Reviewerly/exHarmony huggingface dataset:
Named Entity Recognition in Multi-level Contexts.

Named entity recognition is a critical task in the natural language processing field. Most existing methods for this task can only exploit contextual information within a sentence. However, their performance on recognizing entities in limited or ambiguous sentence-level contexts is usually unsatisfactory. Fortunately, other sentences in the same document can provide supplementary document-level contexts to help recognize these entities. In addition, words themselves contain word-level contextual information since they usually have different preferences of entity type and relative position from named entities. In this paper, we propose a unified framework to incorporate multi-level contexts for named entity recognition. We use TagLM as our basic model to capture sentence-level contexts. To incorporate document-level contexts, we propose to capture interactions between sentences via a multi-head self attention network. To mine word-level contexts, we propose an auxiliary task to predict the type of each word to capture its type preference. We jointly train our model in entity recognition and the auxiliary classification task via multi-task learning. The experimental results on several benchmark datasets validate the effectiveness of our method.
Multi-view Classification Model for Knowledge Graph Completion

Most previous work on knowledge graph completion conducted single-view prediction or calculation for candidate triple evaluation, based only on the content information of the candidate triples. This paper describes a novel multi-view classification model for knowledge graph completion, where multiple classification views are performed based on both content and context information for candidate triple evaluation. Each classification view evaluates the validity of a candidate triple from a specific viewpoint, based on the content information inside the candidate triple and the context information nearby the triple. These classification views are implemented by a unified neural network and the classification predictions are weightedly integrated to obtain the final evaluation. Experiments show that, the multi-view model brings very significant improvements over previous methods, and achieves the new state-of-the-art on two representative datasets. We believe that, the flexibility and the scalability of the multi-view classification model facilitates the introduction of additional information and resources for better performance.
An Agile Methodology at Telecommunications Morpho

It is winding up clear, not minimum from the pages of this distribution, that lithe advancement strategies are being embraced or possibly considered by a developing number of programming improvement groups and associations. Regardless of whether you are as of now a functioning specialist coordinated advancement, or thinking about its appropriation on your venture, you will know about the business benefits that can be determined through quicker and increasingly powerful programming conveyance also the persuasive effect it can have on improvement groups[1]. On the other hand, possibly you work for a substantial association that presently cannot seem to make any genuine advances into dexterous improvement and are left considering how deftness could be made to chip away at a vast scale. In case you're in the last camp, or regardless of whether you are not effectively thinking about spry improvement in that capacity but rather are attempting to convey expansive and/or complex projects utilizing customary methodologies and wishing there was a superior way, at that point you are most likely where British Telecom (BT) wound up in 2004. [2]That was previously the landing in the organization of another CIO who methodically started supplanting the organization's long-standing cascade-based conveyance forms with one that encapsulated the key standards of nimble conveyance. This article shows a review of the methodology taken by BT, outlining how light-footed advancement standards can be connected effectively at the venture level. Obviously, the methodology taken by BT is not for the timid – it has incorporated a high level of hazard, and surely a great deal of torment. Presently very much into its second year be that as it may, even though the change is a long way from finish, it is as of now paying profits.
A consumer protection approach to platform content moderation in the United States

