Diptera: Culicidae) is the primary arthropod vector responsible for the transmission of dengue, which is present in more than one hundred countries. The application of synthetic larvicides is one of the most common strategies used for dengue control, but their prolonged use can cause larvicide resistance or tolerance, environmental damage, and have toxic effects on human and animal health. Thus, faced with this problem, there have been increasing efforts to find alternative larvicides against Ae. Aegypti. This search has been mainly focused on naturally occurring chemical compounds, driven by the evidence of their potential effectiveness, and by a desire to find more sustainable, environmentally friendly, and safe alternatives to synthetic larvicides. Thus, the present study aimed to review the effects of terpenes and their derivatives on mortality of the Ae. aegypti larvae, focusing mainly on a lethal concentration of 50% (LC50), in addition to summarizing information on its mechanisms of action and effects on non-target organisms. We searched the main databases for studies published up to April 2024 using relevant keywords, and data were extracted and analyzed qualitatively and quantitatively. Twenty-one articles describing 69 different terpenes and derivatives met the criteria of the review and meta-analysis. Among them, 76.8% were terpenoids and 23.2% terpenes. The LC50 ranged from 0.4 to 1628.2 ppm. The present review and meta-analysis showed that the terpenes and terpenoids can be promising chemical templates for use in eco-friendly larvicides against Ae. aegypti. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： Invertebrates

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Empowering Urban Accessibility: A Prototype System for People with Disability

Empowering Urban Accessibility: A Prototype System for Peopl...

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International Conference on Advanced Learning Technologies (ICALT)

作者： Arlley Dos Santos Costa Luis Carlos Costa Fonseca Sofiane Labidi Graduate Program in Computer and Systems Engineering State University of Maranhão – UEMA São Luís Brazil Bachelor of Science and Technology Program -BICT Federal University of Maranhão – UFMA São Luis Brazil

ISBN: (数字)9798350362053

ISBN: (纸本)9798350362060

This work demonstrates the development of a prototype system that could improve urban and digital accessibility for People with Disability - PwD. The research involves using an academic questionnaire to enable a wider perspective of the central subject and assessing the effectiveness of the proposed solution. The main goal is to help social integration and make the future solution implementable for smart cities through an experiment in an academic campus. The dissertation is related to technological and social issues that might be used as a resource by researchers, public or private bodies interested in more profound studies. The document recognizes the lack of studies on this subject, especially in Brazil because there are few available articles. The prototype system is designed to tackle the issues faced by persons with disability in urban settings through platforms, applications and mobile phones as it proposes a comprehensive set of solutions when addressing accessibility for PwDs. In turn, this research fosters knowledge advancements in the field of urban accessibility and provides vital recommendations for developing inclusive technologies and policies.

关键词： Smart cities Prototypes People with disabilities Mobile handsets

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Tree Counting with Deep Forest Algorithm for Kulon Progo District in Yogyakarta, Indonesia Using Pleiades Satellite Imagery

Tree Counting with Deep Forest Algorithm for Kulon Progo Dis...

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ICT Conference (AICTC), Arab

作者： David Wijaya Ibrahim Seto Aditama Stanley Armando Austen Calvin Surya Widjaja Bakti Amirul Jabar Edy Irwansyah Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia Computer Science Department School of Computer Science Bina Nusantara University Tangerang Selatan Indonesia Computer Science Department School of Computer Science Bina Nusantara University Bandung Indonesia BINUS Graduate Program Master of Computer Science Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9798350342086

ISBN: (纸本)9798350342093

Trees are one of the most important living things on the planet. Trees help by being one of the largest producers' oxygens on planet, by absorbing groundwater and by maintaining soil fertility. Trees can also be one of the keys to reducing existing air pollution. Therefore, the number of existing trees must be maintained. The first step in maintaining the number of existing trees is to count or map them. One of the easiest ways is to do this use an algorithm. This study uses a tree-counting algorithm called Deep Forest. Deep Forest is a Python package that can detect trees through RGB satellite imagery. This study used satellite imagery from Pleiades on an area in Kulon Progo district, Yogyakarta, Indonesia for the image-one of the four regencies within Yogyakarta Province in Indonesia. In addition to the Deep Forest algorithm, this research also used an application provided by Esri called ArcGIS Pro. With this application, data preprocessing such as labeling the data and creating the deep learning dataset for research is much easier, while ArcGIS Pro provides tools for labeling and exporting the data to jupyter notebook. The result obtained using the Deep Forest algorithm is the F1 score with an accuracy of 0.76 for the first experiment, 0.774 for the second experiment, and 0.779 for the final experiment.

