Reviewerly/exHarmony huggingface dataset:
QUALITY OF EDUCATION AND SUSTAINABLE DEVELOPMENT GOALS IN PAURI GARHWAL

Education is that thread which ties the society with the discipline and knowledge. Role of education is experienced universally which transforms societies in a fastidious way and leading to the sustainable development. It is essential to development of any nation. It is the backbone of development and is critical for improving the ability of the human beings to handle environmental and development issues for which basic education is a foundation of environmental knowledge and higher education needs to be integrated as an important part of learning. Education sustains the human values which contribute to individual and collective well-being. Education can enhance the effectiveness of each policy instrument by developing information engagement, agency and empowerment among all affected stakeholders. Education can build a drastic change that is sustainable change because it is created by the learner and reaches hearts and minds. Education can also sustain different human values that can collectively contribute to well beings of individuals and the society. It is the basis for increasing confidence for facing challenges and lifelong learning deeds that can achieve every goal of the individual building. The definition of quality education is different from person to person. There are many important factors responsible for quality of education for example teacher pupil ratio, infrastructure of the school, expenditure of the school on various teaching aids and projects, etc. Major problems of quality education are; limited policy relevant knowledge, policies related to quality education are not based on thorough research, Absence of standardized outcome measures and absence of highly skilled researchers and research capacity in general. Present study is supposed to focus on quality parameters of education that can help achieve goal 4 of sustainable development goals therefore the purpose of this study is to give a brief review of quality parameters of education and status of sustainable development goals in Pauri Garhwal district of Uttarakhand.
Ethical Leadership and Attitudinal Outcomes with Reference to Tunisian Companies

The main objective of this paper is to investigate the effect of ethics based leadership on employees’ attitudes including job satisfaction and commitment to organization. A quantitative methodology was chosen to test hypotheses and investigate causality between variables. The findings were tested using Smart PLS 3 software. This research confirms the positive association among both ethical leadership and followers’ job satisfaction and commitment.
Caracterização do Nível de Atividade Física em Doentes com Artrite Reumatoide sob Terapêutica Biológica

In the current available literature, there is strong evidence about the benefits of physical activity (PA) in patients with rheumatoid arthritis (RA). PA has shown an improvement in the disease activity that contributes to increase stability and joint strength, promoting a sense of well-being and reducing the symptoms of anxiety and depression, which are often associated with chronic diseases. The aim of this study is to relate the levels of PA in patients with RA under biological treatment and disease activity. Secondarily we intend to increase the educational role of the family doctor in the management of these patients.
Peningkatan Keterampilan Berbicara Peserta Didik Dengan Media Whatsapp Di SD Negeri 1 Suana Selama Pembelajaran Daring

This study aims to determine the description of the improvement in speaking skills of SD Negeri 1 Suana students by using WhatsApp as a medium that helps in the process of improving speaking skills. This research is a qualitative research type where this research only examines the role of WhatsApp in improving speaking skills in students. The reference used is the assessment conducted by the teacher in several stages of treatment. The assessment indicators are from the category of less, enough, good and very good. The system for determining the success of this research is seen in each class collectively. The data collection technique is carried out by providing stories, pictures and videos at several stages. The data obtained are then collected in a table and analyzed according to the indicators of improvement made. The formulation of the problem in this research is whether there is an increase in speaking skills among SD Negeri 1 Suana students using Whatsapp. From the results and discussion, it can be concluded that there was an increase in students' speaking skills with WhatsApp media for students of SD Negeri 1 Suana in online learning during the Covid Pandemic 19.
A Study of Google Translate Translations: An Error Analysis of Indonesian -to-English Texts

Nowadays, internet technology allows everyone to access information from all corners of the world anytime and anywhere. One of the tool that helps internet users to find information effectively is Google. Google currently offers a variety of applications, one of which is Google-Translate. Google-Translate is used to translate from the source language to the target language. However, the results of the translation are often inappropriate or have some errors. The error analysis always occurs in grammar and selection of inappropriate words. Therefore, the objective of this research is to find out whether there are translation errors and to find out the types of translation errors that occur in the translation results in Kompas.com news text. The data analyzed are the news text of Kompas.com in Indonesian translates into English by Google-Translate. This study used thedescriptive qualitative method. To examine the validity of this research the researchers use triangulation. From the data analyzed, there are 25 translation errors in Kompas.com news text. The dominance of translation error occurs in translation errors on the deviation of meaning where the number of translation errors is 16.
An Analysis of Confidentiality Issues in Data Lakes

