Reviewerly/exHarmony huggingface dataset:
An Optimized K-means Algorithm for Text Clustering

In the process of data mining, the two major problems confronted by K-means clustering analysis are the determination of the initial cluster center and the valuing of k. The traditional K-means algorithm has obvious subjectivity in the above-mentioned two aspects, which will directly affect the clustering effect. In this paper, an analysis method combining relational matrix and degree centrality is proposed to determine the initial center point and the k value of K-means algorithm. The improved K-means algorithm is applied to the clustering analysis of the Chinese entrepreneurial policy text collection, and the clustered topic effects are visually displayed through the word cloud graphs. This empirical analysis not only verifies its effectiveness and objectivity for the improved algorithm in processing large clusters of long text document clusters with random unknown number of categories and category topics, but also provides an approach for the objective classification of Chinese entrepreneurial policy text collections in the meanwhile.
PEMBELAJARAN MENULIS TEKS PUISI MENGGUNAKAN METODE THINK TALK WRITE ( TTW) BERBANTUAN MEDIA AUDIO VISUAL PADA SISWA KELAS X SMK BINA INSAN BANGSA NGAMPRAH

This study aims to determine students’ interest in learning, especially in writing poetry texts. Students are very difficult in terms of developing an idea or ideas into written form. The methods used by the teacher are sometimes less attractive sometimes less effective. As for the purpose of this study: 1) to know the scenario and implementation in writing poetry texts with method think talk write based audio visual  in class X student of  SMK Bina Insan Bangsa ; 2) to determine the response of teachers and students in writing in writing poetry texts by method think talk write based media audio visual in class X student of  SMK Bina Insan Bangsa; 3) to know the obstacles in writing poetry texts by method think talk write based media audio visual in class X student of  SMK Bina Insan Bangsa. The method used is descriptive qualitative  with samples student research in class X student of  SMK Bina Insan Bangsa. Learning to write poetry texts by using the method think talk write  assisted by media audio visual goes well scenarios and their implementation very suitable. Teacher and student against learning write excellent poetry texts. Difficulty from the lowest knowledge result 20 from 100 about disclosure and while the lowest average skill score is 65 less than 100 the contents of the language. From 37 students exist 26 students who get a value above average, KKM= 75  by percentage 95% very high category is declared passed.
An Efficient Closed Maximal Pattern Sequences Mining on High Dimensional Datasets

Previous methods have presented convincing arguments that mining complete set of patterns is huge for effective usage. A compact but high quality set of patterns, such as closed patterns and maximal patterns is needed. Most of the previously maximal pattern sequences mining algorithms on high dimensional sequence, such as biological data set, work under the same support. In this paper, an efficient algorithm Closed Maximal Pattern Sequences (CMPS-Mine) for mining closed maximal patterns based on multi-support is suggested. Careful exhibitions once Beta-globin gene sequences have exhibited that CMPS-Mine expends less memory utilization and run time over Prefix Span. It generates compacted outcomes and two kinds of interesting patterns.
Digital image contrast assessment based on the Weibull distribution parameters

The goal of the studies described in the paper is to find a quantitative assessment that maximally correlates with the subjective assessment of the contrast image quality in the absence of reference image. As a result of the literature analysis, 16 functions were selected that are used for no-refernce image quality assessment: BEGH, BISH, BREN, CMO, CURV, FUS, HELM, EBCM, KURT, LAPD, LAPL, LAPM, LOCC, LOEN, SHAR, WAVS. They all use the arithmetical mean of the local contrast quality. As an alternative to averaging local estimates (since the mean is one of two parameters of the normal distribution), it is proposed to use one of two parameters of the Weibull distribution of the same data – scale or shape. For the experiments, digital images with nonlinear contrast distortion from the available CCID2014 database were used. It contains 15 original images with a size of 768x512 pixels and 655 versions with modified contrast. This database of images contains the average visual quality assessment (Mean Opinion Score, briefly MOS) of each image. Spearman’s rank correlation coefficient was used to determine the correspondence between the visual MOS scores and the studied quantitative measures. As a result of the research, a new quality assessment measure of contrast images in the absence of references is presented. To obtain the estimate, local quality values are calculated by the BREN measure, their set is described by the Weibull distribution, and the scale parameter of the distribution serves as the best numerical estimate of the quality of contrast images. This conclusion is confirmed experimentally, and the proposed measure correlates better than other variants with the subjective assessments of experts.
Analysis on the Utilization of Digital Resources in University Libraries

