Reviewerly/exHarmony huggingface dataset:
ECONOMIC ASPECTS OF CHILDREN’S NUTRITION ORGANIZATION IN SCHOOLS

The management of general secondary education (ZZSO) seeks financial autonomy by identifying sources of additional income, including by providing catering services based on functioning food units, which necessitates improving the level of catering services that will meet competitive conditions. This need increases the relevance of compliance with the principles of marketing in the process of organizing ZSSO this type of activity to meet the needs of consumers, increase their loyalty and, consequently, increase the level of income from the organization of food. The need to determine the range of possibilities for the application of marketing approaches and the potential of the marketing mechanism, which can be done using the methods of economic and mathematical modeling, in particular cognitive and scenario modeling, is gaining relevance. Research of the potential of the marketing mechanism of children’s nutrition organization in general secondary education institutions. To achieve this goal, the following tasks were performed: formed cognitive maps and cognitive model of the system of potential development of the marketing mechanism of children’s nutrition in ZSSO, based on the implementation of scenario modeling of system behavior identified factors influencing the development of marketing mechanism. The method (methodology). Methodological and theoretical foundations of the study are economic theory, scientific developments of scientists in the organization of children’s nutrition in the system of general secondary education. The research used general scientific methods (abstract-logical, empirical, comparative analysis, averages, generalizations, etc.) and methods of cognitive and scenario modeling. The article presents the results of the analysis of the system of potential development of the marketing mechanism on the basis of cognitive and scenario modeling, which allowed to determine the levers and performance factors of the system. According to the results of the study, it is concluded that a good basis for building the potential of the marketing mechanism to improve the nutrition of school children is to focus on maximizing customer satisfaction and increasing their loyalty while creating the necessary conditions to increase production efficiency and sales in school canteens. supported by activities to promote the principles of nutrition among students ZSSO and society as a whole. To this end, it is advisable to increase the level of automation of production and service processes in canteens ZSSO, information and communication support, stimulate the welfare of key actors of the marketing mechanism by coordinating the interaction of stakeholders in ensuring proper nutrition of children in educational institutions.
A Bayesian Account of Memory for Text

The study of memory for texts has had an long tradition of research in psychology. According to most general accounts, the recognition or recall of items in a text is based on querying a memory representation that is built up on the basis of background knowledge. The objective of this paper is to describe and thoroughly test a Bayesian model of these general accounts. In particular, we present a model that describes how we use our background knowledge to form memories in terms of Bayesian inference of statistical patterns in the text, followed by posterior predictive inference of the words that are typical of those inferred patterns. This provides us with precise predictions about which words will be remembered, whether veridically or erroneously, from any given text. We tested these predictions using behavioural data from a memory experiment using a large sample of randomly chosen texts from a representative corpus of British English. The results show that the probability of remembering any given word in the text, whether falsely or veridically, is well predicted by the Bayesian model. Moreover, compared to nontrivial alternative models of text memory, by every measure used in the analyses, the predictions of the Bayesian model were superior, often overwhelmingly so. We conclude that these results provide strong evidence in favour of the Bayesian account of text memory that we have presented in this paper.
HANet: Hybrid Attention-aware Network for Crowd Counting

An essential yet challenging issue in crowd counting is the diverse background variations under complicated real-life environments, which makes attention based methods favorable in recent years. However, most existing methods only rely on first-order attention schemes (e.g. 2D position-wise attention), while ignoring the higher-order information within the congested scenes completely. In this paper, we propose a hybrid attention-aware network (HANet) with a high-order attention module (HAM) and an adaptive compensation loss (ACLoss) to tackle this problem. On the one hand, the HAM applies 3D attention to capture the subtle discriminative features around each people in the crowd. On the other hand, with the distributed supervision, the ACLoss exploits the prior knowledge from higher-level stages to guide the density map prediction at a lower level. The proposed HANet is then established with HAM and ACLoss working as different roles and promoting each other. Extensive experimental results show the superiority of our HANet against the state-of-the-arts on three challenging benchmarks.
Micro Analysis of Natural Forking in Blockchain Based on Large Deviation Theory

