Miracle-dz/UniFAR-FTUs huggingface dataset:
An Enhanced Feature Acquisition for Sentiment Analysis of English and Hausa Tweets

Due to the continuous and rapid growth of social media, opinionated contents are actively created by users in different languages about various products, services, events, and political parties. The automated classification of these contents prompted the need for multilingual sentiment analysis researches. However, the majority of research efforts are devoted to English and Arabic, English and German, English and French languages, while a great share of information is available in other languages such as Hausa. This paper proposes multilingual sentiment analysis of English and Hausa tweets using an Enhanced Feature Acquisition Method (EFAM). The method uses machine learning approach to integrate two newly defined Hausa features (Hausa Lexical Feature and Hausa Sentiment Intensifiers) and English feature to measure classification performance and to synthesize a more accurate sentiment classification procedure. The approach has been evaluated using several experiments with different classifiers in both monolingual and multilingual datasets. The experimental results reveal the effectiveness of the approach in enhancing feature integration for multilingual sentiment analysis. Similarly, by using features drawn from multiple languages, we can construct machine learning classiﬁers with an average precision of over 65%.
Petén, Guatemala, desde la colonización interna hacia migración transnacional: ¿Nuevos paradigmas para el siglo XXI?Petén, from internal colonization to transnational migration: new paradigms for the 21st century

Desde su integración en el Estado guatemalteco, se ha tomado al departamento de Petén como único, un lugar separado con el resto del país en dinámicas socioeconómicas. Con la ¨colonización interna¨ en la segundaparte del siglo veinte, se ha fijado más aún la identidad del petenero, lo cual indica a comunidades tradicionales con generaciones de conocimiento acumulado sobre el manejo de suelos tropicales. Con la creación de la Reserva de la Biósfera Maya, (RBM), quedaron los peteneros como beneficiarios, y el pueblo q’eqchi’ quedó como inmigrante. Primero, este artículo rastrea los cambios en las identidades sociales en Petén, preguntando por qué los peteneros son “como indígenas” y los q’eqchi’s han llegado a ser inmigrantes indígenas. Al hacerlo, rastreé las diferencias entre las agencias nacionales y el tratamiento de las agencias internacionales del pueblo q’eqchi’ y el requerido por las convenciones legales. Segundo, sugiero que el estatus único de Petén debido a su relativo aislamiento está disminuyendo, mientras que su papel de enlace entre México, Guatemala y Belice está aumentando. La participación petenera en migraciones transnacionales señala nuevas épocas con efectos inciertos en tenencia de tierra y conservación ambiental.
Frameworks para implementação do lean construction: uma revisão sistemática da literatura

A indústria da construção enfrenta vários desafios, como a necessidade de reduzir o elevado número de desperdícios, melhorar as condições de trabalho e aumentar sua eficiência. Adicionalmente, nos últimos anos, essa indústria vem sofrendo ainda mais com pressões internas e externas, como crises econômicas, aumento da concorrência e clientes mais exigentes em relação a qualidade dos produtos e prazos de entrega. Essa conjunção de desafios tem estimulado as empresas do setor da construção a buscarem soluções inovadoras para a gestão da produção, tais quais as soluções oferecidas pela Construção Enxuta. Inspirada na Produção enxuta, essa filosofia tem como objetivo a eliminação de todas as formas de desperdício e concomitantemente a promoção da melhoria dos processos das empresas da construção. Apesar de todos os benefícios, a construção enxuta ainda é pouco adotada pelas empresas do setor da construção no Brasil. Uma forma de facilitar a implementação da construção enxuta é a utilização de frameworks ou modelos que possam auxiliar a implementação desta filosofia. Entretanto, apesar da existência de vários frameworks voltados para a implementação da construção enxuta, estudos visando identificar e analisar esses frameworks na literatura internacional são poucos. Nesse sentido, essa pesquisa tem como objetivo realizar uma revisão sistemática da literatura nas bases Web of Science e Scopus, no intuito de mapear e analisar os frameworks para implementação da construção enxuta propostos entre 1992 e 2020. Dentre os resultados obtidos, uma lista com 9 frameworks foram apresentados, discutidos e posteriormente classificados quanto ao objetivo, tópicos abordados e metodologia adotada.
THE INFLUENCE OF STORE ATMOSPHERE ON REVISIT INTENTION AT SHOPPING TOURISM

