Reviewerly/exHarmony huggingface dataset:
Argumentation as a Speech Act: A (Provisional) Balance

This paper investigates whether, and if so, in what way, argumentation can be profitably described in speech-act theoretical terms. I suggest that the two theories of argumentation that are supposed to provide the most elaborate analysis of it in speech-act theoretical terms (namely van Eemeren and Rob Grootendorst’s Pragma-Dialectics and Lilian Bermejo-Luque’s linguistic normative model of argumentation) both suffer from the same two flaws: firstly, their “illocutionary act pluralism” assumption and secondly, a lack of interest in where arguing belongs in the classification of illocutionary acts. I argue that these flaws derive from the authors’ reliance on an intention-based speech-theoretical framework. Finally, I adopt a deontic framework for speech acts in order to propose an alternative way of accounting for argumentation which seems to overcome the two limitations outlined above. According to this framework, argumentation may be conceived as a speech act sequence, characterized by the conventional effects brought about by the communicative moves (as illocutionary acts) of which it is composed.
Study on Product Opinion Analysis for Customer Satisfaction on E-Commerce Websites

The E-commerce websites have been emerged in a high range of marketing benefits for the users to publish or share the experience of the received product by posting review that contain useful comments, opinions and feedback on the product. These days, a large number of clients acquire freedoms to look at comparative items in online sites and pick their top choices in computerized retailers, like Amazon.com and Taobao.com. Client audits in online media and electronic trade Websites contain important electronic word data of items. Sentiment Analysis is broadly applied as voice of clients for applications that target showcasing and client care. Sentiment extractors in their most essential structure classify messages as either having a good or negative or once in a while neutral supposition. A typical application of sentiment investigation is the programmed assurance of whether an online review contains a positive or negative review. Subsequently, in this paper, with the use of the strategies on sentiment analysis, obstinate sentences alluding to a particular element are first recognized from item online audits. We have proposed deep learning strategy as a classification model for discovering the condition of review. The outcomes showed suggested site for the client dependent on the early audits, past reviews and answer given to inquiry audit for the client. Additionally, it is seen that the proposed strategy can ready to answer every one of the reviews with a superior closeness like a human reaction to the client.
An Analysis of Several Concepts of Virtualisation

The abstraction of computer resources is referred to as virtualisation.The goal of a computing environment which is virtual is to enhance source efficiency with supplying users and programs with a single integrated operating platform depending upon on the accumulation of dissimilar and self-sufficient assets.Virtualisation at whole levels (network, storage and system) has lately resurfaced with means of improving security of system, dependability, and accessibility, lowering prices, and increasing versatility.Virtualisation" may be defined as environment with virtual machine which offers "sufficient demonstration of fundamental hardware to enable host operating systems to operate devoid of alteration.This article covers the fundamentals of system virtualisation, as well as the benefits and drawbacks of virtualisation, as well as taxonomies and difficulties.
Overview of Big Data and Natural Language Processing: A Powerful Combination for Research

Over the years, there has been a remarkable interchange between Big Data and Natural Language Processing (NLP) with insights from different computer science field enhancing the development of theory, methodology, and resources. Due to the in-constructed multifaceted nature of normal dialects, numerous regular language errands are not well modeled for scientifically characterized algorithmic solutions. To maintain a strategic distance from this issue, statistical machine learning (ML) approaches are utilized. The rise of Big Data empowers another paradigm for taking care of NLP issues dealing with the unpredictability of the issue space by doling out the intensity of information for building top-notch models. This section gives a prolog to different core NLP errands and features their information-driven arrangements. A couple of delegate NLP applications are depicted that are fabricated utilizing the core NLP assignments as the fundamental foundation. Different wellsprings of Big Data for NLP investigation are examined trailed by Big Data-driven NLP research and applications. At long last, the part finishes up by demonstrating patterns and future research headings [1–9].
An Efficient Vehicle Localization Method by Using Monocular Vision

Accurate localization of surrounding vehicles helps drivers to perceive surrounding environment, which can be obtained by two parameters: depth and direction angle. This research aims to present a new efficient monocular vision based pipeline to get the vehicle’s location. We proposed a plug-and-play convolutional block combination with a basic target detection algorithm to improve the accuracy of vehicle’s bounding boxes. Then they were transformed to actual depth and angle through a conversion method which was deduced by monocular imaging geometry and camera parameters. Experimental results on KITTI dataset showed the high accuracy and efficiency of the proposed method. The mAP increased by about 2% with an additional inference time of less than 5 ms. The average depth error was about 4% for near distance objects and about 7% for far distance objects. The average angle error was about two degrees.
Annotating OGC web feature services automatically for generating geospatial knowledge graphs

