Reviewerly/exHarmony huggingface dataset:
Pandemia Covid 19: A atuação e mudança de hábitos dos escritórios contábeis e as Experiências do trabalho em home office / Pandemic Covid 19: The Performance and Change of Habits of Accounting Offices and the Experiences of home office work

O presente artigo apresenta uma dissertação sobre os impactos provocados pela Pandemia da Covid 19 nos escritórios contábeis no município de Sertanópolis, Estado do Paraná. O estudo tem como objetivo verificar como a pandemia do covid-19 afetou a rotina do dos profissionais de contabilidade da cidade de Sertanópolis estado do Paraná. O estudo se enquadra como pesquisa quantitativa, com levantamento de dados e opiniões em campo. A coleta de dados foi realizada através de questionário aplicado nos meses de setembro e outubro de 2021. O público desse estudo foi os escritórios de contabilidade no município de Sertanópolis – PR, onde recebemos 16 questionários respondidos. O resultado da pesquisa mostrou que a Pandemia realmente provocou alterações nas rotinas e nos hábitos nas pessoas, de forma que algumas coisas se tronaram muito mais acessíveis e práticas para realização de forma digital, e mesmo que tenha sido de forma rápida e repentina, foi capaz de atingir obrigações da rotina de trabalho de forma remota, trabalhando um lugar com equipamentos e ambientes corretos.Abstract: This article presents a dissertation on the impacts caused by the Covid 19 Pandemic in accounting offices in the municipality of Sertanópolis, State of Paraná. The study aims to verify how the covid-19 pandemic affected the routine of accounting professionals in the city of Sertanópolis state of Paraná. The study is classified as quantitative research, with data collection and opinions in the field. Data were collected through a questionnaire applied in September and October 2021. The public of this study was the accounting offices in the municipality of Sertanópolis - PR, where we received 16 questionnaires answered. The result of the research showed that the Pandemic caused changes in routines and habits in people, so that some things became much more accessible and practical for digital realization, and even if it was quickly and suddenly, it was able to achieve obligations of the work routine remotely, working a place with the right equipment and environments.Keywords: Pandemic; Office; Habits; Home Office.
WEB APPLICATION DEVELOPMENT: RESEARCH OF REGULATORY AFFAIRS IN THE OFFICIAL JOURNAL OF THE UNION

The agricultural industry in Brazil is one of the largest in the world in the consumption of pesticides, in 2016 the country had a consumption of this compound around 300 thousand tons per year.The great demand caused the country to launch 76 new products in this sector only in 2020.During the approval process of an agricultural pesticide, several stages of approval are required before federal agencies such as ANVISA, MAPA and IBAMA, with the Official Diary of Union (ODU) the main portal for consulting the status of the product.The entire approval process for a new product takes time, which can harm the company during the patent, if it does not frequently follow the publications in the ODU.Currently, the Federal Government has free tools for this information to be accessed through web service applications, which is a technology that allows interaction between software regardless of the language used in them and is increasingly used in the industry due to its efficiency, speed and reliability.From this context, the objective of this paper is to develop an application that assists in accessing the ODU data in order to allow agility and better understanding of the approval stages in which the pesticide is, in addition to establishing an overview of the market.Thus, a complete web service will be created with an application programming interface (API) using NODE.js, which will retrieve the data from the ODU and insert them into a Database to be used by a WEB application developed in Angular, allowing the user carry out specific queries about the product being approved.
APPLICATION RESPONSE TIME COMPARISON BETWEEN ETHEREUM SMART CONTRACT AND SQLITE DATABASE

This work aims to evaluate the storing and retrieving data response time using an Ethereum Smart Contract application to verify the feasibility of its utilization instead of using relational databases in web application development.To achieve the objectives of this work.There was a comparison between the Ethereum Smart Contract and the SQLite, considering response time as the user experience for database choice decisions in future application development.This study consisted of the development of two similar applications.The first one was the Ethereum Smart Contract Application, and the other was the SQLite Application.Using these applications to build graphs of response time behavior as the number of records processed grows.For storing data Blockchain application was much faster than the SQLite application.When retrieving data, the Blockchain application usually starts slower but finishes faster than the SQLite application.Blockchain is a recent technology for secure data storage in a distributed architecture.The hypothesis to be checked was if it also has a good response time compared with other databases.The contribution of this work is to provide information about the efficiency and possible user satisfaction of Blockchain applications.
INTERACTIONS BETWEEN FORESIGHT AND KNOWLEDGE MANAGEMENT: PROPOSAL OF A RESEARCH AGENDA