The tourism sector in Indonesia is growing rapidly, so the level of competition is getting higher. Shopping tourism is as one of the industries that is able to attract tourists must innovate considering the products that are sold are the same and the storeping behavior of tourists is different. This study used SEM-PLS analysis and was conducted on 110 respondents who visited Shopping Tourism in Batu city. The results showed that a well-designed store atmosphere can stimulate positive emotions of tourists, provide comfort when shopping so as to create a memorable experience, and make tourists intend to visit again in the future. This study, not only provides recommendations for creating the right store atmosphere for retailers, but also provides information on understanding the storeping behavior of tourists.
FORM FACTORS AND VOLUME MODELS FOR ESTIMATING TREE BOLE VOLUME OF MAHOGANY AT COMMUNITY FORESTS IN CENTRAL JAVA

Form factors and volume models are often be used in the estimation of tree volumes. However, a few studies have developed and evaluated the accuracy of form factors and volume models for estimating tree volumes of community forests. This study aimed to formulate form factors and volume models and assess their prediction accuracy for estimating tree bole volumes of mahogany at community forests in Central Java. This study used 120 sample trees with diameters of 6–38 cm to formulate artificial and absolute form factors and to develop tree bole volume models. These form factors coupled with bole height and total height were used in simple volume equations. Regression analyses were used to develop volume models using the diameter and total height as predictors. The simple volume equations and volume models' prediction accuracy was evaluated using a cross-validation dataset and independent dataset (30 sample trees). The artificial form factor (0.68 ± 0.11) of mahogany, which was higher than the absolute form factor (0.46 ± 0.09), provided accurate estimates of tree bole volumes when it was used with the bole height instead of the total height. The volume model that uses diameter and total height produced the most accurate estimates, while the volume model that uses diameter alone provided the most practical yet reliable tool for estimating tree bole volumes of mahogany. The results of this study are useful for improving community forest management.
Ecological Approach to the Second Language (L2) Teaching and Nepali English Teachers

Ecological approach to L2 teaching is based on the concept of language ecology. In this ever changing world nothing is static. After so many approaches, methods, views, and ideas, ecological approach has made its appearance on the ELT stage. The approach is new to many Nepali English teachers who equate it with teach­ing ecology through the English language. The present paper explores the origin of the approach, shows differences between ecological approach to L2 (English) from teaching ecology through English, presents situation of language ecology, and ELT in Nepal, and suggests what could be possibly the best ways to teach English in Nepal.
An enhanced online learning environment in the time of COVID-19

The coronavirus has forced educational institutions and universities all around the world to close their doors. There are about 1.2 billion learners outside of educational institutions in 191 nations around the world. To ensure the safety of workers, learners, and educators, the world is currently converting training, learning, and work online to reduce total disease mortality and flatten the infection curve. This paper examines the problems of the existing learning environment and proposes a framework to address them to make the transition to online learning simple, manageable, secure, and effective. Securing private data, forged certifications, payment systems, tracking student behavior, low quality of the learning process, and centralization of authority are all issues that learning environments confront. Educational institutions must build efficient, effective, transparent, immutable, and secure learning environments. We give a comprehensive analysis that introduces research papers that address learning-related concerns. Most of this research has focused on leveraging blockchain technology to improve the learning process while ignoring other crucial technologies such as the semantic web. The semantic web and blockchain will be combined to form a semantic blockchain. The semantic web is being utilized to improve the representation of learning processes based on blockchain, such as annotations, and to enable reasoning, inferences, and queries using SPARQL. In the event of a COVID-19 pandemic, the semantic blockchain will aid educational institutions in improving their learning processes. It is seen as a critical component of the next generation of e-learning systems. The proposed framework for improving the learning process via a semantic blockchain is presented in this paper
Ana Batik Magelang’s Business Development Strategy Based on SWOT and Business Model Canvas