The US Congress should consider legislation to regulate the content moderation practices of platforms. Failure to act will leave platform users unprotected and will allow other countries, notably the European Union and China, to seize global leadership in yet another area of tech policy. But a law requiring content rules against the most salient kinds of harmful platform content including hate speech, terrorist material and disinformation campaigns would not pass constitutional muster under the First Amendment. In contrast, a consumer protection approach to content moderation might be effective and pass First Amendment scrutiny. The Federal Trade Commission, on its own or with authorization from Congress, could treat the failure to establish and maintain a procedurally adequate content moderation program as an unfair practice. This would effectively require platforms to have a content moderation program in place that contains content rules, enforcement procedures and due process protections including disclosure, mechanisms to ask for reinstatement and an internal appeals process, but it would not mandate the substance of the platform’s content rules. It would respond to strict First Amendment scrutiny as a narrowly crafted requirement that burdens speech no more than necessary to achieve the compelling government purpose of preventing an unfair trade practice. In addition, or alternatively, the FTC might be authorized to use its deception authority to require platforms to say what they do and do what they say in connection with content moderation programs. The FTC would treat failure to disclose key elements of a content moderation program as a material omission, and the failure to act in accordance with its program as a deceptive or misleading practice. Its First Amendment defense would rest on the compelling government interest in preventing consumer deception. The unfairness version would be more effective but less likely to survive a constitutional challenge. The pure disclosure version would be less effective, but more likely to be found consistent with current First Amendment jurisprudence. One additional advantage of this consumer protection approach is that it does not require controversial modification of Section 230 immunities for platforms.
NETWORK INTERACTION AS A MECHANISM FOR DEVELOPING THE HUMAN RESOURCES OF CULTURAL INSTITUTIONS

The article presents the results of the analysis of the possibilities of using network interaction in solving the problems of developing the personnel potential of cultural institutions. There is a weak development of the topic andthe need to extrapolate its content from pedagogical practice. The possibilities of using network forms of advanced training in relation to employees of cultural institutions are described.
CHALLENGES FACED BY NON-NATIVE WRITERS IN PUBLISHING PAPERS IN REPUTED ENGLISH LANGUAGE JOURNALS

Publication of a paper or article in a journal is a common practice. However, publication in apeer reviewed online journal is more difficult due to journals’ guidelines and publication criteria.But, publication of a paper of English language seems to be extremely difficult in reputed orhighly indexed journals. Every researcher or writer faces problems in quality publications, but anon-native author of English language related papers faces huge problems due to probability ofmanuscript rejection for many reasons including ‘non-native’ case. It has been felt that someeditors out rightly reject one’s manuscript without giving due attention that deprives the authorof a second stage review of his manuscript. There are many publishing criteria for considerationsof sending a manuscript for ‘peer- reviews’ in disciplines like medical sciences, sciences andcomputer sciences where non-native authors’ papers are easily published despite the languagequality which may not be at par. On the other hand, despite quality content and appropriatemethodology, papers tend to get rejected at first and later peer review stage possibly due to thenon-native issue. In other words, ownership of English seems to become a problem inconsideration of even a genuine manuscript. The present paper is a qualitative-analytical studyinto challenges which non-native writers face in the process of publication of their manuscriptsin the field on English language or English language education. Data gathered through interviewshave been thematically analyzed, and duly supported by the literature review. The findings willsupport the future authors to be alert while submitting manuscripts to reputed journals, avoidrejection and possible publications.
Perpustakaan dalam Pengembangan Makerspace sebagai Pendukung Metode Pembelajaran Blended Learning di Era Revolusi Industri 4.0

The library has a facility called makerspace which is considered to have a big influence on the blended learning method, especially in the era of the industrial revolution 4.0, developments have been very advanced and flexible thus libraries can easily follow changes in providing services for the user. The research method used in this research is qualitative research with a descriptive analysis method. The results obtained from this study are the perceived influence of makerspace services on blended learning and also the efforts of libraries in makerspace services to the blended learning method.
THE EFFECT OF DIRECT READING THINKING ACTIVITY (DRTA) ON STUDENTS’ READING COMPREHENSION

The aim of this study was to investigate the effect of directed reading thinking activity (DRTA) on students’ reading comprehension at second grade students of SMA Negeri 4 Bogor. The population of this study consisted of 60 secondary grade students at SMA Negeri 4 Bogor. The two groups’ including pre-post test true experimental design was used in this study. The instrument tools are students’ reading score such as pre-test and post-test such as summarizing and responding test; and reading assessment rubric. The result showed that t-calculated is 14.136 with the value of df is 58 while the result of t-table in the level significant t0.05 = 1.684 and t0.01 = 2.423. Since the t-calculated is higher than t-table (14.136 > 1.624 < 2.423), it can be concluded that the alternative hypothesis (Ha) is accepted and null hypothesis (Ho) is rejected. It is concluded that Directed Reading Thinking Activity (DRTA) effects on student’s reading comprehension.
PENGARUH PEMBELAJARAN LISTENING MELALUI YOUTUBE UNTUK MENINGKATKAN KEMAMPUAN LISTENING TARUNA

