Reviewerly/exHarmony huggingface dataset:
IMPROVING STUDENTS’ SPEAKING ABILITY THROUGH DEBATE TECHNIQUE

Lecturers can use many strategies to improve speaking ability. Speaking abilities include making questions, providing explanations, and also being able to provide answers. This study aimed to determine how debate techniques can improve students' speaking ability to make questions, give explanations, and give responses. The current study applied the classroom action research method and consisted of 3 cycles. Two batches of English Education College Students of 2019/2020 at Universitas Potensi Utama, totaling 60 students, were involved as the study subjects. An observation checklist and field notes were used to collect the data. The researchers observed students' activity in the classroom by using an observation checklist and fieldnotes. The researchers summarized the problem during the debating process. Based on the research findings, the debate technique applied by the research subjects reflects the improvement in the students' speaking ability. Based on the observations' results, it can be seen that the students' speaking ability in making questions and providing explanations and answers improved. The students' activities in the class when arguing in the first cycle were 42.83%, 59.17% in the second cycle, and 85.17% in the final one. It shows that the debate technique has improved the students' speaking ability to make questions and provide explanations.
Problems and solutions for assessing the knowledge of students in distance learning

To improve the quality of education, the management process distance learning has been built systematically. The concept of a quality assessment system for distance learning presupposes the presence of diagnostic and evaluative procedures implemented by various subjects of state administration entity. It has been delegated separate powers to assess quality of education, as well as a set of organizational structures and normative legal materials ensuring the quality of education. As a rule, assessing tasks with the level of knowledge set quality control helps. It is designed and intended to provide feedback and collect basic information that will allow teachers to judge on the effectiveness of the distance learning process, as well as a system control needs to be developed. Taking into account the basic requirements in this system is imperative. Individuality, consistency, variety of forms and methods, comprehensiveness is considered as key factors. In addition, summative assessment should cover all passed material, objectivity, reliability, trustworthiness and validity.
Experimental Study of Some Properties of Knowledge Distillation

For more complex classification problems it is inevitable that we use increasingly complex and cumbersome classifying models. However, often we do not have the space or processing power to deploy these models.Knowledge distillation is an effective way to improve the accuracy of an otherwise smaller, simpler model using a more complex teacher network or ensemble of networks. This way we can have a classifier with an accuracy that is comparable to the accuracy of the teacher while small enough to deploy.In this paper we evaluate certain features of this distilling method, while trying to improve its results. These experiments and examinations and the discovered properties may also help to further develop this operation.
ARSENIC AND OTHER METALS CONTAMINATION IN GROUND WATER RESOURCE IN DAK NONG PROVINCE, VIETNAM

This study aimed at understanding the concentrations of selected heavy metals including arsenic, iron, manganese, cadmium and mercury in groundwater used for domestic purposes in Dak Nong Province of Vietnam. A total number of 572 groundwater samples including 61 duplicates were collected during October, 2018 – April, 2019. The collected samples were measured onsite for pH and preserved with 2% HNO3 before being analyzed in the laboratory for heavy metals by inductively coupled plasma mass spectrometry. The relative percent differences of all duplicate samples were less than 30%, indicating that the analytical results were within acceptable ranges. The average concentrations of As, Fe, Mn, Cd, Hg and Pb in groundwater were 9.53±46.36, 307.1±1,178, 166±478, 4.66±6.2, 1.0±1.8 and not detected, respectively. Amongst all the analytical results, however, some values on the concentrations of studied metals exceed the Vietnamese regulation values for groundwater quality and for domestic use requirements. The research results therefore suggest that groundwater containing rather high concentrations of heavy metals at the studied area should not readily be used for domestic purposes without proper treatments.
PENGUKURAN MINAT BACA MAHASISWA DENGAN METODE CLUSTERING DI PERPUSTAKAAN AKADEMI KEPERAWATAN RS.DUSTIRA CIMAHI MENGGUNAKAN DATA MINING

Based on the results of research to measure students' reading interest in Akper RS. Dustira Cimahi Library can be done by using clustering method. In this study using library data, namely Akper RS. Dustira Cimahi library database. taken from three main table sources such as visitorlog table, collection table and member table which will then be integrated and selected so that it can be put together into a data warehouse. In using data mining, checking the title of the book collection to find out the title of the book that is in great demand by students and students of what level borrows the most books and also the most books read in Akper RS. Dustira Cimahi library. From this information, it can be concluded that final-level students prefer to borrow and read books than students who are still in the early semester. The book with the title Introduction to Basic Human Needs is most in demand and widely borrowed and read while the title of the collection of books that are very little borrowed and read is a book with the title Learn Computer Science. By using the cluster method it can be known that the category of Nursing books is a book that is in great demand by students while Computer Science books belong to the category of book collections that are very little in demand by all nursing students. Keywords: Clustering Method, Data Mining, Collection Table, Member Table, Visitorlog Table.
A Novel Layer Sharing-based Incremental Learning via Bayesian Optimization

