Reviewerly/exHarmony huggingface dataset:
РАЗВОЈ СОФТВЕРА ЗА УПРАВЉАЊЕ ПРОЈЕКТИМА ЗАСНОВАН НА РАЗЛИЧИТИМ АГИЛНИМ МЕТОДОЛОГИЈАМА

In the beginning, the same software development approach, traditional methodologies, was used for all IT projects. However, due to the rapid growth of the IT industry, projects were frequently unsuccessful and therefore agile methodologies began to develop. The first part of the assignment will provide an overview of traditional and agile methodologies from a theoretical point of view, as well as their current representation, whereas further in the assignment attention will be focused on agile methodology. The research will be conducted on the three most common agile methods: Scrum, Kanban, and Extreme Programming. All three methods will be analyzed separately along with their values and characteristics, after which a combination of their values will be presented, which is the basis for software development. The second part of the assignment is related to the practical work, namely the development of project management software which would give a visual presentation and more distinctly explain the theoretical aspect of the paperwork.
Sentiment Classification Based on Public Reviews of Different States Towards the Police

Sentiment analysis can be referred to as an Opinion Mining which is an exemplary example of machine learning and is a significant element of NLP that is agitated with the persistence of opinion and individuality in a text, which also includes many applications. This analysis not only identifies the opinions but also extracts the attributes for the expressions. This research will enlighten and set forth the facts and statistics about classifiers for sentiment analysis of public opinion towards police working in different states through comments and tweets via Support Vector Machine (SVM). The proposed with the help of NLP classifies the text into positive and negative tweets where processes like stemming and tokenisation are used to remove the unwanted characters and patterns that are neither positive nor negative in the document. Usage of logistic regression is intended to classify the document into sentence level to consider the polarity of the document. The model has indicates to extract the features from the dataset used and extract the positive and negative tweets as to how they feel about the working of the police in their states. Through SVM and Logistic regression we intend to find the accurate score for the analysis that is classified from the input text to the classes of interest which specifies the need to use the keywords mentioned. After training the model results show that Delhi is the one of the top state with less working of the police whereas Chennai becomes the state where the work of the police is appreciated by their citizen’s which is shown with the help of pie and bar chart. Comparing the accuracies of logistic regression and the SVM techniques accuracies, SVM accuracy made out to be better with 55.4% and for logistic regression gives 56.7% accuracy.
Development of DPB6043 E-Notes Business Project Mobile Applications

The Covid-19 pandemic and Movement Control Order (MCO) resulted in the closure of all higher education institutions throughout the country to prevent the spread of this contagious outbreak. The teaching and learning process becomes fully online learning due to this situation. Students living in rural areas face the problem of no internet access. Hence, the purpose of the innovation DPB6043 E-Notes in the form of mobile application to assist students who faced problem with online learning during Covid-19 pandemic. This mobile application was developed using Thunkable and Google Sites based on TAM theory, CBAAM, and ADDIE model. Data were obtained using the survey research method. A total of 33 students from the final semester of Diploma in Business Studies (DPM) program from the Commerce Department, Politeknik Mukah Sarawak participated in the survey. The survey findings further revealed that DPB6043 E-Notes improves students' understanding and is very important for online learning with the highest mean = 4.484. The outcome of this research can benefit the decision-makers of higher institutions in Mukah Sarawak regard to the way to enhance m-learning and promote effective teaching and learning activities as well as strengthening the quality of learning delivery.
Information system’s implementation on governance quality and its impact on university organization performance

espanolEste estudio tiene como objetivo determinar el efecto del exito de la implementacion de los sistemas de informacion sobre la calidad de la gobernanza y su impacto en el desempeno de la organizacion universitaria. Este estudio utiliza un analisis estadistico descriptivo y un analisis de verificacion utilizando el Modelo de Ecuacion Estructural (SEM). La recoleccion de datos se realizo a traves de un cuestionario en linea distribuido a 163 universidades en West Java con acreditacion B y C. Los hallazgos indican que el exito de la implementacion de sistemas de informacion tambien tiene un efecto positivo en el desempeno de las organizaciones universitarias en West Java a traves de la calidad de gobernancia. EnglishThis study aims to determine the effect of information systems’ implementation success on governance quality and its impact on university organization performance. This study uses descriptive statistical analysis and verification analysis using the Structural Equation Model (SEM). Data collection was conducted through an online questionnaire distributed to 163 universities in West Java with accreditation B and C. The findings indicate that the success of information systems’ implementation also has a positive effect on the performance of university organizations in West Java through the quality of governance.
Possibility of using CMS Maple to study laws of distribution of random variables

