Reviewerly/exHarmony huggingface dataset:
Development of Professional Communication Skills in Students in the ESP Class: Integration of Communicative and Critical Thinking Approaches

The present study is aimed at checking the efficiency of the four thinking-based communicative teaching strategies: guided discussions, role-based group work, the use of thinking maps, creative writing for developing professional communication skills in veterinary undergraduate students in the ESP class.These strategies were used to instruct a 72-hour ESP course at Omsk State Agrarian University.The comparative analysis of students' performance in the experimental and control groups in the end-course examination and direct teacher observation in class allows the conclusion about the efficiency of the implemented strategies.The study produced several findings.1.If students are equipped with the thinking mapping strategy and the creative writing 4-step management strategy, they perform better in reading, writing, and speaking and they are more organized in learning.2. The role-based group work proved to be the most effective in relation to practicing reading, speaking and listening skills.3.Although a guided discussion was really an effective strategy to engage students into intellectual communication, there is still the need for further development in all-level communication engagement of the students.4. The traditional teaching methods such as grammar and vocabulary drills proved to be more beneficial for mastering grammar structures and profession-related terminology.
Video Summarization using Subtitles

the main objective of this paper is to propose an improvised method to summarize videos in a way such that important and concise information is presented to end users. In our system we aim to present important aspects of a video through summarization of subtitles in a video with the help of text summarization and video mapping algorithms. The summarized video will be played with an audio generated version of the summarized subtitle file. The end result of the system would be a summarized video backed with a summarized audio generated version.
TINDAK TUTUR KOMISIF DAN EKSPRESIF DALAM DEBAT CAPRES-CAWAPRES PADA PILPRES 2019

This study aims to: (1) formulate the types of commissive speech acts used by presidential and vice presidential candidates in the presidential and vice presidential debates at the 2019 presidential election, (3) formulate the types of expressive speech acts used by presidential and vice presidential candidates in the presidential and vice presidential debates at the 2019 presidential election, (2) formulating the speech strategy used by presidential and vice presidential candidates in the presidential and vice presidential debates at the 2019 presidential election. This type of research is a qualitative research with descriptive methods. The data source in this study is the speech of the 2019 presidential and vice presidential candidates downloaded via Youtube. Based on the results of data analysis, three findings were concluded. First, the types of commissive speech acts used by presidential and vice-presidential candidates in the presidential and vice presidential debates at the presidential election, namely (1) promising, (2) vowing, (3) offering, (4) swearing, and (5) intending. Second, the types of expressive speech acts that exist in the vice presidential debate in the 2019 presidential election are, (1) congratulate, (2) say thank you, (3) apologize, (4) praise, (5) criticize, (6) insinuate , and (7) complaining. Third, the speech strategy used in the vice presidential candidate debate in the 2019 presidential election, (1) speaking without further ado, (2) speaking with positive politeness politeness, (3) speaking with negative politeness pleasantries, and (4) speak vaguely.
Golden Ratio and Its Application to Bayes Classifier Based Face Sketch Gender Classification and Recognition

Machine learning is a subarea of artificial intelligence based on the idea that systems can learn from data and make decisions automatically.Bayes Theorem is widely used in machine learning.The main objective of this paper is to classify the gender of the human being based on their face sketch images by using a golden ratio features and Bayes Classifier.This paper presents a method for human face sketch gender classification and recognition.It is inspired in our other model which was pre-trained on the same task, but with sixteen features and fuzzy approach.Toward this end, just two features will be extract from the input face sketch image based on two face golden ratios.The detection stage passes by Viola and Jones algorithm.The classification task is evaluated through Bayes classifier.An experimental evaluation demonstrates the satisfactory performance of our approach on CUFS database with 80% for training, 20% for testing.The proposed machine learning algorithm will be a competitor of the proposed relative the stat of the art approaches.
Improving students’ reading comprehension ability using task based language teaching

This study was conducted in response to the fact that the students’ reading comprehension ability was much lower than they should have achieved. It was caused by several reasons, one of themwas related to the poor teaching learning process. In this study, Task-based Language Teaching (TBLT) was used to improve the teaching learning process and the students’ reading comprehension ability. This research was a Classroom Action Research (CAR) study and it was done in two cycles. Observation and interviews were used to collect data which were then analyzed qualitatively. Students’ achievement of daily-test, the students’ self reflection in the form of rating format and the students’ achievement of post-tests were used in order to support the data collected. The results of this study indicate that TBLT can improve not only the teaching learning process but also the class 8D of MTsN Yogyakarta II students’ reading comprehension ability in recount text. It is shown that the students are interested to learn reading and they enjoy the reading teaching learning process using TBLT. The students’ average score before the action is 62.81. In the first cycle the mean score is 72.03, meanwhile the mean score in the second cycle is 79.06. It means that there is an improvement of students’ scores from cycle to cycle.
On the usage of postquantum protocols defined in terms of transformation semi- groups and their homomophisms