Incremental learning means the methodology that continuously uses sequential input data to extend the existing network&rsquo;s knowledge. The layer sharing algorithm is one of the representative methods which leverages general knowledge by sharing some initial layers of the existing network. In this algorithm, estimating how much initial convolutional layers of the existing network can be shared as the fixed feature extractors for incremental learning should be solved. However, the existing algorithm selects the sharing configurations through not a proper optimization strategy but a brute force manner. Accordingly, it has to search for all possible sharing layer cases, leading to high computational complexity. To solve this problem, we firstly define this problem as a discrete combinatorial optimization problem. However, this problem is a non-convex and non-differential optimization problem which can not be solved using the gradient descent algorithm or other convex optimization methods, even though these are the powerful optimization techniques. Thus, we propose a novel efficient incremental learning algorithm based on Bayesian optimization, which guarantees the global convergence in a non-convex and non-differential optimization problem. And the proposed algorithm can adaptively find the optimal number of sharing layers via adjusting the threshold accuracy parameter in the proposed loss function. The proposed method produces the global optimal sharing layer number in only 6 iterations without searching for all possible layer cases in experimental results. Hence, the proposed method can find the global optimal sharing layer and achieve both high combined accuracy and low computational complexity.
Retrieval of Shape using Curves and Contours

Proposed method is dealing with multi-dimensional data modeling, extrapolation and interpolation using the set of high-dimensional feature vectors. Identification of handwriting, signature, faces or fingerprints need data modeling and each model of the pattern is built by a choice of characteristic key points and multi-dimensional modeling functions. Novel modeling via nodes combination and parameter γ as N-dimensional function enables data parameterization and interpolation for feature vectors. Multi-dimensional data is modeled and interpolated via different functions for each feature: polynomial, sine, cosine, tangent, cotangent, logarithm, exponent, arc sin, arc cos, arc tan, arc cot or power function.
Intellectualization Of Modern Robotic Systems Used In Doctor Training

Since no simulator is able to evaluate and work out the skill of communicating with a patient, there is a need to determine the capabilities of artificial intelligence in the process of training doctors. Artificial intelligence must meet many requirements, but primarily creative functions that are unique to humans. Artificial intelligence has already found application in many industries, including the training of medical personnel for the harmonious and holistic development of a specialist.
Enriching English in School Education: Some Problems and Principles

English is a widely used language in international communication. It is a storehouse of knowledge that most of the books, and journal articles have been published in English, and it is the dominant language in the Internet. Realizing this fact, the government of Nepal has made English one of the core components of school education curricula. However, teaching and learning of English in the schools in Nepal has been influenced by several problems. Using systematic literature review as the methods, this article makes an attempt to highlight the major problems that exist in teaching and learning of English in school education in Nepal, and points out some principles for enriching English in the learners. This study has been expected to add at least some insights to those who are interested in enhancing English education in Nepal.
The Innovation of batteries and inverters as energy saving technology without fuel

Electrical energy is a primary need in modern human life. However, with the increase in fuel prices, the right technology is needed to overcome it, in the form of battery and inverter innovations which are combined to produce an output of 220 volts ac which has the same capacity as PLN electricity. This PkM DPRM activity was held in Manggar Village for 3 days, namely @ u on July 30, August 3 and August 4, 2020 which was attended by fishermen, fried food traders and Manggar Village employees themselves. The equipment is designed with a capacity of 300 watts and 1000 watts, tailored to the needs of the residents. The benefit greatly eases the use of diesel generator sets for fishermen, which from Rp. 108,000 / month, has now become Rp. 0, -. Likewise for fried food traders, who originally paid Rp. 70,000 / month for electricity for lighting at night, now it is Rp. 0, -. Based on the results of the questionnaire, participants are very grateful for the presence of this technology in their village. At least the motivation for other residents to implement these tools in everyday life.&#x0D; Keywords: power plants without fuel, save energy, fuel, lighting, manggar kelurahan&#x0D; &#x0D; &#x0D; &#x0D; &#x0D; &#x0D; &#x0D;
Introduction to the Special Theme on Models and Evolution.

