Reviewerly/exHarmony huggingface dataset:
Integrating Clinical Knowledge in a Thyroid Nodule Classification Model Based on

Deep neural network models are currently facing problems due the weak interpretability of predicted results. One solution would involve integrating the clinical knowledge and classifiers. In this study, we utilized mature clinical experiences from TI-RADS, and also trained a multi-label cost-sensitive classification network. The results show that the end-to-end classification model based on cost-sensitive loss function is a more effective way to integrate clinical knowledge into the deep neural network.
The Effectiveness Of Mr Dhanis’s Video On Instagram Toward Students’ Vocabulary Mastery

Vocabulary is the central of the language and critical important that must be mastered by the students. However, most of the students just know the common vocabulary that they usually used. The use of Mr. Dhanis’s video on Instagram is believed to be able to increase the student’s vocabulary mastery. The aim of this research is to find out the effectiveness of Mr. Dhanis’s video on Instagram toward students’ vocabulary mastery. This research uses quantitave research and experiment method. The population of the research consist of 142 students at the eleventh grade students in SMA N 01 Metro. The researcher takes 62 students as the sample, then divided the students into two group, 31 students as the experiment class and 31 students as the control class. The researcher uses cluster random technique and uses t-test formula. The instruments of this research are pre-test and post-test. The result of the first hypothesis indicated that the value of t obtained (13.590) was higher than that of t table (2.042) at the significance level 0.05 and the significance (0.000) was lower than 0.05. Because of this the hypothesis is accepted. Then, the second hypothesis indicated that the value of t obtained (12.242) was higher than t table (2.042). That is why, the second alternative hypothesis (H a ) is accepted. It means that teaching vocabulary using Mr. Dhanis’s video on Instagram at the eleventh grade students of SMA Negeri 1 Metro is effective to increase vocabulary mastery and to give a significant difference on English vocabulary mastery.
IMPROVING STUDENTS’ WRITING SKILLS USING COOPERATIVE LEARNING AT SMPN 2 SUKODONO

This research was conducted in order to find out whether using Cooperative Learning is effective to improve students’ writing skills or not. Also, it is to find the result of the students’ ability in writing when the researcher using Cooperative Learning. The main problems were: (1) the students seldom do the writing tasks; (2) they had difficulty in grammar during writing; (3) they got difficulty in developing ideas. The research methodology of this research was Classroom Action Research (CAR), which was done in two cycles. Every cycle consists of four steps, that is planning, implementing, observing, and reflecting. The techniques for collecting the data were documentation, observation and test. The subject of this research is class VII-H that consists of 33 students, one English teacher as a collaborator and the researcher herself involved in this research. Based on the results of the study, it showed that the mean score of students increased from 62.9 to 74.7 in cycle 1. On the other hand, in cycle 2, the mean score increased classically from 76.7 to 83.5. Considering the data above, the achievement of the students in writing skills has achieved the indicator of success using cooperative learning. From the result, the researcher concluded that applying cooperative learning can improve writing skills for seventh grade of SMPN 2 Sukodono.Keywords: classroom action research, writing skills, cooperative learning
Studi Komparatif Metode Ekstraksi Fitur pada Analisis Sentimen Maskapai Penerbangan Menggunakan Support Vector Machine dan Maximum Entropy

Almost all companies use social media to improve their product services and provide after-sales services that allow their customers to review the quality of their products. By using Twitter social media to be an important source for tracking sentiment analysis. Sentiment analysis is one of the most popular studies today, using sentiment analysis companies can analyze customer satisfaction to improve their services. This study aims to analyze airline sentiments with five different features such as pragmatic, lexical n-gram, POS, sentiment, and LDA using the Support Vector Machine and Maximum Entropy methods. The best results can be obtained using the Maximum Entropy method using all feature extraction with an accuracy of 92.7% and in the Support Vector Machine method, the accuracy obtained is 89.2%.
Collection and judgment of electronic data evidence in criminal cases: From the perspective of investigation and evidence collection by public security organs

With the continuous progress of science and technology, the Internet has gradually entered every field of daily life. In addition to the information generated by the Internet in the form of digitization, it has become the main media for people to store information. In the field of criminal offenses, the network is likely to be used to perpetrate criminal schemes, implement crimes, or help hinder investigations afterward. These acts will leave an electronic data trail, such as WeChat information, emails, or blogs. After a crime occurs, an evidence investigator should accurately, timely, and comprehensively obtain all electronic data related to the case by collecting, extracting, and transferring this data according to the law, and examining the authenticity, legality, and relevance of the evidence. Through a comprehensive review, the investigator should clarify the relationship between the electronic data and the facts to be proved and make full use of the obtained electronic evidence in criminal proceedings.
Steganografi Pada Digital Image Menggunakan Metode Least Significant Bit Insertion