We suggest new applications of protocols of Non-commutative cryptography defined in terms of subsemigroups of Affine Cremona Semigroups over finite commutative rings and their homomorphic images to the constructions of possible instruments of Post Quantum Cryptography. This approach allows to define cryptosystems which are not public keys.
Machine learning based network traffic classification approach for Internet of Things devices

Due to design flaws, problems with implementations and improper network configuration, the Internet of Things devices become vulnerable in the network. They can be easily compromised and can also be attached to the Botnet network. IoT devices classification allows for strengthening of the overall network security through better VLAN planning and better firewall rule fine-tuning (e.g. per device class). In this paper only two classes of devices are considered: single-purpose devices (such as a bulb) and multi-purpose devices (such as mobile phone). Existing solutions do not provide the required accuracy within the given timeframe. We propose ML-based classification method based on supervised machine learning technology (Random Forest). With advanced packets flow analysis, our proposed approach demonstrates 94% of accuracy (7% better than the existing prior art). Additionally a very low False Positive rate is guaranteed for single-purpose IoT devices (e.g. a bulb must never be classified as a multi-purpose device).
EVALUATING SECTOR RING HISTOGRAM OF ORIENTED GRADIENTS FILTER IN LOCATING HUMANS WITHIN UAV IMAGES

Abstract. Developing systems to find injured people quickly after natural disasters is an important topic. In recent years, special attention has been paid to the use of UAV images for this purpose. In this regard, an accurate and strong feature is required. It is shown that the Sector Ring Histogram of Oriented Gradients, is a feature very much independent from rotation and scale. The aim of this paper is to evaluate the performance of a human detection algorithm which is based on this strong feature. Experiments carried out suggest that using SRHOG feature humans can be detected with an accuracy of 73.69%. However, despite giving good accuracy, SRHOG results contain more than 33.33 % false labels.
RANCANG BANGUN MEDIA PENGENALAN HURUF HIJAIYAH UNTUK ANAK USIA DINI BERBASIS ANDROID

Learning hijaiyah letters is one alternative to understand Arabic. Basically it is used to read Al-Qur’an in the initial stages. The introduction of hijaiyah letters is an important element to educate the children in comprehending religious knowledge. Therefore, it needs an appropriate learning method or media and exact strategy to deliver it in early childhood stage so that it will contribute well in the learning process.&#x0D; The purpose of this study is to create a media to introduce and to learn hijaiyah letters with 2D animation on android-based to facilitate that knowledge especially for children. This application is equipped with cartoon characters image and quiz menu to practice children’s ability in recognizing hijaiyah letters. This application can produce sound pronunciation of hijaiyah letters and the children can learn to write the letters as well. This application is created using Android Studio, wavePad sound editor and CorelDRAW X7 for drawing and coloring. The method used is Luther-Sutopo, while the data collection applies literature search and interviews.&#x0D; This application can be installed on smartphones with the Android operating system for at least 4.2 (Jellybeand) version. The results of the questionnaire show that the responses from the users are in average value of 92.67% so that this application is worthy to be the appropriate hijaiyah letters learning
Implementasi Web Service untuk Aplikasi Pemantau Coronavirus Disease 2019 (COVID-19)

The SARS-CoV-2 coronavirus outbreak, or commonly abbreviated as Covid-19, is currently almost paralyzing human life in various sectors. Compared to other coronaviruses such as SARS-Cov and MERS-Cov, Covid-19 spreads very quickly in multiple countries and regions. Also, the difficulty of information obtained accurately and in real-time for the community. The role of information technology is vital for the community in monitoring the coronavirus. This research utilizes web service technology to collect data and integrate services from various sources. The protocol and web service architecture used is representational state transfer (REST), with independent data exchange using the JSON format. Web service is made with node.js as well as android applications using an android studio. The results of this study have obtained a mobile-based android application that can present covid-19 data accurately and in real-time. Data recapitulation coronaviruses distribution from four service sources that have been integrated can display globally and locally in Indonesia.
Effects of Selected Macroeconomic Variables on Stock Market Returns in Nigeria

