Reviewerly/exHarmony huggingface dataset:
Analisis Tingkat Kematangan Adopsi Service Oriented Architecture Menggunakan ISO/IEC 16680 (OSIMM)

Enterprise application integration makes data sharing easier, efficient and provides flexibility for organizations to seize opportunities and respond to stakeholder needs. Faculty of Mathematics and Natural Sciences (FMIPA) Tanjungpura University is an organization that wants to apply information technology effectively to support its business processes. Currently the application at FMIPA is built with different platforms and databases so that it cannot be integrated to share data between parts of the organization. FMIPA intends to build a service-oriented technology architecture to support the realization of organizational goals. SOA (Service Oriented Architecture) can be used as a framework for enterprise application integration. SOA adoption is often not as expected because organizations do not plan their processes comprehensively. It is necessary to measure the maturity level of the organization's SOA adoption so that the current state of the organization's SOA and future expectations can be found. ISO/IEC 16680 (OSIMM) is a method for measuring the SOA maturity level with 7 levels of maturity and 7 dimensions. To expedite the SOA adoption process in FMIPA, SOA maturity level was measured using ISO/IEC 16680. Based on measurements of the seven dimensions of SOA at ISO/IEC 16680, it was found that the current level of SOA adoption maturity (As-Is) at FMIPA Untan was at the level one (Silo), while the expected maturity level (To-Be) is level four (Service). Gap analysis then carried out related to the gap in maturity levels, and is followed by making recommendations dan roadmap for SOA adoption.
The Project “Distance Extracurricular Courses” as a Condition for the Professional Competencies Development of Students – Future Primary School Teachers

The article presents the experience of the Institute of Childhood of the Herzen University in the implementation by future primary school teachers of the project of distance education for primary schoolchildren “Distance extracurricular courses”. The similar projects for organizing distance learning formats for schoolchildren by senior students of pedagogical universities in the country are analyzed. The authors describe the concept of the project, its main tasks, highlight the key differences of the project in the framework of analog analysis, reveal the ways of developing students’ competencies in the process of project implementation. The article presents the first results of the project, interprets the reflection data of students and university teachers, outlines the prospects for work in this direction. The methodological basis of the project was the idea of the activity and subject approaches. As part of the study, the following methods were used: analysis and systematization of data, analysis of opportunities for the implementation of educational ideas. These methods were used in the implementation of analytical work on the project, identifying the limitations and possibilities of the project implementation mechanism as a way of organizing practical training for students of a pedagogical university. The obtained results of the study allowed to substantiate the concept of the project, to determine effective ways of organizing it, to reveal the variable methods of interaction between the project participants, and to highlight the key results. Keywords: distance education, distance technologies, primary school, primary schoolchild, practice (practice for obtaining professional skills and professional experience)
Analysis and Design of a Crowdsourcing-Based Flooded Road Reporting Sys-tem Indonesia (FROSTID) Application

The problem of flooded road infrastructure mainly occurs in urban areas, due to low soil bearing capacity, high rainfall intensity, and failure of rainwater flow to the drainage system. Flooded roads, when traversed by motorized vehicles, will be very detrimental to the rider. Flood water can damage engines, transmissions, electrical components, and motor vehicle electronic computer systems. Water is also very dangerous to car safety devices, such as airbags and braking systems that use ABS (Antilock Braking System). Also, there may be health problems involving fungi and bacteria, due to damp vehicles, especially on cars. Other problems related to water may not be immediately apparent, such as rust and corrosion, which will develop over time. The flooded road reporting system is an early warning system that provides information to road users so they can take anticipatory steps. This research proposes a crowdsourcing-based flood road reporting system, called Frostid (Flooded Road Reporting System Indonesia), that involves local road users in collecting flood information. Frostid application users can not only access geospatial information for flooded roads but also can collect location data using the Global Positioning System (GPS) and upload the location points of flooded roads using their smartphones. The Frostid application uses a navigation map to describe the location of flooded roads. Flood information stored in the Frostid application is built entirely by local road users. The Frostid application is built on a mobile Android platform.
ETHNOCULTURAL EDUCATION IS AN IMPORTANT ASPECT IN PEDAGOGY

The problems of personality formation are actualized by the social conditions of modern life: the former system of spiritual values and guidelines is deformed. In social life, the desire for wealth and comfort has a significant specific weight, the ideals of collectivism are supplanted by individualism, the values of former selfless service - by the principle of personal benefit. All this, changing the value orientations of people, limits the development of their spiritual world.
ABOUT THE USE OF ELEMENTS OF EDUCATIONAL ROBOTICS IN SCHOOL (ON THE BASIS OF TEACHING PHYSICS)

