Reviewerly/exHarmony huggingface dataset:
A Collaboration Between Communicative Language Teaching (CLT), Audiolingual, and Community Language Learning (CLL) Approach in Teaching and Learning English at SMA 1 Singorojo Kendal

This research aimed to investigate and analyze the collaboration of communicative language teaching approach, audiolingual method, and cooperative language learning method which were applied during teaching - learning process in twelve grade of science 2 students in SMA 1 Singorojo Kendal. This research employed descriptive qualitative research design. The instruments of this study were interview and observation which took approximately fifty minutes. In order to motivate and improve students’ speaking ability, so the teacher taught them in simple way first, then followed by synthesizing both of essentials methods and techniques. The result showed that teacher designed the classroom activity by implementing curriculum 2013 in which emphasized on communicative language teaching (CLT) approach. The researchers found that the teacher organized some methods in delivering material. He also provided fun and interesting games to encourage students’ motivation in learning English.The researchers infer that there are collaboration between CLT approach, audiolingual method, and CLL method as an alternative strategy in learning English.
Novel Image Steganography Based on Preprocessing of Secrete Messages to Attain Enhanced Data Security and Improved Payload Capacity

Image steganography hides secret messages in cover images by manipulating their content.There is a fundamental requirement of maximizing secrecy and payload capacity.This paper presents a novel algorithm for achieving two layer security as well improved payload capacity by prepossessing the secret images before hiding it in a cover image.The secret image is divided in to small windows of fixed sizes and is searched from a database of 255 images.Each window of secret image is replaced by the address of its closet match in database.Instead of hiding a secret image this algorithm hides the address of database.Consequently makes it impossible for any third party to retrieve the secret image without having access to the database.The size of the database address is less than the size of secret message thus it improves the payload capacity of the proposed algorithm.
THE EFFECT OF FISHBOWL STRATEGY ON STUDENTS’ READING COMPREHENSION AT THE ELEVENTH GRADE OF SMA MUHAMMADIYAH 18 SUNGGAL IN ACADEMIC YEAR 2019/ 2020

This study aimed to find out whether using Fishbowl Strategy effects students’ reading skill of the 2019/2020 eleventh grade students At Muhammadiyah 18 Sunggal Senior High School. In this study, the writer used Fishbowl Strategy as the independent variable (X) and students’ reading skill as the dependent variable (Y), with the hypothesis: using Fishbowl Strategy significantly affects students’ reading skill of the 2019/2020 eleventh grade students of Muhammadiyah 18 Sunggal Senior High School. The population of this study was the 2019/2020 eleventh grade students of Muhammadiyah 18 Sunggal Senior High School which consisted of 76 students. The sample was taken by using cluster random sampling that consists of 76 students. Then, the sample was divided into two groups, the group taught by using Fishbowl Strategy was as the experimental group and the group taught without Fishbowl Strategy was as the control group. The writer used multiple choice tests as the instrument of collecting data. The data was analyzed by using t-test formula. Based on the data analysis, it was found that the value of t-observed (t0) was higher than the value of t-table, (tobserved = 4.75 &gt; ttable = 1.666). Therefore, the hypothesis proposed by the writer was accepted. In the other words, using Fishbowl Strategy significantly affects the students’ reading skill of the 2019/2020 eleventh grade students At Muhammadiyah 18 Sunggal Senior High School.
A Hardware Friendly Haze Removal Method and Its Implementation

The images captured in hazy weather are always affected by haze, hence image dehazing has become a hot field in image processing. However, the existing dehazing algorithms are hard to be implemented on hardware to speed up because of high computational complexity. In this paper, we propose a novel hardware friendly image dehazing method to improve the image quality and save the execution time simultaneously. First, it selects airlight from the local patch with the current densest haze to obtain estimated airlight in real time. Then, it adopts the TDM (Time Division Multiplexing) strategy when searching the optimal transmission to save nearly 86.5% of hardware resources. Finally, it uses the fixed-point guided filter to improve the precision of the final refined transmission. The experimental results indicate it outperforms other dehazing algorithms in terms of SSIM and CIEDE2000. The hardware architecture for our proposed method trades off dehazing accuracy against throughput, which can obtain high-quality restored images with a high-throughput of 166. 67Mpixels/s when processing 80frames/s FULL-HD 1080p at 500MHz frequency.
Improved Security Evaluation of SPN Block Ciphers and its Applications in the Single-key Attack on SKINNY