The use of CMS Maple for students' practical and independent work is described. The study of random variable distribution laws is actual.&#x0D; Statistical calculations without computer are difficult and require many functional and quintiles tables of standard distributions. This does not contribute to feeling the element of novelty in the material being studied, to be able to arbitrarily change the conditions of tasks, etc., it takes a lot of time in solving applied production problems, which is inappropriate&#x0D; Thus to determine and research random variable distribution laws both in practical applications and in studying we must use special mathematical packages. The most extended of them are Mathcad, MatLab, Mathematica, Maple. Specialized statistical packages (SAS, SPSS, STATISTIKA, STATGRAPHICS) are not relevant to study. Their use for studying requires very high education level in mathematical statistics.&#x0D; Most of the existing math packages allow users to operate at random variables, including the Computer Mathematics System (CMS) Maple.&#x0D; Thus, the purpose of this article is a description of the studying possibilities of the random variables distribution laws with CMS Maple and the application of the acquired skills to the independent work of students.&#x0D; The Maple Statistics Library has a large set of commands for analyzing data, computing various numerical characteristics of random variables, graphing their distribution laws, and for statistical data processing.&#x0D; Thanks to a powerful set of statistical tools, the possibility of symbolic calculations and data processing of CMS Maple, wide possibilities of graphical interpretation of the results obtained not only in a static but also in a dynamic form, it is advisable to use it when studying the topic "Distribution Laws of Random Variables" in students' practical and independent work to use their acquired skills in solving applied problems of science and technology.
A 3-phase approach based on sequential mining and dependency parsing for enhancing hypernym patterns performance

Abstract Patterns have been extensively used to extract hypernym relations from texts. The most popular patterns are Hearst’s patterns, formulated as regular expressions mainly based on lexical information. Experiences have reported good precision and low recall for such patterns. Thus, several approaches have been developed for improving recall. While these approaches perform better in terms of recall, it remains quite difficult to further increase recall without degrading precision. In this paper, we propose a novel 3-phase approach based on sequential pattern mining to improve pattern-based approaches in terms of both precision and recall by (i) using a rich pattern representation based on grammatical dependencies (ii) discovering new hypernym patterns, and (iii) extending hypernym patterns with anti-hypernym patterns to prune wrong extracted hypernym relations. The results obtained by performing experiments on three corpora confirm that using our approach, we are able to learn sequential patterns and combine them to outperform existing hypernym patterns in terms of precision and recall. The comparison to unsupervised distributional baselines for hypernym detection shows that, as expected, our approach yields much better performance. When compared to supervised distributional baselines for hypernym detection, our approach can be shown to be complementary and much less loosely coupled with training datasets and corpora.
Issuing and Verifying of Blockchain Based Certificates

The issuance of fraud certificates has become an unrestrained and unchecked problem around the globe, because of its inevitable simplicity. A fake academic certificate can be defined as a counterfeit degree from a legitimate or even an illegitimate university. As a result, companies end up spending millions of dollars to simply verify the legitimacy of the certificates and transcripts of the applicants. Blockcerts, MIT Lab project, presented a solution, but their design was based on the Bitcoin chain which limited the scope of the project and left several functionalities unaddressed. Our approach implements a technique that uses the Blockchain (Ethereum) technology that can implement functional logic, to solve this issue. The two major advantages of Blockchain are that the verification can be done through an application and authentication or verification can occur instantaneously once the certificate holder approves the access. Also, the records cannot tamper as changes to individual blocks can be done only with the approval of all the parties processing the block. For years now, we have been relying on just a password to be the guardian of our most confidential information. In today’s modern world, this has become the greatest threat to our security. Passwords are very easily decodable and can be cracked in just a matter of seconds, while users are being subjected to phishing scams with alarming regularity. A way to reduce this security threat is two factor-based authentication. Two-factor authentication (2FA) is a type of multi-factor authentication method which confirms a users claimed identity by utilizing a combination of two different components, instead of one. This paper is on issuing certificates, verification and proposed decentralized two factor-based authentication feature using the Ethereum smart contract, which makes the entire authentication process even more secure.
LibGuides: News and Newspapers: College and University Newspapers

Covers current and past events in a variety of websites and newspaper sources. Online newspaper sources that cover College and University news.
Transformer-based Sarcasm Detection in English and Slovene Language

Sarcasm detection is an important problem in the field of natural language processing. In this pa-per, we compare performances of the three neural networks for sarcasm detection on English and Slovene datasets. Each network is based on a di˙erent transformer model: RoBERTa, Distil-Bert, and DistilBert – multilingual. In addition to the existing Twitter-based English dataset, we also created the Slovene dataset using the same approach. An F1 score of 0.72 and 0.88 was achieved in the English and Slovene dataset, re-spectively.
중국인 학습자를 위한 주어와 서술어의 호응관계 교육 내용 연구