Natural forking in blockchain refers to a phenomenon that there are a set of blocks at one block height at the same time, implying that various nodes have different perspectives of the main chain. Natural forking might give rise to multiple adverse impacts on blockchain, jeopardizing the performance and security of the system consequently. However, the ongoing literature in analyzing natural forking is mainly from the macro point of view, which is not sufficient to incisively understand this phenomenon. In this paper, we fill this gap through leveraging the large deviation theory to conduct a microscopic study of natural forking, which resorts to investigating the instantaneous difference between block generation and dissemination in blockchain. Our work is derived comprehensively and complementarily via a three-step process, where both the natural forking probability and its decay rate are presented. Through solid theoretical derivation and extensive numerical simulations, we find 1) the probability of the mismatch between block generation and dissemination exceeding a given threshold dwindles exponentially with the increase of natural forking robustness related parameter or the difference between the block dissemination rate and block creation rate; 2) the natural forking robustness related parameter may emphasize a more dominant effect on accelerating the abortion of natural forking in some cases; 3) when the self-correlated block generation rate is depicted as the stationary autoregressive process with a scaling parameter, it is found that setting a lower scaling parameter may speed up the failure of natural forking. These findings are valuable since they offer a fresh theoretical basis to engineer optimal countermeasures for thwarting natural forking and thereby enlivening the blockchain network.
Sanity Simulations for Saliency Methods.

Saliency methods are a popular class of feature attribution tools that aim to capture a model's predictive reasoning by identifying important pixels in an input image. However, the development and adoption of saliency methods are currently hindered by the lack of access to underlying model reasoning, which prevents accurate method evaluation. In this work, we design a synthetic evaluation framework, SMERF, that allows us to perform ground-truth-based evaluation of saliency methods while controlling the underlying complexity of model reasoning. Experimental evaluations via SMERF reveal significant limitations in existing saliency methods, especially given the relative simplicity of SMERF's synthetic evaluation tasks. Moreover, the SMERF benchmarking suite represents a useful tool in the development of new saliency methods to potentially overcome these limitations.
PENGGUNAAN MODEL GROUP INVESTIGATION (GI) UNTUK MENINGKATKAN HASIL BELAJAR SISWA PADA PEMBELAJARAN IPA DI KELAS IV SDN 15 PADANG SARAI KEC. KOTO TANGAH KOTA PADANG

Elementary school (SD) remains the top priority of the Indonesian government today. The increase in education is aimed at improving the quality of Indonesian people as a whole through exercise, thought, feeling, and sports in order to have competitiveness in facing global challenges.
한국어 초급 학습자의 학습동기와 탈동기 연구

The purpose of this study is to analyze the motivation and de-motivation factors of the beginner learners of Korean language. The survey was conducted for the self-determination motivation and de-motivation factors in 297 Vietnamese and Chinese learners studying at a Korean language institute in Seoul. According to the results of the study, the beginner learners of Korean language appeared to be intrinsic motivated. This study confirms previous research results that motivation is generally high in the early stages of learning. Among the de-motivational factors, ‘difficulty of learning’ was the most important factor in both groups. It is difficult to avoid the unfamiliarity and difficulties of Korean language itself, but a methodological approach to solve it in the teaching and learning process will be needed. Anxiety about learning failure also appeared to be an important motive for de-motivation, which is also closely related to external factors. (Hankuk University of Foreign Studies)
The impact of social networking sites on the lives of individuals within Palestinian society during the period 2015-2020 "Afield study applied to the residents of Bethlehem – Palestine": أثر مواقع التواصل الاجتماعي الإلكترونية على حياة الأفراد داخل المجتمع الفلسطيني خلال الفترة ما بين 2015 – 2020 " دراسة ميدانية مطبقة على سكان مدينة بيت لحم – فلسطين"

The aim of this research is to determine the extent of the impact resulting from electronic social networking sites with their various indicators on the lives of members of the Palestinian society in all aspects of living. The researcher has used the descriptive analytical method and the questionnaire tool in collecting field data, as the research community was a resident of the Palestinian city of Bethlehem located south The West Bank from all aspects of life and living for them, and the sample taken from the research community reached (888) individuals, with a percentage (3%) of the entire research community, and this research has reached a set of important results on this topic, one of the most important being that most users The reality of social media are from the young category, and that the most used website is Facebook compared to jealousy, as it turns out that the most affected aspects of life from electronic social networking sites are the social aspect, whose impact ratio has reached a value (1.90%) followed by the religious side, which came The percentage of being affected by social media has reached a value of (3.87%), then came the educational aspect, which has reached an impact rate of (4. 83%), then the behavioral aspect came with an impact rate of (3. 81%) then, culturally, at a value of (78%), as for the psychological aspect, which reached a value of 2.63%), another and the lowest of these values ​​came to the economic aspect, which reached a value (9.58%), thus forming the least effects resulting from the existence and use of sites. Electronic social networking within the Palestinian society. As for the nature of the relationship between social media and the aspects of life for members of Palestinian society, a strong and statistically significant relationship has emerged, and the nature of this relationship came in a direct way between each of the subscription period, the number of hours of daily use, the number of added friends, the goal of the subscription, and the number of sites The electronic system used and between the various aspects related to the life of the members of the Palestinian society represented in the social, religious, educational, behavioral, cultural, psychological and economic fields. At the end of the research, the researcher made a number of recommendations at the public and private levels that came from the most important of them. The time for awareness-raising by educational institutions represented in schools and universities to warn against the increase in the use of such sites and warn of the negative consequences resulting from them, and to identify the main issues in which the use of electronic social networking sites that are beneficial to the user are required, especially in social, behavioral, and other aspects.
Memoriam: Ronald Richard Butters (1940-2021)