&lt;span lang="SV"&gt;Steganography is a way to hide messages or confidential data in a medium called a carrier file. Embedding is done by the Least Significant Bit Insertion method, which is to replace the lowest bit of Red Green Blue (RGB) each pixel with the data bit you want to insert. With this method the difference between pixels that have not been pasted by messages and pixels that have been pasted by messages cannot be distinguished by human eye sight. Because the LSB insertion method is used, it is necessary to consider the type of digital image format used, this is necessary to avoid the loss of messages when extracting. And the best digital image format used is the 24-bit BMP because the BMP format is lossless compression&lt;/span&gt;
Pengaruh Kemampuan Awal terhadap Hasil Belajar IPA Biologi Peserta Didik Kelas VIII SMP Negeri 1 Kaledupa Kabupaten Wakatobi

This study discusses fatherly learning about the initial ability of learning outcomes of Biology participants in grade VIII students of SMP Negeri 1 Kaledupa. This research can help educators in preparing teaching materials for students before starting learning. This type of research used in this study is ex post facto. The population in this study were all class VIII of SMP Negeri 1 Kaledupa with a total of 3 classes, while the sample was obtained by 1 class using purposive sampling. The instrument for collecting data uses test instruments for students' initial abilities as well as for learning outcomes. The results of the research show what is meant by Preliminary Principles on the learning outcomes of Biology Science VIII grade students of SMP Negeri 1 Kaledupa. This is based on the results of hypothesis testing using simple regression analysis obtained significance value of 0.004 &lt;0.05. Also, from a simple regression analysis table supported by an initial ability regression coefficient of 0.764 which is claimed to support every 1% of the initial ability score, the added learning outcome score is 0.764. This regression coefficient is positive, so it can be agreed that the direction of the effect of the initial ability variable on learning outcomes is positive.
MADAFE: Malicious Account Detection on Twitter with Automated Feature Extraction

Nowadays, more and more massive cyber-attacks have been launched over social networks. Using compromised or fake accounts, criminals can exploit the inherent trust between connected users to effectively spread malicious content and perform scams against users. Detecting those malicious accounts on social networks like Twitter has received increasing attention from government, industry, and academia. Traditional methods on malicious account detection often leverage features that are created and selected based on domain knowledge of user data, which is inefficient, time-consuming, and possibly biased due to different understanding and observations of the data. In this paper, we propose a new framework, called MADAFE, for accurate and efficient malicious account detection on social networks like Twitter. To overcome the limitation of existing work on manual feature extraction, MADAFE utilizes an autoencoder to automate feature extraction and selection from unlabeled user data. A softmax regression model is also established and trained with the extracted features for classification of benign and malicious accounts. We test MADAFE on different datasets, and extensive simulation results show that MADAFE is effective in detecting malicious accounts, which outperforms state-of-the-art detection methods.
STUDENTS’ PERCEPTION ON THE APPLICATION OF TIMED WRITING PRACTICE (TWP)

Abstract This preliminary research is as a part of learning need analysis for developing a discourse based writing material with a timed-writing technique in an English teacher education department in Indonesia. In timed writing practice (TWP), students must write a paragraph on a sheet of paper without help in a given time limit. However, no empirical information on whether the students agree or disagree with the application of timed writing and the reasons behind their perceptions is not yet avaiable.The research subjects consist of 31 students who take writing course. The objectives are to investigate (1) the extent of the students’ acceptance and (2) the reasons behind the acceptance on the application of timed-writing practice (TWP) in writing class. A qualitative analysis is administered by identifying and classifying contents of students’ opinions and reflections expressed in the students’ responses to questionare. Twenty five students (81%) agree with the application of TW. Four students (13%) disagree and 2 students (6%) give no preference. Timed writing are perceived as (1) Encouraging Writing Activity, (2) Improving Time Management and Control, (3) Training Thinking Skills, (4) Improving Writing Skills, (5)Training Speed Writing, (6) Improving Soft Skills, (7) Giving Challenging Activity, and (8) Improving Concentration and Accuracy. The reasons from those who disagree are: (1) Feeling nervous and confused (2) Having insufficient preparation time, and (3) Expecting Variation of Activity. In conclusion, timed writing is mostly accepted and positively perceived by the students with very high category. Reasons from those who disagree must also be taken into consideration for future betterment. Based on the research findings, the timed writing, accordingly, can be used as a technique or a strategy to be integrated in a discourse-based writing material for students of English teacher education program.Key Words: Timed-Writing, Students’ Acceptance, Reasons
Multi-Level Head-Wise Match and Aggregation in Transformer for Textual Sequence Matching

