Reviewerly/exHarmony huggingface dataset:
Communicative Competence as a Component of the Professional Development of Psychology Students

The paper analyzes the issue of communicative competence as an element of the professional development of students studying psychology. It is established that in order to become a professional psychologist, a person should possess a number of essential psychological skills, such as communicative competence realized in the possession of verbal and nonverbal means of communication, ability to initiate and maintain contact. Based on this, the aim of the article was to conduct an empirical study on the communicative competence features as a component of the professional development of upcoming psychologists. A set of psychodiagnostic methods was selected, which helped to study the main parameters of communicative competence, features of professional orientation and motivation of future professional activity. The obtained results were subjected to quantitative and qualitative analysis. The sample included 72 Bachelor’s degree psychology students studying at Vasyl’ Stus Donetsk National University. The research consisted of two stages. The first stage incorporated the assessment of communicative competence, based on which the sample of subjects was divided into 3 subgroups according to their level of communicative competence development. The second stage analyzed the features of professional motivation and attitude to one’s own professional development of psychology students with different levels of communicative competence development. The results demonstrate that students with a high level of communicative competence in comparison with students with medium and low levels of communicative competence in the structure of professional motivation are dominated by intrinsic motivation, which indicates that for such students their future profession itself is very important. Moreover, these students have a clear idea of their future professional activity, are more professionally oriented, which will contribute to their successful professional development.
Information System For Receiving Inpatients For Covid-19 Cases

Coronavirus (Covid-19) cases are increasing now and it makes the hospital should be ready to receive patients. The problems faced made the queues of patients mixed up, between general patients and Covid-19 cases, which overwhelmed the officers in serving. So it should be a must for the hospital to upgrade the system of inpatient administration, especially for Covid-19 patients. The information system of inpatient administration for Covid-19 cases has become a very important thing to simplify the performance of officers, make reports easier to be more computerized, and simplify the administrative process to be easier and more efficient. The research method of this research is done by interview and observation, where the information system development is using the design uses data flow diagrams with the implementation of visual studio 2010 programming language and the database is using Microsoft Access. based on the results obtained from Covid-19 inpatient admission system, the system input consists of log-in form, new patient data entry form, inpatient registration form, and doctor form. Testing using the Black box, which results in a successful test for each form. The test results in the input that generates an as-expected output. The design has created an information system for receiving inpatients for COVID-19 cases according to needs which are obtained from the interview with the IGD registration officer at the hospital X in Bandung. This information system is very helpful for hospital management and improves the quality of service of the hospital.
Text Insertion By Utilizing Masking-Filtering Algorithms As Part of Text Message Security

For a secret message to be read and understood by a specific person only, a way is needed to hide the message, namely by steganography. Steganography is the concealment of secret messages in other media, such as images, audio, or video, so that the media inserted into the message looks as usual. Digital photos are one of the container media that are widely used for data hiding. However, when processing images such as compression, rotation, noise, and so on, confidential messages in the picture are prone to damage or loss. Then it takes the correct steganography method to hide secret messages into images to keep messages safe, not damaged even if the container image is manipulated, and the hidden message can be extracted again. on this thesis, applied masking method – filtering. Masking-filtering is included in the spatial domain. Message hiding is done by manipulating the luminance value of the image. Its use is applied to color or grayscale images. Masking serves as a tagging place on the picture that can be inserted message. Filtering passes a value to the marked section. the result is a stego image where the news is integrated with the container image, more robust to image processing when compared to methods that are also classified in the spatial domain, such as the least significant bit.
Teaching and Learning Writing on Descriptive Text

