Reviewerly/exHarmony huggingface dataset:
An analysis of form and function of a research article between and within publishers and journals

Abstract The identification and subsequent analysis of research articles for machine learning and natural language processing is a complicated task given the lack of consistent article organization principles and heading naming conventions across publishers and journals. Given this, an understanding of how research articles organizationally follow a common function and their use of various heading terms, or forms, is a critical step in applying machine learning techniques for data and information mining across a corpus of articles. To address this need, the authors developed and implemented an article heading form and function analysis across 12 publishers including both research articles and nonresearch articles. Our aim was to (a) identify each of the labeled sections used by research articles, define these sections based on their rhetorical function, and determine frequency of use; (b) within the given data set, determine all of the alternative labels used to identify these sections; and (c) determine whether these sections can be used to consistently determine (1) whether an article is a true research article, or (2) whether an article is not a research article. The results indicated wide variability in the organization of research articles with 24 common sections, known by 186 different names both within and across publishing houses.
The Effect Of Dictogloss Strategy On the Students’ Writing Ability At MTsN 1 Medan

The objective of this research is to find out whether or not there is significanteffect of Dictogloss strategy on students’ writing ability in narrative text at ninthgrade students’ of MTsN 1 Medan. This research is quantitative research withquasi experimental design. This research was carried out in the ninth gradestudents of MTsN 1 Medan academic year 2020/2021. The total number ofpopulation was 426 students, and the researcher took 37 students for experimentalclass and 36 students for control class, which means 73 students as total of thesample. To collecting data in this research, the researcher used written tests as theinstrument. The tests were pre-test was given before the treatment and post-testwhich was given after the treatment. The data in this research obtained wereanalyzed by using t-test with 5% (0,05) significance level. Furthermore, theresearcher found that the mean score of post-test in experimental class was higherthan the mean score of post test in control class (77,92>71,11). The t-test resultalso presents that t0 (4,434) was higher than ttable in the significance level 5%(0,05) with the degree of freedom 71 is 1,667. Therefore, t0 result >ttable generatedthat H0 (null hypothesis) was rejected and Ha (alternative hypothesis) wasaccepted. The calculation of effect size was 1,04 which in the range of effectcriteria included to strong effect. It means, Dictogloss strategy has significanteffect on the students’ writing ability in narrative text at ninth grade students ofMTsN 1 Medan.
L2 성인의 콜로케이션 지식 향상을 위한 음악의 효과

The purpose of this paper is to investigate the co-relationship between L2 adult learners and music. In this study, three songs were used: Coward of the County, Lucille, and The Gambler sung by Kenny Rogers. The participants were five graduate students majoring English education in a Korean university, and their English language proficiency was high intermediate with advance reading and grammar knowledge. Participants were asked to memorize the lyrics of the three songs and to respond to a question about the difficulty of the memorization. All the participants responded negatively; that is, they found the songs problematic to memorize. They were then asked to highlight both familiar and unfamiliar expressions. The collected data was analyzed in terms of lexical collocation (LC) and grammatical collocation (GC). The results showed that the participants were unfamiliar with about half of the LC and most likely lead to causing issues memorizing the lyrics. However, the participants had fewer problems with GC due to their prior knowledge of GC. It was learned that the participants had never been trained to develop awareness of collocation. If the participants had learned vocabulary in a specified context, they would have learnt the relevant collocations. Western music can provide this context because it is story based and consequently learners would maintain interest in the music and learn the collocations more readily.
Automatic Modulation Classification Using Combination of Variational Mode Decomposition and Multifractal Analysis

Automatic modulation classification (AMC) plays a key role in intelligent wireless communication. AMC is widely used in civil and military field for its ability of identifying the modulation type of unknown signal without any prior knowledge. To improve the classification accuracy of feature based AMC at low signal-to-noise (SNR), a novel modulation classification scheme based on Variational Mode Decomposition (VMD) and multifractal analysis is proposed in this paper. The proposed scheme applies VMD to decompose the original signal into multiple intrinsic mode functions(IMFs). Then, multifractal analysis is used to extract multifractal features from each IMF, which combine with statistical features extracted from each IMF as the input of Extreme Learning Machine (ELM). In this paper, we use SMW200A Vector Signal Generator to generate real RF data to verify the effectiveness of the proposed scheme, and simulate the additive white Gaussian noise (AWGN) to verify the robustness of the scheme to noise. The results show that the proposed scheme can reach an average accuracy of 95% when the SNR is 0dB.
UCSF Guides: Getting Started at UCSF Library: The Basics