In this paper, a new method for evaluating the integral property, truncated and impossible differentials for substitution-permutation network (SPN) block ciphers is proposed. The main assumption is an explicit description/expression of the internal state words in terms of the plaintext (ciphertext) words. By counting the number of times these words occur in the internal state expression, we can evaluate the resistance of a given block cipher to integral and impossible/truncated differential attacks more accurately than previous methods. More precisely, we explore the cryptographic consequences of uneven frequency of occurrences of plaintext (ciphertext) words appearing in the algebraic expression of the internal state words. This approach gives a new family of distinguishers employing different concepts such as the integral property, impossible/truncated differentials and the so-called zero-sum property. We then provide algorithms to determine the maximum number of rounds of such new types of distinguishers for SPN block ciphers. The potential and efficiency of this relatively simple method is confirmed through applications. For instance, in the case of SKINNY block cipher, several 10-round integral distinguishers, all of the 11-round impossible differentials, and a 7-round truncated differential could be determined. For the last case, using a single pair of plaintexts differing in three words so that (a = b = c) ≠ (a’ = b’ = c’), we are able to distinguish 7-round SKINNY from random permutations. More importantly, exploiting our distinguishers, we give the first practical attack on 11-round SKINNY-128-128 in the single-key setting (a theoretical attack reaches 16 rounds). Finally, using the same ideas, we provide a concise explanation on the existing distinguishers for round-reduced AES.
Video Denoising for the Hierarchical Coding Structure in Video Coding

Modern video codecs explore the temporal and spatial correlations of video signal to achieve the goal of compression. The noise in video signal corrupts such temporal and spatial correlations and thus is difficult to compress. Denoising of video signal is a potential solution to this problem. Despite the significant progress in video denoising in recent years, there is few research exploring the feasibility of denoising for video compression. In this work, we demonstrate that video denoising is able to significantly reduce bit rates while maintaining the subjective and objective quality when appropriately incorporated into the hierarchical coding structure of video coding. We present a temporal filtering algorithm for denoising and apply it to AV1 for lossy video compression. We obtain a significant compression efficiency improvement over videos of different resolutions, types, and noise.
Analisa Model Rapid Application Development Dalam Membangun Sistem Informasi Sekolah Mengemudi

Technological developments, especially in the automotive sector, make automotive companies competing to produce vehicles or means of transportation that are in accordance with the demands of society at this time. The public wants a means of transportation that is safe, comfortable, environmentally friendly and economical. To drive a private vehicle properly and correctly one of them follows training from institutions or driving schools. In this study, the authors helped overcome it by Building a Driving School Information System by analyzing using the Rapid Application Development (RAD) model. Use the Rapid Application Development (RAD) model for software development by minimizing the planning stage and maximizing prototype development. Through this system, prospective drivers can find out all information relating to driving schools, such as training schedules, names of instructors, costs required, types of cars available and comments of prospective drivers who have attended training at the school. This information system is very important for prospective drivers, it is also very useful for the driving school to display all information related to driving learning that will be applied.
Sentiment Analysis Based on Bi-LSTM Using Tone

In view of most of sentiment analysis texts are too short to get enough textual features, a method of bidirectional Long Short-Term Memory using tone (Word, Character and Tone model based on Bidirectional Long Short-Term Memory, WCT-Bi-LSTM) was proposed. Distinguished from the general method of sentiment analysis only taking word as the feature, the model also used character and tone features as input to enrich the characteristics of the text. After that, the model integrated the deep semantic meaning of word, character and tone. It could better grasp the emotion of the text and improve the accuracy of sentiment classification. The experimental results show that, compared with the model which does not integrate tone, the accuracy of the proposed model is increased by 1.2% and 0.9%on two experimental datasets respectively, which proves that the proposed method can effectively improve the accuracy of sentiment classification.
Analysis of the state of formation of future teacher’s communicative competence as a condition of providing the quality of general secondary education

The scientific novelty of the article is that the authors have revealed the average level of the state of formation of communicative competence (CC) of the third-year students. The cognitive and emotional components dominate among all CC components (it can be observed among students of the Faculty of Natural Sciences, Faculty of Arts). The behavioral component of the CC is better formed among students of the Faculty of Foreign Philology and the Faculty of Arts and Graphics. The communicative tolerance prevails among students of the Faculty of Physical Education as well as the Faculty of Arts and Graphics. Moreover, the two factors influencing CC were revealed: the external factors (organization of students’ subject leisure; professional-oriented educational work with students; content of education at institutions of higher pedagogical education: specialty of the chosen profession, increased cycle of humanities and psychological and pedagogical disciplines, active pedagogical practice of students; age of students to work with, different categories of children and adults to communicate with, pedagogical skills and CC of teachers); the internal factors (students’ attitude towards self-development, self-education, students’ life and social experience, motivation for acquiring a specialty and CC, humanistic orientation of future teacher’s personality, persona’s orientation to “person to person” profession)
MediExpert: An Expert System based on Differential Diagnosis focusing on Educational Purposes