Abstract The Spatial Data Infrastructure initiatives are now broadly developed and deployed. However, while plenty of tools use them, some tasks are still complex to perform by non‐expert users, such as finding, accessing, and using some of their related OGC Web Services (OWS). One of the main reasons for these challenges is associated with semantic heterogeneity within these services. This entails a lack of proper descriptions and requires knowledge about data structure and domain‐specific query languages to discover and retrieve these services. Semantic annotations of OWS play a crucial role in achieving semantic interoperability and addressing these associated challenges. In this article we describe an approach for enabling the automatic generation of semantic annotations of Web Feature Services (WFS) at their three request levels ( GetCapabilities , DescribeFeatureType , and GetFeature ), which are used to generate knowledge graphs. This approach uses various external services, ontological resources (POSM, DBpedia, GeoSPARQL, GeoNames, and datos.ign.es vocabularies), and knowledge bases (DBpedia and datos.ign.es ). Moreover, this approach enables us to validate annotations obtained as a previous step to generating geospatial knowledge graphs. Additionally, we present our proposal through an application case and assess it using a representative set of 21 WFS services, achieving an average of 46.70% annotations, of which 22.29% and 35.52% were validated using DBpedia and datos.ign.es initiatives, respectively. This shows the feasibility of our approach to generate knowledge graphs from WFS services in an automatic way.
Implementing Augmented reality in Tourism

Abstract. Modern technology is becoming a necessity of many destinations to stay competitive and attractive to the tourist. A new form of technology that is being used increasingly is Virtual and Augmented Reality (AR). The aim of this paper is to display the development of a mobile AR tourism application in urban heritage called PazinAR. Although Augmented Reality has passed the initial hype stage, the technology is just on the verge of being implemented in the tourism industry. This paper describes preparation, design, implementation and execution of prototype touristic application based on Augmented Reality (AR) technology. The application was made using Unity software and AR SDK Vuforia and exported as Android applications. Created application enables overlapping old photos with current view. Furthermore, several significant implications for AR Tourism research and practice are revealed.
Modernizing Language Courses In Digital Education: A Coup Or Changing The Scenery?

Improvement in any area, including socio-economic sphere, is determined by human factor, the formation of which is connected with the educational system.Digitalization penetrates into all spheres of reality, becomes a key factor in effective interaction between the state and citizens.Digitalization of educational environment is the response to the challenge from the state, which aims at making the scientific and pedagogical staff transform education from the process of transferring and receiving knowledge, cultural values into driving force of the country's social and economic progress.Digital technologies determine the informational and educational environment of a person.However, the impact of digital technologies on the acquisition of knowledge, skills of the graduate of the humanitarian areas of universities remains controversial.The authors consider the issues of effective methods for competencies formation connected both with the content of philological disciplines and the use of digital environment in professional activities of graduates.Experience of teaching different philological disciplines reveals the following points: ways of information literacy development among students (information needs, analyzing content, assessing the relevance of the source and content, ability to correlate the content of different sources, etc.); issues of teaching students the professional communication in digital environment; creating digital content within academic disciplines.
HRPDF: A Software-Based Heterogeneous Redundant Proactive Defense Framework for Programmable Logic Controller

Programmable logic controllers (PLCs) play a critical role in many industrial control systems, yet face increasingly serious cyber threats. In this paper, we propose a novel PLC-compatible software-based defense mechanism, called Heterogeneous Redundant Proactive Defense Framework (HRPDF). We propose a heterogeneous PLC architecture in HRPDF, including multiple heterogeneous, equivalent, and synchronous runtimes, which can thwart multiple types of attacks against PLC without the need of external devices. To ensure the availability of PLC, we also design an inter-process communication algorithm that minimizes the overhead of HRPDF. We implement a prototype system of HRPDF and test it in a real-world PLC and an OpenPLC-based device, respectively. The results show that HRPDF can defend against multiple types of attacks with 10.22% additional CPU and 5.56% additional memory overhead, and about 0.6 ms additional time overhead.
Staycation and Leisure Time Analysis during The Covid-19 Pandemic

The many changes as a result of the Covid-19 pandemic make people need to adjust to new habits and most of these activities are carried out at home. This community service is in the form of providing understanding and advice regarding activities that can be done during the pandemic for children and to fill their leisure time to be more productive. Measurement of the effectiveness of this activity is done by asking questions before the activity (pretest) and after the activity (posttest) and then comparing the results. The object of the activity is elementary school VB class students. The results of the activity showed that before giving the material, many students knew the term staycation from the mass media but did not really understand the use of leisure time. After giving the material, many students began to understand the use of leisure time with more productive activities, such as reading. They also get used to literacy activities before starting online learning activities, so that they can increase students' reading interest and foster literacy habits.
Principal Component Regression in Statistical Downscaling with Missing Value for Daily Rainfall Forecasting

