Reviewerly/exHarmony huggingface dataset:
SOSYAL MEDYA KULLANIMININ SATIN ALMA DAVRANIŞLARINA ETKİSİ: UŞAK ÜNİVERSİTESİ'NDE BİR ARAŞTIRMA

In the globalized world, Internet usage has increased with the developing technology. The use of social media, which has become widespread with the Internet, has become a new marketing field where producers and consumers meet. The high number of alternatives and the increase in the competition led enterprises to develop consumer-centered policies. The content in social media, which allows consumers to reach more easily, affects consumers and affects consumers' purchasing decisions. The aim of this research is to reveal the frequency of social media usage of university students and their effects on purchasing behaviors. The study was carried out by using face-to-face questionnaire technique to Uşak University students (225) and the data were analyzed by SPSS program. 13 hypotheses were developed under three different headings. It was found that consumers’ buying function is that the use of social media does not differ according to the demographic variables; however, the purchase of purchases was only revealed when social media behaviors differ according to the time spent on social media (H7). In addition, the social media used in the acquisition affected the social media (H11). Finally, it was concluded that there was a significant relationship between social media behaviors before and after the purchase (H13). Consumers and firms should learn their roles in social media and propose correct procurement and product promotion methods accordingly. Information was obtained to disseminate and to neutralize the purchasing behavior of the social media, and to present ideas about management and marketing strategies.
A retrospective of Roland Shack’s "Global View of Diffraction"

In April of 1972 Professor Roland Shack presented a series of four colloquium talks at the Optical Sciences Center at the University of Arizona in which he reformulated scalar diffraction theory in terms of the direction cosines of the propagation vectors of the angular spectrum of plane waves described by the Fourier integral transform of the diffracting aperture. The fourth lecture, entitled Radiometry and Lambert’s Law, describeddiffuse reflectance and surface scatter phenomena as merely a diffraction phenomenon caused by random phase variations in the system pupil function. In 1974 he elegantly condensed these four lectures into a single colloquium talk entitled A Global View of Diffraction. This paper is intended to provide a compilation showing the further development of that work over the last forty-six years.
An Evaluation of the Robustness Chi-Square Steganalysis Method on Wav Audio Files with Various Content

Abstract: This paper presents the performance of the chi-square method for steganalysis purposes on audio files through various content. Predetermined rates of stego data have been embedded into 4500 distinct cover wav files via LSB (Least Significant Bit) method using three types of audio input files: music, human voice, animal sounds. Results of the experiment have revealed that hidden data in wav files containing dissimilar audio samples cannot be easily detected by chi-square steganalysis method. However, wav files containing similar audio samples demonstrate better performance compared to dissimilar samples.
KORELASI KEMAMPUAN MENYIMAK DENGAN MENULIS PUISI MAHASISWA PROGRAM STUDI PENDIDIKAN BAHASA DAN SASTRA INDONESIA UMI

ABSTRACTThe research aims to see a significant correlation between the ability to listen to poetryand the ability to write poetry for students of the Indonesian Language and LiteratureStudy Program at the Faculty of Literature at the Muslim University of Indonesia(UMI).Research is an expose facto that is correlational, which consists of variable X thatis the ability to listen to poetry as an independent variable and the Y variable the abilityto write poetry as the dependent variable. In this study the population and sample werePro students gram Stuin Indonesian Language and Literature, Faculty of Letters UMI insemester 3, as well as technique used to collect this research data is observation and test.Furthermore din this study, the data collected was analyzed using descriptive statisticsof product moment correlation. The results of this study show that calculations using theproduct moment formula reach 0.08 because to find out whether or not there issignificant correlation between listening ability and writing student poetry. So, it appearsthat the acquisition value of 0.08 (r xy arithmetic) &lt;0.388 of (t value of the productmoment table) at a significant level of 95% with the number of students 27 people. So, itneeds to be emphasized that the high ability to listen to student poetry, less influence onhis ability to write poetry.Keywords: Correlation, Listening to Poetry, Writing Poetry
Proof systems for Geometric theories (PROGEO)

