Reviewerly/exHarmony huggingface dataset:
Real Time Principal Component Analysis

By processing the data in motion, real-time data processing enables us to extract instantaneous results from online input data that ensures timely responsiveness to events as well as a much enhanced capacity to process large data sets. This is especially important when decision loops include querying and processing data on the web where size and latency considerations make it impossible to process raw data in real-time. This makes dimensionality reduction techniques, like principal component analysis (PCA), an important data preprocessing tool to gain insights into data. In this paper, we propose a variant of PCA, that is suited for real-time applications. In the real-time version of the PCA problem, we maintain a window over the most recent data and project every incoming row of data into lower dimensional subspace, which we generate as the output of the model. The goal is to minimize the reconstruction error of the output from the input. We use the reconstruction error as the termination criteria to update the eigenspace as new data arrives. To verify whether our proposed model can capture the essence of the changing distribution of large datasets in real-time, we have implemented the algorithm and evaluated performance against carefully designed simulations that change distributions of data sources over time in a controllable manner. Furthermore, we have demonstrated that our algorithm can capture the changing distributions of real-life datasets by running simulations on datasets from a variety of real-time applications e.g. localization, customer expenditure, etc. We propose algorithmic enhancements that rely upon spectral analysis to improve dimensionality reduction. Results show that our method can successfully capture the changing distribution of data in a real-time scenario, thus enabling real-time PCA.
미디어 리터러시(Media Literacy)를 활용한 영화영어 수업 방안에 관한 연구

The purpose of the paper is to suggest a way to get college students to become active in screen English classes. In order to do this, the concept of...
CODE MIXING IN A NOVEL CELEBRITY WEDDING BY ALIAZALEA

This study is aimed to describe code mixing facts or presence in the novel Celebrity Wedding by AliaZalea. In fact, there are a lot of factors that influence people using code mixing, to mention one or two, can be due to someone’s bilingualism or multilingualism condition. The writers use descriptive and content analysis method to analyze the forms code mixing, the types of phrases and compound of code mixing found in the novel Celebrity Wedding. The (English) data taken from the Novel are phrases, compounds. The writers then identified, collected, sorted and classified all the data, and made the analysis to find and determine the types of the phrases and the forms/types of modifiers present in the novel itself. From the result of analysis/discussion there are more Noun Phrase Types than Verb Phrase Types. There are five Noun Phrases containing premodifiers and four postmodifiers five containing both premodifiers, the dominant modifiers are Adjective followed by Noun the Preposition Phrases.
Rapid Annotation Tool to Train Novel Concept Detectors with Active Learning

Annotating a large set of images, especially with bounding boxes, is a tedious task. In this paper, we propose an intuitive image annotation tool. This tool not only allows (non-expert) users to annotate images with novel concepts, but is also able to achieve acceptable performance with a smaller number of annotated images. The tool can also propose detections on unannotated images, to provide faster annotation and insight in the performance of the system. The tool is based on a Single Shot Multi-box Detector (SSD) neural network with active learning, based on showing the images with high-confidence detections first, to have a fast verification and re-training. An experiment on simulated data shows that this active learning method can achieve higher performance in a shorter expected annotation time with a small number of images (less than 500). A small experiment on user annotated data shows that the annotation tool allows faster annotation compared to without the annotation tool
Seismic Soundoff

The following is an excerpt from SEG's Seismic Soundoff podcast. The episode features Priyank Jaiswal discussing the potential threats to infrastructure from low-level earthquakes, how citizens and public officials can monitor and address the impact, and how geophysicists can contribute to the safety of infrastructure. Listen to the full episode at https://seg.org/podcast/post/6630/ .
An approach for public cloud trustworthiness assessment based on users' evaluation and performance indicators

Aiming at the problem of how to quantify the trustworthiness of public cloud services, this paper proposes a method to evaluate the trustworthiness of public clouds based on users' subjective evaluations and objective monitoring values of performance indicators. According to the objective values obtained from monitoring organisations, the objective trustworthiness is calculated by using a multi-attribute decision-making method based on the ideal point (TOPSIS). Meanwhile, qualitative users evaluations are quantified by exploiting the cloud model. Finally, a comprehensive assessment of the trustworthiness of cloud service is formed based on the above results. To meet the personalised requirements, users could configure the weight of parameters included in the proposed algorithms, ranking cloud services for specific needs. Compared with other assessment algorithms, both the subjective source and objective source are taken into account, the customised weight scheme for users is provided, the model and the algorithms are designed, and a prototype is developed.
Strengthening Oral Competence Through Computer Assisted Pronunciation Training, a Preliminary Study