Drought is a serious problem that often arises during the dry season. Hydrometeorologically, drought is caused by reduced rainfall in a certain period. Therefore, it is necessary to take the latest actions that can overcome this problem. This research aims to predict the potential for a drought to occur again in the Kupang City, Indonesia by developing a rainfall forecasting model. Incomplete daily local climate data for Kupang City is an obstacle in this analysis of rainfall forecasting. Data correction was then carried out through imputed missing values using the Kalman Filter method with Arima State-Space model. The Kalman Filter and Arima State-Space model (2,1,1) produces the best missing data imputation with a Root Mean Square Error (RMSE) of 0.930. The rainfall forecasting process is carried out using Statistical Downscaling with the Principal Component Regression (PCR) model that considers global atmospheric circulation from the Global Circular Model (GCM). The results showed that the PCR model obtained was quite good with a Mean Absolute Percent Error (MAPE) value of 2.81%. This model is used to predict the daily rainfall of Kupang City by utilizing GCM data.
WhatsApp Chat Fraud Analysis Using Support Vector Machine Method

Fraud is one of the most cyber crime on social media. One of the popular social media in Indonesia is Whatsapp. Cases of fraud through chat on Whatsapp application often occur in Indonesia, its due to lack of information. The research conducted related to the detection of words containing fraud in WhatsApp chat application. The methods in this research applies the literature study method to find secondary data in the references theories and relevant research. The data collection is carried out by collecting chats that lead to fraud cases and then processing them using RapidMiner application with SVM (Support Vector Mechine) method. The results of this research can be concluded that this research succeeded in implementing SVM algorithm for whatsapp fraud chat analysis with an accuracy rate of 84.21%
On the Use of the Wilcoxon Criterion in the Practice of Pedagogical Research

The article discusses the use of nonparametric measures of influence in pedagogical research. The Wilcoxon criterion for comparing indicators obtained as a result of measurements in a connected sample is highlighted. The necessary conditions for the application of the criterion, as well as the advantages of its use are indicated. The possibility of using the Wilcoxon criterion is illustrated by the example of determining the effectiveness of the proposed teaching methodology using the Uchi.ru online platform in educational activities. Most modern studies in the field of pedagogy and psychology, along with qualitative descriptions of the results of the research, actively use quantitative analysis. Last analysis includes processing of the data using methods of mathematical statistics. In order to show the effectiveness of the developed methodology for the learning process, it should be considered as a factor influencing changes in the studied trait. Further study of these changes allows the researcher to determine the statistical reliability (significance) of the influence of the factor under consideration. The subsequent analysis of the reliability of the influence of a particular factor, the comparison of the measure of influence of various factors is carried out using parametric (variance analysis) and nonparametric measures of influence (the sign criterion, the Wilcoxon criterion). This article discusses the use of nonparametric measures of influence in pedagogical research. The Wilcoxon criterion is selected for comparing the indicators obtained as a result of measurement in a connected sample and allowing to diagnose not only the direction of changes, but also their severity. The necessary conditions for the application of the criterion, as well as the advantages of its use, are indicated. The possibility of using the Wilcoxon criterion is illustrated by the example of determining the effectiveness of the proposed teaching methodology using the Uchi.ru online platform in educational activities. Conclusions are made about its inefficiency for mastering the material in mathematics for younger schoolchildren.
CAREER GUIDANCE IN EDUCATIONAL INSTITUTIONS IN UKRAINE: DEVELOPMENT, CHALLENGES AND SOLUTIONS

Career guidance in educational institutions in Ukraine: development, challenges and solutionsIntroduction.Career guidance is a mandatory element of the labor market that combines personal and social interests.On the one hand, high-quality performance of professional activity is possible in case of conformity of individual features to the occupation requirements.On the other hand, professionalism and conscientious performance of professional duties ensure the development of certain
A New Framework Approach Enhances Security to Efficient Remote Collaboration in TPA Scheme for Cloud Storage

Abstract: Cloud computing provides customers with storage as a service, allowing data to be stored, managed, and cached remotely. Users can also access it online. A major concern for users is the integrity of the data stored in the cloud, as it is possible for external invaders or criminals to attack, repair, or destroy the data stored in the cloud. Data auditing is a trending concept that involves hiring a third-party auditor to perform a data integrity test (TPA). The main purpose of this project is to provide a safe and effective testing system that combines features such as data integrity, confidentiality, and privacy protection. The cloud server is only used to store encrypted data blocks in the proposed system. It is not subject to any additional computer verification. TPA and the data owner are in charge of all the functions of the scheme. A variety of materials are used to evaluate the proposed audit process. The proposed solution meets all the processes while minimizing the load on cloud servers. Data dynamics actions such as data review, deletion, and installation will be performed in the future. Keywords: Cloud storage; Third Party Auditor; Public Auditing; Privacy Preserving; Integrity;
Common Fallacies about Multivalued Circuits