This guide will show you the things you need to know to make the most of UCSF Library, whether you are a student, resident, fellow, faculty or staff The mechanics of access and use of the library
399 Using Machine Learning to Inform Extraction of Clinical Data from Sleep Study Reports

Abstract Introduction In-laboratory and home sleep studies are important tools for diagnosing sleep disorders. However, a limited amount of measurements is used to inform disease severity and only specific measures, if any, are stored as structured fields into electronic health records (EHR). We propose a sleep study data extraction approach based on supervised machine learning to facilitate the development of specialized format-specific parsers for large-scale automated sleep data extraction. Methods Using retrospective data from the Penn Medicine Sleep Center, we identified 64,100 sleep study reports stored in Microsoft Word documents of varying formats, recorded from 2001–2018. A random sample of 200 reports was selected for manual annotation of formats (e.g., layout) and type (e.g. baseline, split-night, home sleep apnea tests). Using text mining tools, we extracted 71 document property features (e.g., section dimensions, paragraph and table elements, regular expression matches). We identified 14 different formats and 7 study types. We used these manual annotations as multiclass outcomes in a random forest classifier to evaluate prediction of sleep study format and type using document property features. Out-of-bag (OOB) error rates and multiclass area under the receiver operating curve (mAUC) were estimated to evaluate training and testing performance of each model. Results We successfully predicted sleep study format and type using random forest classifiers. Training OOB error rate was 5.6% for study format and 8.1% for study type. When evaluating these models in independent testing data, the mAUC for classification of study format was 0.85 and for study type was 1.00. When applied to the large universe of diagnostic sleep study reports, we successfully extracted hundreds of discrete fields in 38,252 reports representing 33,696 unique patients. Conclusion We accurately classified a sample of sleep study reports according to their format and type, using a random forest multiclass classification method. This informed the development and successful deployment of custom data extraction tools for sleep study reports. The ability to leverage these data can improve understanding of sleep disorders in the clinical setting and facilitate implementation of large-scale research studies within the EHR. Support (if any) American Heart Association (20CDA35310360).
Learning profile-based recommendations for medical search auto-complete

Query popularity is a main feature in web-search auto-completion. Several personalization features have been proposed to support specific users' searches, but often do not meet the privacy requirements of a medical environment (e.g. clinical trial search). Furthermore, in such specialized domains, the differences in user expertise and the domain-specific language users employ are far more widespread than in web-search. We propose a query auto-completion method based on different relevancy and diversity features, which can appropriately meet different user needs. Our method incorporates indirect popularity measures, along with graph topology and semantic features. An evolutionary algorithm optimizes relevance, diversity, and coverage to return a top-k list of query completions to the user. We evaluated our approach quantitatively and qualitatively using query log data from a clinical trial search engine, comparing the effects of different relevancy and diversity settings using domain experts. We found that syntax-based diversity has more impact on effectiveness and efficiency, graph-based diversity shows a more compact list of results, and relevancy the most effect on indicated preferences.
BATIK GUMELEM BANJARNEGARA SEBAGAI PEMBENTUK IDENTIFIKASI MEREK KONSUMEN

Banjarnegara as one of the batik producing centers in the Indonesia, namely in the Susukan District, which borders the Banyumas area. However, Batik Gumelem is not as famous as Batik Pekalongan, Batik Solo, or Batik Banyumas. The aim of this research is to analyze the effect of social identity to positif words of mouth that mediated of consumer brand identification. This research uses a quantitative approach with a survey method. Primary data were obtained through distributing questionnaires to 185 respondents who knew about Batik Gumelem Banjarnegara. Validity testing uses confirmatory factor analysis and all items have factor loading above 0,6. Reliability testing uses cronbach’s alpha and all variables have cronbach’s alpha above 0,6. The data analysis method uses regression with mediating variable. The results showed that social identity has a positive effect on positive word of mouth, social identity has a positive effect on consumer brand identification, and consumer brand identification has a positive effect on positive word of mouth. Consumer brand identification as role as mediating variable. This shows that Batik Gumelem is perceived to have the power to be able to create an identity for consumers and lead to behavior to disseminate information about Batik Gumelem to others.
Can Bitcoinâ€™S Price Be A Predictor Of Stock Prices?