This article deals with the actual problems of using elements of robotics in school on the example of teaching physics. It is conducted a review of the state of robotics teaching in school courses in other countries. The main attention is concentrated on the preparatory activities by the MES RK according to the State Educational Standards of secondary education of the discipline "Initial military preparation and technology" and to create an educational-methodical base.This article does not represent a specific learning model, a certain methodology or algorithm. The goal is to justify the need and expediency of going beyond additional education and using robotics in the study of various school disciplines, in particular physics. Attention is focused on the fact that previously robotics was a tool for the development of technical skills, now it is proposed to shift as a means of teaching related disciplines. This approach is considered necessary for improving the propaedeutic base for further technical education of the labor reserve.
Ultra-key Space Domain for Image Encryption using Chaos-based Approach with DNA Sequence

Recently, image encryption has taken an importance especially after the dramatic evolution of the internet and network communication.The importance of securing the images contents is due to the simplicity of capturing and transferring of digital images in various communication media.Although there are many approaches for image encryptions, chaos-based image encryption approach is considered one of the most appropriate approaches because of its simplicity, security, and sensitivity to the input parameter.This research paper presents a new technique for encrypting RGB image components using nonlinear chaotic function and DNA sequence.A new image with the same dimensions of the plain-image is used as a key for confusions and diffusion process for each RGB components of plain-image.Experimental results show the efficiency of the proposed technique, simplicity, and high level of resistant against several cryptanalyst.
The Digital Culture Of The Academy And The Limits Of Technology

This disruptive nature of the COVID-19 pandemic has created a large-scale scramble to translate offline modes of instruction to online teaching. Furthermore, this massive shift in teaching and learning in general and higher education, in particular, has seen those digital technologies being used for teaching and learning offer convergent modalities for synchronous and asynchronous classroom delivery. The effect of the COVID-19 pandemic on education globally indicates that while the affordances of digital technologies provide interesting opportunities for teaching and learning, in no way has it definitively proven to be as emancipatory or revolutionary as some proponents of educational technology have argued before the pandemic occurred. Also, rather than merely reflect, highlight, or exacerbate inequalities, divisions, and conflicts in the real world, the social phenomenon of online teaching en masse due the pandemic serves to demonstrate the importance of multimodal communication and the very social nature of university learning and formal education more broadly. Arguably, the digital identity of both students and teachers have been in constant negotiation since the start of this pandemic has occurred, as online teaching moved from being a marginal pedagogical practice to a widespread social phenomenon. At this juncture in world history, it is worth considering the viability of higher education and the social production of teachers and learners under the unstable and disruptive conditions brought about by the COVID-19 pandemic. The implications of this critical intervention pertain to the evolving role of the social institution of the academy itself, the nature of disciplinarity, and the activity that occurs within higher education institutions.
Sign Language Recognition for Deaf and Dumb

The оnly feаtures humаn beings use tо соmmuniсаte with eасh оther аre sрeeсh аnd vосаbulаry.Beсаuse оf оur аbility tо heаr, we саn see оne аnоther's feelings.In оrder tо give instruсtiоns right nоw, we саn even use sрeeсh reсоgnitiоn. But whаt if it саn't be heаrd аnd yоu саn't finаlly tаlk аbоut it. Visuаl соmmuniсаtiоn соntinues tо be the mаin соntасt methоd оf рeорle with develорmentаl disаbilities аnd deаf рeорle, аnd аutоmаtiс соmрrehensiоn оf sign lаnguаge is therefоre а соmрrehensive аreа оf study intended tо ensure their indeрendent lives. With the use оf imаge reсоgnitiоn аnd аrtifiсiаl intelligenсe, а number оf teсhniques аnd innоvаtiоns hаve been рrороsed in this field. Fоr reсоgnize оr соnvert the signs intо аn аррrорriаte sequenсe, eасh simрle sign deteсtiоn system is built. In this аrtiсle, the duаl-hаnded Indiаn fоreign lаnguаges аre соlleсted аs а соlleсtiоn оf imаges аnd interрreted with the аid оf Рythоn аnd then соnverted intо sрeeсh аnd text. The рrороsed аррrоасh is meаnt tо give vоiсe tо sрeeсhless рersоns.
On some relations which tie exponential and geometrical record random variables

Different record achievements are fixed in many domains of the human activities. Very often this process happens with some rate of discretization (up to seconds, up to meters or up to thousands of individuals) of the observed results. On the examples of exponential and geometrical distributions it is shown how such type of the transition from continuous to discrete distributions can vary the numbers of the record values in the corresponding sequences of the random variables.
Assessment of the sorption capacity of PET microparticles in natural water with respect to metals

