Reviewerly/exHarmony huggingface dataset:
EASY ASSISTANT: UMA FERRAMENTA DE AUXÍLIO PARA O DESENVOLVIMENTO DE CHATBOTS DE DOMÍNIO ESPECÍFICO

Intelligent systems are mainly linked to the act of bringing more and more support to people. Currently, there is a growing use of elements related to the machine learning capacity, that is, Artificial Intelligence (AI). In AI, chatbots stand out, personalized and virtual agents with a certain emotional and cognitive level, usually employed in collaborative, social or learning systems, in order to offer some service with persistent and strongly relational interaction to users. Developing such an agent is not trivial. A chatbot that provides consistent and immersive communication requires several techniques, sometimes even complex,related to natural language processing, understanding and generation, which involve classification of entities, objectives, among others; also self-healing to avoid conversation inconsistencies and loss of context. Therefore, this work presents a web tool that allows the user to develop, train and customize their chatbot virtual agent. This agent uses two training and response models based on recovery and generative models, built on neurais networks that manipulate a database defined by the user. The tool was tested and evaluated in order to qualify its accuracy, which proved to reach its goals, as well as allow the creation of a personalized chatbot.
Cybersecurity project implementation for resources protection: a case study of the National Narcotics Board

Abstract Cybersecurity is currently being used by government organizations in protecting their resources such as data and assets as well as avoiding catastrophic pollution and the failure of key infrastructure that can harm human health and environment. The increasingly modus operandi of modern drug crime syndicates which utilizing technology to attack the network of the National Narcotics Board (NNB) is a threat and vulnerability for NNB, so NNB must make efforts to mitigate the risk. Research on the implementation of cybersecurity projects at the National Narcotics Board aims to explore information related to the implementation of cybersecurity projects in securing and defending data and information networks at NNB. The research method used is a descriptive approach with qualitative methods through semi-structured interviews and observation. This cybersecurity project provides benefits for data and information protection at NNB, through a cybersecurity monitoring system assisting NNB in monitoring cyber traffic conditions in real-time. From this study, it was found that the factors influencing the implementation of cybersecurity projects that were mapped to critical success factors for information technology projects, namely involvement and effective communication, capability and motivation of the team, capability, and leadership of the project manager, requirements management, clear project objectives, and top-level management support levels.
Supplemental Material for The Similarity-Updating Model of Probability Judgment and Belief Revision

Several different variants of similarity and updating processes were tested in a preliminary explorative analysis only using the data of Study 1.In this preliminary analysis we tested similarity processes separately by fitting them to the first probability judgments in each trial.The best similarity component (the similarity component that is described in the main article) was then used to test several different updating components by estimating the models to both probability judgments in each trial. Similarity processes.In past research various similarity processes have been used to predict probability judgments and we tested the models that could be adapted for our data.We implemented the similarity heuristic by Read and Grushka-Cockayne (2011) as:
FEATURES OF APPLICATIONS OF THE LOTKA-VOLTERRA MODEL IN PROJECT KNOWLEDGE MANAGEMENT

The paper proposes the use of the Lotka-Volterra model for project knowledge management. As input indicators of the model it is proposed to use: the probability that the amount of useful and necessary information will increase (α); the probability that the available useful and necessary information will turn into knowledge (β); the probability that the necessary information will be missing for the formation of knowledge (γ); the probability that to form and increase the amount of knowledge will be enough available useful information and established communication channels at the enterprise during the project (δ); the average initial value of available information from different areas of knowledge for project implementation on a 10-point scale (x); the average initial value of available knowledge from different areas of knowledge for project implementation on a 10-point scale (y). The duration of the project is 100 weeks. The model is implemented using the Python programming language. The influence of input indicators on the maximum level of generated knowledge in its oscillating process during the project implementation is investigated. The establishment of means of communication and the timely receipt of the necessary information have a significant impact on the generated amount of knowledge. An increase of 0.2 for this indicator, compared to situation 2, leads to an oscillating process of knowledge required for project implementation, and achieving their maximum amount at more than 8 points, which is quite high and increases the likelihood of successful project implementation. The study shows that the model "predator-victim" can be used in the knowledge management system of projects in order to increase the likelihood of its successful implementation in a timely manner.
Transmission Mechanism of Monetary Policy Channels and Economic Growth in Ethiopia: Cointegration and Causality Analysis Approach