The early and accurate identification of a disease is important for its effective treatment.However, medical errors represent a serious problem and pose a threat to patient safety.To this direction, appropriate and continuous education of the medical personnel has been widely recognized as an important mean to reduce medical errors and increase the quality of the health system.In this paper, we present MediExpert, an expert system targeting on continuous education of health personnel, providing also guidelines to persons that either cannot easily move due to age related comorbidities, or because they are away from healthcare units, further recommending users to talk with their doctors.It is based on differential diagnosis, employs ontologies for effective classification of health related problems and intelligent algorithms to enhance continuous education.We present the various components of the system and we elaborate on the benefits gained when using it for education.
Diversifying Effect of Digital Competence

Information and communication technology determines not only the development of companies but also the development of nations. Among other things, with the usage of eGovernment, the administrations can put „digitally pressure“ on their citizens which can lead to the appreciation of the role of digital competence. Based on data from the European Statistical Office, the digital competences of the EU Member States were examined between 2015 and 2017. A significant relationship was found between the level of digital knowledge and the level of unemployment. There is a strong positive correlation between the levels of digital competence and corporates training. In the clustering of countries, three distinct groups were created. The underdeveloped, developing and developed countries differed not only in the number of digitally educated people but also in the distribution of the digitally qualified groups.
Cultural/Social Media Space of the Digital Generation

Taking the example of Kazakhstan, this study examines the formation and analysis of the cultural media space of the digital generation. Information and communication technologies are the basis of a communicative media environment that has an internal regulated structure, which affects the socialisation of a person. The content of the cultural media space of the digital generation is formed on the basis of digital technologies and represents people’s visual worldview with images, signs and symbols.&#x0D; The processes of transformation of society affect the young generation and the content of the media space that determines their social and ethnocultural identity. The study presents the results of working with schoolchildren and students aged 14-18 using focus groups to explore the impact of digital culture (media culture) on adolescents in Kazakhstan. Based on the interdisciplinary approach, the findings demonstrate intergenerational contradictions because of the active involvement of Kazakhstan in the global internet community. The cultural media space of Kazakhstan has been shaping the social communications of the digital generation that has grown up in a sovereign state. The theoretical concepts of P. Bourdieu, C. Mannheim and other scientists served as a methodology for this study. Based on the interdisciplinary approach, the findings demonstrate intergenerational contradictions because of the active involvement of Kazakhstan in the global internet community. The findings also unravel that the transformation of the value orientations of adolescents is influenced by the factors of geographical location and ethnicity.
Prediction of Medical Concepts in Electronic Health Records: Similar Patient Analysis

Medicine 2.0-the adoption of Web 2.0 technologies such as social networks in health care-creates the need for apps that can find other patients with similar experiences and health conditions based on a patient's electronic health record (EHR). Concurrently, there is an increasing number of longitudinal EHR data sets with rich information, which are essential to fulfill this need.This study aimed to evaluate the hypothesis that we can leverage similar EHRs to predict possible future medical concepts (eg, disorders) from a patient's EHR.We represented patients' EHRs using time-based prefixes and suffixes, where each prefix or suffix is a set of medical concepts from a medical ontology. We compared the prefixes of other patients in the collection with the state of the current patient using various interpatient distance measures. The set of similar prefixes yields a set of suffixes, which we used to determine probable future concepts for the current patient's EHR.We evaluated our methods on the Multiparameter Intelligent Monitoring in Intensive Care II data set of patients, where we achieved precision up to 56.1% and recall up to 69.5%. For a limited set of clinically interesting concepts, specifically a set of procedures, we found that 86.9% (353/406) of the true-positives are clinically useful, that is, these procedures were actually performed later on the patient, and only 4.7% (19/406) of true-positives were completely irrelevant.These initial results indicate that predicting patients' future medical concepts is feasible. Effectively predicting medical concepts can have several applications, such as managing resources in a hospital.
Bayesian inference for latent chain graphs