The research was aimed to know process teaching and learning writing on descriptive and the reason why the teaching and learning process of English writing on descriptive conducted as it was observed. The research was in the form of a case study. The object of the research was the teaching and learning English writing at class X-3 of Senior High 1 Luragung in Academic Year 2015/2016. The main data analyzed using five steps: (a) analyzing; (b) interpreting; (c) summarizing; (d) concluding and implementing; and (e) recommending.  Based on the findings,  researcher concluded that the teaching learning process of English writing ran well, active and in general can achieve the learning objectives determined in the Lesson Plan. The material which has taught by the teacher includes the material of descriptive text.  The result of evaluation is good. Most of students can reach minimum Passing Score 75. Only 12 students or 36,3 % from 33 students who get score under the minimum passing score in multiple choice test and writing composition, only 11 students or 33.3% from 33 students who get score under the minimum passing score in writing composition.
An Enhanced Technique for Fractal Image Compression Using Block Based Features (BBF)

Image Compression is very active research area specializing on how to compression and decompression of images. The various methods have been proposed for fractal image compression techniques for storage and drawbacks. The complexity in process will affect performance of the existing system to make insufficient. In this paper, the proposed research work presented a block based feature compression of image in the generation of feature sets. The feature sets are generated based such as vertical, horizontal and are extracted from the image based on range and domain blocks. The extracted features are carried out with encoding and decoding the images. The experimental result shows that block based feature method provides better compression ratio and other parameters when compared with the existing methods such as BTC, Wavelet and DCT.
An approach to benchmark fraud detection algorithms in the COVID-19 era

To address the challenges in the fight against financial crime, particularly in the COVID-19 pandemic context, this paper focuses on financial synthetic data and the use of a reliable benchmark tool to test fraud detection algorithms. Compliance departments at financial institutions face the challenge of reducing the number of innocent people erroneously accused of fraud. To cope with this problem financial institutions are exploring the application of machine learning fraud detection algorithms and data analysis technologies to develop a more accurate and precise fraud detection system. However, approaches to streamlining and automating banks’ monitoring and testing processes is challenging as there is no consensus on a benchmark. We explore the relevance of measuring the applicability of a financial crime benchmark in the presence of a growing digital financial sector, such as in the case of Mexico. This study is particularly important due to serious threats that are faced by a rapidly developing financial system (2019 Mexican Central Bank Report). These risks have been further exacerbated as a result of the COVID-19 pandemic accelerating the shift towards digital payments.
Deep Learning Based Neural Network Model for Anomaly Detection in Automobile Industry

Because of the recent advancement in the technologies like Internet of things andArtificial Intelligence, most of the industries have adapted into automation. In our routinelife most of the devices have become automated one with the help of more connectivity andflawless integration of information technology. Most of the modern vehicles are equippedwith smart technologies with security concepts. To identify the abnormality in vehicle network,an anomaly detection mechanism is proposed in this paper. By using this anomalydetection system we are able distinguish the vehicular attacks in the networks and also ableto detect the manufacturing defects for ensuring the quality assurance. Due his paper describesa deep learning based neural network model that will explore the abnormalities inthe vehicular network data. Various steps in the neural network implementation part havebeen illustrated. It also evaluates the experimental results by applying the deep learningmethod on the given real-time data. Due to the immediate responsiveness of the system, ithas been gaining much more attention in the automobile industry.
ENT 530 Business Plan : Fluffy Foaam / 'Adilah Safiah Asran ... [et al.]

Fluffy Foaam is a company that provides health and hygiene products called tablet soap. Manufactured tablet soaps have three different functions for hand washing, clothes washing and for the body as well. Each function has a different scent. Fluffy Foaam is founded by Mr. Fareez, CEO of Fluffy Foaam and assisted by four partners, Ms. Zahirah as an administrative manager, Ms. 'Adila as a marketing manager, Ms. Anis as an operating manager and last but not least, Ms. Afiqah as a financial manager. These five individuals are responsible for Fluffy Foaam
РОЗРОБЛЕННЯ МОДЕЛІ ЩОДО ПІДГОТОВКИ МАЙБУТНІХ УЧИТЕЛІВ БІОЛОГІЇ ДО ДОСЛІДНИЦЬКОЇ ДІЯЛЬНОСТІ У ЗАКЛАДАХ ЗАГАЛЬНОЇ СЕРЕДНЬОЇ ОСВІТИ