This paper aims to investigate the relationship between transmission mechanism of monetary policy channel and economic growth in Ethiopia.Johansson co-integration, vector error correction model (VECM), Granger causality test were utilized for a time series data collected from 1972 to 2018.Broad money supply, real effective exchange rate and deposit interest rate have positive and domestic credit has negative effect on real economic growth in the long-run whereas in the short run broad money supply, real effective exchange rate have positive but, domestic credit and deposit interest rate have negative relationship with real economic growth.Real economic growth, broad money supply, domestic credit and real effective exchange rate have bidirectional causality whereas deposit interest rate has one directional causality with real economic growth, broad money supply, domestic credit and real effective exchange rate.Monetary policy transmission mechanisms channels are most important in promoting real economic growth in Ethiopia through creation of modern banking sector, so as to enhance domestic investment, the instrument to increase output per capital and hence promoting economic growth in the long-run.
SCADA-based Self-adaptive Configuration System

This paper proposes an adaptive traffic control system capable of efficiently handling the always changing traffic volume without any changes in the hardware.The system is designed using SCADA (Supervisory Control and Data Acquisition) for easy control and access of the historic sensor values.This system can be operated in two modes, one is the traditional mode of operation of the traffic signals and the other is based on machine learning prediction method.The system is also powerful enough to handle multiple junctions and can show the status of the sensors in real-time on the SCADA console.Using this system problems like congestion can be reduced in order to provide smooth flow of traffic.
Determinants of Deposit Mobilization of Commercial Banks in Ethiopia

The aim of this study is to assess the determinant of deposit mobilization in reference to Commercial banks in Ethiopia.The study adopts explanatory research type.The study was also guide by pure quantitative research approach.The necessary data required for this study was secondary data.The secondary data was the audited financial statement for the period of 2005 to 2017.The data was collected from the National Bank of Ethiopia and ministry of finance and economic development (MOFED).The study used non probability sampling, through purposive method in order to take sample size.Currently, there are 18 Commercial banks with their respective branch operation in Ethiopia.The researcher base on their year of establishment considering that, the bank that operates long life expected to have large number of customer and deposit amount than that of new one.Thus, seven Commercial Banks was taken as sample namely, Commercial bank of Ethiopia, Awash International Bank S.C, Bank of Abyssinia S.C, Wegagen Bank S.C, United Bank S.C, Nib International Bank S.C, and Dashen Bank S.C .Data was analyzed using descriptive statistical techniques like mean, standard deviation, minimum and maximum.The correlation analysis is also used.Fixed effect Econometric model was adopted.The result shows that number of branch (NOBR) had positive and significant effect on deposit mobilization (DM) of Commercial banks in Ethiopia.This result may indicate that increase in number of branch was increase the accessibility of bank service, therefore the more banks accessible the more customers was access and as the same time the more deposits was collected.Saving Deposit Interest Rate (IR) had positive and significant effect on DM of Commercial banks in Ethiopia.Loan to Deposit Ratio (LDR) had positive and significant effect on deposit of Commercial banks in Ethiopia.This result implies that when the amount of loan is high there is high amount of money is circulated in the country.Inflation Rate (INF) had a negative and insignificant effect on DM of Commercial banks in Ethiopia.Gross Domestic Product (GDP) had a negative and insignificant effect on DM of Commercial banks in Ethiopia.This is because of the absence of favorable economic conditions in our country.And also inconsistent increase of GDP in the country during the study period was negatively affect Commercial bank deposit in Ethiopia.
Energy consumption information census mode and tool design based on data acquisition network

In order to grasp the accurate energy consumption information, promote the optimization of social energy consumption structure and help achieve the "double carbon" goal, this paper proposes a "new method and new tools" customer energy consumption information census mode based on the data acquisition network. Adopt the combination of centralized census and normal census, and the combination of energy consumption information and system construction. Based on the existing information system, with the transformation of sg186 marketing business application system, combined with the construction of three-party census tools at mobile operation end, wechat applet and PC end, a flexible and available energy consumption information acquisition system is constructed. The general census mode of customer energy consumption information described in this paper can provide application reference for customer side energy consumption information collection and management.
The Integrated Augmented Reality and Google Scholar as the Test Instrument to Improve High Order Thinking Skills and Digital Literacy Skills

