Reviewerly/exHarmony huggingface dataset:
Formation of information culture of Ukrainian students

Ukraine has entered the phase of the information society. The process of development of the information society is connected with the intensive processes of formation of a new educational paradigm, which is replacing the classical one. The modern man must not only have a certain amount of knowledge, but also be able to learn: to seek and find the necessary information to solve certain problems, to use various sources of information for this purpose, to constantly acquire additional knowledge. The article proposes the means for forming the information culture of Ukrainian students.
The Big Bass Liftoff Scenario

Author(s): Hull, Mark A. | Abstract: This music score was submitted for the Kaleidoscope 2020 Call for Scores, an open access collaboration with the UCLA Music Library.
IMPROVING STUDENTS READING COMPREHENSION OF VIII GRADE STUDENTS AT SMP NEGERI 1 DAKO PEMEAN THROUGH HERRINGBONE TECHNIQUE

This study is conduct to find out whether there is a significant difference between reading comprehension ability of students at SMP Negeri 1 Dako Pemean who are teach by using Herringbone technique. The method use is experimental method. The instrument for collecting the data is a reading comprehension test. It is conduct in one class (VIII C). The data are obtained through a pre-test and post-test. The researcher use SPSS 16.0 program to analyze the data collection. The result of the analysis show that the application of Herringbone technique improve students’ ability in reading comprehension. The mean score of pre-test is 39.30 while in the post-test improve up to 73.43. Moreover the minimum mastery criterion of English lesson is 65 (sixty-five). Then the data of both test are analyzed by using T- test , and the result show that the T- count value is 13.074 greater than T- table value is 2.074. it can be inferred that the application Herringbone technique is very effective to improve students’ ability in reading comprehension. Keywords : Improving, reading comprehension, Herringbone technique
Cloud resource prediction model based on triple exponential smoothing method and temporal convolutional network

The container cloud represented by Docker and Kubernetes has the advantages of less additional resource overhead and shorter start-up and destruction time.However there are still resource management issues such as over-supply and under-supply.In order to allow the Kubernetes cluster to respond “in advance” to the resource usage of the applications deployed on it,and then to schedule and allocate resources in a timely,accurate and dynamic manner based on the predicted value,a cloud resource prediction model based on triple exponential smoothing method and temporal convolutional network was proposed,based on historical data to predict future demand for resources.To find the optimal combination of parameters,the parameters were optimized using TPOT thought.Experiments on the CPU and memory of the Google dataset show that the model has better prediction performance than other models.
Acceptance of Accounting Information Systems in Saudi Banks in the Light of the Corona Pandemic: A Pilot Study

Aim: Accounting Information Systems (AIS) exchange identified to reduce on associated costs and improves banks efficiency. Nevertheless, as a result of the impacts associated with Covid-19 pandemic the preference to use (AIS). The study below examines the factors associated with effect on (AIS), acceptance of Use of Technology (UTAUT2) model and Unified Theory of Acceptance. This has been highlighted as the new methodology that is used on the evaluation acceptance of (AIS). The study proposes to use a theoretical model to give an explanation on the exercise of behavior of accountants when they use the (AIS).Methods: the study bases its results by conducting a pilot test in Saudi Arabia banks by collecting data from different accountants in different departments who are identified to be familiar in using Accounting Information Systems (AIS). The study collected data from 120 responses questionnaires that were collected during the pilot study.
SECURE AND HIGH-SPEED CRYPTOGRAPHY ARCHITECTURAL DESIGN TECHNIQUES FOR INTERNET OF THINGS

Providing protection for the exchanged statistics performs a key role inside the modern-dayworld unsecured contact among IoT devices. As the technology develop giant portions of information are beingexchanged, call for secure standards of encryption is as a result increasing. Security is more desirable so that inthe center of the facts attack with the aid of intruders it isn't always possible for the guys to be inside theconversation link. The protection method was carried out the use of the principle of symmetric, asymmetric, andhash algorithms. Elliptic Curve Cryptography is accomplished to encrypt and share the secret AES key amongsender and receiver, As well because the Sophisticated Encryption Method for the encryption / decryption of thereceiving data. In this paper, especially green architectures are carried out to ensure statistics conversationamong users in the IoT perceptual layer via related to initialization, authentication technique and key generation,other than encryption. Sender combines facts encryption and key encryption earlier than it is despatched to thereceiver with signature schemes. The receiver verifies the signature and decryption of the key applied to realizeoriginal statistics transmitted among the Perceptual Layer devices within the Internet of Things.
Deep F-measure Maximization for End-to-End Speech Understanding