This study aims to analyze Ana Batik's business conditions as one of the MSMEs in Magelang based on the Business Model Canvas (BMC) analysis to develop a business strategy based on a SWOT analysis. The research was developed based on a descriptive qualitative approach. The data used in this study are primary data and secondary data. Primary data were collected through observation and interviews, while secondary data were collected through literature studies. The data that has been collected is analyzed based on the Business Model Canvas (BMC) analysis and the SWOT analysis. The Business Model Canvas (BMC) analysis is used to describe Ana Batik's business conditions, while the SWOT analysis is used to formulate a business development strategy that is applied to the new business model. The results of the data analysis indicate that the appropriate strategy for Ana Batik Magelang's business development is the SO strategy. SO strategies that can be applied are developing products according to fashion trends, using brand ambassadors to attract and increase consumer buying interest, and expand the market to the scope of the global market. By implementing this strategy, it is hoped that Ana Batik Magelang's business can develop and be sustainable.
Proposição de um Sistema de Inferência Neuro-Fuzzy para Segmentação de Fornecedores

O objetivo deste estudo é avaliar a adequabilidade da utilização de sistemas de inferência neuro-fuzzy (ANFIS) no apoio à segmentação de fornecedores. Para isso, foi proposto um modelo de segmentação de fornecedores que combina modelos ANFIS em uma matriz quadrática, baseada em diversos critérios associados às capacidades dos fornecedores e à disposição em colaborar. Posteriormente, 24 topologias candidatas foram implementadas e avaliadas utilizando ANFIS no software MATLAB. Calculou-se o erro quadrático médio (MSE) entre os valores desejados e os valores estimados por cada modelo ANFIS a fim de selecionar as melhores topologias e verificar a acurácia dos modelos. Os resultados fornecidos pelas topologias com menor erro quadrático médio foram analisados por meio de regressões lineares e do cálculo do coeficiente R, indicando uma alta correlação positiva entre os valores desejados e os valores estimados pelos modelos ANFIS. Por último, os resultados dos testes de hipóteses baseados em amostras pareadas indicaram que não houve diferenças estatisticamente significativas entre os valores desejados e os valores estimados, reforçando assim a adequabilidade do modelo proposto no estudo. Diferentemente das abordagens prévias, o modelo proposto possui habilidade de aprendizagem supervisionada, sendo capaz de ajustar alguns parâmetros internos para se adequar ao ambiente de uso com base em dados históricos de desempenho dos fornecedores. Os resultados deste estudo podem ser úteis para auxiliar pesquisadores e desenvolvedores de soluções computacionais na área de segmentação de fornecedores, principalmente por fornecer parâmetros topológicos adequados para obtenção de resultados precisos na aplicação em questão.
Deep Hierarchical Product Classification Based on Pre-Trained Multilingual Knowledge

The customer experience of online shopping is largely contingent on the accuracy of product classiﬁcation. Considering the amount of products and all the possible categories, it is desirable to construct a framework to auto-assign products into correct categories at scale. Machine learning based systems often suffer from poor data quality, such as incomplete item descriptions, adversarial noise in the training data, etc., causing low precision/recall of predictions. To overcome these difﬁculties, we propose a deep hierarchical product classiﬁer based on BERT pretrained knowledge. Additionally, we propose several learning strategies, e.g., bootstrap learning, negative sampling, soft label and semantic augmentation, to capture consistent knowledge hidden behind noisy data to prevent overﬁtting. Experiments on a large data set with different data conﬁgurations prove the effectiveness of the proposed model.
Enabling High-Efficiency Organic Light-Emitting Diode with Trifunctional Solution-Processable Copper(I) Thiocyanate