We plan to study the problem of finding conservative extensions of first order logics. In this project we intend to establish a systematic procedure for adding geometric theories in both intuitionistic and classical logics, as well as to extend this procedure to bipolar axioms, a generalization of the set of geometric axioms. This way, we obtain proof systems for several mathematical theories, such as lattices, algebra and projective geometry, being able to reason about such theories using automated deduction.
PENGARUH PEMAHAMAN PERPAJAKAN TERHADAP PRESTASI AKADEMIK MAHASISWA: MOTIVASI DAN KUALITAS PEMBELAJARAN DOSEN SEBAGAI MODERASI

This study aims to analyze the role of motivation and learning quality of lecturer as the moderating in the effect of understanding taxation on student academic achievement of accounting students at the Faculty of Economics, UNISRI Surakarta. This study using quantitative descriptive methods. The population is all students of the faculty of economics, accounting study program UNISRI Surakarta. Sampling using a purposive sampling technique. Sample criteria are students who are active until the academic year 2019/2020 and have taken Tax Accounting I and II courses. Data analysis techniques using multiple linear regression analysis and absolute residual test. The results showed that (1) understanding taxation, motivation, and learning quality of lecturer significantly effect on student academic achievement; (2) motivation is a moderating variable that can strengthen the effect of understanding taxation on student academic achievement; (3) learning quality of lecturer is a moderating variable that can strengthen the effect of taxation understanding on student academic achievement.
Fraseologismi e lingua della politica. Considerazioni sull’esempio dei post di alcuni partiti tedeschi e italiani

In the multimedia age the post published on social media becomes an efficient and powerful medium that some parties use to present and support their ideas in the attempt to appeal to voters and hold their attention. Moreover, the use of phrasemes, including slogans, proverbs, quotations etc., aims to impress voters by focusing attention on the emotional aspects of the discourse. Because of the immediacy and intelligibility of such phrases, they ensure clear communication between sender and recipient. The aim of this study is to describe some of the functions that idiomatic phrasemes perform in such multimedia texts, focusing in particular on the role they play in the text organization and in the creation of a contact with the reader. The analysis is carried out on a bilingual German-Italian corpus consisting of the posts of the main German and Italian political parties on the occasion of the federal elections in Germany on September 24th, 2017 and of the Italian general elections on March 4th, 2018.
From FreeBelt, LifeShirt and digital twin to BigBrother

The creation of an unstoppable Internet of Things (IoT) is about the worst that can happen to us as humanity. Not only will the IoT soon use more energy than all our current air traffic, it will also be quite easy to create an Orwelian (1984) terror from it. In particular, the IoT is powered by sensors, in cars, shavers, mirrors and ultimately probably even in printed newspapers and magazines...
Applying Clustering to Optimize Markovian Models in Human-Machine Interactions

Much like human-human interactions, human-machine interactions require an appropriate level of trust.If the human's trust on the machine is ill-calibrated, the interaction's result will be suboptimal.If a machine wishes to improve trust, it must fi rst know the state of the human's trust in it.To this end, partially observable Markov decision processes (POMDPs) have been used to estimate trust.Given observations resulting from trust (e.g., compliance or defi ance), POMDPs can estimate the probability of high or low trust in a machine given its previous action.
MOTIVASI BELAJAR MEMPENGARUHI TERHADAP HASIL BELAJAR SISWA KELAS V DI SEKOLAH DASAR

ABSTRACT&#x0D; The purpose of this study was to determine how much motivation to learn affects the learning outcomes of fifth grade students in elementary schools 064021 Medan City. The method used is a quantitative correlational method with data collection techniques by means of library research and field research through interviews, observations and documentation. With the results of the calculation of the correlation number of variable X (learning motivation) to the variable Y (learning outcomes) of 0.965. This means that the effect of learning motivation on student learning outcomes in grade V SDN 064021 Medan Helvetia Medan city is very high.&#x0D; Keywords: learning motivation, influencing, learning outcomes, students
The Effect of Academic Stress on the Successful Intelligence According by the Types of High School (Regular High School and Alternative School)