Spoken language understanding (SLU) datasets, like many other machine learning datasets, usually suffer from the label imbalance problem. Label imbalance usually causes the learned model to replicate similar biases at the output which raises the issue of unfairness to the minority classes in the dataset. In this work, we approach the fairness problem by maximizing the F-measure instead of accuracy in neural network model training. We propose a differentiable approximation to the F-measure and train the network with this objective using standard backpropagation. We perform experiments on two standard fairness datasets, Adult, and Communities and Crime, and also on speech-to-intent detection on the ATIS dataset and speech-to-image concept classification on the Speech-COCO dataset. In all four of these tasks, F-measure maximization results in improved micro-F1 scores, with absolute improvements of up to 8% absolute, as compared to models trained with the cross-entropy loss function. In the two multi-class SLU tasks, the proposed approach significantly improves class coverage, i.e., the number of classes with positive recall.
Webly Supervised Semantic Embeddings for Large Scale Zero-Shot Learning

Zero-shot learning (ZSL) makes object recognition in images possible in absence of visual training data for a part of the classes from a dataset. When the number of classes is large, classes are usually represented by semantic class prototypes learned automatically from unannotated text collections. This typically leads to much lower performances than with manually designed semantic prototypes such as attributes. While most ZSL works focus on the visual aspect and reuse standard semantic prototypes learned from generic text collections, we focus on the problem of semantic class prototype design for large scale ZSL. More specifically, we investigate the use of noisy textual metadata associated to photos as text collections, as we hypothesize they are likely to provide more plausible semantic embeddings for visual classes if exploited appropriately. We thus make use of a source-based voting strategy to improve the robustness of semantic prototypes. Evaluation on the large scale ImageNet dataset shows a significant improvement in ZSL performances over two strong baselines, and over usual semantic embeddings used in previous works. We show that this improvement is obtained for several embedding methods, leading to state of the art results when one uses automatically created visual and text features.
빈도성과 시간적 국소 한정성의 상관관계: 한국어의 문법적 연어를 중심으로

The purpose of this paper is to ascertain an interrelation between usuality and temporal localization in Korean with special reference to grammatical collocations -nun pep-i-ta, -ki ma-lyen-i-ta, -ki sip-sang-i-ta, -ki il-sswu-i-ta and -ki-to ha-ta. Considering these grammatical forms from syntactic and semantic viewpoints and in terms of usuality and temporal localization, we have come to the following conclusions: (1) While -ki-to ha-ta represents both positive and negative aspects of a proposition, the other forms represent only the positive side of it. (2) The higher the usuality represented by one grammatical collocation is, the weaker its temporal localization becomes. On the other hand, the lower the usuality is, the stronger its temporal localization becomes. Hence, usuality is inversely proportional to temporal localization.
APPLICATIONS OF FUZZY TWO AND FOUR RULES FOR SEGMENTATION OF BLOOD CELLS

The effective diagnosis of blood disorders is one of most important problems in image processing in biomedicalengineering. It is done by careful microscopic examination of stained blood smear. In performing morphologicalanalysis of blood slides under microscope, haematologistsexperience tiredness, resulting in inaccurate reports. Tobetter analyse and examine stained blood quantitatively and qualitatively, microscope images for accuratesegmentation and detection, fuzzy rule-based image segmentation is used in this work. The results presented arebased on parameters edge strength and entropy values. Results obtainedby fuzzy two and four rule techniquearecompared with the results with different methods by graphical representation. The entropy values of Fuzzy-2 and 4rule based entropy showed better values than its previous techniques
PERFORMANCE EVALUATION OF ELM WITH A-OPTIMIZED DESIGN REGULARIZATION FOR REMOTE SENSING IMAGERY CLASSIFICATION

Abstract. The automatic classification technology of remote sensing images is the key technology to extract the rich geo-information in remote sensing images and to monitor the dynamic changes of land use and ecological environment. Remote sensing images have the characteristics of large amount of information and many dimensions. Therefore, how to classify and extract the information in remote sensing images has become a crucial issue in the field of remote sensing science. With the development of neural network theory, many scholars have carried out research on the application of neural network models in remote sensing image classification. However, there are still some problems to be solved in artificial neural network methods. In this study, considering the problem of large-scale land classification for medium resolution and multi-spectral remote sensing imagery, an improved machine learning algorithm based on extreme learning machine for remote sensing classification has been developed via regularization theory. The improved algorithm is more suitable for the application of post-classification change monitoring of features in large scale imaging. In this study, our main job is to evaluate the performance of ELM with A-optimal design regularization (here we call it simply as A-optimal RELM). So the accuracy and efficiency of A-optimal RELM algorithm for remote sensing imagery classification, as well as the algorithms of support vector machine (SVM) and original ELM are compared in the experiments. The experimental results show that A-optimal RELM performs the best on all three different images with overall accuracy of 97.27% and 95.03% respectively. Besides, the A-optimal RELM performs better on the details of distinguish similar and confusing terrestrial object pixels.
THE ANALYSIS OF STUDENTS’ MOTIVATION IN USING ENGLISH ABBREVIATION ON WHATSAPP GROUP (A Case Study of the Seventh Semester Students of English Education Department of IAIN Salatiga)