In general, software artefacts and applications are subject to many kinds of changes at all levels, from requirements through architecture and design, to source code, documentation and test suites.They typically affect various kinds of models, and for this reason managing the evolution is therefore an essential discipline.This JOT theme issue takes directly his roots
Simile in Harry Potter and The Chamber of Secrets

This research focused on simile analysis and meaning on Harry Potter and The Chamber of Secrets novel. Simile is a figurative language that makes a comparison, showing similarities between two different things. Qualitative research is used in conducting this research. The result of the research has found 55 sentences of Simile on Harry Potter and The Chamber of Secrets from chapter one up to chapter nine. The author used Simile to describe emotion of characters, to explain circumstances and to raise the interesting impression in the novel.
Αναγνώριση σημαίνει ενοχή; Mια ανασκόπηση των παραγόντων επιρροής της επίδοσης των αυτοπτών μαρτύρων

Eyewitness identification stands as one of the core aspects of the judicial system. However, when it comes to identifying faces, people often make mistakes. Thus, it should not come as a surprise that eyewitness identification has been shown to be the number one factor of wrongful convictions (www.innoccenceproject.org). Therefore it is importantto understand the reasons that make eyewitnesses so error prone and investigate how we could enhance their performance. In the present article we examine the factors that have an impact on eyewitnessidentification performance. More specifically, we will refer to those variables over which the research community has reached consensus. These include estimator and system variables as well as postdictors,which are variables capable to diagnose the identification accuracy once it has taken place. In doing so we aim to reveal those parameters that are based on a sturdy research base, but have notwithstanding beenneglected by the Greek judicial system. We suggest a number of alterations and improvements, based on this research basis that can improve identification performance.
Secure Image of Reversible Data Hiding and Deep Learning Algorithms for Image Reconstruction

Steganography is one of the powerful techniques in data hiding.It is the branch of secret communication where the cover image is recovered after the embedded data is extracted from the stego image.One of the applications of steganography is Reversible Data hiding (RDH) and deep learning.RDH is the method in which original cover can be losslessly recovered after the embedded message is extracted.Deep learning models are well known as deep black boxes in which the process from the input to the output is very complex, and thus the deep learning model for information hiding is almost impossible for opponents to reconstruct.An attempt has been made to present a Threshold Based Reversible Data Hiding (TBRDH) and deep learning by creating space before encryption and different metric parameters like mean square error, PSNR, SSIM, NAE and NCC are calculated for the cover image and reconstructed image.
Natural mapping between voice commands and APIs

Abstract After a voice control system transforms audio input into a natural language sentence, its main purpose is to map this sentence to a specific action in the API (application programming interface) that should be performed. This mapping is usually specified after the API is already designed. In this paper, we show how an API can be designed with voice control in mind, which makes this mapping natural. The classes, methods, and parameters in the source code are named and typed according to the terms expected in the natural language commands. When this is insufficient, annotations (attribute-oriented programming) are used to define synonyms, string-to-object maps, or other properties. We also describe the mapping process and present a preliminary implementation called VCMapper. In its evaluation on a third-party dataset, it was successfully used to map all the sentences, while a large portion of the mapping was performed using only naming and typing conventions.
Rational Expectations in Games

A player i's actions in a game are determined by her beliefs about other players; these depend on the game's real-life context, not only its formal description. Define a game situation as a game together with such beliefs; call the beliefs— and i's resulting expectation—rational if there is common knowledge of rationality and a common prior. In two-person zero-sum games, i's only rational expectation is the game’s value. In an arbitrary game G, we characterize i's rational expectations in terms of the correlated equilibria of the doubled game 2G in which each of i's strategies in G appears twice. (JEL C72, D83, D84) (This abstract was borrowed from another version of this item.)
Virtual Currency And Global Business - The New Trend In The Net-Economy

The rapid development of information technology has made generating cryptocurrencies and fast, cheap and uncontrollable transactions using virtual space possible. Among virtual currencies, Bitcoin is considered to be a major challenge for traditional financial operations, and especially for the fight against money laundering and terrorist financing. This article presents the following points of discussion: the spectacular appearance of Bitcoin, its exponential evolution, its popularity, its growing demand, lack of anonymity and predictability, the cross-border nature of transactions.
THE FINANCING OF INFORMATION SECURITY MANAGEMENT IN ENTITIES PERFORMING MEDICAL ACTIVITIES

All healthcare organizations process “sensitive data” that needs special protection. To ensure an appropriate level of security for this data, it is necessary to allocate adequate financial resources for security measures. The exploratory aim of the research here is the recognition of the current state of information security management systems in selected entities performing medical activities. An analysis and evaluation of these systems and the financing of information security were conducted. The methods and techniques used in the research are Computer Assisted Telephone Interviews, literature studies, and a questionnaire survey with applications for access to public information. The subjects of the research were medical entities subordinate to the local governments of three Polish voivodeships (Łódź, Świętokrzyskie and Pomeranian). The research was conducted between 2017 and 2018. Research findings show that the surveyed entities did not properly manage information security and did not allocate adequate financial resources to ensure information security. The lack of efficient information security management in medical entities may entail negative consequences in the future.
Keberagaman Jenjang Kelas Untuk Meningkatkan Efisiensi Tempat, Hasil Dan Aktivitas Belajar Di Sekolah Indonesia Den Haag (SIDH) Belanda