Conduct a systematic literature review associating foresight and knowledge management, aiming to propose a research agenda.Scientific literature draws attention to the need for integration between foresight and knowledge management, with the need for studies on these topics, leaving the subject under explored and under theorized.There are calls for articles on the topic in dominant journals in the area, as well as international conferences.Using a qualitative approach, a systematic literature review was carried out, in which 298 (two hundred and ninety-eight) articles were searched in the Science Direct and Web of Science databases, with the selection of 10 (ten) articles from the last ten years.As a result, the words related to the theme were found: Futures, Strategic, Technology, Intelligence.As for the theoretical frameworks, the constructions of Nascimento et al. ( 2021), Zang & Huang (2020), Shujahata et al ( 2017) and Eerola & Miles (2011).In the research agenda, the application of theories to analyze the relationships between foresight and knowledge management, the constitution of these constructs and the evolution of foresight practices stood out.The work gathered and selected the main articles in the area, generating suggestions for future studies and the compilation of existing theoretical approaches.The article highlights the importance and advantages, for an organization, of carrying out the integration between these two distinct research fields (foresight and knowledge management), favoring innovation and the search for actionable knowledge based on environmental intelligence.
THE VIRTUALIZATION APPLIED IN EDUCATION: THE BENEFITS OF VIRTUALIZATION IN REMOTE AND PRESENTIAL TEACHING

The computational resources are fundamental and convered in the Pedagogical Projects of the courses offered by the Faculdade de Tecnologia de Santana de Parnaíba.In addition to high-performance hardware, the computers need various software such as programming languages, text editors, databases, integrated development environments, simulators and virtualization.With the closing of schools due to the COVID-19 pandemic in 2020, the emergency remote teaching was decreated and practical classes were suspended in all teaching units in Brazil.The lack of practice and these resources, accumulated a learning deficit in several subjects.However, through a remote connection software installed on all computers in the lab, a subject in the Information Security course, it allowed students to take some "practical" classes virtually.The activity was to create a virtual machine with a virtual client and a virtual server to teach and apply in practice to the students the concepts of Microsoft Active Directory, Virtualization was the resource used in all of the computers during this period and will be used in several subjects when classes are returned in person at the Fatec Santana de Parnaíba.In addition to providing several virtual environments, the virtualization contributes to the reduction of new hardware to emulate network environments, the use of only one computer per student as needed for the class, and also contributes to the reduction of energy consumption due to the use of a single computer.For the development of this research, bibliographic research and computers from computer labs were used, in person and remotely.
WEB PORTAL QR CODE: GALLERY OF MUNICIPAL MAYORS OF ITAPETININGA

This undergraduate paper is an initiative for researching, valuing and disseminating the memory and historical heritage of the municipality of Itapetininga/SP that presents to the population the biography and history of public management of former mayors of the Municipality of Itapetininga through a WEB portal with access via QR Code.
A BIBLIOMETRIC ANALYSIS OF THE USE OF GAMES FOR TEACHING SOFTWARE ENGINEERING FROM A SYSTEMATIC LITERATURE REVIEW

Conducting a Systematic Literature Review (RSL) with the purpose of presenting a general assessment of the state of the art regarding the use of games and gamification to assist in teaching Software Engineering.Identify what kind of games and gamified approaches are being used in the Software Engineering teaching process, in addition to identifying which areas of Software Engineering and competences each game or approach aimed to develop in the participants.Systematic Literature Review Through the RSL it was possible to recognize that there is a variety of games that are used for teaching HE, ranging from board games to role-playing games.The RSL results that were presented in this work serve as a foundation for future works that aim to create games or approaches that help in teaching Software Engineering.Show the main trends and ways used to deal with the teaching-learning process of ES with the use of games and gamified approaches.
AFER (AFFECTIVE FACIAL EXPRESSION RECOGNITION) - AN ALGORITHM FOR DETECTION AND AFFECTIVE ANALYSIS OF FACIAL EXPRESSIONS IN HUMAN COMPUTER INTERACTION

This work presents the AFER algorithm to detect and classify emotions through facial expressions, developed by associating computer vision tools (Face Recognition and OpenCV) and psychological studies by Ekman et al. (2002).In this context of technological advancements and the Information Revolution, connecting humans and machines has become imperative.Affective Computing studies show that one of the biggest challenges nowadays is making computers capable of identifying human emotions and, perhaps, understanding them, seeking to strengthen the man-machine relationship.The algorithm captures points on the face, associates them in pairs to represent the muscle movement indicated by each AU, checks if there was movement in such pairs of points to identify whether or not there was visually perceptible change in facial features, to, finally, indicate which emotions was detected.Using computer vision libraries implemented in Python, satisfactory results were obtained after parameter adjustments in the algorithm, achieving recognition of more than 80% in 5 of the 6 analyzed emotions.AFER presents a different proposal from other researched algorithms and tools because it was developed based on FACS knowledge and enables the manipulation, treatment and storage of data obtained through the capture of face landmarks, clearly exposing the way in which such processing was conducted.It also encourages the active and inclusive participation of users whose interaction with the computer needs to go beyond the simple mouse, keyboard and monitor setting, especially in with user experience evaluation processes.
MULTIWORDS EXPRESSIONS IDENTIFICATION THROUGH RECURRENT NEURAL NETWORKS