References “Linguistic Change in Words One Owns: How Trademarks become ‘Generic’.” In Studies in the History of the English Language II, edited by Anne Curzan and Kim Emmons, 111–123. New York: Mouton de Gruyter. “A Linguistic Look at Trademark Dilution.” Santa Clara Computer and High Technology Law Journal 24, no. 3: 101–113. “Trademarks and Other Proprietary Terms.” In Dimensions of Forensic Linguistics, edited by John Gibbons and M. Teresa Turrell, 231–247. New York: John Benjamins. “Trademarking: Language That One Owns.” Routledge Handbook of Forensic Linguistics, edited by Malcolm Coulthard and Alison Johnson, 351–364. New York: Routledge. “Linguistic Issues in Copyright Law.” Oxford Handbook of Language and Law, edited by Lawrence Solan and Peter Tiersma, Oxford: Oxford University Press. “Semiotic Interpretation in Trademark Law.” In Law, Culture, and Visual Studies, edited by Anne Wagner and Richard Sherwin, 261–282. New York: Springer.
Precious and Critical Metal-Bearing Assemblages in the Ann Mason Copper Porphyry Deposit, Yerington, Nevada

Porphyry deposits are an important source of copper and their value may be upgraded by minor contents of precious metals, if they are extractable.The mechanisms for enrichment of precious and base metals in these systems are not well understood.This study investigates the deportment of trace metals in the Ann-Mason porphyry deposit, including gold, silver, palladium, mercury, lead and bismuth.Petrographic and geochemical data are integrated to characterise the size and habit of minerals, the host mineral assemblages, and their association with alteration assemblages.Ann-Mason is one of several ore deposits hosted by the Yerington batholith in Nevada, and is being assessed for copper extraction from bornite and chalcopyrite ore assemblages, associated with potassic alteration.Mineralisation assemblages at Ann-Mason have been categorised as chalcopyritebornite, chalcopyrite-pyrite and pyrite > chalcopyrite zones.Limited two-metre assay data indicates that gold is most closely associated with bornite, although it is found in all three mineralisation zones.Analysis by SEM-EDS shows that trace elements are mostly present as microparticles hosted by sulfide minerals.Of the 438 grains measured, 89% are hosted by a sulfide mineral, with 68% hosted by bornite.Silver is most commonly present as hessite and gold as electrum, hosted by bornite and associated with potassic alteration.Palladium, mercury and bismuth are most commonly observed as telluride and selenide minerals.Palladium minerals are associated with potassic alteration, while mercury and bismuth minerals are mostly found with sericitic alteration.High fineness native gold is observed as three round blebs hosted by pyrite or silicates.Observations suggest that the trace metals in the chalcopyrite-bornite zone may have been incorporated by bornite and chalcopyrite, and exsolved upon cooling.In the chalcopyrite-pyrite and pyrite > chalcopyrite zones, the trace metals may have been deposited directly from a mineralising hydrothermal fluid and incorporated into the growing sulphide minerals.These findings have implications for the paragenesis of porphyry deposits, as well as for the milling processes that would be needed to extract precious metals at the Ann-Mason porphyry deposit.
Identity Concealment Games: How I Learned to Stop Revealing and Love the Coincidences

In an adversarial environment, a hostile player performing a task may behave like a non-hostile one in order not to reveal its identity to an opponent. To model such a scenario, we define identity concealment games: zero-sum stochastic reachability games with a zero-sum objective of identity concealment. To measure the identity concealment of the player, we introduce the notion of an average player. The average player's policy represents the expected behavior of a non-hostile player. We show that there exists an equilibrium policy pair for every identity concealment game and give the optimality equations to synthesize an equilibrium policy pair. If the player's opponent follows a non-equilibrium policy, the player can hide its identity better. For this reason, we study how the hostile player may learn the opponent's policy. Since learning via exploration policies would quickly reveal the hostile player's identity to the opponent, we consider the problem of learning a near-optimal policy for the hostile player using the game runs collected under the average player's policy. Consequently, we propose an algorithm that provably learns a near-optimal policy and give an upper bound on the number of sample runs to be collected.
Optimal Parameter Selection for DWT based PCG Denoising