The paper empirically examines the effects of selected macroeconomic variables on stock market returns in Nigeria within the period 1985 and 2014 with a view to determining the macro-factors determining stock market returns in Nigeria. The Autoregressive Distributed Lag (ARDL) approach was employed to examine both the short and long-run effects of selected macroeconomic variables on stock market returns using annual time series data spanning 1985 to 2014. The findings show that both foreign direct investment inflows and external debt do not have significant impact on stock market returns in Nigeria while money supply and trade openness have significant positive effect on stock market returns in the long-run. The annual speed of adjustment towards equilibrium is 91 per cent. The causality results show two-way causality between the nominal stock market returns and foreign direct investment inflows, while one-way causality runs from nominal stock market returns to trade openness.
An ocular biomechanics environment for reinforcement learning

Reinforcement learning has been applied to human movement through physiologically-based biomechanical models to add insights into the neural control of these movements; it is also useful in the design of prosthetics and robotics. In this paper, we extend the use of reinforcement learning into controlling an ocular biomechanical system to perform saccades, which is one of the fastest eye movement systems. We describe an ocular environment and an agent trained using Deep Deterministic Policy Gradients method to perform saccades. The agent was able to match the desired eye position with a mean deviation angle of 3.5°±1.25°. The proposed framework is a first step towards using the capabilities of deep reinforcement learning to enhance our understanding of ocular biomechanics.
Sparser: Secure Nearest Neighbor Search with Space-filling Curves

Nearest neighbor search, a classic way of identifying similar data, can be applied to various areas, including database, machine learning, natural language processing, software engineering, etc. Secure nearest neighbor search aims to find nearest neighbors to a given query point over encrypted data without accessing data in plaintext. It provides privacy protection to datasets when nearest neighbor queries need to be operated by an untrusted party (e.g., a public server). While different solutions have been proposed to support nearest neighbor queries on encrypted data, these existing solutions still encounter critical drawbacks either in efficiency or privacy. In light of the limitations in the current literature, we propose a novel approximate nearest neighbor search solution, referred to as Sparser, by leveraging a combination of space-filling curves, perturbation, and Order-Preserving Encryption. The advantages of Sparser are twofold, strengthening privacy and improving efficiency. Specifically, Sparser pre-processes plaintext data with space-filling curves and perturbation, such that data is sparse, which mitigates leakage abuse attacks and renders stronger privacy. In addition to privacy enhancement, Sparser can efficiently find approximate nearest neighbors over encrypted data with logarithmic time. Through extensive experiments over real-world datasets, we demonstrate that Sparser can achieve strong privacy protection under leakage abuse attacks and minimize search time.
The construction of tenor, identities and power relations in online discourses on indigenous people of Biafra (Ipob)

Previous studies on ethnic, religious and political expressions and activities in Nigeria have examined issues such as religious and political intolerance between and among groups. In particular, the activities of pro-Biafra groups such as that of the Movement for the Actualisation of the Sovereign State of Biafra (MASSOB), Biafra Zionist Movement (BZM), Indigenous People of Biafra (IPOB) and Biafra Independent Movement (BIM) among others in real life and in online forums have also been studied by scholars from different ideological and theoretical standpoints. However, none of these studies examined the deliberate expression of ethnic, religious and political identities and otherness in the discourses that emanate from the arrest, detention and trial of Nnamdi Kanu, the separatist founder of IPOB, by the government of Nigeria. This study aims at unearthing the deep sense of exclusion that underlies the reactions that trail his arrest and trial in online platforms. A total of twenty online comments were purposively selected and analysed within the tenets of critical discourse analysis (CDA) in order to unearth the ethnic, religious and political ideologies that underlie them. This study gives an insight into how individual and group ideologies in online discourses can threaten the autonomous face wants of others and also that of the corporate existence of the nation. The theoretical orientation adopted for the study leads to the understanding that ethnic, political and religious sentiments underlie the use of language in crisis/conflict situations in the Nigerian context. This study significantly espouses the notion that there is the need for equity, social justice and mutual trust between groups in Nigeria.
Paradigm Shifts in Computer Adaptive Testing in Nigeria in Terms of Simulated Evidences