Astuti, Fitriana. 2020.The Analysis Of Students’ Motivation In Using EnglishAbbreviation On Whatsapp Group (A Case Study of the Seventh Semester Students of English Education Department of IAIN Salatiga). A Graduating Paper. EnglishEducation Department. Teacher Training and Education Faculty. StateInstitute for Islamic Studies of Salatiga. Counselor: Dr. Ruwandi, S. Pd., M.A.This research aims to 1) To describe the types of abbreviation used in WhatsApp group, 2) To describe what the abbreviations stand for, 3) To describe students’ motivation in using abbreviation in WhatsApp group. This is a descriptive qualitative research. The object of the study is abbreviations found in WhatsApp chat group. The data of this research are abbreviations used in the WhatsApp chat group and the reasons of the users to use them. The researcher used documentation to collect the data found in the WhatsApp group. The result shows that there are 14 abbreviations used. There are 6 contractions, 2 acronyms, 3 initials, and 4 clipping words. The motivations of students’ used abbreviation are to simplify or/and to shorten the long text, the abbreviations used are those familiar or/and the readers have understood, because of tired or are lazy to type, and as a trend or demand of modernity. Keywords: Students’ motivation in using English abbreviation, WhatsApp group
An Analyisis of Grammatical and Lexical Cohesion Used in Scientific Article

There are so many ways for people to communicate and interact with others and one of it is a text. Text can be analyzed by using discourse analysis theory. There are two fundamental aspects in discourse analysis. They are cohesion and coherence. This study aims to describe what are the types of grammatical and lexical cohesions used in the scientific articles, and what are the grammatical and lexical mostly used in the scientific articles. Cohesion occurs where the interpretation of some element in the discourse is dependent on that of another (Halliday & Hasan,1976). It can be said that cohesion is a tool to analyzed the discourse. The cohesion devices separated into two forms. First, grammatical cohesion consists of reference, substitution, ellipsis, and conjunction. Second, lexical cohesion consists of reiteration and collocation. This research used descriptive qualitative and quantitative research. The object of this study is scientific articles, especially from Journal of English Language and Education. In this research there are five articles which has been discussed. The technique of collecting the data: Identifying the fragment that contained grammatical and lexical cohesion devices. Technique of analyzing the data were: (a) read each words of the text, (b) give marks the data that related to the subject of this study, (c) put the data into the table, and (d) conclusion. Based on the results, the grammatical cohesion were found in The Journal of English Language and Education namely : 23 references, 2 substitutions, 5 ellipsis, and 16 conjunctions while lexical cohesion : 6 repetitions, 3 synonyms, and 2 superordinate. The total of cohesion devices were found in five journals both of grammatical and lexical cohesion, there are : 46 devices. Devices which are the most appear in the journals was reference with 23 data. Keywords : Discourse analysis, grammatical cohesion, lexical cohesion.
Reaching Commercial Deployment of Electric Road Systems : Barriers and Opportunities from the Perspective of eRoadArlanda

This master's thesis is written on behalf of the Royal Institute of Technology and the Swedish Transport Administration. The purpose of the study was to investigate, from a theoretical framework, t ...
An Analysis of category shifts in the Geostorm movie