We report on a low-temperature solution processed trifunctional inorganic p-type semiconductor, copper(I) thiocyanate (CuSCN), as a hole injection/transporting and electron-blocking layer for high-efficiency organic light-emitting diodes (OLEDs). The electroluminescence (EL) characteristics of CuSCN and poly(3,4-ethylenedioxythiophene)-poly(styrenesulfonate) (PEDOT:PSS) based devices were studied with the structure of 4,4′-bis(N-carbazolyl)-1,1′-biphenyl as the host, bis[2-(2-pyridinyl-N)phenyl-C](acetylacetonato)iridium(III) [(ppy)2Ir(acac)] as the green emitter, 2,2′,2″-(1,3,5-benzinetriyl)-tris(1-phenyl-1H-benzimidazole) as the electron transporting layer, and lithium fluoride/aluminum as the cathode electrode. The power efficacies for the CuSCN based devices are found to be 51.7 and 40.3 lm/W at 100 and 1000 cd/m2, respectively, which are 13 and 60% higher than the PEDOT:PSS based counterparts. These are the highest power efficacies ever reported for this particular device architecture. The superior E.
SUST TTS Corpus: A phonetically-balanced corpus for Bangla text-to-speech synthesis

: This paper presents the Shahjalal University of Science and Technology Text-To-Speech Corpus ( SUST TTS Corpus ) , a phonetically balanced speech corpus for Bangla speech synthesis. Due to the advancement of deep learning techniques, modern speech processing researches such as speech recognition and speech synthesis are being conducted in various deep learning methods. Any state-of-the-art neural TTS system needs a large dataset to be trained eﬃciently. The lack of such datasets for under-resourced languages like Bangla is a major obstacle for developing TTS systems in those languages. To mitigate this problem and accelerate speech synthesis research in Bangla, we have developed a large-scale, phonetically-balanced speech corpus containing more than 30 hours of speech. Our corpus includes 17,357 utterances spoken by a professional voice talent in a sound-proof audio laboratory. We ensure that the corpus contains all possible Bangla phonetic units in suﬃcient amounts, making it a phonetically-balanced speech corpus. We describe the process of creating the corpus in this paper. We also train a neural Bangla TTS system with our corpus and obtain a synthetic voice which is comparable to the state-of-the-art TTS systems.
Algorithm for optimal denoising of Raman spectra

Raman spectroscopy has been demonstrated to have diagnostic potential in areas such as urine and cervical cytology, whereby different disease groups can be classified based on subtle differences in the cell or tissue spectra using various multi-variate statistical classification tools. However, Raman scattering is an inherently weak process, which often results in low signal to noise ratios, thus limiting the method's diagnostic capabilities under certain conditions. A common approach for reducing the experimental noise is Savitzky–Golay smoothing. While this method is effective in reducing the noise signal, it has the undesirable effect of smoothing the underlying Raman features, compromising their discriminative utility. Maximum likelihood estimation is a method for estimating the parameters of a statistical model given an available dataset and a priori knowledge of the model type. In this paper, we demonstrate how Savitzky–Golay smoothing may be enhanced with maximum likelihood estimation in order to prevent significant deviation from the ‘true’ Raman signal yet retain the robust smoothing properties of the Savitzky–Golay filter. The algorithm presented here is demonstrated to have a lower impact on Raman spectral features at known spectral peaks while providing superior denoising capabilities, when compared with established smoothing algorithms; artificially noised databases and experimental data are used to evaluate and compare the performance of the algorithms in terms of the signal to noise ratio. The proposed method is demonstrated to typically provide at least a 50% increase in the signal to noise ratio when compared to the raw data, and consistently out-performs two alternative smoothing filters.
Effect of nanoparticles on dielectric, mechanical and thermal characteristics of XLPE/TiO2 nanocomposites