Solona, Yu. Development of a model for preparing future biology teachers for research activities in general secondary / Yu. O. Solona, M. M. Sydorovych // Scientific World Journal : International periodic scientific journal. 2020. ­ Issue № 3. – Part 1. – Svishtov, P. 114-125. DOI: 10.30888/2410-6615.2020-03-01-012
The Potential Taxation Of The Digital Sector In Indonesia That Comes From Digital Products From Abroad

This study aims to analyse the potential for taxation in the digital sector in Indonesia.As one of the countries with the most significant internet users, Indonesia makes many foreign companies interested in selling their digital content and services.The increasing number of foreign companies as developers and providers of digital content is in line with high technology in developed countries.Because of the enormous potential for taxation in this sector, the Government through Law No. 2 of 2020 in article 6 mentions tax treatment in trading activities through the electronic system, which is then regulated more clearly in the Regulation of the Minister of Finance Number 48/PMK.03/2020.This study uses qualitative methods using secondary data.Secondary data is in the form of other people's research, reviews, and summaries.In this study, the data taken is literature data that explain government policies to maximise the digital economy's tax potential.The results of this study explained that digital product transactions reached Rp102.67 trillion with a potential Value Added Tax (VAT) of Rp10.26 trillion.With this vast potential, and there will inevitably be an increase every year, the Indonesian Government in 2020 issued a tax policy for this digital product through Government regulation in place of Law No. 1 of 2020 and stipulated by Law no. 2 of 2020.
Enhancement of Cloud Stationed Healthcare Information Security by Dimensionality Reduction

The security of healthcare information can be secured by the use of cloud environment, and takes finite estimating power. The security of patient’s data shared over the internet can be distressed by healthcare institutions because of growing high popularity. The Eigen decomposition (ED) and Single Value Decomposition (SVD) of a matrix are relevant to maintain the security and the study of Dimension Reduction and its advantages are also applicable. To reduce the data without loss, Principal Component Analysis (PCA) is used. Fast retrieval methods are critical for many large-scale and data-driven vision applications. Recent work has explored ways to embed highdimensional features or complex distance functions into a lowdimensional space where items can be efficiently searched. However, existing methods do not apply for high-dimensional kernel based data The proposed method covers how to generalize locality-sensitive hashing and the implementation of Kernel PCA based methods for Dimensionality Reduction can be applied to Medical data provides high security and utilize the resources of the cloud to inhibit data efficiently.
Removal Of Haze Using Image Processing Techniques

Road fatalities on account of weather condition such like fog, Haze, run inthousands every year. Here we propose an best method to separate haze or snow from avideo and images. Photography of hazy scenes tends to low-contrast that removes thevisibility of scene. In our project use of image processing tech- nique victimization cV2 toolthat accustomed observe the haze and take away from the still pictures and video.Cv2 is atool which mainly concentrate on image processing, video capture and analysis includingobject detection. Here we use additional method such as genetic programming andGaussian method to over- come the different problems. This method is highly efficientwhen compared to other methods. Our method manufacture de-hazing which resultsincreases with higher visual quality compared with alternative progressive ways.
RANCANG BANGUN VIDEO CONFERENCE HOLOGRAM BERBASIS ANDROID

Video conferencing that currently exists only displays objects on media such as monitors, smartphone screens and projectors.The design of communication media that the writer will build will display the object in a hologram. Holographic mediamakes objects come alive. Android smartphone-based video conferencing will be connected to four monitor screens facingthe sides of a trapezoidal building. Where this tool will be able to be used for an interest in a meeting if the director oraudient who is unable to attend can attend the meeting wherever and whenever.
Error-Correcting Output Codes in the Framework of Deep Ordinal Classification