Analysis of PCG signals helps in diagnosis of cardio vascular disorder non-invasively. PCG signals are non-stationery in nature and hence time-frequency analysis of PCG is the most suitable means for analysis to determine the basic features of it. However, the PCG signals need to be denoised before feature extraction process and DWT proves to be most suitable for this purpose. During acquisition of HSS technically known as PCG various types of noises and artifacts contaminate the signal of interest. Hence denoising of the signal is inevitable before proceeding for diagnosis. DWT has been proved to be a powerful and handy tool along with thresholding for this purpose. However, the main challenge lies in the fact of selection of the suitable MWT with required number of DL and the type of thresholding function. The present work deals with the optimization of the selection process using varieties of MWT with varying DL and thresholding functions. Rigorous experiments have been conducted using codes in MATLAB environment to select the suitable MWT, DL and thresholding function. After optimization, the selected MWT, DL and Thresholding function have been applied on 22 PCG signals obtained from open data source and the performance of the process has been measured in terms of SNR and RMSE. It has been observed from the extensive experiments using different combination that sym20 wavelet with 10 decomposition level along with Bayesian Soft thresholding function provide the best result in denoising the applied PCG signals. The database used is that of MHSDB available at www.med.umich.edu/Irc/psb/heartsounds/index.htm provided by the University of Michigan Health System.
Using Formants to Extract Short Vowels from Arabic Words with (Consonant Vowel)&amp;lt;sup&amp;gt;3&amp;lt;/sup&amp;gt; Structure

Arabic texts suffer from missing short vowels.Arabic Speech Recognition is not as good as English speech recognition due to the short vowels not being recognized.And the Arabic language is unlike the English language in characteristics such as the number of vowels.English has more than 24 vowels that are close to each other in pronunciation.The Arabic language only has three short vowels that are far from each other in utter and measurement, by elongating those short vowels, long vowels arose.Researchers said that the vowels could be recognized using formants.The formants' measurements of Arabic vowels are far from each other too, so it is possible to recognize them so that Arabic Speech recognition can give more accurate results.The paper applies this idea to the corpus Phonemes of Arabic.It uses the Euclidian distance method to measure the distances between formant values to recognize Arabic from words with a CV3 structure, the Linear Predictive Coding method and MATLAB to develop the programs that will extract the formants and calculate the means of the short vowels by using the corpus to identify the short vowels within words in the corpus.The results showed that if highly qualified readers were chosen to read the Arabic text, then higher rates of recognition of the short vowels involved in words will be achieved.This paper revealed that some of the characteristics of a language can be utilized for vowel recognition or to enhance the existing methods for speech recognition.
Evolutionary Encryption Algorithm Ensuring Privacy in Video Surveillance

The widespread use of video surveillance and the development of embedded information processing systems raise the issue of affecting the confidentiality and integrity of video data and even the individuals’ privacy. In order to secure the content of video and protect the public privacy, we propose a new system for detecting and encrypting regions of interest (ROIs). The ROI detection is based on an improved Gaussian mixture model where we use supervisors to control the changes in the image. The regions of interest encryption is performed through the use of an enhanced evolutionary encryption algorithm, exploiting the representation of the RGB color space to get real time system. Results and comparisons presented in this paper show that the proposed scheme can effectively detect and obscure the identity of people to achieve the privacy protection.
문재인 대통령의 SNS 정치 담화에 대한 텍스트언어학적 분석

This study analyzed the political discourse of social network service through the Twitter of President Moon Jae-in from a textlinguistic perspective. The analysis process is to discover the linguistic characteristics of the text using an analytical framework that divides the text of President Moon’s tweets into three dimensions: comprehensive identity, verbal strategy, visual element based on the New literacies. The results of comprehensive identity analysis are ‘presupposing the legitimacy of government by the people, emphasizing national and government identity, suggesting solutions and giving the government responsibility.’ The results of verbal strategy analysis are ‘introducing public emotion by introducing individual stories, transformating and directing specific objects, presenting the problem in contrast.’ The results of the visual image analysis are ‘visualizations focused on facial expressions or postures’, ‘it is characteristic of visualization that presents real life’. President Moon’s Twitter is a digital environment in which communication with the people takes place. Through the media, various strategies for communication with the people can be seen.
Using cellphone-based games in EFL instruction

The advent of technology has influenced education, even in the most remote parts of the world. Nowadays, it is totally normal for a person to have some technological devices such as laptops, iPads, tablets, and especially cell phones. Ecuador is not far from this reality. Moreover, in the English Language Learning Standards, the Ministry of Education suggests using technological resources in teaching (eg internet, software, computers and related devices). Given this warm welcome to the use of technology in Ecuador’s English classes, as well as the number of students using cell phones in Ecuador, this chapter is intended to provide basic information on the use of cell phone games within English class.