Bitcoin has become widely used, and it can be expected that the price would have impacts on stock prices. Along with interest rates, some economic variables have been focused as deterministic elements of stock prices. This study examines whether or not Bitcoinâ€™s price can be a predictor of stock prices. Empirical results show that interest rates and stock prices are deterministic elements of stock prices. Also, among economic variables, Bitcoinâ€™s price is not a predictor of stock prices. Instead, interest rates and stock prices are suitable for predictors of stock prices.
진로적응성과 진로자신감의 관계에서 자아존중감의 매개효과

The purpose of this study is to improve the job environment and provide qualitative academic data for beauty workers by improving career adaptability and career confidence. The subjects of this study were set up for the hairdressers working in the seoul, Gyeonggi-do area. This survey was conducted from January 10, 2019 to march 10, 2019. A total of 800 questionnaires were distributed and 792copies were collected. Used as analytical 782data. Collected data were analyzed using spss 22.0 program. As a result of evaluating the validity and reliability of career adaptability, self-esteem and career confidence it consisted of three factors of career adaptability, career interest, career control and career aspiration. As a result of investigating the effect of career adaptation on self-esteem, the higher the factors of career interest career control and career aspiration the higher self-esteem. The higher the career confidence the higher the factors of career interest career control and career aspiration. As a result of the mediating effect of self-esteem in the relationship between career adaptability and career confidence the following is suggested you need to believe in yourself as valued person have a positive attitude toward yourself improve your confidence in your career improve career adaptability by overcoming challenges and maintain a positive attitude toward yourself.
PENERAPAN ALGORITMA NEURAL NETWORK UNTUK KLASIFIKASI KANKER PARU

Neural Network Algorithm is an algorithm that is used to study the workings of the human brain which is applied to neurons connected to billions of network requirements and is able to work in many data learning processes, in this case the neural network algorithm will study the classification of lung cancer. Lung cancer is the third largest type of cancer in Indonesia. Lung cancer is divided into three classes of lung cancer pathologically. Class 1 consists of 9 observations, class 2 consists of 13 observations and class 3 consists of 10 observations. The results of lung cancer testing with this neural network algorithm produce an accuracy value of 75%, thus the neural network algorithm can be ascertained in classifying the pathology of lung cancer obtained from a survey by Stefan Aeberhard with a total sample size of 32 people and a total of 57 attributes. , one class label attribute and 56 attributes in the form of a nominal integer with a limit between 0-3 classes in the UCI Dataset.
LibGuides: GALILEO Discovery at Columbus State University: Overview and Searching GALILEO Discovery

This guide will introduce you to the GALILEO Discovery search and provide you with tips and tricks of how to use Discovery to find resources for your research.
Arithmetic Soundness of Deduplication Security Frameworks

The incomplete theory suggest that in real world conditions, contracts cannot specify what is to be done in every possible contingency. A contact may be a simple economic tie up or maybe a contacts between multiple software components .Future contingencies may not even be describable when the contact or software is been build . Same is true, when a security frameworks are designed for Deduplication. Not all breaches in security structure of Deduplication System can be defined beforehand. However, the concept of provable security suggests that the adversary model and security model must be defined beforehand only then the security can be implemented. In this research work, we discuss how the axioms and postulates change and expand to satisfy new technical scenarios. As the expansion occurs the system can handle more security issues but at each stage there is a need to check the completeness, arithmetic soundness or arithmetic validity of the system in question. The computations of the checking the arithmetic validity and Proof of ownership schemes take some degree of overhead The work attempts to compute over head in computing the validity of provable security system of Deduplication in multiple Deduplication security scenario.
Perancangan Sistem Informasi Akuntansi Berbasis Microsoft Access Pada Apotek Samaritan

The Apotek Samaritan Singkawang uses a manual accounting system so that the information required cannot be on time, and can even lead to neglect of relevant and faithful representation. Therefore, our community service aims to design and produce a computerized accounting information system using Microsoft Access. We have conducted in-depth interviews with pharmacy owners and field observations. The resulting accounting information system includes a list of accounts forms, customer forms, inventory forms,  supplier forms, purchase forms, debt payment forms, sales forms, general journal forms, and inventory adjustment forms. In addition, financial reports include balance statements, income statements, statements of financial statements, statements of changes in capital, purchase reports, sales reports, ending inventory reports, and accounts payable reports. All information systems are integrated with each other and become a relational database. Thus, the implementation of this community service has succeeded in improving the quality of bookkeeping of the Samaritan Singkawang Pharmacy, and can even be adopted by similar industries.
Analisis Usability Pada Aplikasi Belido.id Menggunakan Metode System Usability Scale (SUS)