Insulators are required in a power system network to provide ground isolation and mechanical support for line conductors. Different kinds of insulators are being utilized in transmission lines and substations. Many power utilities are now using non-ceramic insulators like Cross-Linked Polyethylene (XLPE) composite insulators. This research aims to develop XLPE nanocomposites for use as power cable insulation in industrial applications. To attain this, XLPE nanocomposites were made with five different loadings of Titanium Dioxide (TiO 2 ) nanoparticles: 0, 1, 3, 5 and 7 weight (wt)% in the presence of a Dicymul Peroxide agent, which is used to minimize nanoparticle agglomeration and enhance compatibility within the polymer matrix. A Scanning Electron Microscope (SEM) was utilized to investigate the structure and distribution of nanoparticles inside the XLPE. The dielectric properties of these developed XLPE/TiO 2 nanocomposites were studied by measuring the AC dielectric strength with a regulated high voltage testing transformer (50Hz). The mechanical properties such as tensile strength and elongation at break were also assessed. The thermal properties of nanocomposites were examined using Thermo Gravimetric Analysis (TGA). When TiO 2 nanoparticles are included in the XLPE matrix, the dielectric strength of XLPE/TiO 2 is shown to be higher than pure XLPE. This indicates that XLPE/TiO 2 nanocomposites have higher dielectric characteristics, with a TiO 2 filler loading of 5 wt% being the best. This might be because TiO 2 nanoparticles have a low surface energy, which prevents them from clustering together. Also, the addition of nano TiO 2 improves the mechanical and thermal characteristics of XLPE nanocomposites. XLPE with 5 wt% nano TiO 2 showed the best improvement in different properties.
Gestão de Desempenho Organizacional e Sustentabilidade do SAD: um Olhar Norteado pela Perspectiva da Revisão Integrativa

O objetivo deste trabalho é analisar a literatura científica a fim de evidenciar como o processo de institucionalização da sustentabilidade do Sistema de Avaliação de Desempenho (SAD) contribui para a Gestão de Desempenho Organizacional. Para tanto, foi realizada uma revisão integrativa com suporte do instrumento de intervenção ProKnow-C para seleção dos 40 artigos que fizeram parte do Portfólio Bibliográfico (PB) base da análise. A análise do PB possibilitou a apresentação da evolução da área de Avaliação de Desempenho (AD); a elaboração do conceito de Gestão de Desempenho Organizacional, que norteou esta pesquisa; e a definição de uma lente denominada Sustentabilidade do SAD. Essas construções viabilizaram a elaboração de uma taxonomia que correlaciona os aspectos da lente com os elementos do conceito norteador. Como principais contribuições da pesquisa, tem-se a apresentação da evolução de um tema maduro na literatura (Avaliação de Desempenho) sob nova perspectiva e com ênfase na integração dos aspectos relacionados à gestão. O desenvolvimento da investigação possibilitou constatar o ‘uso das informações’ como elemento comum e o elo entre a Gestão de Desempenho Organizacional e a manutenção da vida útil do SAD ao promover aprendizagem organizacional, apoiar a comunicação e fornecer embasamento para a tomada de decisão. Foram identificadas lacunas na literatura que direcionaram à elaboração de uma agenda de pesquisas futuras para questões relacionadas à importância da cultura no incentivo do processo contínuo da gestão de desempenho; à relação da aprendizagem organizacional com o contexto e alinhamento estratégico; e à contribuição do fator humano e da cultura para a melhoria contínua do desempenho organizacional. Como palavra final, os autores argumentam que esta investigação oferece uma nova perspectiva orientativa para a Gestão de Desempenho Organizacional.
ACADEMIC CAREER INTERESTS IN ACCOUNTING AND DARK TRIAD: EVIDENCE OF THE BRAZILIAN STUDENTS

Objective: The study aimed at verifying the association between Dark Triad and the interest in activities related to academic career among postgraduate accounting students. Method: The sample consisted of 124 students from postgraduate programs in the Accounting Sciences in Brazil. Data were collected through a survey and submitted to multivariate analysis. Results: The results show that narcissism and psychopathy are related to activities inherent to the academic career, while Machiavellian traits do not exhibit the same association. The lack of correlation between Machiavellianism and academic career activities may be related to the desired academic career profile. Students with narcissistic traits are adept at academic career activities mainly related to research and teaching. Psychopathic traits were not adept at activities related to teaching and extension (service to the external community), which may be related to the lack of empathy, lack of concern related to compliance with rules and insensitivity. Contributions: The study contributes to the gap in accounting research that discusses non-pathological personality traits and career interests, since previous research has demanded attention in view of the objective and subjective issues inherent to the career and, at times, marginalize the relevant activities career choice. In addition, such discussions are presented as an advisory material for HEIs in terms of outlining the performance and interest of future teachers regarding the activities inherent to the academic career.