Oral skills development is a critical aspect when learning English since it is a complex process which involves much more than simply pronouncing isolated words. The purpose of this study was to determine the relationship between the use of the software My English Tutor and the oral skill competence. This research was applied to 18 pupils from third semester and 11 pupils from fourth semester in the English Teacher Training Program at Technical University of Ambato. This preliminary study was carried out using both a control and experimental group design, pre-tests and post-tests were applied as well. Pupils from the experimental group took active part in the practice of MyET Software activities, and the employment of a t-test was used to proof the hypothesis. Furthermore, surveys were used to determine the degree of acceptance and usefulness of this software. The results revealed that the improvement in pronunciation was the same for both control and experimental groups. Additional testing should be done to validate the scores obtained by students with the use of this tool. Pupils showed a positive attitude about using this technological tool.
PENGEMBANGAN MEDIA PEMBELAJARAN BERBASIS VIDEOSCRIBE PADA MATERI SEJARAH KERAJAAN ISLAM DI SUMATRA DAN AKULTURASINYA KELAS X SMA MUHAMMADIYAH 1 METRO

The purpose of this study is (1) to analyze the learning conditions in class; (2) determine the design of videoscribe-based learning media in the material history of the Islamic kingdom in Sumatra and its acculturation; and (3) analyze the feasibility of learning media using videoscribe based videos on the material history of the Islamic empire in Sumatra and its acculturation. Research and development was carried out using the design model of research and development (R&amp;D) development adapted by Sugiono Level 1 (producing a design but not testing). The results of the study show that (1) learning media as an intermediary for the learning process has not been utilized efficiently; (2) the media developed in the form of videoscribe based learning media in the material history of the Islamic empire in Sumatra and its acculturation are associated with character values; (3) the results of the feasibility of developing videoscribe based learning media in the material history of the Islamic empire in Sumatra and its acculturation validated by media experts stage 1 (62%), after revising the product and conducting stage 2 validation of (76%) so that it increased 14% by category "Decent". Validation results by material experts stage 1 (79%), after revising the product and doing stage 2 validation (95%) so that it increased 16% in the category of "very feasible". Videoscribe based learning media were tested with the results of student response questionnaires (85.2%) with the category "very feasible".
Цифровизация инженерного образования в глобальном контексте (обзор международных конференций)

The paper addresses the advanced topics of engineering education, including digitalization, which were discussed at the 21st International Conference on Interactive Collaborative Learning (ICL) and 47th IGIP International Conference on Engineering Pedagogy (IGIP) held on the Kos Island, Greece in September, 2018. The conference set out a wide range of problems relating to a new interactive educational technology, to developing online-, digital, and e-learning, to the visualization and gamification of education, to developing in engineers academic and applied competences, to implementing new education environments, etc. The Russian researchers’ contribution to the development of engineering pedagogy was emphasized, including improving training of engineering university professors and holding the SYNERGY Engineering Education Research and Practice Network Conference in the leading technical universities of Russia.
Морфологический и спектральный анализ гистологической ткани с использованием глубоких сверточных сетей

The results of a study of the application of deep neural convolutional networks to hyperspectral images are presented.
A Multi-view Deep Learning Approach for Detecting Threats on 3D Human Body

Deep Neural Network-based methods have recently shown an outstanding performance on object detection tasks in 2D scenarios. But many tasks in real world requires object detection in 3D space. In order to narrow this gap, we investigate the task of detection and localization in 3D human body in this paper, and propose a multi-view-based deep learning approach to solve this issue. The experiments show that the proposed approach can effectively detect and locate specific stuff in 3D human body with high accuracy.
“The Effectiveness of Computer- Based Sight Words to Improve Reading Skill in Autism. "Discuss

Specialists in the field of Special Education endeavour to achieve educational integration for people with special needs, particularly people with autism.The term "Autism" means that is a developmental disorder (Dautenhahn & Werry,2004).However, academic problems stand as barriers towards achieving the principle of educational integration for this category.These academic problems are due to the developmental and educational features of this students, such a weak in Social communication, a difficulty with social relationships and in the development of play and imagination (Dautenhahn & Werry,2004).It seems that some of the most serious problems faced by autism persons in the classroom is difficulties of reading due to their inability to read and understand information conveyed through writing, and this negatively impacts their independence and selfreliance capabilities (Alotaibi,2001).It has been argued that sight words strategy could be a solution to this problem.This essay will describe that definition and effectiveness of sight words strategy as well as teachers' problems with autism students.
AN ANALYSIS OF WORD FORMATION PROCESSES FOUND IN INSTAGRAM