본 연구는 유형에 따른 고등학생들의 성공지능과 학업스트레스의 차이를 알아보고, 학업스트레스가 성공지능에 미치는 영향을 분석하기 위한 연구이다. 이를 위해 일반 고등학교와 대안학교 학생을 대상으로 성공지능과 학업스트레스 검사를 실시하였으며, 결과는 다음과 같다. 첫째, 성공지능은 일반 고등학교 학생이 높은 반면, 학업 스트레스의 경우 대안학교 학생이 낮은 것으로 나타났다. 둘째, 학업스트레스와 성공지능 하위 요인 간 두 유형의 학교 학생들 모두 유의한 상관을 나타내었다. 셋째, 학업스트레스가 성공지능에 미치는 영향은 일반 고등학교 학생에게 더 큰 것으로 나타났으며, 유형에 따른 고등학생들의 성공지능에 영향을 미치는 학업스트레스 하위 요인에 차이가 나타났다. 본 연구를 통해 학업스트레스가 성공지능에 영향을 미치며 학교간 차이가 있음이 나타났다. 또한 학업스트레스를 줄일 수 있는 방안에 대하여학교 유형에 따른 학습자의 특성과 학교의 여건을 충분히 활용하는 노력이 필요함을 시사하고 있다.This study is to find out the difference between successful intelligence and academic stress according to type of high school students and to analyze the effect of study stress on successful intelligence. Ordinary and alternative school students were tested for it. The result of this study is as follows. First, the analysis showed that the successful intelligence was high among ordinary high school students, while for academic stress, the alternative school students were low. Second, between academic stress and successful intelligence sub-factors, both students at regular and alternative schools showed significant correlation. Third, ordinary high school students were more effected by academic stress on successful intelligence and there were differences of sub-factors by type of school. This study suggested that efforts should be made to reduce academic stress by full use of learners characteristics and conditions by type of school.
Modern Implementation of the Design Pattern in Android Applications

Presentations patterns used in android application development are analyzed. Pros and cons of implementation of presentation patterns with android framework requirements are described. The idea of an architectural framework for android development is proposed.
SPOTTER: Detection of Human Beings Under Collapsed Environment

Collapse of man-made structures, such as buildings and bridges earth quakes and fire accident, occur with varying frequency across the world. In such a scenario, the survived human beings are likely to get trapped in the cavities created by collapsed building material. During post disaster rescue operations, searchand-rescue crews have a very limited or no knowledge of the presence, location, and number of the trapped victims. Deep learning is a fast-growing domain of machine learning, mainly for solving problems in computer vision. One of the implementation of deep learning is detection of objects including humans, based on video stream. Thus, the presence of a human buried under earthquake rubble or hidden behind barriers can be identified using deep learning. This is done with the help of USB camera which can be inserted into the rubble. Spotter also gives an audio message about the location of the human presence and gives the area where the human is likely to be present. Human detection is done with the help of Computer Vision using OpenCV.
Platform Digital Kelurahan Babau

Managing letters related to residence in Babau Village usually takes a long time. Residents must meet directly with the head of the RT/RW in the domicile area to obtain a cover letter, then they can go to the Kelurahan office to arrange the intended documents. The problem that then arises is if the community cannot meet the RT/RW leader because of busy life. Likewise if it arrives at the Kelurahan office, it turns out that the Lurah is not there. This will certainly hinder the management process. In addition to the above problems, another problem that can also arise is the RT/RW cover letter that has the potential to be falsified.These problems can be solved by building a Digital Village platform where the community does not need to meet directly with the RT/RW but can use the existing platform to manage the required documents. The proposal letter that goes to RT/RW can be directly approved and forwarded to the Village Head to be approved and ready to be printed. Everything is done without the need for paperless paperwork.
Empowerment in the Learning of Wine Technology Based on Emotional Motivation Using the Moodle Platform