A data lake is a relatively recent technology to maintain and allow access to voluminous and heterogeneous data sources. Governments, large corporations and startups have increasingly considered it for storing useful data and obtain valuable business trends. However, there is still a long evolutionary path related to data lake management, where data security is an open issue. In this paper we investigate confidentiality issues in the context of data lakes, with a focus on authentication and authorization. We apply a systematic review methodology focusing on approaches that provide some technology for authentication and authorization management. In the following, we compare the selected studies w.r.t. the used technologies and we also analyze how they are positioned w.r.t. a reference architecture for a data lake management system. This is the first paper that presents such a kind of analysis for data lakes.
U-M's Public Access to Research Data Working Group Report

The Public Access to Research Data working group was charged by the Provost's Office and the Office of the Vice-President of Research to craft a set of recommendations for supporting U-M researchers in making their data publicly accessible. These recommendations are to specifically address how U-M could improve compliance, reduce the burden to researchers in sharing their data, and make the process as seamless as possible in a financially responsible manner.
From Big Ideas to Real Talk: A Front-line Perspective on New Collections Roles in Times of Organizational Restructuring

Academic libraries across North America are restructuring to meet user needs in an e-preferred environment, resulting in major changes to traditional collection development roles and workflows. Responsibility for collection work is increasingly assigned to functional librarians dedicated to collection development activities across a broad range of subject areas, often serving an entire faculty or college. This paper discusses the history, process, and outcomes of the transition to functional collection development roles at two mid-sized universities. Both Carleton University and the University of Guelph support a wide range of undergraduate and graduate research needs from a single central library, but have implemented a different type of organizational design and are at different stages in the restructuring process. One year into their new functional roles, Carleton’s librarians are preparing to assess the state of change around collection development in their organization, and identify next steps for the restructuring process. By contrast, the University of Guelph has worked with a functional team model for ten years, and is undertaking a 10-year review to assess whether the original goals of the reorganization were met. How does collections work compare under a functional team model, compared to a traditional liaison model? Both perspectives offer strategies for consultation and change management that may be helpful to other institutions restructuring their collection development activities.
SSLBM: A New Fraud Detection Method Based on Semi- Supervised Learning

The increment of computer technology usage and rapid development of the Internet and electronic business lead to an increase in financial transactions. With the increase of these banking activities, fraudsters also use different methods to boost their fraudulent activities. One of the ways to cope their damages is fraud detection. Although, in this field, some methods have been proposed, there are essential challenges on the way. For example, it is necessary to propose methods that detect fraud accurately and fast, simultaneously. Lack of non-fraud labeled data and little fraud labeled data for learning is another challenge in this field particularly in banking. Therefore, we propose a new fraud detection method for bank accounts called SSLBM. In this method, after preprocessing phase, a helpful learning method called SSEV is used that is based on semi-supervised learning and evolutionary algorithm. The results imply improvement of detection by using SSLBM with 68% accuracy and acceptable speed.
Foreign Internships as A Factor of Foreign Language Teachers’ Professional Development

The aim of the study is to find ways to expand teacher efficacy by participating in foreign internships. Survey methods were used to collect the data from students. Descriptive statistics was used to examine the overall trends in foreign language teachers’ professional development. Thus, passing a training abroad leads to the development and improvement of language, professional, and cultural competencies of not only teachers, but also students; improving the skills of teachers, their motivation; increasing not only the prestige of the educational organization, but also the publication activity of university employees in world scientific publications; improving educational technologies. And most importantly, students, as direct participants of the educational process, are more than satisfied with their results. The article is of interest for the foreign language teachers.
Instance-Specific Causal Bayesian Network Structure Learning

Much of science consists of discovering and modeling causal relationships in nature. Causal knowledge provides insight into the mechanisms acting currently (e.g., the side-effects caused by a new medication) and the prediction of outcomes that will follow when actions are taken (e.g., the chance that a disease will be cured if a particular medication is taken). In the past 30 years, there has been tremendous progress in developing computational methods for discovering causal knowledge from observational data. Some of the most significant progress in causal discovery research has occurred using causal Bayesian networks (CBNs). A CBN is a probabilistic graphical model that includes nodes and edges. Each node corresponds to a domain variable and each edge (or arc) is interpreted as a causal relationship between a parent node (a cause) and a child node (an effect), relative to the other nodes in the network. In this dissertation, I focus on two problems: (1) developing efficient CBN structure learning methods that learn CBNs in the presence of latent variables (i.e., unmeasured or hidden variables). Handling latent variables is important in causal discovery since it can induce dependencies that need to be distinguished from direct causation. (2) developing instance-specific CBN structure learning algorithms to learn a CBN that is specific to an instance (e.g., patient), both with and without latent variables. Learning instance-specific CBNs is important in many areas of science, especially the biomedical domain; however, it is an under-studied research problem. In this dissertation, I develop various novel instance-specific CBN structure learning methods and evaluate them using simulated and real-world data.
Extracting Rhetorical Question from Twitter