Abstract&#x0D; Evaluation instruments in the student learning process in interactive, fun, challenging, motivating, and developing students 'creativity and independence are needed to improve students' High Order Thinking Skills (HOTS) and digital literacy skills (DLS). HOTS and digital literacy are part of the 21st-century skills that are important for every individual. This study developed a test instrument integrated with Augmented Reality (AR) and Google Scholar (GS) to encourage HOTS and students' digital literacy skills. This type of research was development research. The subject matter was the scale and comparison. Product trials were applied to 11th-grade students in Sleman, Indonesia. Product validity was based on expert judgment, item validity, distinguishing power, difficulty level and reliability. AR was created using the ARLOOPA application operated with android. The research instrument was designed to increase HOTS and DLS.
Geochemical and morphological evaluation of indicator mineral anomalies in Northeastern Utah and Southwestern Wyoming, USA

Minerals of upper mantle origin occur in conglomerates, pediments and on antmounds in the southern Green River Basin.Chrome-bearing pyrope, pyropealmandine, diopside, spinel and pircoilmenite 6 mm in size are found on antmounds with similar minerals as large as 12 mm in diameter in the Bishop Conglomerate.These minerals are part of the kimberlite indicator mineral suite, because their presence in secondary environments commonly indicates a nearby kimberlitic source (Gurney et al., 1993).
A Study on the Intention of Production Planning of Vocal Reality Programs by Broadcasting Company

Vocal reality programs are used as a gateway to the trend of certain music genres and stars, and in order to succeed in the long run, it is important to develop them into new and specialized programs through more diverse production methods. This paper studied the direction of production of vocal reality programs by broadcaster and was studied with the aim of providing information to enable formatting of various programs with a fixed production element called vocals. The research method presented various vocal reality programs' planning, production intentions, and formats through analysis of related literature, and selected programs that could confirm their intentions from the vocal reality programs produced until December 2020. First of all, the terrestrial broadcasting channel was formatted as an interesting and fun-oriented program for all ages to enjoy, and as a result, stable operation was possible. &quot;Second, the 'comprehensive programming channel' was relatively specific to the participants and music genres, and it was broadcast in the long term through a recess if it was a popular program.&quot; Finally, the 'cable channel' produced a program with a competitive structure that caused tension.An analysis has been derived that '. This paper has limitations because the derivation and change of vocal reality programs are produced within the same broadcasting company, and suggested that the creation and change process of vocal reality programs could be expanded to various perspectives.
The Main Directions of University Professors' Research-Oriented Activity

The willingness to organize and carry out academic research, gain new knowledge and apply it into practice should become a distinctive feature of any modern and creative university lecturer. The federal state higher education standards oblige faculty members to possess research competencies. The research-oriented activity of a university lecturer implies that scientific and pedagogical search become an integral part of lecturers’ professional practice. The following directions of research-oriented activities can be distinguished within the framework of higher education: publication activity, network research interaction, integrated research in various scientific areas, participation in scientific events, academic advising for young scientists; supervision over students' research activity etc. This research is aimed at identifying problems that a university faculty member faces when organizing and carrying out scientific and pedagogical work as well as using new knowledge, which should become a condition for the faculty member's competitive advantage and the basis for their research-oriented activities.
Peridotite xenoliths from Udachnaya kimberlitepipe

Speculation on the composition and structure of cratonic lithosphere must be constrained by bulk analyses of large xenoliths.Those of sufficient size to provide suitable analytical samples are rare, but a suite of forty-one has been collected at Udachnaya.These include spinel facies peridotites, coarse low-temperature garnet peridotites and high-temperature sheared lherzolites and harzburgites.Bulk analyses have been carried out on samples that are predominantly in excess of 300 grams and these are combined with electron probe analyses to provide modes.
Training of Teaching Staff for Education System of Students with Disabilities: Problems and Prospects