The virtual university education required by the global pandemic has promoted the use of virtual platforms such as moodle, which allows for permanent interaction with the student. The influence of the independent variable called “Emotional motivation” was measured, which has as a stimulus the application of a reading about all the biblical verses that mention wine, considering as a dependent variable “Empowerment of learning about wine technology” as well as in the levels of the variable: “Cognitive” and “Previous knowledge”. The objective was to determine if a relationship existed between both variables. In the results of the dependent variable, there was a decrease in the low and middle levels; and an increase in the high level. Applying results of the pre-test and post-test, the chi-square test determined that in the dependent variable, if there is significant difference so the alternative hypothesis is accepted and the null hypothesis is rejected.
Testing Data Binnings.

Motivated by the question of data quantization and we revisit the problem of identity testing of discrete probability distributions. Identity testing (a.k.a. one-sample testing), a fundamental and by now well-understood problem in distribution testing, asks, given a reference distribution (model) 𝐪 and samples from an unknown distribution 𝐩, both over [n] = {1,2,… ,n}, whether 𝐩 equals 𝐪, or is significantly different from it.In this paper, we introduce the related question of identity up to binning, where the reference distribution 𝐪 is over k ≪ n elements: the question is then whether there exists a suitable binning of the domain [n] into k intervals such that, once binned, 𝐩 is equal to 𝐪. We provide nearly tight upper and lower bounds on the sample complexity of this new question, showing both a quantitative and qualitative difference with the vanilla identity testing one, and answering an open question of Canonne [Clement L. Canonne, 2019]. Finally, we discuss several extensions and related research directions.
A Wavelet-based Algorithm for the Computation of Intraseasonal Oscillations Intensity and Frequency Indices and Application to Central Africa

The rainfall modeling at regional scale remains a great challenge in the tropics because of the complexity of the processes that induce rainfall variability.Then the good parameterization of some atmospheric processes will be of great contribution towards the improvement of regional models.In this paper we applied wavelet transform on 2.5°×2.5°daily Outgoing Long-wave Radiation (OLR) datasets for the period 1981-2015 (35 years) to extract Intraseasonal Intensity (ISOI) and intraseasonal Period (ISOP), with application to Central Africa (CA).In fact for each grid point in the study area, the wavelet transform was applied to the 25-70-day filtered daily OLR time series and the wavelet spectrum is obtained.In the resulting spectrum, the maximum variance for each day is taken as ISOI and the period exhibiting that maximum variance is the ISOP.The plots of seasonal mean ISOI and ISOP obtained showed that the ISO characteristics (amplitude, frequency) strongly vary from season to another.The ISO amplitude is extremely high during December-February (DJF) and March-May (MAM) and lower during JJA and SON seasons.As for the period of oscillations, the ISOP peaks during MAM and JJA seasons.But for the four seasons, the period is predominantly contained between 40-50 days, suggesting the dominance of Madden-Julian Oscillation (MJO) signal.
Largest molecular quantum computation performed

Researchers have used a quantum computer to model the electronic energy of diazene isomerization ( 2020, DOI: ). The scientists and other experts say the demonstration will be a building block for more complex simulations. Classical computers encode information using bits, which can toggle between two states: 0 or 1. That means they can only encode approximations of electrons, which exist in quantum superpositions. Quantum bits (qubits) also exist in a superposition of states, meaning that one qubit can exactly represent one electron. Exact solutions on classical computers are impossible, but quantum computers may be capable of them. Researchers have previously modeled electronic states of simple atomic and . Google scientists have now successfully performed Hartree-Fock simulations of diazene isomerization using 10- and 12-qubit systems. Both were able to accurately predict transition-state energies as the molecule changed conformations. Current quantum computers are prone to errors, so the group paired Google’s
Double Attention-based Multimodal Neural Machine Translation with Semantic Image Regions

