Reviewerly/exHarmony huggingface dataset:
Varying Annotations in the Steps of the Visual Analysis

Annotations in Visual Analytics (VA) have become a common means to support the analysis by integrating additional information into the VA system. That additional information often depends on the current process step in the visual analysis. For example, the data preprocessing step has data structuring operations while the data exploration step focuses on user interaction and input. Describing suitable annotations to meet the goals of the different steps is challenging. To tackle this issue, we identify individual annotations for each step and outline their gathering and design properties for the visual analysis of heterogeneous clinical data. We integrate our annotation design into a visual analysis tool to show its applicability to data from the ophthalmic domain. In interviews and application sessions with experts we asses its usefulness for the analysis of patients with different medications.
To the issue of raising the level of leadership activity of the class teacher

The article actualizes the problem of increasing the importance of classroom leadership in the educational activities of the school, reveals the essence of modern approaches to organizing and ensuring the educational potential of an educational institution, analyzes pedagogical actions that contribute to increasing the effectiveness of teacher-educator activities. The author introduces a complex of interconnected individual educational influences that contribute to raising the effectiveness of education. The importance of a personality-oriented approach in improving the qualifications of a teacher-educator as a factor in ensuring the successful development of an individual style of activity formed on the basis of individual characteristics is noted.
IMPROVING EFFICIENCY OF LOAD TESTING OF LOCALISATION SOFTWARE Y USING THE FUNCTION OF CONSTRUCTING A TRANSLATION TEST DICTIONARY

The article discusses the features of the implementation of software for the localisation of developed software at the initial stage of its development; we compiled a list of problems necessary to consider when choosing software for localisation; an option is proposed for solving the main problems by developing a function for constructing a test dictionary that allows it to be scaled for software under development; we present the results of a study of a number of existing dictionaries of localisation of popular software; it is concluded that it is necessary to calculate the values of the parameters of the construction function depending on the type of software; the analysis of localisation dictionaries is carried out and a number of parameters of the function for constructing a test dictionary for the requirements of the developer are prepared.
Research on Fast Detection and Recognition of Object Features Based on Feature Line Matching

Abstract As one of the most prominent and important features of visual information, feature lines exist in real objects and target scenes. The characterization features of the pixels on the feature line are constructed. The pixels are classified and output by representing the eigenvalues to complete the classification of different target feature lines. The local gradient information of the points in the straight line segment is extracted and the midpoint descriptor is formed to match the straight line segment accurately. The edge detection is performed sequentially, the edge line of the object feature is extracted, and the edge principal point is obtained simultaneously according to the distance judgment. The research shows that the feature line matching method greatly reduces the calculation amount of matching and greatly improves the matching accuracy. The flexibility of building samples is strong, and different levels of sample forms can be selected according to different application requirements, and the robustness of matching and identification is good. The method is suitable for rapid detection and identification of object features, as well as product feature detection and recognition.
PENGARUH MIND MAPPING TERHADAP KETERAMPILAN MENULIS PUISI KELAS VIII SMPN 1 LUMAR KABUPATEN BENGKAYANG

AbstractThe purpose of this study is to describe the average poetry writing skills in students with the application of the Mind Mapping Learning model, the average poetry writing skills in students with the application of the Learning Learning Model.The theory used in this research is a mind mapping learning model and writing poetry. The method used is an experimental method with a form of research Quasi Experimental Design. The design used is the Two-Group pretest-Posttest Only. The population in this study is class VIII A, VIII B, and VIII C while the samples are Class VIII A and VIII B. Data collection techniques used are direct observation techniques, measurement techniques, and documentation techniques as well as data collection tools namely guidelines or observation sheets poetry skills tests and documents.The results of data analysis show that the average pre-test experimental class with a total score of 69.38 while the post-test 76.38 and the pre-test control class with a total score of 60.96 while the post-test 66.88 and there is influence with evidence scores 1.13 and 1.28.The results of this study are expected to be useful for readers, especially Indonesian Language teachers in Lumar 1 Junior High School, Bengkayang Regency, students and subsequent researchers who use mind mapping learning object models. For teachers this mind mapping learning model can be used as a reference for teaching in class, especially in learning to write poetry. Keywords: Mind Mapping, Writing Poetry
Chemist documents North America’s ancient art﻿