This thesis was conducted to focus on the word formation processes found in Instagram . Words also underwent some processes in their formation. The research method of this study was descriptive qualitative. This study used documentation as  its instruments. The theoretical framework of word-formation processes was promoted by Delahunty and Garvey (2010) and Plag (2003). The data were obtained through document analysis. The writer found that there were 38 words of acronym, 17 words of borrowing, 15 words of abbreviation, five words of blending, two words of coinage, and one word of affixation from the total of 78 data found. It can make the conclusion that the aim of different types of word formation processes assisted people to understand the function of each word formation processes in order to avoid mistake in their writing. Expectantly, it might be useful for other researchers who are interested in word formation processes.
USING RASPBERRY PI HUMAN MACHINE INTERFACE TECHNOLOGY FOR VIRTUAL TALKING SYSTEM WITHOUT SENSOR AND VIRTUAL DISPLAY SYSTEM FROM VOICE COMMAND IMPLEMENTATION

Every day we see many people who are facing problem like deaf, dumb and blind etc. Cooperating with others individual without preparing is issue for better communication. Recently created methods are all sensor based and they didn't gave the general arrangement. This paper clarifies another strategy of virtual display system from voice command without sensors utilizing Raspberry Pi. A picture preparing system called Histogram of gradient (HOG) alongside artificial neural network (ANN) has been utilized to prepare the picture. Web Camera is utilized to take the picture of various signals and that will be utilized as contribution to the Mat lab along with a digital display will convert voice to hand gestures which are stored in database. The product will perceives the picture and distinguishes the relating voice yield which is played utilizing voice replay pack. This will be a two way communication between Deaf and Mute, when a mute shows hand signal the device will convert it to voice, whereas when a deaf speak to mute voice will convert to hand gestures which will be useful for mute to communicate . This paper discloses hand flag to voice correspondence between the hard of hearing, imbecilic and typical individuals.
Predictive Analysis in Power Query with R

In this chapter, the process of doing machine learning inside Power BI Query Editor by writing R code will be explained. The main aim here is to provide some examples of how we can use R codes for predictive analysis (classification and regression). The concepts and codes related to some of the algorithms will be provided. In addition, the process of automating predictions via parameters inside Power BI Query Editor also will be discussed.
Powering the Internet of Things and Big Data through Machine Learning

Eventually Internet of Things, Big Data, and Machine Learning will be an exposure to the wide-ranging scale of current applications. The Internet is getting linked to numerous appliances equipped in simple things, which allows them to deliver and accept the information or data. Big data is more of a progress than a thing. It has become the cover for the compilation, study and repository for huge amount of data. Machine learning is a function of Artificial Intelligence that implements the system’s intelligence to automatically learn and advance from experience without using any special programs. The focus of Machine learning is to advance the computer programs that can approach the data and utilize it to learn for them.  An increasing measure of powerful data origins, drive in Internet of Things & Big Data improvement, also the convenience of a large variety of Machine learning computations attempts new possibilities to bring logical control to industries. Extensive amount of data have been generated, since the past decade as the downgrade of Internet of Things tools increments. Yet, such data is not beneficial without experimental abilities. Different Big Data and Internet of Things analysis arrangements have granted individuals to achieve effective knowledge into broad information generated by Internet of Things objects. Nonetheless, these arrangements are fixed in their original stages and the domain does not have a detailed report on this. This paper gives an acceptable deeper understanding about the Internet of Things and Big Data structure parallel to its various issues and challenges. It also gives possible solutions addressed by Machine Learning.
A Survey: A Social Explanation System Applied to Group Recommendations

Recommendation systems are currently successful solutions to enable online users to access information that meets their preferences and needs in congested environments.In recent years, various methods have been developed to improve their performance.This paper provide an overview of the use of fuzzy tools in recommended systems to identify common research topics and the pillars examined and to identify candidates for future research lines to support current societal developments.Based recommendation systems there is a need to research analytical analytics systems that design the design and development of the reporting system, not just the latest products.This design and development process uses analysis, visual design analysis, information modification approaches, and scientific research.In addition, experiments are required to determine the impact of these systems on learning behaviour, its range, and capabilities to add to the small evidence available.
Some Suggestions for the Wide Adoption of Integrated Report of Corporations in Korea