关键词： Deep learning Training Codes Planets Vegetation Soil Regression analysis Satellite images Labeling Random forests

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Implementation of Fine-Tuned BERT for Enzyme Classification Based on Gene Ontology

Implementation of Fine-Tuned BERT for Enzyme Classification ...

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International Conference of Advanced Informatics: Concept, Theory and Application (ICAICTA)

作者： Matthew Martianus Henry Christian Kenneth Bens Pardamean Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9798331520311

ISBN: (纸本)9798331520328

Enzymes are biocatalysts with vital roles in biological functions and many industrial applications. Diverse enzymes are classified using Enzyme Commission (EC) nomenclature, making differentiation challenging. On the other hand, another biological information, gene ontology (GO), can describe the biological aspects of enzymes, covering related biological processes (BP), molecular functions (MF), and their locations within cells (CC). This study proposes a novel EC class and subclass classification of enzymes within the ontology subclass based on their GO semantics using a Bidirectional Encoder Representation of Transformer (BERT). The BERT model is first fine-tuned using the preprocessed GO term name and definition, with the enzymes in each ontology class (BP, MF, or CC) are also divided based on how the GO assigned, either through manual annotation (NONIEA) or electronically inferred (IEA). BERT successfully obtained 0.93, 0.60, 0.99, 0.90, 0.40, and 0.35 F1 scores during fine-tuning for BP IEA, BP NONIEA, MF IEA, MF NONIEA, CC IEA, and CC NONIEA, respectively. On the test set, the fine-tuned BERT significantly outperformed GOntoSim, a framework to calculate semantic similarity based on classical information theory, in EC class classification across all metrics with less inference time in all ontology subclass. Expanded further to the EC subclass, BERT can classify the enzyme on the EC subclass level in BP IEA and MF IEA ontology subclass. However, longer epochs are needed in fine-tuning. This result shows that the names and definitions of GO terms are distinguishable features in classifying enzymes as an alternative to the information content approach.

关键词： Measurement Enzymes Semantics Bidirectional control Manuals Ontologies Transformers Encoding Biological information theory Informatics

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Development of an air quality station using low-cost sensors

Development of an air quality station using low-cost sensors

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Brazilian Symposium on Computing System Engineering (SBESC)

作者： Mateus Maruzka Roncaglio Edson Tavares de Camargo Leila Droprinchinski Martins Marcio Seiji Oyamada Graduate Program in Computer Science State University of Western Paraná (UNIOESTE) Cascavel Brazil Federal Technology University of Paraná (UTFPR) Toledo Brazil Federal Technology University of Paraná (UTFPR) Londrina Brazil

Air pollution is one of the most important health problems causing various diseases. According to the World Health Organization (WHO), it is estimated that more than 7 million deaths are due to air pollution. For this reason, air quality monitoring is an important indicator for guiding public policy. However, government stations are widely scattered and their high cost makes it unprofitable to invest in higher resolution. Low-cost air quality monitoring sensors can overcome this problem, but also bring new challenges. This paper presents the development of a low-cost air quality monitoring device. The low-cost station collects the following measurements: carbon monoxide (CO), nitrogen dioxide (NO 2 ), sulfur dioxide (SO 2 ), ozone (O 3 ), and particulate matter. The collected data is corrected using a machine learning model and sent to the Internet in real time via the LoRaWAN protocol. Mean square error (MSE), root mean square error (RMSE), mean absolute error (MAE), linearity coefficient (R 2 ), and Pearson r were used to compare model performance. Our results show that linear models such as the Alphasense equation and linear model regression cannot accurately describe the sensor response to the reference gas sensor, whereas the RF model performs better in each metric. The performance of the RF model demonstrates the potential to improve air quality monitoring and the decision-making process.

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