Because of dams built on the Rio Grande and an increase in flash floods in Southwest Texas, the nonprofit Shumla Archaeological Research & Education Center has embarked on a quest to document more than 350 ancient rock paintings near the Lower Pecos Canyonlands before they’re irreparably damaged. Among Shumla’s archaeologists is a chemist, Karen Steelman, who is incorporating portable X-ray fluorescence methods to help rediscover the painting techniques of the people who once lived there. In the latest episode of Speaking of Chemistry, we talk to Steelman about one of the stories that Shumla’s team thinks it has uncovered peering beneath the surface of the rock paintings—among the oldest known in North America. Watch the episode at cenm.ag/x-raytools. Subscribe to C&EN’s YouTube channel for more Speaking of Chemistry and news videos.﻿
Characterizing Stage-Aware Writing Assistance in Collaborative Document Authoring

Writing is a complex non-linear process that begins with a mental model of intent, and progresses through an outline of ideas, to words on paper (and their subsequent refinement). Despite past research in understanding writing, Web-scale consumer and enterprise collaborative digital writing environments are yet to greatly benefit from intelligent systems that understand the stages of document evolution, providing opportune assistance based on authors' situated actions and context. In this paper, we present three studies that explore temporal stages of document authoring. We first survey information workers at a large technology company about their writing habits and preferences, concluding that writers do in fact conceptually progress through several distinct phases while authoring documents. We also explore, qualitatively, how writing stages are linked to document lifespan. We supplement these qualitative findings with an analysis of the longitudinal user interaction logs of a popular digital writing platform over several million documents. Finally, as a first step towards facilitating an intelligent digital writing assistant, we conduct a preliminary investigation into the utility of user interaction log data for predicting the temporal stage of a document. Our results support the benefit of tools tailored to writing stages, identify primary tasks associated with these stages, and show that it is possible to predict stages from anonymous interaction logs. Together, these results argue for the benefit and feasibility of more tailored digital writing assistance.
Investigating the Effect of Intraclass Variability in Temporal Ensembling

Temporal Ensembling is a semi-supervised approach that allows training deep neural network models with a small number of labeled images. In this paper, we present our preliminary study on the effect of intraclass variability on temporal ensembling, with a focus on seed size and seed type, respectively. Through our experiments we find that (a) there is a significant drop in accuracy with datasets that offer high intraclass variability, (b) more seed images offer consistently higher accuracy across the datasets, and (c) seed type indeed has an impact on the overall efficiency, where it produces a spectrum of accuracy both lower and higher. Additionally, based on our experiments, we also find KMNIST to be a competitive baseline for temporal ensembling.
Research Guides: ADV 208: The Big Idea in Advertising (Fall 2020): Industry & Market Research Databases

An SU Libraries research starting points guide for students enrolled in ADV 208 (course sections taught by Profs Brian Sheehan and Mel White)
Perancangan Infografis Bahaya Anoreksia Nervosa

Anxiety in someone about his own body will bring up a sense of dissatisfaction with what he has now and has the urge to follow the physical appearance that has been desired by the community.Anxiety in a person can lead to changes in physical appearance such as fear of being fat which causes disturbed eating patterns.Due to the disruption of a person's diet, his organs lack a nutritional intake which can cause stomach, heart and endocrine disorders in a person.For this reason, researchers see an urgency to provide information to readers of the dangers of anorexia nervosa.For this reason, we chose infographic media, which is a medium for drawing data using icons and the message is packaged so that the message content can be embedded in the people's mind.The results of this infographic visual style we use flat visual style because it's simple and easy to understand like an icon of a woman who looks so sad.Then the typography we used is the type of san serif type which provides the reader and uses purple tones to mean sadness.In this study we use a secondary data approach by collecting data using literature studies by reading journals, the web, and articles.
Nature of Government - Subject - Index to the AMA archive

Nature of Government - Subject - Index to the AMA archive - NAME is a biographical, bibliographical and archival database of SUBJECT with links to related articles and images. ADD MORE DESCRIPTION AS REQUIRED
THE COMPARATIVE STUDY OF READING COMPREHENSION ABILITY BETWEEN STUDENTS WITH EXTROVERT AND INTROVERT PERSONALITYAT SMAN 1 BANDAR LAMPUNG