With the development and application of network technology, information technology and multimedia technology, colleges and universities at all levels pay more and more attention to the construction, development and utilization of library digital resources.This paper analyzes the significance of the digital resources construction, explores the current situation of the college library digital resources utilization and the existing problems, and discusses the using strategy of college library digital resources, from the investment, talent cultivation, and resource integration optimization, aiming to be helpful to the college's digital library construction and development.
THE DIALOGUE BETWEEN SOLOIST AND ORCHESTRA WITHIN THE CONCERTO PRESENTED THROUGH PEIRCE'S “THEORY OF SIGNS”

The dichotomy between individualism and collectivism, deeply rooted in the development of social life, reflects an anthropological aspect that is also reflected in the art of music. This opposition, which is manifested through the relationship between the soloist and the orchestra within the concerto, is one of its main genre features. It survives despite all the changes that have taken place throughout history, but it is still subject to modifications. However, the role of these entities, apart from the style of the epoch, was also influenced by the composer`s personal style which must also be taken into account when considering the work from any point of view. The proposal to apply the method of Charles Peirce's “Theory of Signs” is to help to elucidate the meanings that this type of dialogue produces and which are hierarchically arranged and positioned within the pyramidal structure. Accordingly, the theme of the paper aims at showing the relationship between the soloist and the orchestra, showing what their function is within the concerto, as well as how their roles have changed throughout the change of epochs in history and the meaning this type of dialogue conveys.
LibGuides: Library Equipment Rules of Use: Webcams

A public guide collecting the various rules and policies that govern the circulation of library equipment, such as laptops, hotspots, and webcams. Information regarding library laptops; Rules of Use and how to use them.
Operational Efficiency Technologies Subjects of the Pedagogical Process Through the Application of the Efficiency Formula

The article is devoted to topical issues on technology to ensure the effectiveness of the activities of subjects of the pedagogical process by applying the formula for effectiveness. The forms and features of pedagogical processes in universities are highlighted and described. The idea is substantiated that the "formula of efficiency" developed by the authors allows to achieve high activity and efficiency of students' activity in pedagogical processes.
A Supervised Machine Learning Approach for Post-OCR Error Detection for Historical Text

Training machine learning models with high accuracy requires careful feature engineering, which involves finding the best feature combinations and extracting their values from the data. The task becomes extremely laborious for specific problems such as post Optical Character Recognition (OCR) error detection because of the diversity of errors in the data. In this paper we present a machine learning approach which exploits character n-gram statistics as the only feature for the OCR error detection task. Our method achieves a significant improvement over the baseline reaching state-of-the-art results of 91% and 89% F1 score on English and Swedish datasets respectively. We report various experiments to select the appropriate machine learning algorithm and to compare our approach to previously reported traditional approaches.
Tempus mutatur: analysing collocations of tempus ‘time’ with distributional semantic models

In recent years, distributional semantic models (DSM) built from large corpora have become an important tool in modelling word meaning. They not only have proved to be efficient in a variety of traditional sense-related tasks, but have also been successfully employed in diachronic semantics (Heylen et al. 2008). Although, in order to yield meaningful results, the method does not require painstakingly annotated corpora, it does not seem to have gained major popularity in Classical or Medieval Latin research so far. In the present chapter, we employ DSMs to cluster collocations of the lexeme tempus ‘time’ in two corpora: the Classical Latin Texts collection composed of mostly old and Classical Latin texts (ca. 8M tokens) and the first 60 volumes of the Patrologia Latina (ca. 22M tokens), which comprise Christian writings from the early centuries. In a series of analyses, we show how DSM-based clustering may help in the diachronic study of vocabulary. The analysis shows that, in Latin, time was consequently conceptualised as space, spatium temporis, as was recently showed by Thomas (2011) for Classical Latin. What varies, though, across the two corpora is mostly the depth of the spatial mapping and the nature of the time reference.
Web Mining System in a Natural Language Processing Based for Social Media Analysis

Social Media Monitoring and Analysis are the new trends in technology business. The challenge is to extract correct information from free-form texts of social media communication. Natural Language Processing methods are sometimes used in social media monitoring to improve accuracy in extracting information. This paper discusses a web mining system that is based on Natural Language Processing to analyze social media information. In that process, this research examines Natural Language methods that are important for such analysis. Then the traditional web mining steps are discussed along with proposed use of Natural Language Processing methods.
A Comprehensive Analysis of Various Text Detection and Extraction Techniques for Complex Degraded Images