Propose an alternative method for to identify Multiwords Expressions extracted from documents through Recurrent Neural Network (RNN) model Multiword Expressions could be used to represent the meaning of the document in the more semantic way, in many activities of the natural language processing.We found few researches that use RNN as a method to obtain MWE.It was the definition of the training corpus created within lines classified as bigrams or not, extracted from documents through traditional statistics methods; It was to train the model based on the corpus created; It was to validate the results obtained aim to generalize the process through RNN method.As results we obtained an accuracy around 80,54% in test train to identify bigram in the new documents.We propose the use of machine learning algorithm to generalized the extraction of bigrams in the documents in the specific domain.The idea is to do the information retrieval process to obtain searched documents through of a document rather than using keywords.
BIG DATA MINING: CLASSIFIER PERFORMANCE ANALYSIS

Data mining is a vast field that combines different areas like artificial intelligence, database management, data visualization, machine learning, mathematical algorithms, and statistical techniques.Big data is about large amounts of data coming from a variety of sources such as social networks, sensors, devices, third parties, web applications and social media and in a variety of formats such as text, video, audio, diagrams, images, and combinations of two or more formats.Performing data mining tasks on large-scale data sets, Big Data, is called Big Data Mining, and is considered a complex activity.To perform big data mining tasks, data scales far beyond the capacity of a single computer.The big data mining platform needs to rely on clustered computers on high-performance computing platform.This study aimed to perform a performance evaluation of complex classifiers in a local environment and in a cloud environment, using data mining and distributed processing tools.The methodology used for this research was experimental.The data set used in the experiment were related to Fatec students from the Sorocaba and Indaiatuba campuses, the cloud computing platform used was Microsoft's Azure.5 virtual machines were created to build the cluster.Through this study it was possible to observe that there was an average drop of 66% in the processing time of the classifiers in the cloud in relation to the local machine, it was also possible to stipulate an ideal virtual machine configuration for the analyzed dataset, thus avoiding wasted resources.
IMPACTS OF TECHNOLOGY ON THE ACCOUNTING PROFESSION

This paper aims to point out the impacts that technology has brought to the accounting profession, briefly tracing from the beginning, its evolution, the objectives of this applied social science, which developed along with social, political and cultural transformations over time. .The main point is how technology has provided in practice, what accounting theory has long indicated as its main work, which is to help companies with regard to management and decision-making, that is, intellectual work.It took into account the posture of the modern accountant, the importance of information systems, the starting point for what they call digital accounting, and finally, the accountant's expectation after the pandemic period.In the methodological part, bibliographic and documentary research techniques were applied in order to collect information about a problem, thus constituting a descriptive research.During the pandemic period, Brazil is going through a crisis that goes beyond the health area and has a strong impact on all economic activities, with a direct influence on the mental disposition of each entrepreneur and employee of an organization.This adaptation of the traditional work model to the digital and distance model was observed during the research of this work.Thus, the results achieved the expected objectives when verifying a strong impact of technology on the development of the accounting professional.
Cyclic Implicit Complexity

Circular (or cyclic) proofs have received increasing attention in recent years, and have been proposed as an alternative setting for studying (co)inductive reasoning. In particular, now several type systems based on circular reasoning have been proposed. However, little is known about the complexity theoretic aspects of circular proofs, which exhibit sophisticated loop structures atypical of more common 'recursion schemes'. This paper attempts to bridge the gap between circular proofs and implicit computational complexity. Namely we introduce a circular proof system based on Bellantoni and Cook's famous safe-normal function algebra, and we identify suitable proof theoretical constraints to characterise the polynomial-time and elementary computable functions.
Detection of Fake News Based on Typical Machine Learning Models

With the rapid expansion of the network, the glut of news spread everywhere. Because of the obscurity of news sources and the unrestricted types of viewers, the harmful impact of false news is more pervasive than ever before. The goal of this study is to evaluate the efficacy of five machine learning models, namely Decision Tree, Logistic Regression, Random Forest, Multilayer Perceptron (MLP) and Naive Bayes to detect false news using a dataset obtained from Kaggle. Following the application of five models for predicting false news based on the news' title and comparison of the training and testing accuracies of each model, the results indicate that Random Forest is the best model, with Decision Tree and MLP models also having very high testing accuracies. Surprisingly, the Naive Bayes model, widely recognized as the optimal classifier for text data, had the lowest testing accuracy in this study, implying that more research is required to explain this outcome. Finally, the limits of current machine learning algorithms, as well as the possibility of bias in datasets, provide a good direction for future studies.
Motion Control of Three-Degree-of-Freedom Spherical Actuator Driven by Four-Phase