Existing studies on multimodal neural machine translation (MNMT) have mainly focused on the effect of combining visual and textual modalities to improve translations. However, it has been suggested that the visual modality is only marginally beneficial. Conventional visual attention mechanisms have been used to select the visual features from equally-sized grids generated by convolutional neural networks (CNNs), and may have had modest effects on aligning the visual concepts associated with textual objects, because the grid visual features do not capture semantic information. In contrast, we propose the application of semantic image regions for MNMT by integrating visual and textual features using two individual attention mechanisms (double attention). We conducted experiments on the Multi30k dataset and achieved an improvement of 0.5 and 0.9 BLEU points for English-German and English-French translation tasks, compared with the MNMT with grid visual features. We also demonstrated concrete improvements on translation performance benefited from semantic image regions.
Improved Compressed String Dictionaries.

We introduce a new family of compressed data structures to efficiently store and query large string dictionaries in main memory. Our main technique is a combination of hierarchical Front-coding with ideas from longest-common-prefix computation in suffix arrays. Our data structures yield relevant space-time tradeoffs in real-world dictionaries. We focus on two domains where string dictionaries are extensively used and efficient compression is required: URL collections, a key element in Web graphs and applications such as Web mining; and collections of URIs and literals, the basic components of RDF datasets. Our experiments show that our data structures achieve better compression than the state-of-the-art alternatives while providing very competitive query times.
ПРОЦЕСУАЛЬНА МОТИВАЦІЯ СТУДЕНТІВ ПІД ЧАС ЗМІШАНОГО НАВЧАННЯ ДІЛОВОЇ АНГЛІЙСЬКОЇ МОВИ

The article discusses the issue of improving the efficiency of teaching Business English to students of economic specialties using educational Internet resources. The described method of blended learning involves the active independent work of students with resources hosted on the platform www.edx.org and active discussion of the results of this work during the classroom. The results of the survey indicate a high motivation of students to learning Business English according to the main principles of the blended learning approach. According to the survey conducted in the framework of the first stage of experimental research, during the work with the offered educational materials of the Internet, the intrinsic motivation of students was at a high level. In particular, the students themselves found such work useful and effective for developing competence in listening, reading, writing and speaking. Observation of the practical classes showed that students’ involvement in the educational process has increased significantly. Students ‘subjective feelings about the effectiveness of their online learning resources were supported by objective data, including the students’ performance charts, which were recorded by the platform. All students successfully completed more than half of the proposed assignments. Based on the results of the study, it can be argued that the use of edx massive open online courses in the framework of blended learning method (both in Ukrainian and in a foreign languages) in the teaching practice of higher educational establishments is very promising for improving the quality of education not only in Business English but also in other professional disciplines. Moreover, the use of edx massive open online courses in the framework of blended learning method will help students to develop continuing education tools and high intrinsic motivation to use these tools in their future professional and personal growth.
Solving the disclosure auditing problem for secondary cell suppression by means of linear programming

National Statistical Institutes (NSIs) have the obligation to protect the privacy of individual persons or enterprises against disclosure of potentially sensitive information. For this reason, NSIs protect tabular data against disclosure of sensitive information before they are released. For tabular magnitude data, the starting point of this protection process usually is a sensitivity measure for individual cells. Such a sensitivity measure defines when a cell value is considered safe for publication or not. An often used method to protect a table with unsafe cells against disclosure of sensitive information is cell suppression. [5] argues that the standard criterion for deciding whether a table after suppression is safe or not is somewhat inconsistent and proposes a new criterion. [5] also gives a mixed-integer programming problem formulation for applying this new criterion. The problem with that formulation is that it is quite large and very hard to solve for even moderately sized tables. To be more precise, that mixed-integer programming problem formulation suggests that the auditing problem based on the criterion of [5] is NP-hard. The general assumption among operations research experts is that the computing time for NP-hard problems is non-polynomial in their input parameters. In the current paper, we propose solving a number of smaller and computationally much easier linear programming problems instead of solving one large mixed-integer programming problem. Solving linear programming problems can be done in time polynomial in their input parameters