The purpose of this paper is to observe the errors of subject-predicate concord in sentences (composition + Sentence completion test) generated by Chinese learners, and then to analyze the causes of the errors. Correspondingly, this study aims to provide some educational contents for subject-predicate anaphora. First, by analyzing the learners’ writing texts with data of 8262 words, it shows two aspects of errors. The grammatical concord error and semantic concord error, and the former includes the absence of subject or predicate, concord between the nominative of auxiliary words and predicate, the errors of predicate, sentence pattern anaphora, and the courtesy anaphora, of which the error rate of the concord between nominative of auxiliary words and predicates shows the highest frequency. Next, in order to observe the learners’ concord errors specifically, an inductive test, namely, a sentence completion test (50 copies), was conducted. Based on the above discussion, specific educational contents for the correspondence between subjects and predicates are presented in the paper. (Jilin Normal University)
A decision design pattern to detect and present the maturity-level of decision-relevant information

This work proposes to use a combination of Semantic Web concepts, including consistency, inferencing, and constraints to detect premature information. We calculate the information maturity-level and present it using well-known data presentation concepts. We propose the decision design pattern to reduce the time and expertise domain experts need to build Semantic Web-based ontologies that can detect premature information and present the information maturity-level. Additionally, the transparent information maturity-level helps decision-makers to move from intuition-based decision-making to evidence-based decision-making. Decisions, especially in the software product management discipline, are mostly complex and made based on intuition due to missing information or the lack of time to analyse the available information. A software product manager can understand if this is the right time to make that decision by understanding the information maturity-level of the decision-relevant information. The decision design pattern calculates the information maturity-level using the completeness, reproducibility, consensus, and conflict violations. We detect the completeness, reproducibility, consensus, and conflict violations using Semantic Web constraints. Domain experts can re-use the decision design pattern and apply it for their decisions. Based on the presentation of the information maturity-level, the decision-maker can decide to continue the decision-making process or elaborate on the information. We need to have the domain knowledge to validate the Semantic Web constraints. Therefore, we use two decisions from the software product management domain to validate our approach: requirement prioritisation and alternative solution selection. We create a supporting ontology structure for both decisions and instantiate the decision design pattern.
Experiencia Erasmus+ KA2 en el CEIP Al-Yussana: Proyecto “M.A.C > Traction”

espanolNuestro proyecto Erasmus+ KA229, de 30 meses de duracion, titulado M.A.C.>Traction ha involucrado a centros de Turquia (coordinador), Rumania, Chipre, Grecia, Italia y Espana. Esta denominacion es un juego de palabras en ingles en el que se combinan vocablos como Distraction, Atraction, Action y las iniciales M.A.C. (mental, art, cultural). Lo que pretende es, a traves de estos tres tipos de actividades (mentales, artisticas y culturales), trabajar con alumnado que tiene cierto deficit de atencion, procurando al mismo tiempo mejorar las habilidades informaticas y el idioma ingles, conocer los principales rasgos culturales de cada pais, actuar de forma cooperativa, compartir conocimientos y, finalmente, recibir una formacion especifica sobre el tema. Para ello, junto con la aplicacion de diversos tests diagnosticos y posterior verificacion, se desarrollan, entre otros elementos, juegos cognitivos y digitales, juegos infantiles tradicionales, de ritmo, ajedrez, estudios visuales, disenos, origami, artes tradicionales. EnglishOur 30-month Erasmus + KA229 project is entitled M.A.C.> TRACTION and it involves schools in Turkey (coordinator), Romania, Cyprus, Greece, Italy and Spain. The reason for this name has to do with a play on English words in which words such as DISTRACTION, ATRACTION, ACTION and the initials M.A.C. (mental, art, cultural). What is intended is, through these three types of activities (mental, artistic and cultural), to work with students who have a certain attention deficit, while trying to improve computer skills and the English language, to know the main cultural traits from different countries, act cooperatively, share knowledge and, finally, receive specific training on the subject. For this, along with the application of various diagnostic tests and subsequent verification, cognitive and digital games, traditional children's games, rhythm games, chess, visual studies, designs, origami, traditional arts ... are developed, among other elements.
A Binary Relevance Adaptive Model-Selection for Ensemble Steganalysis