Teaching and learning activities have standardization in accordance with the Regulation of the Minister of National Education of the Republic of Indonesia Number 24 of 2007 concerning Standard for Facilities and Infrastructure. In fact, the limited facilities and teaching staff are owned by the Sekolah Indonesia Den Haag (SIDH) so that it can affect the teaching and learning process for students. The purpose of this study was to determine the steps taken by the Sekolah Indonesia Den Haag (SIDH) in increasing student learning activities by combining small and large elementary class levels. The research method used is descriptive qualitative. The subjects of this study were the teaching staff and students of the Sekolah Indonesia Den Haag (SIDH) Elementary School with a total of nine regular level students. Combining class levels is a step to improve student learning outcomes and activities by looking at the limitations of class fitness, teaching staff, and students. Finally, the authors conclude that based on the above discussion, there has been a success. In other words, combining class levels in the grouping of small SD and large SD can improve the results and activities of students in classrooms with limited class space.
Semisupervised Deep Embedded Clustering with Adaptive Labels

Deep embedding clustering (DEC) attracts much attention due to its outperforming performance attributed to the end-to-end clustering. However, DEC cannot make use of small amount of a priori knowledge contained in data of increasing volume. To tackle this challenge, a semisupervised deep embedded clustering algorithm with adaptive labels is proposed to cluster those data in a semisupervised end-to-end manner on the basis of a little priori knowledge. Specifically, a deep semisupervised clustering network is designed based on the autoencoder paradigm and deep clustering, which well mine the clustering representation and clustering assignment by preventing the shift of labels in DEC. Then, to train parameters of the deep semisupervised clustering network, a back-propagation-based algorithm with adaptive labels is introduced based on the pretrain and fine-tune strategies. Finally, extensive experiments on representative datasets are conducted to evaluate the performance of the proposed method in terms of clustering accuracy and normalized mutual information. Results show the proposed method outperforms the state-of-the-art methods of DEC.
Students’ Grammatical Error in Writing Narrative Text

Students made errors in writing narrative text. Two reasons why students made errors because less in grammar mastery and confuses to differenciate of the verb. This writing is to find out the grammatical errors. The method of research is descriptive quantitative. Process of data are analyzed by reading students’ writing firstly, identification, classification, tabulating, describing, and taking conclusion about the errors. After analyzing the data, it found that students made errors in omission, addition, misformation, and misordering categories. The highest frequency of item error was in using verb tense with total of 61 errors. Meanwhile, the lowest frequency of item errors were in using adverb and adjective with total of 6 errors. Total of the errors was 204.
Temporal analysis of interaction between spoken and digitally mediated dialogue in knowledge building

Paper in Symposium entitled 'Dialogic interactions in digital contexts: Multi-modal, multi-level and temporal analysis'
School Libraries and COVID-19

We have been dealing with many challenges in the past months. and such is the case at School Libraries Worldwide. This issue is getting out a bit later than usual due to added responsibilities of authors, reviewers and myself – editor of this issue. However, we have an outstanding array of topics. And although the research was conducted before the COVID epidemic, the subjects resonate with issues we are dealing with today.
Book Review: Your Passport to International Librarianship

For those interested in recharging their career, exploring new places, or gaining unique experience, Carlyle and Winn’s approachable and pragmatic volume Your Passport to International Librarianship will prove useful. The book covers the entire process of working internationally as a librarian, including visiting libraries while on personal vacations, as well as volunteering with international organizations, such as library nonprofits. The authors cover the benefits of international travel and volunteering, preparations necessary both personally and professionally, personal experiences, and advice for collaborating with your host library after returning home.
Automatic Arabic Named Entity Extraction and Classification for Information Retrieval

This article tries to explain our rule-based Arabic Named Entity recognition (NER) and classification system. It is based on lists of classified proper names (PN) and particularly on syntactico-semantic patterns resulting in fine classification of Arabic NE. These patterns use syntactico-semantic combination of morpho-syntactic and syntactic entities. It also uses lexical classification of trigger words and NE extensions. These linguistic data are essential not only to name entity extraction but also to the taxonomic classification and to determining the NE frontiers. Our method is also based on the contextualisation and on the notion of NE class attributes and values. Inspired from X-bar theory and immediate constituents, we built a rule-based NER system composed of five levels of syntactico-semantic combination. We also show how the fine NE annotations in our system output (XML database) is exploited in information retrieval and information extraction.