The objectives of this research are to find out whether there is any significantdifference of students’ reading comprehension achievement between students withextrovert and introvert personality. The population of the research was the studentsof the first grade of SMAN 1 Bandar Lampung in the academic year 2019/2020totally 287 students. The sample of this research was X MIA 2 consisting of 35students.The result showed that there was difference between the mean score of extrovertstudents (78.2) and that introvert students (72.5). The researcher used Sig. (2-tailed) in SPSS 16 to do the calculation with the significant level of 0.05. The resultshowed that the Sig. (2 - tailed) is 0.001 < 0.05. Due to the value of Sig. (2 tailed)is lower than 0.05, it means there is a significant difference between introvertstudents’ reading comprehension ability and extrovert students. Based on the resultof the research, it is proved that the extrovert students have better result thanintrovert one in reading comprehension test. So, from this statement the researcher’shypothesis (Hi) is accepted.Keywords: comparative study, extrovert and introvert personality, readingcomprehension
Efficient streaming data association rule mining

Recently, number of applications including social networks, stock market trading and sensor network devices generate a massive amount of data in the streaming form.Streaming data have characteristics different from static data, such as streaming data arrives continuously at high speed with huge amount.Mining and discovering information from these data is a non-trivial issue.Most of traditional algorithms have limitations to deal with streaming data, so there are new issues raised and need to be taken into consideration while developing techniques for mining association rules from such data.In this paper, a technique to mine an association rules from streaming data efficiently is proposed.The proposed technique develops a tree structure called Fast Update Frequent Pattern Tree (FUFP-Tree) that reduce the number of traversing between tree nodes in both inserting a new transaction and extracting an association rules between items.Also, to avoid congestion during inserting incoming streaming data to FUFP-Tree, a sliding window approach is used to divide incoming data equally to all available windows.The complexity and the performance of this technique are investigated, and a dataset of storehouse is used to test the proposed technique and measure its efficiency.The efficiency of the proposed technique is compared with other most related algorithms.
Defining collocation for Slovenian lexical resources

In this paper, we define the notion of collocation for the purpose of its use in machine-readable language resources, which will be used in the creation of electronic dictionaries and language applications for Slovene. Based on theoretical and lexicographically-driven studies we define collocation as a lexical phenomenon, defined by three key aspects: statistical, syntactic, and semantic. We take lexicographic relevance as a point of departure for defining collocations within the typology of word combinations, as well as for distinguishing them from free combinations. Free combinations are (frequent) syntactically valid word combinations without lexicographic value and consequently there is no need for the description of their meaning, or syntactic role. Next, we distinguish collocations from all multiword lexical units (compounds, phraseological units and lexico-grammatical units) using the lexicographic view that multiword lexical units, whose meaning is not a sum of its parts, require a description of their meaning whereas collocations do not. In the final part, we return to the three aspects of collocation and their role in automatic extraction of collocational information from corpora. Semantic criterion or dictionary relevance of extracted collocations has particularly exposed the problem of semantically broad collocates such as certain types of adverbs, adjectives and verbs, and word which feature in different syntactic roles (e.g. pronouns and adjuncts). We discuss a particular issue of collocations related to proper names and the decisions about their inclusion into the dictionary based on the evaluation of lexicographers.
LibGuides: TigerHow: Set Up Email, Blackboard and Banner Web (Distance Education): New Students: First, Set Up Email

Learn how to set up and log into email, Blackboard and Banner Web. New Students: First, Set Up Email
Hubungan antara Komunikasi Nonverbal Pengajar dengan Motivasi Belajar Siswa

Abstrak — communication is one thing that cannot be released. The message must be conveyed between the teacher and student through the communication process. The communication process is not only done with verbal communication, but also with nonverbal communication. However, not many teachers pay attention to their nonverbal languages when teaching and learning are carried out. In fact, the application of nonverbal communication in the learning process is very important in efforts to increase student motivation. Student motivation is one thing that plays an important role in teaching and learning activities. One of the non-formal educational institutions engaged in the English language and paying attention to the teaching of nonverbal communication is the Global Learning Education Center. Nonverbal communication is highly considered in Global Learning because it is expected to foster motivation of the student to learn English. This study aims to determine whether there is a relationship between nonverbal communication provided by the teachers with learning motivation of the student in Global Learning. This research used stimulus-response theory and used correlational quantitative research methods. In this study, the variable (X) is nonverbal communication and the variable (Y) is learning motivation. The population of this study is 75 people whose value would be the research sample. From this study, it was found that all indicators have a relationship. Nonverbal communication indicators, namely facial expressions, eye contact, touch, body posture, voice and gesture have a relationship with learning motivation. variable (X) nonverbal communication has a strong relationship with variable (Y) English learning motivation. Keywords — Communication, Nonverbal, Student Motivation.
Using Ensemble Classifiers to Detect Incipient Anomalies