본 연구의 목적은 우리나라 기업의 통합보고서 확산을 위한 제언을 하는 것이다. 이를 위해 2013년 12월에 공표된 IIRC의 통합보고 프레임워크의 특징과 핵심 개념을 기술하고, KPMG 재 펜에서 실시한 일본 기업의 통합보고서 실태조사를 참고하였다. KPMG 재펜은 2017년 12월 말 현재 통합보고서를 발간하고 있는 341개 기업을 대상으로 장기지향, 가치창출, 지배구조, 중요성, 리스크와 기회, 주요 지표 6가지 항목의 실태를 파악하였다. 우리나라의 통합보고서 발간과 확산을 위한 주요 제언을 요약하면 다음과 같다. 첫째, 내용적 관점에서 최고경영자 메시지에 장기비전을 담아야 하고 가치창출 프로세스의 독자성과 실효성을 높여야 한다. 전략과 연계된 지배구조 구축과 지배구조 책임자 메시지를 별도로 게재할 필요가 있다. 경영자의 실질적 관여 속에 중요성 평가가 실시되어야 한다. 둘째, 형식적 관점에서 비재무지표의 비교가능성과 객관성을 확보하고 가치창출 프로세스, 리스크와 기회 인식에서 구체적 기간을 명시하여야 한다. 리스크와 기회정보의 제공에 균형이 필요 하다. 셋째, 제도적 관점에서 이해관계자의 실질적 참여를 보장하고 재무보고서와 지속가능성보고서 같은 기존 보고서를 통합보고서로 대체하는 방안을 강구해야 할 것이다. 통합보고서의 신뢰성 확보를 위해 외부감사제도의 확립이 요구된다. 본 연구결과는 우리나라 기업의 통합보고서 정착과 확산을 위한 실무와 이론적 토대 구축에 기여할 것이다.The purpose of this study is to provide suggestions for wide adoption of integrated reports of corporations in Korea. To do so, the characteristics and fundamental concepts of the IIRC s international <IR> framework (December 2013), and contents from KPMG s Survey of Integrated Reports in Japan were analyzed. In December 2017, KPMG Japan has surveyed and analyzed 341 companies that issued integrated reports in 2017 based on six evaluation criteria; Long-term orientation, value creation, governance, materiality, risks and opportunities, and key performance indicators. For the wide adoption and publication of integrated reports of corporations in Korea, this study suggests: First, regarding the contents, the messages from CEO should incorporate long-term orientation, and the identity and effectiveness of their own value creation process should be enhanced. Creation of the governance system in relation to the strategy as well as the appointed director s message should be listed. Material issues should be assessed with actual involvement of management in the process. Second, format-wise, comparability and objectivity for non-financial key performance indicators should be secured and detailed timeline should be explained in both value creation and risks and opportunities sections. Also, disclosure of information on risks and opportunities should be balanced. Lastly, the system should guarantee the actual participation of all stakeholders, and seek for ways to substitute integrated report for conventional financial reports and sustainability reports. Also, third-party audits should be required to assure the credibility of integrated report. Results of this study will contribute to construct the practical and theoretical foundation for adoption and adaption of integrated report of corporations in Korea.
Unsupervised Joint Learning for Headline Generation and Discourse Structure of Reviews

This is an extension from a selected paper from JSAI2019. Recently, using a large number of reference summaries, supervised neural summarization models have achieved success. However, such data is rare, and trained models cannot be shared across domains. As a solution for such a problem, we propose the first unsupervised end-to-end headline generation model for a single review. We assume that a review can be described as a discourse tree in which the headline is the root and the child sentences elaborate on their parent. By estimating the parent from their children recursively, our model induces the tree and generates the headline that describes the entire review. Through the evaluation of the generated headline on actual reviews, our model achieved competitive performance with supervised models, especially on relatively long reviews. In induced trees, we confirmed that the child sentences explain the parent in detail and the generated headlines abstract for the entire review.
HTTP Link Hints

This memo specifies HTTP Link Hints, a mechanism for annotating Weblinks to HTTP(S) resources with information that otherwise might bediscovered by interacting with them.
Application of the data of space decoding for the study of ore-controlling structures of the Lebedinsky ore-placer cluster, South Yakutia

New data about the ore-controlling structures of the Lebedinsky ore-pleaser cluster have been obtained on the basis of space decoding. A stadial analysis of the territory from the ore cluster scale to the ore body (the Myatezhnaya zone) was carried out, as a result of which the position of this zone was clarified. The major ore-hosting structures were identified by space images decoding, and the local structures were revealed by detailed study, and these latter were certified in the course of geological routes with sampling identified for detailed study. Based on the positive results of testing and identification of the mineralization accompanying metasomatic zones were laid mine workings – a trench and several drill holes. As a result of the mining operations, the presence of the ore zone was confirmed; the forecast gold resources for the categories P1 and P2 were tested.
Descriptive Analysis in Power Query with R

This chapter focuses on descriptive analysis in Power BI. A brief introduction explains how we can use descriptive analysis to help decision making. Next comes a brief introduction to clustering, how clustering is performed in Power BI Report, and how we can do clustering in Power Query Editor. Finally, I will cover how to do market basket analysis in Power BI.
Mapping User Knowledge

The granular knowledge cube is a well-suited tool for abstracting knowledge, based on its level of granulation and affiliation to granules. In its current state however, it is not capable of indicating what concepts users have contributed, simply because users are not incorporated. Therefore, it has to be extended with a separated user layer and user-to-concept, as well as user-to-user relationships, to provide this capability. This extension will be introduced and elaborated in Sect. 6.1. Based on the extended, granular knowledge cube, all relevant concepts of a user can be identified, which is an essential, preliminary step, before any knowledge assessment can be performed. To identify the relevant concepts for each user, different algorithms are at deposal, of which some will be introduced in Sect. 6.2.