&amp;lt;p&amp;gt;Contamination of the World Oceans with microplastics (MPs) is one of the most discussed environmental problems of the last decade. MPs are able to accumulate on their surface pollutants present in water in very low concentrations. Concentrations of pollutants, such as metals, can reach values that exceed the natural background in water bodies.Thus, MPs can act as a secondary source of contamination of water bodies with metals.The sorption capacity of artificially grinded and aged in the natural environment microparticles of polyethylene terephthalate (PET) with respect to metals in the natural water of Lake Onego was assessed in laboratory conditions.The Total Content method was used to characterize the sorption process and to obtain the dependence of the concentration of a substance in the stationary phase on its concentration in the mobile phase (experimental sorption isotherms were obtained). Subsequent mathematical processing of the experimentally obtained metal sorption isotherms on PET for Mn, Ni, Cu, Cd, and Pb allowed us to determine the monolayer capacities, adsorption equilibrium constants, and adsorption values at the equilibrium adsorbate concentration for each of the studied metals. This information is valuable to assess the role of MPs in metals transport in water bodies. The study was supported by the Russian Science Foundation grant number 19-17-00035.&amp;lt;/p&amp;gt;
Eye Tracking System using Matlab

There are many people around us who suffer from diseases like paralysis, quadriplegia due to which they cannot move their hands and legs. People suffering from such diseases need a person to be with them all the time to understand their needs and assist them. So, for their aid we want to implement an EYE DIRECTIVE WHEEL CHAIR, which moves in the direction based on the movement of eye balls of the person, helping in mobility. For this project we are designing a system called EYE TRACKING SYSTEM. This system consists of a camera, which is mounted on the wheel chair, which captures the movement of the eye balls of the person continuously. And these images are processed by a simulation software called MATLAB. This directs the motion of the EYE DIRECTIVE WHEEL CHAIR. When the person looks in a direction, the angle of rotation of the eyeball is calculated using MATLAB by processing the images continuously captured by the camera. When the person moves his eye balls in left direction, it shows to move left. Similarly, if he moves his eye balls in right direction, it shows move right. It shows move forward when eye balls or looking straight. And in every other situation it shows stop.
Does FDI Induce Knowledge Spillovers? Evidence from Indian Pharmaceutical Industry

The study examines knowledge spillovers from multinational firms in the Indian pharmaceutical industry. Specifically, we examine whether FDI catalyses diffusion of knowledge transfer from multinational firms’ R&D activities during 2000-01 to 2019-20 and four sub-periods of five years each. The empirical evidence suggests that multinational firms do not have any impact on the output of domestic firms in the first two sub-periods. However, generate positive knowledge spillovers in the last two sub-periods, increasing the output of domestic firms. FDI flows in the pharmaceutical sector increased mainly in the last two sub-periods due to policy changes and more relaxed FDI norms. The study finds that competition effect exists and distinguishes domestic firms. Firms not investing in R&D face enhanced competition from firms investing in R&D activities.
Improving Learning Performance in Neural Networks

In this paper, we propose an optimization framework for a robust deep learning algorithm using the influences of noisy recurring on artificial neural networks.Influences between nodes in the neural network remain very steady in the convergence towards a superior node even with several types of noises or rouges.Several characteristicss of noisy data sources have been used to optimize the observations in a group of neural networks during their learning process.While the standard network learns to emulate those around, it does not distinguish between professional and nonprofessional exemplars.A Collective system can accomplish and address such difficult tasks in both static and dynamic environments without using some external controls or central coordination.We will show how the algorithm approximates gradient descent of the expected solutions produced by the nodes in the space of pheromone trails.Positive feedback helps individual nodes to recognize and hone their skills, and covering their solution optimally and rapidly.Our experiment results showed how longrun disruption in the learning algorithm can successfully move towards the process that accomplishes favorable outcomes.Our results are comparable to and better than those proposed by other models considered significant, e.g., "large step Markov chain" and other local search heuristic algorithms.
Multilingual comparable corpora of parliamentary debates ParlaMint 2.0

ParlaMint is a multilingual set of comparable corpora containing parliamentary debates mostly starting in 2015 and extending to mid-2020, with each corpus being about 20 million words in size. The sessions in the corpora are marked as belonging to the COVID-19 period (after October 2019), or being reference (before that date).The corpora have extensive metadata, including aspects of the parliament; the speakers (name, gender, MP status, party affiliation, party coalition/opposition); are structured into time-stamped terms, sessions and meetings; with speeches being marked by the speaker and their role (e.g. chair, regular speaker). The speeches also contain marked-up transcriber comments, such as gaps in the transcription, interruptions, applause, etc. Note that some corpora have further information, e.g. the year of birth of the speakers, links to their Wikipedia articles, their membership in various committees, etc.The corpora are encoded according to the Parla-CLARIN TEI recommendation (https://clarin-eric.github.io/parla-clarin/), but have been validated against the compatible, but much stricter ParlaMint schemas. This entry contains the ParlaMint TEI-encoded corpora with the derived plain text version of the corpus along with TSV metadata on the speeches. Also included is the 2.0 release of the data and scripts available at the GitHub repository of the ParlaMint project.Note that there also exists the linguistically marked-up version of the corpus, which is available at http://hdl.handle.net/11356/1405.
Project activity in the sphere of digital technologies