The purpose of the study is to identify the resources of Surgut State Pedagogical University (SurGPU) in teaching staff training for the education system of students with disabilities. The analysis of native and foreign experience allowed defining a number of problems and leading ideas in teaching staff training for the education system of students with disabilities and revealing the regional experience in speech pathologists training in SurGPU. The methodological framework of the research is in axiological, competency-based, system-activity and technological approaches. The above indicated approaches provided the basis for the development and introduction of training system of pedagogical staff for educating students with disabilities and its mechanisms: implementation of directions and orientations providing the professional competency formation in pedagogical, psychological and pedagogical, social educations; provision of interdisciplinary integration of disciplines of general professional and subject training for the work with students with disabilities; presence of special department of pedagogical and special education; interaction realization of higher-education institution, educational institutions and the Regional resource centre of educational technologies in work with students with disabilities; future teachers participation in leading forms of social and pedagogical practices.The obtained results allow talking about high indices achievement in training system of future educators for educational process organization with students with disabilities, define the increase of students’ interest level in personal and professional growth, motivation increase to mastering general cultural and professional competences. That all proves the efficiency of our suggested mechanisms of professional staff training for education system of students with special educational needs.
Nonlinear Feedback Control

Since pneumatic systems, commonly powered by compressed air or compressed inert gases, provide a lower cost, more flexible, or safer alternative to electric motors and actuators, this field has drawn lots of attentions [1]. Especially in pneumatic robots, flexibility of dexterous robot hands plays an important role in space exploration, industrial manufacture, and service robot industry.
A Service Support for Selection of E-Journal Subscription: An Evidence-Based Practice

The selection of an e-journal title is one of the challenging tasks for librarians in the process of collection development. As libraries receive a limited budget, librarians need to be careful and carry out thorough analysis based on the evidence-based approaches in selecting which e-journal to be subscribed. One of the different ways to analyse user demand for e-journals is to analyse access denied reports or known as turn-away reports from publishers. This study reports on how a support service was developed to select a new e-journal subscription for the National University of Malaysia (UKM) Library based on the COUNTER Journal Report (JR2). From this report, the number of access denied to full-text articles from four main commercial online databases; Science Direct, Springer Nature, Wiley Online Library, and Taylor &amp; Francis were analysed. The Pareto Principle method was used to analyse e-journal titles that received high demand from library users. Profiling the journal's coverage in Scopus, Web of Science (WoS), and Journal Citation Reports (JCR) as well as mapping their subject and publisher's price was carried out. The results showed that from a total of 7,474 e-journal titles, 1,495 (20%) e-journal titles that received 132,008 (68%) number of access denied were selected for further analysis. This evidence service can help the Journal Unit, UKM Library in a selection of new e-journal titles based on library users' needs and assist the library management to make better decisions for e-journal subscriptions.
SPA-GCN: Efficient and Flexible GCN Accelerator with Application for Graph Similarity Computation

While there have been many studies on hardware acceleration for deep learning on images, there has been a rather limited focus on accelerating deep learning applications involving graphs. The unique characteristics of graphs, such as the irregular memory access and dynamic parallelism, impose several challenges when the algorithm is mapped to a CPU or GPU. To address these challenges while exploiting all the available sparsity, we propose a flexible architecture called SPA-GCN for accelerating Graph Convolutional Networks (GCN), the core computation unit in deep learning algorithms on graphs [1]. The architecture is specialized for dealing with many small graphs since the graph size has a significant impact on design considerations. In this context, we use SimGNN, a neural-network-based graph matching algorithm, as a case study to demonstrate the effectiveness of our architecture. The experimental results demonstrate that SPA-GCN can deliver a high speedup of 18.2x compared to the multi-core CPU implementation of Pytorch Geometric (PyG) library and 26.9x with respect to its GPU implementation, showing the efficiency of our design.
Unsupervised Query-Focused Multi-document Summarization Using uSIF Sentence Embedding Model and Maximal Marginal Relevance Criterion

Extractive query-focused multi-document summarization provides a substitute summary for a collection of documents, by ranking sentences according to their relevance to a pre-given query. In the current study, we propose a novel unsupervised method for query-focused multi-document summarization based on uSIF sentence embedding model and maximal marginal relevance (MMR) criterion. uSIF model is exploited to represent the documents’ sentences and users’ queries into dense vectors that capture the semantic relationships among multiple words and phrases. MMR criterion is used to re-rank sentences by maintaining query relevance and minimizing redundancy. The proposed method is simple, efficient, and requires no labeled training data. Experiments on the three DUC’2005-2007 benchmarks assess and confirm the effectiveness of the proposed method. The obtained results using ROUGE metrics show that the proposed method outperforms several state-of-the-art systems, including complex deep learning-based systems.