Reviewerly/exHarmony huggingface dataset:
ORTHOGONAL MULTIPLES IN DIGITAL PROCESSING PROBLEM

The paper deals with the application of classical orthogonal Jacobi and Chebyshev–Lagerra polynomials to solving digital information processing problems and solving Volterra convolution integral equations, used to solve the problem of remote sensing of the Earth and the problem of identification of natural objects. The presence of two free parameters in Jacobi polynomials satisfies the conditions under which the problem of approximation of signals is solved, and the use of Chebyshev–Lagerra polynomials avoids the sampling procedures for solving Voltaire type integral equations.
INSET: Sentence Infilling with Inter-sentential Generative Pre-training

Missing sentence generation (or sentence infilling) fosters a wide range of applications in natural language generation, such as document auto-completion and meeting note expansion. Such a task asks the model to generate intermediate missing sentence that can semantically and syntactically bridge the surrounding context. Solving the sentence infilling task requires techniques in NLP ranging from natural language understanding, discourse-level planning and natural language generation. In this paper, we present a framework to decouple this challenge and address these three aspects respectively, leveraging the power of existing large-scale pre-trained models such as BERT and GPT-2. Our empirical results demonstrate the effectiveness of our proposed model in learning a sentence representation for generation, and further generating a missing sentence that bridges the context.
Interpreting Information of Deep Neural Networks for Profiled Side Channel Analysis

Security has become ever more important in today's quickly growing digital world as the number of digital assets has quickly grown. Our thesis focuses on devices that compute a secure cryptographic operation such that information can be communicated or authenticated. The attack vector utilized is known as Profiled Side-Channel Analysis (SCA) which aims at extracting a cryptographic key from a device through unintended behavior expressed through power monitoring or electromagnetic radiation. Profiled SCA attacks assume the most powerful adversary and therefore allows us to make a sound security assessment of a device in this setting. Our utilized profiling technique includes deep neural networks such as the multi-layer perceptron and the convolutional neural network. As this adds a layer of complexity to our assessment, we must understand how the properties of the network consolidate our security assessment. Previous research has shown that classical neural network metrics such as accuracy does not correlate to how successful or efficient a side-channel analysis is, therefore, we have proposed a mutual information metric. We measure mutual information across each layer in the neural network such that the behavior of each layer in interpreting how each layer is benefiting our classification. We investigate if the mutual information measure can be used to make a beneficial architectural distinction of the neural network for our side-channel analysis problem. Finally, we show there is a relationship between the mutual information and the guessing entropy for our side-channel attack and that it can be used to confirm that the chosen model is fully optimized for the side-channel problem.
Bunch theory, applications, axioms and models.

In his book A practical theory of programming Eric Hehner proposes and applies a remarkably radical reformulation of set theory, in which the collection and packaging of elements are seen as separate activities. This provides for unpackaged collections, referred to as bunches. Bunches allow us to reason about non-determinism at the level of terms, and, very remarkably, allow us to reason about the conceptual entity nothing, which is just an empty bunch (and very different from an empty set). This eliminates mathematical gaps caused by undefined terms. We compare the use of bunches with other approaches to this problem, and we illustrate the use of bunch theory in formulating program semantics which combines non-deterministic, preferential, and probabilistic choice. We show how an existing axiomatisation of set theory can be extended to incorporate bunches, and we provide and validate a model. Standard functions are lifted when applied to a bunch of values, but we also define a wholistic function application which allows whole bunches to be accepted as arguments, and we develop its associated fixed point theory.
HUBUNGAN AKREDITASI DAN UJIAN NASIONAL PADA SEKOLAH NEGERI DENGAN GENERALIZED STRUCTURED COMPONENT ANALYSIS

There are several views and tendencies that distinguish between schools and madrasas in several aspects, one of them is the curriculum. Madrasah as islamic educational institution contains more religious lessons compared to public schools. As a result, madrasah are considered less able to provide good result in educational achievement. Overall, the education system which is based on National Education Standards (SNP) is used for assessing the educational accreditation. SNP is the minimum criterion of education system in Indonesia can be evaluated from the National Examination (UN). As latent variable, SNP is measured through 124 items as variable indicators. One of methods which is used to measure the relationship among latent variables, and latent variables with their indicator variables is structural equation modeling (SEM). A component-based SEM is called Generalized Structured Component Analysis (GSCA). GSCA analysis based on measurement model, there were 9 indicators were not significant, in which 1 indicator of standard of education and staff (SPT), 5 indicators on standard of infrastructure (SSP), and 3 indicators on standard of cost (SB). Evaluation of the structural model, it was found that the path coefficient of standard of content (SI) to UN was not significant and standard of competency (SKL) given the biggest direct effect to UN. The overall goodness of fit model showed that the total variance that can be explained of all indicators and latent variables in evaluating model of accreditation and national examinations was 63.9%. The difference in the percentage of accreditation status between schools and madrasas shows different UN results. In the 2017-2018 period, MTsN had a higher percentage of accredited schools, in line with that the average MTsN UN obtained was better than that of SMP in all types of subjects.
HYBRID APPROACH FOR ARABIC SENTIMENT ANALYSIS USING MACHINE LEARNING AND LEXICON-BASED CLASSIFICATION