Many types of content exist on SNSs. Sometimes authors' opinions are not properly communicated to the reader. The content might be inflammatory, known as flaming. We infer the importance of extracting passages in which the author's opinion is not communicated correctly when it is presented to the reader. This study particularly examines tweets, a popular message system of the Twitter SNS, and also specifically examines "rhetorical questions." Rhetorical questions are sometimes known as mandarin sentences. People might misunderstand them and might flame the author. We consider it important to extract rhetorical question tweets automatically and present them.
Sparsely Connected DenseNet for Malaria Parasite Detection

Among many promising deep neural models, densely connected convolutional neural network (DenseNet) is considered to be an efficient deep network. It has the significant feature of concatenation of previous layer information which then passes into the subsequent layers. In general, these models give high performance but have a very complex architecture with extremely large tunable parameters and hence attract an effort for an improvement over the complexity of the model. Specifically, for DenseNet, it is observed that not all nodes are equally significant and the feature maps generated by each node may not contribute equally to a desired task. This gives the motivation of developing the strategy which provides the reduced architecture and hence a simplified topology for an otherwise extremely complex DenseNet. This paper uses the concept of dropconnect functionality at the node level to design sparsely connected DenseNet. A predefined threshold value was used to introduce the sparsity in network structure via skip connections. The sparse network thus generated has the collective information of all previously connected nodes. The higher threshold generates a more sparse network. The proposed approach was validated using a benchmark dataset of malaria parasite detection. On the average of five-folds, the generated sparse network gained an accuracy of 95.55% with 396 thousand parameters as compared to the standard DenseNet which has shown the accuracy of 94.9% with 485 K parameters. Thus, it can be observed that for the tested dataset, the generated sparse networks are more effective in terms of performance and parameter economy.
Cryptanalysis on ZUC 1.4

ZUC has been subject to almost a decade of cryptanalysis at the time of this book. There have been some weaknesses found in the earlier versions of the cipher which has led to the improvement in this cipher. The latest version of ZUC, i.e., ZUC 1.6 has withstood cryptanalysis and has not shown any weaknesses as of now. In this chapter, we go over an analysis of the different part of ZUC cipher and also some of the weaknesses found in the earlier version of the cipher, i.e., ZUC 1.4. We first study a few cryptographic properties of the cipher and then we describe a differential attack on ZUC 1.4. Further, we present a forgery attack on an older integrity protocol of EIA3.
Integrating Pen-enabled Tablet PCs in Teaching Engineering Mathematics

The paper analyses the attitudes and experiences of two university lecturers involved in integrating pen-enabled Tablet PCs (penTPCs) in teaching engineering mathematics. The first lecturer has an engineering background and teaches an advanced engineering mathematics course (year four). The second lecturer has a mathematics background and teaches a second year engineering mathematics course. Two rounds of interviews with the lecturers on using penTPCs were conducted in 2015 and 2019. Analysis of these interviews suggests that, for the lecturer in mathematical disciplines, a key factor in their initial adoption of penTPC technology may be their perception of the usefulness of the technology in enhancing delivery within the context of existing pedagogical approaches in a classroom/lecture setting.
Cryptocurrencies and the Evolution of Banking, Money and Payments

This paper explores cryptocurrencies against the backdrop of the history of monetary, banking and payment systems, from a legal perspective. Providing a historical overview beginning in Antiquity, it explores just how today’s cyber revolution compares against some key predicate operations, and situates cryptocurrencies in the context of the long-running evolution of bank payment intermediation and monetary development.
A quick shot of showers overnight with dry conditions Sunday into next week

Showers taper off Sunday morning for a beautiful afternoon!  Highs top out in the upper 40s to low 50s.  A nice ridge builds in for the week giving us more dry days ahead.  Highs will drop slightly to near our seasonal average of 47.  Overnights will fall off too as skies will stay partly clear.  We expect winds to be light so many areas will see patchy morning fog this week too.
Attention-Based Prototypical Learning