Text extraction is a process of converting the image text into plain text. Extraction of text plays a very important role in finding image texts, editing and archiving documents. However, extracting texts from complex degraded images is a tedious work. The main challenges in text detection and recognition from complex degraded images are orientation of text, font size, diversity of background, low quality, difference in color of texts and interference of noise. A significant problem in optical character recognition (OCR) process is to extract text from complex degraded images. Therefore, it is a challenging job to design an algorithm which can produce a good accuracy irrespective of the font sizes, background, color, quality and orientation of image or document texts. In this paper, we discuss about various text extraction techniques for complex degraded images and also discuss the performance analysis as well as compare the advantages and disadvantages of each techniques
Perceptions Of Teachers And Headteachers Regarding The Hurdles Of Curriculum Change Into English As A Medium Of Instruction At The Primary School Level

Medium of instruction plays a vital role in the teaching-learning process. It is a tool in which a teacher delivers the contents of the curriculum to his/her pupils in their classrooms. A successful and smooth teaching-learning process depends upon the medium of instruction; therefore, the main purpose of this study was to explore the hurdles faced by teachers due to English as a medium of instruction at the primary level. The population of the study comprised of all the Public Boys & Girls primary school teachers, of District Lakki Marwat. A closed-form questionnaire of a 5-points Likert scale was used as a research tool for data collection. The research tool was made valid through the field experts. A simple random sampling technique was adopted by the researcher for data collection from the respondents for which the researcher personally visited every school and the questionnaire was duly filled by the respondents. The reliability of the instrument was determined by putting the collected data through Cranach's Alpha to calculate the internal consistency of the items. The results of the collected data were rectified and analyzed by applying Software Package for Social Sciences (SPSS) version 21. The collected data was analyzed and a t-test was applied to find out the results. Results of the study indicated the hurdles faced by teachers due to English as a medium of instruction at the primary level.
Analysing the Sentiments in a Hybrid FLOSS Community based on Commits

Open source repositories, by their nature, are open for study.This has inspired researchers to study them using various tools, leading to an established body of knowledge regarding how developers execute their work, communicate, and coordinate the effort.One flavor of open source community, which has received less attention, is hybrid open source, where developers and other stakeholders with various backgrounds exist.In this paper, we perform a sentiment analysis to a hybrid open source community, based on comments given when making commits.The goal is to understand if the community members behave differently, depending on their background in the company that owns the community IPR, being an independent contributor, or representing a collaborating organization.Based on the results, we find that there indeed is a clear difference in the sentiments, with in-house developers having a tendency to be more negative than independent developers, who in contrast express positive sentiments in their commit comments.
THE BENEFITS OF FOLLOW-UP BY THE MULTIDISCIPLINARY TEAM IN HEALTH FOR PEOPLE WITH SYSTEMIC LUPUS ERYTHEMATOSUS

Objective: Discuss the benefits of monitoring by a multidisciplinary health team for the treatment of patients with systemic lupus erythematosus. Methods: The research proposal is based on a review of bibliographic references, with a source of synthesizing results obtained through secondary research on the theme, in a methodical and orderly manner, seeking to contribute to the knowledge on the proposed subject. Results: Through a thorough analysis of theoretical references, 30 scientific articles were selected that alluded to the systemic lupus erythematosus pathology. Systemic lupus is characterized by articular, cutaneous, renal, vascular, serous, nervous manifestations, decreased mobility, muscle strength, physical conditioning and quality of sleep, increased joint stiffness, pain and fatigue and can cause, even depression, obesity and / or malnutrition, impacting quality of life. Conclusion: The research presented relevant results on the monitoring by the multidisciplinary health team for the treatment of patients diagnosed with systemic lupus erythematosus, presenting data that justify the construction of a structured support network, which will contribute to the therapy of this patient, providing well-being and improvements in quality of life. Taking into account the situation that the pathology presents, these data are at least disturbing. These bases made it possible to expand the discernment on the subject, opening a succession of discussions to find proposals and resolutions that can corroborate with the treatment of people diagnosed with chronic diseases such as SLE.
THE STUDY OF SELF-DETERMINED MOTIVATION OF STUDENTS IN THE CONTEXT OF DISTANCE LEARNING ACTIVITIES