Transformer has been successfully applied to many natural language processing tasks. However, for textual sequence matching, simple matching between the representation of a pair of sequences might bring in unnecessary noise. In this paper, we propose a new approach to sequence pair matching with Transformer, by learning head-wise matching representations on multiple levels. Experiments show that our proposed approach can achieve new state-of-the-art performance on multiple tasks that rely only on pre-computed sequence-vector-representation, such as SNLI, MNLI-match, MNLI-mismatch, QQP, and SQuAD-binary.
The Critical Muse of Vyacheslav Ivanov in Modern Russian Literature. Review of: Ivanov, V. I. (2018). Po zvezdam. Opyty filosofskie, esteticheskie i kriticheskie [By the Stars. Philosophical, Aesthetic, and Critical Essays: Articles and Aphorisms] (A. V. Lavrov et al., Eds.). St Petersburg: The Pushkin House Publishing. Book I: Texts. 430 p. Book II: Comments. 670 p.

This review considers the academic publication of the book By the Stars (1909) by Vyacheslav Ivanov prepared by a team of researchers and published by the Pushkin House Publishing in 2018. The reviewer analyses the principles of publication (design of the cover, Ivanov’s own graphics and spelling, etc.). Special attention is paid to the multistep comments on Ivanov’s articles. The comments in the book are compared with the notes and comments in other editions of Ivanov’s articles. The reviewer points out the inconsistency between the table of contents in the analysed reissue of the book By the Stars and the table of contents in the original book released in 1909: in the modern version, there is no division of articles into sections or their numbering. The reviewer emphasises that the book By the Stars (2018) is of great importance both for the study of the creative heritage of Ivanov and for modern publishing practice as a whole.
Quality Characteristics of Mobile Learning Applications

Software quality evaluation for mobile application is a subject with major implications onto educational evaluating process.The place where teacher and his educable person build a temporary social relation is connected to an environment where success is correlated with a mobile-driven mindset.A suitable examination of such mobile learning -environment implies quality characteristics like functional correctness and testability and should be conducted with proper tools if we desire to use mobile learning applications for implementing into a collaborative scenario toward complex classroom events.In this article we are making a raised mark above quality characteristics of mobile learning applications because this is the starting point to acquire a certain comprehension concerning a better utilization of such methods for obtaining knowledge.We construct a potential bridge between two quality characteristics of mobile learning applications to show how to transfer practical results from one quality characteristic toward another to sustain an experimental study with adjacent outline involving mobile programming laboratory curricula.We focus our attention above a software quality metric, the so-called statement code coverage (CC), to obtain a synergic effect between a blackbox approach and a white-box technique in order for developing and testing Android mobile applications.For reaching our desideratum we studied scientific papers regarding the complexity of quality characteristics applied to mobile learning applications, from a general to a particular view, to shed light above previous gathering observations concerning our mission.We have a genuine desire to reveal technical instructions needed to be executed in order to obtain a reproducible pattern of a manually testing process, concerning an Android mobile application, conducted by a beta-testing team of users.
Multiple vehicles detection and tracking for intelligent transport systems using machine learning approaches

Video surveillance is emerging research field of intelligent transport systems. This paper presents some techniques which use machine learning and computer vision in vehicles detection and tracking. Firstly the machine learning approaches using Haar-like features and Ada-Boost algorithm for vehicle detection are presented. Secondly approaches to detect vehicles using the background subtraction method based on Gaussian Mixture Model and to track vehicles using optical flow and multiple Kalman filters were given. The method takes advantages of distinguish and tracking multiple vehicles individually. The experimental results demonstrate high accurately of the method.
TINGKAT PENDIDIKAN DAN PENDAPATAN ORANG TUA PADA PRESTASI AKADEMIK

Academic achievement is a form of success of a student obtained from the learning process in schools and colleges, this is realized because of the role of parents based on education level and income. The purpose of this study was to analyze the relationship between education level and income of parents with academic achievement. The method used in the study was an analytic observational study with a cross sectional design, involving 85 respondents selected through consecutive sampling. The results of the study stated that the income of male parents was very high at 43.5%, the income of female parents was low at 28.2%, the education level of parents was medium (45.9% for men and 41.2% for women), student academic achievement is high (49.4%), there is no significant relationship between the level of education of parents and student academic achievement (p&gt; 0.05), and there is a significant relationship between parents' income and student academic achievement (p &lt;0.05). Thus, there is no significant relationship between the level of education of parents and the academic achievement of the Nursing Faculty of Klabat University students, but there is a significant relationship between parents' income and the academic achievement of the Nursing Faculty students of Klabat University. The addition of other variables related to academic achievement needs to be done to improve the results of this study.
Digits and Character Recognition using KNN