We propose a novel inherently interpretable machine learning method that bases decisions on few relevant examples that we call prototypes. Our method, ProtoAttend, can be integrated into a wide range of neural network architectures including pre-trained models. It utilizes an attention mechanism that relates the encoded representations to samples in order to determine prototypes. The resulting model outperforms state of the art in three high impact problems without sacrificing accuracy of the original model: (1) it enables high-quality interpretability that outputs samples most relevant to the decision-making (i.e. a sample-based interpretability method); (2) it achieves state of the art confidence estimation by quantifying the mismatch across prototype labels; and (3) it obtains state of the art in distribution mismatch detection. All this can be achieved with minimal additional test time and a practically viable training time computational cost.
Thirty-Six Views of Copyright Authorship, by Jackson Pollock

Humans have long used a variety of tools to convey artistic expression. Perhaps the most recent and mysterious artistic tools are machine learning or “artificially intelligent” (AI) computer systems that have captured popular attention. When taken in isolation, these devices seem to operate autonomously, giving the illusion that there is no author behind their output. In fact, there is a rich web of human effort and support behind any AI undertaking. When we pull aside the AI curtain, it becomes apparent that the attribution of authorship for AI-enabled creations is largely an exercise in tracing legal causation. Indeed, the concept of original expression, which is required for copyright authorship, implies a causal chain tracing the origin of fixed expression. In this Article, I show that concepts of causation, volition, and intention that are familiar from other areas of law also inform copyright authorship, and that the machine learning revolution affords us the opportunity to reveal previously hidden assumptions about copyright authorship. While I will begin by illustrating these concepts with examples from the graphic arts, the same principles are readily applied to other authorial works in other media. The result dispels not only the confusion surrounding mechanical creation but a variety of long-standing problems in copyright authorship.
Inovasi Perpustakaan di Era New Normal

In the era of the new normal library, it must play an active role to provide maximum service to users. The reason is that in this new normal covid-19 era, users who will have a lot of activities at home and one of the steps for the library to reach more users during the new normal era is to create various innovations in the library. According to Ramdani Ardiansyah, there are 4 parts of innovation that can be applied by libraries during the new normal era, namely innovation in administration, innovation in automation and digitization, innovation in the professional field and publications as well as innovations and creations of other librarians.
Effectivity Analysis on Retention Basin in Campus Two Muhammadiyah University of Surakarta for Reducing The Flood Discharge

Retention Basin at Campus 2 Muhammadiyah University of Surakarta is a multifunctional retention basin at University of Muhammadiyah Surakarta. Some of the functions of the Retention Basin at Campus 2 Muhammadiyah University of Surakarta include an aesthetic function for the campus environment, as a campus facility for students to hold student activities and as a reservoir for runoff water. Therefore in reality, the Retention Basin at Campus 2 Muhammadiyah University of Surakarta never been conducted research on whether it can accommodate all the rainwater runoff from the Campus 2 area. Thus, the research was carried out using rainfall data from 2009-2019 at the rainfall station surrounding the retention basin, knowing the land use in the Campus 2 area and using empirical data, namely the dimensions of the retention basin and the dimensions of the channel connected with the retention basin. Based on the research, the normal capacity of Retention Basin at Campus 2 Muhammadiyah University of Surakarta is 7816.847m3 while the runoff water from Campus 2 is 22000.082m3. Thus, it could be concluded that the normal capacity was insufficient and prevention needed to be done by modifying the sill dimensions, lowering the sill elevation or providing the pump. After doing research, these three methods were able to prevent flooding that occurred in the Retention Basin at Campus 2 Muhammadiyah University of Surakarta.
Virtues and Perils Of Algorithmic Enforcement and Content Regulation in The EU – A Toolkit For A Balanced Algorithmic Copyright Enforcement

Within the recent European policies and actions on illegal content, a trend towardsthe algorithmic enforcement of content regulation has emerged. Hard and soft lawprovisions are more or less explicitly requiring online platforms to resort totechnological systems in order to comply with the law. The use of technology toenforce the law is certainly not new, especially in the realm of copyright law. Thelast step in this process is the employment of algorithmic systems to filter contentuploaded by third parties and the use of autonomous decision-making to select thecontent that can appear online. This controversial legislative move raises concernsnot only as to its consistency with the current legal framework but also as to itsimpact on individual rights and societal development in general. This paperproposes a regulatory toolkit for a more balanced algorithmic copyrightenforcement that could, hopefully, also provide insights for a better algorithmicsociety overall.