Steganalysis is an interesting classification problem to discriminate the images, including hidden messages from the clean ones. There are many methods, including deep CNN networks, to extract fine features for this classification task. Also, some researches have been conducted to improve the final classifier. Some state-of-the-art methods use ensemble of networks by a voting strategy to achieve more stable performance. In this paper, a selection phase is proposed to filter improper networks before any voting. This filtering is done by a binary relevance multi-label classification approach. Xu-Net and ResT-Net, the most famous state-of-the-art Steganalysis ensemble models, are considered as the base networks for feature extraction. The Logistic Regression (LR) is chosen here as the last layer of the networks for classification. One large-margin Fisher's linear discriminant (FLD) classifier is trained for each one of the networks to measure its suitability in classifying the query image. The proposed method with different approaches is applied on the BOSSbase dataset and compared to traditional voting and some state-of-the-art related ensemble techniques. The results show significant accuracy improvement of the proposed method in comparison with others.
PENGARUH STRATEGI PEMBELAJARAN SUPERITEM TERHADAP HASIL BELAJAR IPS PADA SISWA KELAS VIII SMPN 1 LABUHAN MARINGGAI

The problems that can be identified in this study are the low learning outcomes obtained by students, the low activity of students in the learning process and students are lazy to ask questions when they encounter difficulties in learning social studies. The purpose of this study was to determine the application of superitem learning to social studies learning outcomes in class VIII even semester students of SMPN 1 Labuhan Maringgai in the 2019/2020 academic year. The method used in this research is the experimental method. The population in this study were all students of class VIII SMPN 1 Labuhan Maringgai totaling 128 students, the sample consisted of two classes, namely class VIIIB and VIIIC, where class VIIIB as an experimental class totaling 32 students and class VIIIC as a control class totaling 32 students. The sampling technique used cluster random sampling technique. The instrument in this study used a multiple choice test and hypothesis testing in this study using the ttest formula. Hypothesis testing uses the ttest statistical formula where the ttest value = 5.42 and the t distribution table at a significant level of 5%, it is known that tdaf is t (1-1 / 2 α) = 2.00 so it is proven ttest> tdaf. Thus it can be concluded that there is an application of superitem learning to social studies learning outcomes in class VIII even semester students of SMPN 1 Labuhan Maringgai in the 2019/2020 school year.
Marketing strategies in university libraries of North-Western India in Present Era: A study of viewpoints of post graduates and research scholars

The purpose of the research paper is to examine the viewpoints of the students belonging to different categories viz. research scholars and post graduates regarding the implementation of various marketing techniques for library resources and services. The traditional marketing tools and those based on Web, Web 2.0 have been taken into considerations. The research study is based on survey method governed by structured questionnaire intended for the users. The data was collected from research scholars and post graduates belonging to eight universities of North Western India. It was then analyzed through Statistical Package for Social Science (SPSS) software to obtain results. The findings revealed that there were significant differences in the view points of the two categories of users with most of the marketing techniques. It was found that there is no significant difference in few marketing tools amongst the two categories of the students with regard to the opinion in adopting those techniques.
The Use Of Augmented Reality Book To Enhance Writing Skill Of Primary School Students using Thai As A Second Language

This research was conducted to 1) develop augmented reality book to enhance writing skill of Thai alphabets and numbers writing of the first-grade students using Thai as a secondlanguage, 2) examine the effectiveness of the AR book usage, and 3) explore the students satisfaction of the AR book. The samples included 64 first-grade students of Demonstration School Prince of Songkla University (Primary). They were divided into an experimental group of 35 students and a controlled group of 34 students. The instruments covered 1) AR book for the writing practice of Thai alphabets and numbers of the first-grade students, 2) AR learning lesson plan, 3) traditional learning lesson plan, 4) achievement test on Thai alphabets and numbers writing, and 5) satisfaction questionnaire towards the AR book usage. Mean, standard deviation and t-test were employed in data analysis. The research findings were as follows. 1) The quality and effectiveness of the AR book was at a high level (mean = 4.79, SD = 0.28) with efficiency at 82.25/81.85. 2) The achievement test score of the experimental group (mean = 82.14, SD = 4.14) was higher than that of the controlled group (mean = 75.47, SD = 5.62) at a significant level of .01. 3) The students satisfaction towards the AR book was at the highest level (mean = 4.52, SD of 0.65).
Rancangan Dan Konfıgurası Jarıngan Pada PT. Samudera Idola Rahayu

A computer network is a very important requirement in a company, a network that is not managed will reduce the level of security and function of the network. The importance of management on the internet network in an agency so that the network that is created is centralized or well managed. The author uses Mikrotik to manage networks in companies that have 2 different providers and combine networks using a bridge and DHCP server as a configuration that will be applied and if one of the networks has problems, one of the internet providers can be a network backup. The author uses the Network Development Life Cycle (NDLC) method as a network design flow, the stages of the Network Development Life Cycle (NDLC) method that the author uses include several stages such as: Analysis, Design, Implementation, Monitoring the following stages will be the author's stage in designing the network. By using the Network Development Life Cycle (NDLC) method, it can make it easier for the author to determine the stages that will be carried out by the author