The proposed work is about offline recognition of digits and characters using machine learning.MNIST dataset has CSV file.From this, image is obtained by reading it.Then it is preprocessed using RGB converter into binary form that contains some noise, this noise is removed using median filter and then convert into filtered image.Some further pre-processing is done on the image.If the characteristics for one class are distinct and remain constant with variations in this class, then we can call the features as good and desired.KNN Technique is used for classification and recognition of handwritten digits through training and testing.Then, system is made portable by using Raspberry pi and text is converted into speech signal.
Usage of i-Vectors for Automated Determination of a Similarity Level between Languages

The article describes results of applying i-vectors-based (both LID and SID) speech identification methods to define a kind of a distance between languages (in a wide sense of the word – including dialects and any other forms of spoken language). Spontaneous speech recordings of many enough speakers of languages are used on the input of the method. The experiments were carried out at recordings of Latvian and Latgalian dialects, but the method is applicable to any other idioms. Cosine similarity, Euclidean metric, standardized Euclidean metric, Jordan (or Chebyshov) metric and city block (or L 1 ) metric were tried out. Cosine similarity worked well for SID i-vectors, but for unknown reasons was senseless for LID i-vectors. Jordan metric worked well for LID, but was not good enough for SID i-vectors. Standardization of the Euclidean metric does not gave any improvement. Thus, the conclusions are: 1) both SID and LID vectors of full length recordings of spontaneous speech are characterizing and representing languages good enough to be used for detection of a distance between languages; 2) the best metrics for such tasks are Euclidean and L 1 (for arithmetic mean vectors computed from i-vectors of all informants coordinate by coordinate).
Silhouette Density Canopy K-Means for Mapping the Quality of Education Based on the Results of the 2019 National Exam in Banyumas Regency

Mapping the quality of education units is needed by stakeholders in education. To do this, clustering is considered as one of the methods that can be applied. K-means is a popular algorithm in the clustering method. In its process, K-means requires initial centroids randomly. Some scientists have proposed algorithms to determine the number of initial centroids and their location, one of which is density canopy (DC) algorithm. In the process, DC forms centroids based on the number of neighbors. This study proposes additional Silhouette criteria for DC algorithm. The development of DC is called Silhouette Density Canopy (SDC). SDC K-means (SDCKM) is applied to map the quality of education units and is compared with DC K-means (DCKM) and K-means (KM). The data used in this study originated from the 2019 senior high school national examination dataset of natural science, social science, and language programs in the Banyumas Regency. The results of the study revealed that clustering through SDKCM was better than DCKM and KM, but it took more time in the process. Mapping the quality of education with SDKCM formed three clusters for social science and natural science datasets and two clusters for language program dataset. Schools included in cluster 2 had a better quality of education compared to other schools.
Regional Vocational Education System In Peer Review

The article analyzes the problems of the system of vocational education in Kuzbass, which are associated with the formation of personnel potential for modernization of the regional economy. The effective solution of the tasks of transforming the labor market largely depends on the positions and actions of the main stakeholders. In this regard, the problem of studying the forms of interaction of various participants in the educational space, which must objectively correspond to the long-term strategy of transition to an innovative model of development of the regional economy, is relevant. In the article this problem is studied from the point of view of the systemic and institutional approaches. The subject of the research was the system of views of the main stakeholders on the interaction of participants in the educational space. The main method of gathering information was determined by an expert survey in the form of a semi-formalized interview (N = 39). The composition of experts is representatives of government, business, media, professional education organizations. The obtained results are analyzed using the method of interpretation of meanings. The article analyzes the system problems of formation of personnel potential for the modernization of the regional economy and the institutional causes of these problems. Problem solving requires institutional measures at the federal and regional levels. One of the ways of cooperation of the real sector of the economy with science and education is the creation of research and educational centers.
An experimental evaluation of the wideband radar measuring set sensitivity

This research concerns the possibility of using a movable broadband radar measuring set based on the vector network analyzer to obtain objects radar characteristics and applicable in practice algorithms of formation and focusing twodimensional inversely synthesized radar images in semi-natural and natural conditions.Modern experimental methods of objects radar characteristics research are implemented by means of measuring sites of both open and closed types.High precision radar cross-section measurements are usually provided by anechoic chambers.The advantage of open-type landfills, including those built on the basis of movable radar measuring sets, is to consider the influence of the real underlying surface and the absence of restrictions associated with closed space.The purpose of this work is an experimental evaluation of the reference reflector radar cross-section measurement lower boundary by the means of a mock-up of a broadband radar measurement set based on vector network analyzer.