In social life, if people can speak in many languages it will be sufficient. But in translation it is different. It is not enough when a translator just changes word from source language (SL) into target language (TL). Translation is process of transferring data or message from SL into TL. It is not only just changing word by word by using dictionary but there some elements that people have to know before doing translation. Usually, people find translation process in novels, songs, movies, or even poems. In this research, researcher focused on translation of a movie. Movie is one of entertainment objects. by watching movies audiences can get some inspiration or something new from movies. Geostorm is one of interesting subjects to be analyzed in terms of translation of category shifts. Therefore, purposes of this research are to examine kinds of category shifts and also examine influences of category shifts in equivalence of meaning of source language and target language. According to Catford (1978: 73), shift is departure from formal correspondence in process of translating from SL into TL. Translation shift has two main types, namely level shifts and category shifts. According to Catford (1965: 76), there are four types of category shifts: there are structural shifts, unit shifts, class shifts, and intra-system shifts. According to Nida and Taber (1982), there are two types of equality namely formal equivalence and dynamic equivalence. Formal equivalence focuses on content and meaning of message itself, both in form and content. And, dynamic equivalence is based on the principle of equal effects. Where, degree of equivalent meaning is comparison of texts in various languages which include theory of equality. This research used qualitative research methods. The qualitative method was used because this research focused on observation data and possible reasons how category shifts happen in process of translation. The research procedures used were collecting data, analyzing data that is translation shifts from Geostorm movie, giving explanations, and drawing conclusions. The source data of this research is an American science fiction disaster movie, Geostorm . The results of this research were devided into two parts. The first is researcher found four categories of category shift namely structure shift, class shift, unit shift, and intra-system shift. All shifts that researcher found is not in same frequency, they have their own number. The researcher found 70 cases from 51 data of all shift occurred in Geostorm movie and its subtitle. Based on researcher analysis, unit shift is highest frequency occurred in translation of subtitle of Geostorm movie, with 27 cases out of all 70 cases. The second is category shifts and researcher also found all of that types and sub types. Based on analysis, complete meaning is highest frequency with 25 cases out of all 68 cases. Keyword: translation shift, category shift, degrees of meaning equivalent.
SimPatch: A Nearest Neighbor Similarity Match between Image Patches

Measuring the similarity between patches in images is a fundamental building block in various tasks. Naturally, the patch-size has a major impact on the matching quality, and on the consequent application performance. We try to use large patches instead of relatively small patches so that each patch contains more information. We use different feature extraction mechanisms to extract the features of each individual image patches which forms a feature matrix and find out the nearest neighbor patches in the image. The nearest patches are calculated using two different nearest neighbor algorithms in this paper for a query patch for a given image and the results have been demonstrated in this paper.
Personalized rankings of educational institutions

Education is one of the important research domains and building intelligent systems is one of the most exciting applications of Artificial Intelligence. A challenging problem in this domain, which involves a lot of potential users and data, is to find a suitable educational establishment that can match the particular preferences and needs of people. Although there exists a number of known national and international ranking lists, however, almost all of these rankings are non-personalized and offer the same lists of schools to absolutely different people. This thesis addresses this problem and presents the design, implementation and evaluation of a personalized recommendation system in the education domain. The system is capable of eliciting preferences from its users, learn from the preferences, and intelligently generate a personalized ranking list of educational institutes for each target user. The quality of the suggested ranking lists has been evaluated in a real user study, and measured in terms of accuracy, diversity, novelty, satisfaction and capability to understand the particular preferences of different users. The results have shown that the users have been satisfied with the quality of the personalized ranking lists and assessed the system as a usable system.
Objective Perceptual Quality Assessment of JPEG2000 Image Coding Format Over Wireless Channel

A dominant source of Internet traffic, today, is constituted of compressed images. In modern multimedia communications, image compression plays an important role. Some of the image compression stan ...
Vocabulary Improvement in EFL Writing through Narrative and Expository Texts

The purpose of this study is to investigate the effect of narrative and expository texts on incidental vocabulary learning of Korean university EFL learners while reading. The experimental groups were divided into 3 groups. The first experimental group were exposed to narrative texts and second group received expository texts. And the third group were administered narrative and expository texts alternately. The vocabulary tests were conducted after the last session to assess the incidental vocabulary gains of the learners. The results indicated the superiority of the expository texts over narratives in terms of enhancing learners' incidental acquisition of unknown words. Moreover, the results showed that the blended reading group of expository and narrative texts did better on the vocabulary gains than those of narrative reading group and expository reading group. However, in the essay writing assessment, the expository group committed the most vocabulary errors in writing.
Disponibile la versione italiana dell’Open Science Training Handbook

Expectations towards librarians, following the latest and less recent developments of the digital revolution, have further broadened and deepened with the introduction of a new model of doing, disseminating and valuating research. Libraries’ traditional mission seems to have developed from storing and delivering knowledge into also helping to create and communicate new knowledge through the implementation of the Open Science principles. By making the Open Science Training Handbook available in Italian, colleagues will find inspiration and ideas for effective information and training events and help the establishment of Open Science practices. In the fact, not only the tasks of librarians have evolved: While they once used to be isolated and stationary, today they increasingly need to be networked, to venture new forms of collaboration and communication. Our experience of collective translation has shown just one way to go.