The article examines the self-determined motivation of students studying at the V.I. Vernadsky Crimean Federal University (Simferopol) in the context of pedagogical activity using the social network VKONTAKTE as a platform for educational interaction and distance knowledge formation. The paper uses the theory of self-determination of Deci and Ryan, which provides an appropriate basis for assessing self-determined motivation in a targeted audience in the context of distance learning based on ICT. The results show that students are motivated to use the pages of the social network VKONTAKTE for educational purposes, which allows them to gain new knowledge and satisfaction from improving their own level of education. Taking into account the motivational aspect of the use of the social network in the university pedagogy of online distance learning, it can be concluded that it has a significant potential for large-scale and effective integration of ICT in higher education.
Aplikasi Pendeteksi Dini Penyakit Hepatitis Menggunakan Mesin Inferensi Forward Chaining Berbasis Android

The development of the world of information technology or commonly known as IT is indeed extraordinary rapid that is in harmony with human needs one of which is helping medical staff to analyze the disease one of which is Hepatitis. Hepatitis is inflammation that occurs in the human liver and its types are Hepatitis A, Hepatitis B and Hepatitis C. Application is a program developed to carry out certain functions for certain users who aim to achieve certain goals. On this occasion the authors developed the Hepatitis Disease Early Detection Application Using an Android-Based Forward Chaining Inference Machine to display the classification of Hepatitis A, Hepatitis B or Hepatitis C. The results obtained in this study are the Early Detection Application of Hepatitis Using the Android-Based Forward Chaining Inference Machine successfully designed to provide support in the form of convenience for doctors regarding the description of hepatitis that is Hepatitis A, Hepatitis B and Hepatitis C and tested using Black Box testing with the results are feasible to use, the White Box test with the results of edges, nodes, predicate nodes and independent pathways is 22 and UAT testing with 92% results from 5 respondents.
Deep Learning Power of TOR: Security Levels

Most of the profound learning applications that we find locally are typically outfitted towards fields like advertising, deals, finance, and so on We scarcely at any point read articles or discover assets about profound getting the hang of being utilized to secure these items, and the business, from malware and programmer assaults. While the enormous innovation organizations like Google, Facebook, Microsoft, and Sales force have effectively implanted profound learning into their items, the online protection industry is as yet playing make up for lost time. It’s a difficult field however one that needs our complete consideration. we momentarily present Deep Learning (DL) alongside a couple of existing Information Security (therefore alluded to as Information security analysts ) applications it empowers. We then, at that point profound plunge into the intriguing issue of unknown pinnacle traffic discovery and furthermore present a DL-based answer for distinguish TOR traffic.
OAAE : Optimized adaptive anomaly detection ensemble—Base model boosting by parameter optimization

Abstract Irregular data or anomalies may occur due to human error, miscalculation, or malicious system behavior. The detection of anomalies is a difficult task that requires the use of multiple strategic methods and models. The ideal detection model should assess the strengths and optimize the results of its base models before making final decisions. This task of optimizing the results of the base models contributes to the generation of more accurate results overall. This work presents an optimized adaptive anomaly detection ensemble using heterogeneous algorithms. In the first stage, it adaptively boosts the outcomes of preceding models by weighting their decisions and finding high‐performance ones, and in the second stage, it optimizes the base models by score margin maximization, which enlarges the contrast between the scores of the anomalies and other data prior to fusion to improve detection accuracy. To validate the model, baselines and test results from 10 benchmark datasets are compared. To assess its effectiveness in terms of distinguishing anomalies, the proposed model is tested and evaluated. The analyzed data are presented as cross‐tabulations, with detailed explanations and interpretations. The experiments show an improvement in results even when the least of anomalies (single cases up to 10%) are used.
PERILAKU PENCARIAN INFORMASI MAHASISWA JURUSAN ILMU PERPUSTAKAAN UNIVERSITAS ISLAM NEGERI SYARIF HIDAYATULLAH JAKARTA DALAM MASA PANDEMIK COVID

This research was conducted to explain what changed from seeking information from students of the Faculty of Adab and Humanities, Syarif Hidayatullah State Islamic University Jakarta during the Covid 19 Pandemic. The method used in this study was descriptive qualitative. This study used a stratified sampling technique, amounting to 83 informants from a population of 500 students of the Department of Library Science, Syarif Hidayatullah State Islamic University Jakarta. Data collection techniques in this research are literature study and questionnaires. The results of this study were slightly constrained by the situation, from the supposed 83 people only 31 people filled out the questionnaire while only 31 people filled out the questionnaire. In meeting these information needs, students conduct a gradual search for information consisting of: starting, determining topics before seeking information: chaining, recording a list of information needed; browsing, looking for information on information sources; differentiating, sorting out the information gathered; monitoring, following information developments; extracting, looking for information on a specific source; verifying, checking data; and ending, the end of the search for information.