In this article we consider Bayesian inference for partially observed Andersson-Madigan-Perlman (AMP) Gaussian chain graph (CG) models. Such models are of particular interest in applications such as biological networks and financial time series. The model itself features a variety of constraints which make both prior modeling and computational inference challenging. We develop a framework for the aforementioned challenges, using a sequential Monte Carlo (SMC) method for statistical inference. Our approach is illustrated on both simulated data as well as real case studies from university graduation rates and a pharmacokinetics study.
A Novel Reversible Data Hiding with Skin Tone Smoothing Effect for Face Images

In order to improve the visual quality of face images while embedding data reversibly, this paper proposes a novel reversible data hiding (RDH) with skin tone smoothing effect for face images. Firstly, data is embedded into the face images by RDH in color images. Then, the skin tone regions are extracted by an improved skin tone extraction algorithm. Lastly, the skin tone regions are smoothed by the proposed reversible smoothing skin tone algorithm. The experiments show that the visual quality of face images can be effectively improved after embedding the data comparing with other RDH methods and beautification algorithms.
Comparison of Acoustical Features for Abnormal Sound Detection by OCSVM

As a method of inspecting the condition inside the pipe, a skilled engineer can know the abnormality of the pipe by sound. However, it is commonly thought that inspections using sound is difficult because sound is different how to hear depending on the person, and it takes an awful lot of time to examine all machines in a plant. In addition, machine learning came to be used easily on these days. We examine an approach to solve the problem using machine learning. In previous studies, anomalies from bearing noise was detected from acoustic features, using machine learning. In this research, we tried to detect anomalies from the flowing sound which measured on a flowing sound generator using the method. In addition, we used two types of acoustic features and we could determine at a higher rate than in the conventional method.
Training in cooperation with the use of information technology

Training of modern graduate takes place in the conditions of requirements of the Federal state educational standards aimed at development of students’ competences. In order to train a competent graduate, higher education institutions are looking for ways that will make this process more effective and dynamic. The purpose of the article is to analyze the experience of higher education institutions in the implementation of training in cooperation with the use of information technology. The wide development of information technologies and their penetration into various spheres of society has determined their implementation in the educational process. The use of information technology is based on the use of personal computers. Now this tool is an integral part of the modern educational process. Placing emphasis on the fact that learning in cooperation is not a fundamentally new technology the authors say that it acquires relevance by incorporating innovative technologies. The article considers the ideas of training in cooperation with the use of information technologies, raises the importance and significance of this issue in modern educational conditions. Training in cooperation expands the students' information field. On the basis of the study of scientific literature, the features of training in cooperation, its essence and value purpose for the formation of competence of students of pedagogical University are highlighted. The study suggests an increase in students ' motivation to study materials after the introduction of information technologies that allow them to be more mobile and creative. The process of mutual learning in the process of cooperation becomes more effective. The higher the motivation of the student to study the discipline is, the higher the level of his knowledge is. The results of the study can be used in the further implementation of information technologies for the development of the learning process in cooperation.
PENGARUH MODEL PEMBELAJARAN CONCEPT ATTAINMENT TERHADAP HASIL BELAJAR SISWA PADA MATA PELAJARAN EKONOMI DI SMA SRIJAYA NEGARA PALEMBANG

This study aims to determine the effect of the concept attainment learning model on student learning outcomes in economic subjects at Srijaya State High School Palembang.The research method used in this study is an experimental method or an experimental quantitative research approach.The population and sample in this study were students of class XI IPS with a purposive sampling technique.Data techniques are documentation, observation, and tests.The re u f he ud u ing he e i n f regre i n e u i n n e 67.07 + 12.93 D obtained the results of testing the hypothesis of the "t" test showed that the difference count 7.183> t table 1.996, so based on the criteria Ho was rejected and Ha was accepted.Means there is an influence of concept attainment learning model on student learning outcomes in Economics in Srijaya, Palembang.Where the effect is 43.8% while the rest (100-43.8)= 56.2% is influenced by other factors not explained in this study.
A Salient Object Detection Algorithm Based on Hierarchical Cognitive Mechanism

The key of salient object detection is to extract the most attractive area in the scene.This paper fully explores the hierarchical cognitive mechanism of visual information, combines color contrast and depth contrast, and puts forward a salient object detection algorithm for the RGB-D image.Three saliency maps were prepared, namely, initial saliency map, middle saliency map and advanced saliency map.The three maps were then fused into a final saliency map.The proposed method was compared with six popular salient object detection methods on three RGB-D image datasets.The comparison shows that our algorithm achieved the best results in accuracy, recall rate and F-value.The research findings shed important new light on salient object detection in RGB-D images.