With the remarkable growth of the social media platforms, a large scale of data is scattered throughout the networks, those data contain valuable information that can be of a great help in many areas. It became a challenge to extract useful information from a big amount of data, since they are large in volume, variety and velocity. Sentiment analysis (SA) or Opinion Mining (OM) is one of the techniques that can help to extract information from a large amount of data, it is a research field in text mining. SA is the task of extracting the opinion or classifying the polarity of a given sentence or text and determine whether it carries positive, negative or neutral sentiments.SA has been well studied for the English language, however, Arabic SA has been considered more challenging due to the natural of the Arabic language, its rules and the fact that multiple dialects exist in the Arab countries. Another challenging issue in SA classification is the need for labeled data for training and the fact that the labeling process is usually carried out manually by humans and thus it is time consuming. Another challenging issue is identifying the most suitable machine learning algorithm for classifying the data accurately.In this thesis, a new hybrid sentiment analysis model is proposed for Modern Standard Arabic (MSA) text, with the goal of achieving an efficient classification of a given unlabeled Arabic text with optimal accuracy. The proposed model uses both lexicon-based approach and machine learning approach by using the ensemble learning technique: majority voting. The issues of data labeling are addressed by taking advantage of the lexicon-based approach for text labeling. The majority voting-based ensemble learning is used to improve the classification performance, where multiple classifiers are used instead of a single classifier and their results are combined. Several sets of classifiers and test datasets have been considered. The experimental results show that the proposed model with the set of classifiers: Naive Bayes, Logistic Regression and Stochastic Gradient Descent outperforms all the models with a single classifier in terms of accuracy, recall, precision and F-score.
Penerapan Metode Inquiry pada Pembelajaran Bahasa Indonesia Siswa di Kelas VIII SMP Negeri 3 Kartasura

The purpose of this study is to know the application of inquiry methods to student learning in class and to know the effect of student learning outcomes through inquiry learning methods. This research is a qualitative research with descriptive method. Data collection is done by using the method of observation, document review, interviews, and tests. Based on the results of research on the application of inquiry methods in learning Ad Text, the results show that there is an influence on learning Ad Text. From the learning outcomes of students on average can achieve high grades and the results of the questionnaire that has been spread after learning shows that many students who strongly agree if the Inquiry method is applied in teaching and learning, students feel happy and have increased grades. With the inquiry method students find it easier to understand ad text material.
The Contribution of Eye Tracking to Quality of Experience Assessment of 360-degree video

The research domain on the Quality of Experience (QoE) of 2D video streaming has been well established. However, a new video format is emerging and gaining popularity and availability: VR 360-degre ...
A Summer of Knowledge Sharing and Collaboration

The ‘Summer of Sharing’ programme was a collaborative idea of the Client Library Services Team. All the Library Engagement Advisors across the campuses belong in one team but we hardly get an opportunity for knowledge sharing and working together. As a result, the ‘Summer of Sharing’ programme was developed to give the LEAs an opportunity to share our knowledge and utilise our skills during the Summer break when the hours are condensed and everyone is available around the same time.
Study of the Slovenian tale »Kekec« through project-based learning