Incipient anomalies present milder symptoms compared to severe ones, and are more difficult to detect and diagnose due to their close resemblance to normal operating conditions. The lack of incipient anomaly examples in the training data can pose severe risks to anomaly detection methods that are built upon Machine Learning (ML) techniques, because these anomalies can be easily mistaken as normal operating conditions. To address this challenge, we propose to utilize the uncertainty information available from ensemble learning to identify potential misclassified incipient anomalies. We show in this paper that ensemble learning methods can give improved performance on incipient anomalies and identify common pitfalls in these models through extensive experiments on two real-world datasets. Then, we discuss how to design more effective ensemble models for detecting incipient anomalies.
Positive Management Tools in Education Management

The purpose of the study is to identify the problem areas in education management and the opportunities to apply positive management tools. The authors believe that it is possible to diminish the issues related to authoritarian education management by using the tools and principles of positive psychology, specifically, positive management connected to addressing the human factor. The authors note the inefficiency of strict and regulated methods of education management as it often requires unorthodox, original solutions. The article contains the results of the pilot study of education workers’ subjective perception of a positive management tool – engagement. The survey method has been utilized for the study. The analysis of the data has resulted in the following conclusions: 1) it has been found that the positive management tools identified through the analysis are insufficiently used in education management; 2) the identified problem areas in education management are related to expectations for work, satisfaction with the evaluation and feedback, interpersonal relations, as well as career and development.
ANALISIS FAKTOR-FAKTOR PENYEBAB KESULITAN BELAJAR SISWA PADA MATA PELAJARAN AKUNTANSI

This study aimed to: (1) to find out Internal factors that influence student learning difficulties in accounting subjects (2) To find out any external factors that influence student learning difficulties in accounting subjects ;(3) To find out dominant factors influence the causes of learning difficulties in accounting subjects. This research method was quantitative research. The population in this study were all students of class XI Accounting in the odd semester of state vocational high school (SMKN) in Serang City. The validity of the questionnaire instrument was performed by item analysis used the Product Moment correlation formula and the reliability test used the Cronbach’s Alpha formula. The data analysis technique used factorial analysis Confirmatory factor analysis model. The results of this study indicated that: the biggest internal factor that causes the learning difficulties for learners was (1) a physical factor with eigenvalue of 3.735 and a variance value of 19,659% (2) the biggest external factor that caused the learning difficulties were family factors with an eigenvalue of 3.735 and a variance value of 19.6%.
QR Code-based Student Attendance System in STMIK "AMIKBANDUNG"

One of the important things that need to be considered in student assessment is the problem of student presence. The student attendance process that is very commonly done by universities is recording attendance manually, as currently applied by STMIK "AMIKBANDUNG". QR Code technology is a technology that can encode and decode all types of data into an image in the form of a code and can be read with a smartphone, this is very suitable for use as data validation, which is usually used for digital payment methods today. With these advantages QR Code technology can be implemented as well as supporting media in the smooth process of lecture attendance, This is interesting to the author to conduct research on lecture presence design using QR Code technology, with QR Code technology, each student is expected to no longer need to sign the form absent because the presence data will be identified automatically via a smartphone that can scan the QR Code and be stored in the system database.
Natural Language Processing in AI: Language Interpreter

With the emergence of Artificial Intelligence in this technocrat world has led to the transformation in the world of technology. With the emergence of Artificial Intelligence it has led to different more technologies such as voice assistants which work for humans in order to make it easy in the workplace but in order to make it more of use and understandable. It has been proved to best suited for study of mathematical and computational modeling of various aspects of language. It widely includes a spoken language system which mainly integrates with speech and natural language. Natural Language Processing mainly focuses on the areas like Research and Language Text type of applications. It is being mentioned that Natural language is viewed in two terminologies as Rule based and Statistical based. Natural Language Processing has the base on heuristic search stemming with a tremendous root cause. Uses majority of English language rules and processing regulation for speechtual. Keywords: Artificial Intelligence, Deep Learning, machine learning, Techniques of Natural Language Processing, Natural Language Processing, Lexical Input, Natural Language Generation, Natural Language Understanding. Cite this Article: Sapna Sharma. Natural Language Processing in AI: Language Interpreter. Journal of Artificial Intelligence Research &amp; Advances. 2020; 7(2): 21–27p.