Belido.id is an online marketplace that provides opportunities for all people to carry out buying and selling transactions online by concentrating on the Sumatran market, especially the southern part of Sumatra, which gets support from AIESEC. In providing Belido.id services, you definitely want to provide the best service, Belido.id does not want to disappoint users because of applications that are difficult to use so that users fail to find information or fail in buying and selling activities. To get a product that suits your needs, both in terms of display design and the system used, of course, it is necessary to analyze the usability of the product. The purpose of this research is to ensure that the Belido.id software is suitable for use by users or not, then a usability test is carried out on the Belido.id application using the System Usability Scale (SUS) testing method. This test uses 10 statements as a benchmark for assessment. With 80 respondents. The results of the usability test of the Belido.id application with the SUS method show that the final results of the research on testing through a questionnaire are 61,5 are in grade D which means the Belido.id application still has a little difficulty or there are obstacles when using this application.
Application and Comparison of Majority Weighted Minority Oversampling Techniques and Random OverSampling Examples Data Balancing Methods on the Vertebral Column Dataset

In recent years, Data science has emerged as most conspicuous multidisciplinary field. The raw data that are gathered from multiple sources usually have issues like missing data, imbalance data, scaling, normalization and so on. Hence, practically almost all raw dataset need to be converted to more application suitable form. From these facts, it is apparent that data preprocessing is extremely necessary phase of any data analysis task. Despite the fact that not all preprocessing method need to be applied on a solitary dataset, but one or more could be required to form usable formatted dataset. Like any dataset, the Vertebral column dataset also isn’t always similarly disbursed to the class label. So right here to solve the problem, in this work, two data balancing algorithms namely Majority Weighted Minority Oversampling Techniques (MWMOTE) and Random Over Sampling Examples (ROSE) applied. Furthermore, simulation results are generated using R Software and assessed estimating processing time. As a result, ROSE algorithm takes less processing time than MWMOTE to balance the data.
Analysis of the effectiveness of WhatsApp in improving online English learning

This research was a quantitative study using a questionnaire instrument. This study aimed to determine the responses of students of SMP Negeri in Bandar Lampung in the learning process using the WhatsApp application and to analyzed its effectiveness from the results of the questionnaire. Students involved in this study amounted to 30 students. Students were asked to fill out a questionnaire that has been made by the researcher, which amounts to 20 statements. dx.doi.org/10.23960/aksara/v21i2.pp185 -190
DEVELOPMENT OF CREATIVE POTENTIAL OF THE FUTURE TEACHER IN THE ORGANIZATION OF PEDAGOGICAL EDUCATIONAL ACTIVITY IN THE CONDITIONS OF CHILDREN'S SUMMER IMPROVING CAMP

Proceedings Article published 2021 in CURRENT TRENDS AND FACTORS OF THE DEVELOPMENT OF PEDAGOGICAL AND PSYCHOLOGICAL SCIENCES IN UKRAINE AND EU COUNTRIES
The Transition of Traditional Pottery-Making into Advanced Ceramics in Context to the Indian Ceramic Industry

The unexpected evolution in the science and technology sector has transformed India's traditional pottery-making into advanced ceramic. Owing to the ceramic industry's market expansion, traditionally based pottery-making industries have now experienced rapid modern machinery growth. Pottery manufacturing has been one of the prestigious arts in the ancient history of India. During these days, pottery making process used for clay fired at low temperatures and open bonfires. They were generally based on hand made techniques and less decorated. A sudden upsurge in technology and industry has made development in the use of ceramic glazes that improved the popularity and practicality of ceramic usage. The present research report delivers information that government support for the housing sector and increasing demand for high-end products have influenced the Indian ceramic industry's significant development. In modern-day industrialization and globalization, India ranks third in its ceramic trading activities with a global industry growth rate of 11%. It demonstrates the achievement of the transition from traditional pottery-making to advanced ceramics. The research paper focuses on various aspects such as origin, history, development, innovation, technology up-gradation, research, and development of the ceramics industry with particular reference to India.
LibGuides Home: 2021 RISE: Research and Innovation Symposium and Exhibition: Write an Abstract

This serves as program and guide to the 2021 Virtual Norfolk State University Research and Innovation Symposium. Tips on how to write an abstract.
Perancangan Enterprise Architecture Sistem Informasi Menggunakan Framework TOGAF ADM 9.2 PT. XYZ

PT.XYZ is a gas oil manufacturing company, which produces offshore oil and gas drilling equipment. In supporting its business processes, this company uses a separate module application which causes data flow to be interrupted and results in the company experiencing delays in managing data and getting information on time. Based on the analysis of the problem, the researcher will design an integrated enterprise information system architecture for sales, finance, raw material procurement, production, project plan, and inventory. The method used is the TOGAF ADM 9.2 framework which consists of four phases, namely the vision architecture, business architecture, information system architecture, and technology architecture phases. This enterprise architecture design produces a blueprint as a guideline or framework in the development of information systems at PT. XYZ. The overall result of this research is to produce an enterprise architecture information system design