This master thesis consists of theoretical and empirical part, which are further divided into several subsections. In the theoretical part, areas related to the use of Project-Based Learning in elementary school are presented. I highlighted the importance of teamwork and cooperation, as well as the essential principles for successful collaborative interacition. Appropriate communication is essential for the use of good collaborative skills in group work. I emphasized the roles of teacher and pupil in Project-Based Learning, where the teacher is not an active leader of the learning process, thus he has to be properly pedagogically-psychologically and professionally qualified to cooperate with pupils, to motivate them during the work and to encourage their creativity.Creativity is based on the ability of divergent thinking, the main characteristics of which are fluency, flexibility, originality and elaboration. In order for them to cultivate, the teacher should carefully plan the learning environment and create tasks to challenge the pupils with an appropriate level of cognitive problems. The purpose of enouraging creativity in school is not an exceptional end product, but development of pupil's potentials. Pupils will experience most freedom and space for creative expression in learning environment that is related to their interests, behaviour and current/relevant cultural trends. Therefore I decided to link the popular hip hop culture with the classical Slovene tale about Kekec.The empirical part describes the lessons carried out in the classroom to introduce the work and later performances of different phases regarding to the Project-Based Learning. I focused on the workflow towards the final product, which was set by pupils. My main poits of observation were motivation, cooperation, active work and creativity while working, as well as the class climate. 22 learners were included in the research. The findings acquired during research confirmed my prior presumptions. On the premise of team-based evaluation I came to the conclusion that Project-Based Learning is a useful method for school work. It enables students to cooperate, motivates them for successful performance in the learning process and encourages them to achieve results. At the same time they are developing their creativity and strengthening their self-confidence. Project-Based Learning approach inspires them for further participation in similar projects, it encourages their willingness to work and develops their persistance for learning more complex topics.
Monocular depth estimation based on unsupervised learning

Due to the low cost and easy deployment, the depth estimation of monocular cameras has always attracted attention of researchers. As good performance based on deep learning technology in depth estimation, more and more training models has emerged for depth estimation. Most existing works have required very promising results that belongs to supervised learning methods, but corresponding ground truth depth data for training is inevitable that makes training complicated. To overcome this limitation, an unsupervised learning framework is used for monocular depth estimation from videos, which contains depth map and pose network. In this paper, better results can be achieved by optimizing training models and improving training loss. Besides, training and evaluation data is based on standard dataset KITTI (Karlsruhe Institute of Technology and Toyota Institute of Technology). In the end, the results are shown through comparing with different training models used in this paper.
LibGuides: Zotero for MLA, APA and Chicago Citations: Shared libraries

Zotero (pronounced zoh-TAIR-oh) is a program that collects, manages, and cites research sources. It's easy to use, lives in your web browser where you do your work, and best of all it's free.
Beginner's Guide to Twitter Data

Learn how to acquire Twitter data and process them to make them usable for further analysis.
The development of reading comprehension for 7th-grade students by using Directed Reading Thinking Activity (DR-TA)

The purposes of this research were: 1) to examine the efficiency of the instructional packages using Directed Reading Thinking Activity (DR-TA) for 7th grade-students, and 2) to compare students’ achievement after using Directed Reading Thinking Activity (DR-TA) through pre-test and post-test. The sample was selected from a purposive sampling of 40 7th grade-students from Phothawattanasenee School in the academic year 2018. The instruments of this study were 1) five 100-minute lesson plans using Directed Reading Thinking Activity (DR-TA), 2) the five sets of instructional packages of reading comprehension; each set consists of an English passage, an exercise, and a reading comprehension test, and 3) a reading comprehension pretest and posttest. The statistics used to analyze the data were arithmetic mean (), percentage, standard deviation (S.D.), percentage, and dependent t-test. The results of the study were as follows;1. The efficacy value of using the instructional packages based on Directed Reading- Thinking Activity (DR-TA) method for 7th-grade students was defined as 83/84 efficiency that was higher the expected standard of 80/80.2. The result of students’ achievement by using Directed Reading Thinking Activity (DR-TA) for 7th-grade students through the post-test scores was higher than pre-test scores at .01 level of significant.The conclusion of this study reveals that using Directed Reading Thinking Activity (DR-TA), through the instructional packages, were quite useful for students’ reading comprehension skill. Students also learn and practice how to develop their reading skill by using the instructional packages with DR-TA. Furthermore, the teaching of reading with DR-TA can improve students’ reading comprehension skill. Students were motivated to read more English texts.
Competence-Based Hierarchical Case Base for Control of Unmanned Vehicle Teams

This work presents a distributed hierarchical competence-based case base for the scenario-case coordination of large teams of unmanned vehicles of different types. Case base is defined as a hierarchically-organized structure, in which some distributed partitions are spatially connected based on geoinformation system. All services can be accessed through Internet connections and special cloud gateways. Such a case repository can provide case-on-demand, case-on-entry, push-on-entry, and other relevant methods of query processing. The case base is able to work properly in real time and provide the necessary performance.
Multi-Cluster Visualization and Live Reporting of Static Analysis Security Testing (SAST) Warnings