Automatic classification tasks have been revolutionized by Convolutional Neural Networks (CNNs), but the focus has been on binary and nominal classification tasks. Only recently, ordinal classification (where class labels present a natural ordering) has been tackled through the framework of CNNs, such as adapting the classic Proportional Odds Model to deep architectures. Also, ordinal classification datasets commonly present a high imbalance in the number of samples of each class, making it an even harder problem. In this work, we present a new CNN architecture based on the Ordinal Binary Decomposition (OBD) technique using Error-Correcting Output Codes (ECOC) and show how it can improve performance over previously proposed methods.
Preparing Annotated Data on Covid -19 by Employing Naïve Bayes

The on-going pandemic has opened the pandora’s box of the plethora of hidden problems which the society has been hiding for years. But the positive side to the present scenario is the opening up of opportunities to solve these problems on the global stage. One such area which was being flooded with all kinds of different emotions, and reaction from the people all over the world, is twitter, which is a micro blogging platform. Coronavirus related hash tags have been trending all over for many days unlikeany other event in the past. Our experiment mainly deals with the collection, tagging and classification of these tweets based on the different keywords that they may belong to, using the Naive Bayes algorithm atthe core.
Digitalization of information resources on the history of the Yaroslav the Wise National Library of Ukraine

The present process of digitalization of historical and cultural heritage through the publication of electronic resources, representation, visualization, as well as the development of online communications with a wide range of users is considered. The presentation of information resources on the history of Yaroslav Mudryi National Library of Ukraine in the structure of its website is described. Emphasis is placed on the features of the application of the results of digitalization in library science and historical research
Sentence Errors in Descriptive Text: A Study on How Students Understand English Sentence Patterns

This research is addressed to discover the mistakes carried out by the students in writing simple sentences and complex sentences of descriptive text in the form of description paragraph .  The research participants are undergraduate students of the first semester. The research objective is identifying kinds of sentence errors in simple sentences and complex sentences conducted by the students in writing a descriptive paragraph. The research data were obtained from the results of the questionnaires. The data tells that, firstly,  96% of total students did not come from a language major when they were in high school y are  and tests given; secondly, 63% of students learn English in one week more than once (generally 2x80 minutes), and thirdly, only 29% of students admit to having studied very ‘complex’ sentences.  Furthermore, the study identifies three types of students’ mistakes related to writing simple sentences. Those mistakes are: 1) mistakes in using the verb form from the review of the English structure and of conformity to the subject of the sentence, 2) the use of types of words in the subject and or  subject complement , and 3) the incompleteness of elements in simple sentences (no  subject , or  verbs , and or  subject complement ). In relation to the ability of writing complex sentences, there were four types of common mistakes related to complex sentences. They are: 1) mistakes in placing complementary clauses according to the type of clause, 2) incomplete sentence elements, both in the main clause and in complementary clauses, 3) mistakes in using types of words in certain parts, both in the main and complementary clauses, and 4) mistakes in using conjunctions. Based on the research results, the researcher concludes that the ability to write complex sentences should be of greater concern both students and lecturers for better writing ability.
PENGARUH STRATEGI PEMBELAJARAN DIRECTED READING ACTIVITY TERHADAP KETERAMPILAN MEMBACA PUISI KELAS VIII SMP NEGERI 2 SUNGGAL : (The Influence Of Directed Reading Activity Learning Strategies On The Skills Of Reading Poetry at SMP Negeri 2 Sunggal)