Farm women need different types of farm information due to higher engagements in agriculture.It is observed from various studies that majority of the farm women were under low social participation and cosmopoliteness level.So, on the basis of the findings, a study was conducted to identify the farm women participation, association and cosmopoliteness with different organisations and to analysis their networking structure in a social system.The study was conducted in Cooch Behar district of West Bengal with the help of expost facto research design.It was found from the study that majority of the farm women were associated with one organisation and regularly involved in self-help groups.It was found from the study that the panchayat office, nearest town, kisan mandi, Krishi Vigyan Kendra, nearest city and the post office play important roles for networking the farm women.
BIBLIOMETRIC ANALYSIS OF SCIENTIFIC COLLABORATION IN RUSSIAN UNIVERSITIES: COOPERATION VS INDIVIDUAL PRODUCTIVITY

The paper studies the dynamics of scientific collaborations in leading Russian universities during 2010–2018. The author analyzes both individual and inter-organizational collaboration. Understanding how scientific cooperation is organized, its disciplinary specifics and qualitative differences provides important information for organizing scientific activities in universities. Based on bibliometric data we analyze changes in the number of authors and affiliated organizations according to publications from various scientific fields and quality segments. The sampling of the universities shows the growth of scientific collaboration both among individual scientists and among organizations. The number of works co-authored with Russian organizations is higher than with foreign ones, but the share of such works is rapidly decreasing. In the segment of high quality publications, universities collaborate more often than in the lower quality segment. At the same time, in the high quality segment universities more often collaborate with foreign institutions, whereas in the lower quality segment – with Russian organizations. The highest share of scientific collaboration is observed in physical sciences, the lowest – in social sciences. The analysis is limited by the data, which do not represent all collaborations between scientists.
The Use of Information Technologies for the Development of Competences in Future Teachers of Foreign Language and Foreign Literature

The article deals with possible ways of using information technologies in teaching future teachers of foreign language and foreign literature. It is established that the primary task of the organizer of the educational process is to build an educational process with a view to facilitating the development of the competences necessary for the future teachers of foreign language and foreign literature. The latest information technologies are analysed and the effective ways of their use are suggested. It was found out that information technologies actively contribute to the unique function of preparing the future specialist for the quality realization of educational services in the information and digital space. It is researched that the functional approach to the analysis of IT in the context of the educational process outlines the specific scientific basis of the proposed scientific search, which allows to organically combine the postulates of media-oriented education with cognitive and communicative principles in the study of the ways of using IT in teaching teachers of foreign language and foreign literature. According to the guidelines of this approach, the functional purpose of IT influences the processes of formation of the form and value of the obtained knowledge. An important element in describing the use of IT is the principle of consistency. It is confirmed that the general competences of future teachers of foreign language and foreign literature are represented by both subject and general competencies, where IT competence is ranked as one of the top priorities. It implies the teacher’s ability to use information technology in the course of his/her professional activities effectively and appropriately. Information technology competence, in turn, is divided into three main competences, which correspond to the separate activities of teachers of foreign language and foreign literature: general, diagnostic and subject-oriented. Examples of tasks aimed at forming different types of competences in future teachers of foreign language and foreign literature with IT involvement are given. It is proved that the use of information technologies in the process of realization of educational and professional training of future teachers of foreign language and foreign literature contributes to a more effective fulfilment of the basic curriculum assignments, in-depth study of the content of the studied discipline, optimization of self-education and self-development of the level of future specialists, an individual way of perceiving information and working with it.
3D RECONSTRUCTION AND MESH OPTIMIZATION OF UNDERWATER SPACES FOR VIRTUAL REALITY

Abstract. In this contribution, we propose a versatile image-based methodology for 3D reconstructing underwater scenes of high fidelity and integrating them into a virtual reality environment. Typically, underwater images suffer from colour degradation (blueish images) due to the propagation of light through water, which is a more absorbing medium than air, as well as the scattering of light on suspended particles. Other factors, such as artificial lights, also, diminish the quality of images and, thus, the quality of the image-based 3D reconstruction. Moreover, degraded images have a direct impact on the user perception of the virtual environment, due to geometric and visual degenerations. Here, it is argued that these can be mitigated by image pre-processing algorithms and specialized filters. The impact of different filtering techniques on images is evaluated, in order to eliminate colour degradation and mismatches in the image sequences. The methodology in this work consists of five sequential pre-processes; saturation enhancement, haze reduction, and Rayleigh distribution adaptation, to de-haze the images, global histogram matching to minimize differences among images of the dataset, and image sharpening to strengthen the edges of the scene. The 3D reconstruction of the models is based on open-source structure-from-motion software. The models are optimized for virtual reality through mesh simplification, physically based rendering texture maps baking, and level-of-details. The results of the proposed methodology are qualitatively evaluated on image datasets captured in the seabed of Santorini island in Greece, using a ROV platform.