Spherical actuators have many advantages such as high accuracy due to multiple-degree-of-freedom direct-drive and downsizing by reduction of the number of actuators. However, the conventional spherical actuators have complicated structures and control units. In order to solve these problems, we proposed a three-degree-of-freedom (3DOF) actuator driven by four-phase. The actuator can generate 3DOF motion by a four-phase inverter and four-coil. This paper describes a dynamic modeling and motion control method for the proposed 3DOF actuator. The simulation results showed that the actuator can be controlled in 3DOF by the proposed control method.
M-Health App for Tracking COVID-19 Infected People: A Case Study of Developing Countries

Abstract The impact of the COVID-19 pandemic has led to the use of M-Health apps for tracking COVID-19 infected people.So, the aim of this study was to develop a model that explains the adoption of M-Health apps for tracking COVID-19 infected people in developing countries. We tested the model based on data collected using an online survey with 283 participants. For data analysis , the partial least squares technique was used. The results revealed that the intention to use the Aman application was positively influenced by performance expectancy, social influence, Aman application quality, perceived self-efficacy, facilitating conditions, and perceived credibility. Moreover, it was negatively influenced by the perceived financial cost and the effort expectancy. M-Health apps are found as an approach to fighting COVID-19. Therefore, it is imperative to address the reasons that prevent the use of these apps. The implications of this are discussed.
AUDITOR INDEPENDENCE, AUDITOR ETHICS, AUDITOR EXPERIENCE, AND DUE PROFESSIONAL CARE ON AUDIT QUALITY

Public accountants are exceptionally important to give certainty to clients that the financial statements introduced by the organization can be trusted, but the risk of misstatement will in any case exist despite the fact that it has been evaluated by a Public Accounting Firm. This study expects to analyze the components that influence audit quality that can lessen the risk of misstatement in the presentation of financial statements, specifically auditor independence, auditor ethics, auditor experience, and due professional care. The subject in this study were employees who worked as auditors at the Tangerang’s Public Accounting Firms. This type of research is a causal study with a convenience sampling method. The research period was completed during the Coronavirus pandemic from March to June 2020. The hypothesis test method used in this research is multiple regression analysis. The results of this study are auditor independence does not affect audit quality, auditor ethics does not affect audit quality, auditor experience has positive effect on audit quality, and due professional care has positive effect on audit quality. This research is expected to be a reference in making decisions by auditors based on audit considerations possessed by an auditor to improve audit quality, especially from the experience and due professional care of the auditor.
Building a Knowledge Graph on Video Transcript Text Data

Youtube is a video platform which not only provides entertainment but also education in which knowledge can be dug based on video transcripts. The results of this knowledge can be formed as a knowledge graph to build a knowledge base that saves storage space. Moreover, it can be used for other purposes such as recommendation systems and search engines. Prosen built a knowledge graph using NLP to extract the text by identifying the subject-verb-object (SVO) and stored in the graph database. The construction of a knowledge graph on a Youtube video transcript was successfully carried out. However, there are still obstacles in the process of extracting text using NLP which is less optimal so it is possible that there is still a lot of knowledge that has failed to be obtained.
Price Intelligence Using K-Means Clustering and Linear Regression, Case Study of Store Dk Nutritionindo at Tokopedia

The ability to find the right price recommendation will determine the fate of product sales in the market. This is necessary to prevent whey concentrate products from being sold in the market and to avoid customers fleeing or switching to other competitors. This study uses a price intelligence approach using the k-means clustering method for price grouping based on the closest competitor and demand forecasting using linear regression to determine fair and competitive prices. The results of the k-means clustering price of 145000 from dk nutritionindo are included in C4. The closest competitor has 7 prices cheaper and 5 prices more expensive. The highest price is 495000 and the lowest price is 90000. The results of the 26th month to 33rd month demand forecasting have 2 graphs up and 6 graphs down. Forecasting confusion matrix test produces 62.5% accuracy, 75% precision, 60% recall. With MAPE = 28.95% according to Lewis (1982) then the influence of forecasting is declared feasible (good enough). Because the trend chart illustrates a decline, it is recommended that the shop lowers the price with a recommended price range from 135000 to 90000.
Determining the Target of Independent Graduation for Beneficiary Families of the Hopeful Family Program

The Family Hope Program (Program Keluarga Harapan) or better known as PKH is the conditional social assistance to the Poor Families which are designated as PKH Beneficiary Families. Self-Graduation is one of the goals of the PKH program, Self-Graduation is a condition in which the PKH Beneficiary Families is declared ‘passed’ from PKH participation with their respective awareness. This recommendation system uses the Simple Additive Weighting (SAW) method to calculate the criteria for several website-based alternatives with the Model View Controller concept.