The article considers the problems that arose in the situation when the world’s system of education has been forced to transfer into distance learning mode because of the pandemic. For the first time mankind had got an experience when it became necessary to abandon traditional training. In such situation, it was possible to continue providing education both in schools and in the universities due to the advantages that “digitalization” of education carries, though a number of shortcomings that both teachers and students faced were also revealed. Empirical experiment allowed to find out that distance education has significant shortcomings which affect both quality of knowledge and physical and mental health of people as well as socio-cultural adaptation and socialization of foreign students. Abandonment of traditional education in favor of distant one carries significant losses in the quality of education and, as a result, decreases the ability to create a harmonious and comprehensively developed personality. Authors of the article come to the conclusion that distance education should be used as an additional form of education in comparison to basic one (traditional), that is, it can provide positive results only in the complex (traditional plus distance).
Consumer Product Recommendation by Sentiment Analysis of Online Reviews

Sentiment analysis, also refers as opinion mining, is a sub machine learning task where we want to determine which is the general sentiment of a given data. Using machine learning techniques and natural language processing we can extract the subjective information of a data and try to classify it according to its polarity such as positive, neutral or negative. It is a really useful analysis since we could possibly determine the overall opinion about a selling an object, buying an object and so on. Sentiment analysis is actually far from to be solved since the language is very complex (objectivity/subjectivity, negation, vocabulary, grammar,) but it is also why it is very interesting to work on. In this research work, five different algorithms were chosen for sentiment analysis that is Decision Tree Classifier, RandomForest, Naive Bayes, and SVM & Logistic Regression.We compare all five algorithms, out of which we found that SVM gives the best accuracy that is 94.08%. I.
ValueRank: Keyword Search of Object Summaries Considering Values

The Relational ranking method applies authority-based ranking in relational dataset that can be modeled as graphs considering also their tuples' values.Authority directions from tuples that contain the given keywords and transfer to their corresponding neighboring nodes in accordance with their values and semantic connections.From our previous work, ObjectRank extends to ValueRank that also takes into account the value of tuples in authority transfer flows.In a maked difference from ObjectRank, which only considers authority flows through relationships, it is only valid in the bibliographic databases e.g.DBLP dataset, ValueRank facilitates the estimation of importance for any databases, e.g. trading databases, etc.A relational keyword search paradigm Object Summary (denote as OS) is proposed recently, given a set of keywords, a group of Object Summaries as its query result.An OS is a multilevel-tree data structure, in which node (namely the tuple with keywords) is OS's root node, and the surrounding nodes are the summary of all data on the graph.But, some of these trees have a very large in total number of tuples, size-l OSs are the OS snippets, have also been investigated using ValueRank.We evaluated the real bibliographical dataset and Microsoft business databases to verify of our proposed approach.
A User-Centered Design of Explainable AI for Clinical Decision Support

Clinical decision support (CDS) systems are computer applications whose goal is to facilitate the decision-making process of clinicians. In recent years, CDSS has developed an interest in applying machine learning (ML) models to make predictions related to clinical outcomes. The limited interpretability of many ML models is a major barrier to clinical adoption. This challenge has sparked research interest in interpretable and explainable AI, commonly known as XAI. XAI methods are used to construct and communicate explanations of the predictions made by machine learning models so that end users can interpret those predictions. However, these methods are not designed based on end-users' needs; rather, they are based on the developersâ intuitions of what a good explanation is. Furthermore, XAI methods are not tailored to the specific tasks that a user will undertake, nor are they tailored to the interface used to perform those tasks. To tackle these issues, we propose to develop a visual analytic tool to explain an ML model for clinical applications whose design will explicitly take into account the context of tasks and the needs of end-users.
DEIXIS FOUND IN THE FIRST VICTORY SPEECH OF JOE BIDEN AS UNITED STATES PRESIDENT

This research aimed to analyze Deixis found in The First Victory Speech of Joe Biden as United States President On 7 November 2020. Deixis is a part of Pragmatics that being used to understand the words and phrases context which identify person, time, and place. The object of the research was to identify the deixis found in the Joe Biden’s speech by categorizing to person deixis, spatial deixis, and temporal deixis, and to find the most dominant deixis used in the speech. A qualitative research method was applied in this research. The data source in this research was the transcript of Joe Biden’s victory speech as the President of the United States. The data was collected by document review, and the data was analyzed by using theory of Miles and Huberman in Sugiyono (2012) which had three steps: Data reduction, data display, and conclusion drawing. The result showed as the most dominant deixis found in Joe Biden’s speech was person deixis with total 198 deixis and the least category found was temporal deixis with total 12 deixis