For more than 60 years, many ternary or quaternary circuits have been proposed based on similar assumptions. We successively examine four of these assumptions and demonstrate that they are wrong. The fundamental reason for which m-valued combinational circuits are more complicated than the corresponding binary ones is explained. M-valued flash memories are used in USB devices because access times in not critical and a trade-off is possible between access time and chip area. If m-valued circuits are reduced to a very small niche in the binary world with semi-conductor technologies, there is a significant exception: quantum devices and computers are a true breakthrough as qbits are intrinsically multivalued. Successful m-valued circuits need m-valued devices as qbits.
Current Challenges and Prospective Benefits of Using UAVs

The modern economy completely changed by offering to industry groups the capability to reorganize their operating processes. Nowadays we become observers of similar in scale revolutionary transformations: technologies for the use of unmanned aerial vehicles substantially modified business models and new operating conditions have been developed in various sectors from industries, agriculture to the emergency, parcel delivery or movie industry. In the very near future, clients’ enterprises from multiple sectors of the economy will recognize the first effect of the use of unmanned aerial vehicles (UAVs) in diverse fields - from commercial sectors to examining and exploring the environment or to reduce the impacts of unexpected disasters. The aim of the present review paper is to analyse the opportunities and advantages of using the application of UAVs technologies. On the other hand, not only the devices (drones) themselves are of importance, but also their wider utilization to acquire extraordinary volumes of data.&#x0D;
Using instance hardness measures in curriculum learning

Curriculum learning consists of training strategies for machine learning techniques in which the easiest observations are presented first, progressing into more diﬃcult cases as training proceeds. For assembling the curriculum, it is necessary to order the observations a dataset has according to their diﬃculty. This work investigates how instance hardness measures, which can be used to assess the diﬃculty level of each observation in a dataset from diﬀerent perspectives, can be used to assemble a curriculum. Experiments with four CIFAR-100 sub-problems have demonstrated the feasibility of using the instance hardness measures, the main advantage is on convergence speed and some datasets accuracy gains can also be verified.
PÉDAGOGIE UNIVERSITAIRE RÉNOVÉE À L’ÉPOQUE DE LA PANDÉMIE : COMMENT PASSER DE L’AUTRE CÔTÉ DE L’ÉCRAN ?

The 2020/2021 pandemic year has been difficult for teachers at all levels of education including higher education. There was a need to switch quickly to another type of education that would achieve the same objectives as before. How did the university teachers face this challenge? What consequences have been drawn for university teaching in general? We propose to take a global perspective of the state of current university pedagogy to highlight the need to renovate its approaches and to put the learner at the center of the process so to provide pedagogical support in his learning. We will analyze the results of three surveys concerning remote teaching and learning in Poland and in Europe. Finally, we will show what tools can be used to better monitor students` learning in virtual classes.
Flower Pollination Algorithm for Software Effort Coefficients Optimization to Improve Effort Estimation Accuracy

Software effort estimation is one of important area in project management which used to predict effort for each person to develop an application. Besides, Constructive Cost Model (COCOMO) II is a common model used to estimate effort estimation. There are two coefficients in estimating effort of COCOMO II which highly affect the estimation accuracy. Several methods have been conducted to estimate those coefficients which can predict a closer value between actual effort and predicted value. In this paper, a new metaheuristic algorithm which is known as Flower Pollination Algorithm (FPA) is proposed in several scenario of iteration. Besides, FPA is also compared to several metaheuristic algorithm, namely Cuckoo Search Algorithm and Particle Swarm Optimization. After evaluated by using Mean Magnitude of Relative Error (MMRE), experimental results show that FPA obtains the best result in estimating effort compared to other algorithms by reached 52.48% of MMRE in 500 iterations.
Analyse and challenges of teaching writing among the English teachers

Teaching is one of the productive skills in English language writing, which involves developing students' linguistic competence, which many ESL teachers find difficult. The study's main goal is to examine the challenges faced by ESL teachers in teaching writing skills to students in university classrooms. This study aims to identify problems faced by teachers of Arts faculty at the Universities level. The researcher used questionnaires to survey teachers' concerns about teaching writing skills. The researcher used a descriptive method to report the problems encountered by the sampled teachers in teaching writing skills. The survey had 12 questions. This study's findings not only revealed the problematic factors but also suggested some practical solutions. This study's findings and recommendations may help teachers reflect on their teaching practices and assist authorities in supporting teachers' efforts to improve student writing skills.