This short paper discusses a case study of multi cluster visualization of Static Analysis Security Testing (SAST) warnings in large clusters catering to a majority of Cisco products in hierarchical organizational and checker views. This serves as a one stop shop for real-time visualization of Static Analysis (SA) warning trends, chart, downloading reports, and to effectively address the potential security weaknesses detected. Presently leading SAST tools like Coverity, codesonar, Klocwork etc do not provide inter-cluster or enterprise-wide visualization to effectively address the SA warnings.
PENERAPAN MODEL PEMBELAJARAN KOOPERATIF TIPE MAKE A MATCH UNTUK MENINGKATKAN HASIL BELAJAR PKn SISWA KELAS V SDN 003 TASIK JUANG

This research is motivated by the still low learning outcomes of PKn students in grade V SDN 003 Tasik Juang. This study aims to improve student PKn learning outcomes by applying a make a match cooperative model. The design of this research is classroom action research, which consists of two cycles. Each cycle consists of planning, implementing, observing, and reflecting. The results showed that, on the base score, of 30 students, the number of students who completed as many as 17 people while students who did not complete as many as 13 people. In the daily test I, the number of students who finished completed increased to 23 students and students who did not complete became 7 students. Cycle II the number of students who completed was 28 people while students who did not complete 2 people. The percentage of classical completeness in the base score of 56.6% then increased in the first cycle to 76.6% and then increased again in the second cycle to 93.3%. Based on the results of the above research, it can be concluded that by applying the make a match type of cooperative learning model can improve the learning outcomes of PKn students in grade V Tasik Juang.
Development and Evaluation of a Mobile-Based MicrolearningApplication on Marine Conservation

The purpose of this study is to raise awareness for marine conservation to the public through a mobile-based microlearning application. Microlearning is used as an approach in this study to produce a non-conventional type of learning resource on marine conservation. Up to 80%of marine pollution is from land-based activities which include oil spills, fertilizers, garbage, sewage disposal and many others that eventually flows into the ocean. Marine pollution is one of the global issues thus marine conservation education for young adults is important.Marine conservation has been conventionally delivered via online courses exhibitions, workshops and events to the general public. This study uses the Kemp Design Model as the instructional design model to guide the design, development and evaluation of the application.Cooperative evaluation has been employed in the formative evaluation process to ensure usability problems are correctly identified and to conduct reviews to test effectiveness of prototype thus a semi-interview after the usability testing process where user completed thegiven task. As a result, this mobile application is designed in hopes to raise awareness for marine conservation via a different learning approach was successfully developed including the evaluation of prototype.
Asynchronous $$\pi $$ -calculus at Work: The Call-by-Need Strategy

In a well-known and influential paper [17] Palamidessi has shown that the expressive power of the Asynchronous $$\pi $$ -calculus is strictly less than that of the full (synchronous) $$\pi $$ -calculus. This gap in expressiveness has a correspondence, however, in sharper semantic properties for the former calculus, notably concerning algebraic laws. This paper substantiates this, taking, as a case study, the encoding of call-by-need $$\lambda $$ -calculus into the $$\pi $$ -calculus. We actually adopt the Local Asynchronous $$\pi $$ -calculus, that has even sharper semantic properties. We exploit such properties to prove some instances of validity of $$\beta $$ -reduction (meaning that the source and target terms of a $$\beta $$ -reduction are mapped onto behaviourally equivalent processes). Nearly all results would fail in the ordinary synchronous $$\pi $$ -calculus. We show that however the full $$\beta $$ -reduction is not valid. We also consider a refined encoding in which some further instances of $$\beta $$ -validity hold. We conclude with a few questions for future work.
IP routing to serve targeted tracing in software product lines

Tracing is a key element to guarantee efficient maintenance and ease to use systems, especially for complex large scale ones like Software Product Lines. However, while developing a system or an application, tracing is not always considered as a priority, as it generates additional effort and cost. For Software Product Lines, generating trace links can even add complexity to the system. However, as part of our research on tracing in Software Product Lines, we found that adopting a targeted tracing approach is more profitable for costs and Return On Investment (ROI). Therefore, we propose in this paper, as continuity to previous publications, a detailed algorithm to implement targeted traceability links in a Software Product Line, inspired from IP routing protocols.
Las redes sociales como herramienta estratégica del rol bibliotecario: experiencia de la biblioteca del Centro Vasco Denak Bat de Mar del Plata

It is necessary to redefine the function of the traditional library in society and because of this it is essential to be part of the virtual environment. The use of networks implies a new way of socializing information and suggests a new paradigm of relationship and interactivity between users and the library through their platforms.
Past and future of linguistics in the Netherlands

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