AbstractThis study aims to determine the effect of the Directed Reading Activity strategy on poetry reading skills of grade VIII students of SMP Negeri 2 Sunggal in Deli Serdang Regency in 2019-2020 school year. The background of this research is that students' low reading ability, especially poetry reading, is still not good because in reading poetry students are still having difficulty pronouncing intonation and expression when reading poetry as a result students still look ordinary like reading texts. This study included quantitative quasi-experimental research. Instructors used are tests using performance tests. The results of this study indicate that from the results of the pretest t test data can be obtained in the form of a significance value t-table of 2.00 t- count 12.32. That means that the probability is <0.05. So that H0 is rejected and H1 is accepted. So it can be said that there are differences in poetry reading skills of students in the class using the Directed Reading Activity strategy with classes that use teaching with the lecture method, the results of analysis between the Directed Reading Activity strategy (variable X) on poetry reading skills of eighth grade students. Keywords: Learning Strategy, Directed Reading, Poetry Reading Skills  AbstrakPenelitian ini bertujuan untuk mengetahui Pengaruh strategi Directed Reading Activity terhadap keterampilan membaca puisi siswa kelas VIII SMP Negeri 2 Sunggal Kabupaten Deli Serdang tahun ajaran 2019-2020. Latar belakang penelitian ini yaitu rendahnya kemampuan siswa dalam membaca khususnya membaca puisi masih kurang baik karena dalam membaca puisi siswa masih kesulitan untuk mengucapkan intonasi dan ekspresi ketika membaca puisi akibatnya siswa masih terlihat biasa saja seperti membaca teks. Penelitian ini termasuk penelitian kuantitatif quasi eksperimen. Instrmen yang digunakan yaitu tes dengan menggunakan performance test. Hasil penelitian ini menunjukkan dari hasil uji t pretes dapat diperoleh data berupa nilai signifikansi t-tabel sebesar 2,00 t-hitung 12,32. Hal itu berarti bahwa probabilitas < 0,05. Sehingga H0 ditolak dan H1 diterima. Maka dengan demikian dapat dikatakan bahwa terdapat perbedaan keterampilan membaca puisi siswa pada kelas yang menggunakan strategi Directed Reading Activity dengan kelas yang menggunakan pengajaran dengan metode ceramah, hasil analisis antara strategi Directed Reading Activity (variabel X) terhadap keterampilan membaca puisi siswa kelas VIII.   Kata Kunci : Strategi Pembelajaran, Directed Reading , Keterampilan Membaca Puisi
BR+ for Addressing Imbalanced Multilabel Data Classification Combined with Resampling Technique

BR+ is a multilabel method that transforms multilabel into binary single label and assumes label dependency.BR+ can use any different classification method such as random forest.Random forest is an advantageous classification method.But presence of imbalanced classes, random forest will result in poor performance.Hence, handling imbalanced data can be done by applying resampling techniques consisting of SMOTE-NC and T-Link.The dataset used was adolescent risk behavior of drug abuse and premarital sex based on SKAP.The dataset has two labels means there are multilabel problems and the dataset is imbalanced.Thus, the combination of BR+ (Stat) and resampling techniques will be compared in handling multilabel imbalanced data in the classification of adolescent risk behavior using random forest.The results show that the optimum Mtry is 7 and the combination of BR+ (Stat) and T-Link is the best method to handle the multilabel imbalanced data.
A multi-group dragonfly algorithm for application in wireless sensor network deployment problem

Metaheuristic algorithm is a popular research field. In recent years, a host of optimisers have been presented. Dragonfly algorithm (DA) mimicking the behaviour of a dragonfly performs markedly competitive to some optimisation problems. However, the DA sometimes does not perform well when encountering some complicated problems, easily falls into the local optimum, and premature convergence. To overcome the deficiencies of the canonical DA, this paper presents an enhanced version of DA, namely the multi-group dragonfly algorithm (MDA). The proposed MDA with three communication strategies applies effectively the multi-group trick to improve the diversity of the population. To verify the performance of the proposed MDA, it is evaluated by different benchmarks including unimodal functions, multimodal functions, hybrid, and composed functions. The experimental data confirm that the MDA performs better than the DA. Besides, the MDA is also applied in the wireless sensor network deployment problem, the simulation results appear that the MDA can obtain a more ideal sensor node distribution.
Composition of KG-and GG-Embeddings: Proof of Lemma 3.34

Proof of Lemma 3.34