You Tube about an emergency situation is believed to be the bearer of the technological revolution in relation to pedagogy, which can provide more comfortable access to language input materials, such as hearing, visuals, and other authentic types of resources to promote progress in all four language learning skills namely listening, speaking , reading and writing. Among these skills, for flight communication cadets and air traffic, listening comprehension provides the opening key to access to language mastery. This study examines and analyzes the effects of YouTube video clips on emergency situations as teaching material for flight communication cadets and Surabaya air traffic policing on their hearing comprehension performance. In more detail, this compares the effect of using various amounts of YouTube clips in three experimental groups with those found in a control group where no clips were used. Certain numbers of YouTube video clips about emergency situations - two, four, or six - used for each group represent an attempt to find out how many results were optimized. The subject of his research, 75 cadets of aviation communication and air traffic in Surabaya Polytechnic participated in a fourteen-week experimental study. Pre and post tests and background surveys are used for the control group (0-video) and experimental (2-video, 4-video, and 6 video clips).
Analysis on the Innovation of Track and Field Teaching Practice in Universities

Athletics teaching is an indispensable part of the modern education system. It can play an important role in cultivating students' comprehensive quality, improving students' practical innovation ability, and promoting students' all-round development. In carrying out physical education activities in colleges and universities, we should increase the effective attention to track and field teaching, improve the physical and mental quality of students, so that students can maintain a positive state and participate in daily life and study. This article first expounds the significance of college track and field teaching, then analyzes the main problems existing in college track and field teaching at this stage, and finally puts forward innovative countermeasures for college track and field teaching practice, hoping to provide some help for the smooth development of college track and field teaching.
PENERAPAN MODEL PEMBELAJARAN KOOPERATIF TIPE THINK,TALK,WRITE UNTUK MENINGKATKAN KEMANDIRIAN DAN PRESTASI BELAJAR PESERTA DIDIK

The research purpose is to describe the cooperative type learning model Think,Talk,Write to increase  the students’ independence  and achievement of the student learning at English subject of the first class SMA Negeri 1 Merapi Selatan Lahar Regency. The subjects of the research are the students of X IPA at the second semester of the academic year 2019/2020 SMA Negeri 1 Merapi Selatan. The research design used is   classroom action research and quotient experiment. The instuments used are the tes instruments of objective questions given ti the students at every cycle.Non test instruments used are the observation sheet of teacher’s activity and the observation sheet of students’  independence. The data of test result is analized by using descriptive statistics and the data of on test result is analized by using quantitative description. From the  result of this research  shows that the cooperative type learning model Think,Talk and Write  can increase independece and achievement of the students learning of X IPA class SMA Negeri 1 Merapi Selatan Lahat regency.
Ambient UX for Cyber-Physical Spaces

Ambient User Experience (Ambient UX) is a conceptual framework providing a strategy for design processes that target cyber-physical spaces. Such design processes interface Wireless Sensor-Actuator Networks (WSAN), Artificial Intelligence (AI), and physically built environments. For managing the complexity of such design processes and ensuring the development of a design facilitating users’ satisfaction, design approaches focused on experience and user activities linked to bio-cyber-physical feedback loops are needed. This paper points out how Ambient UX supports decision-making in a design process.  It outlines the importance of mapping user experiences for cyber-physically enhanced environments by discussing design practices that can support this activity and presenting a representative case study implemented with students at TU Delft.
Forecasting Public Opinions from Twitter Data using Regression and Time Series Methods

Forecasting public opinions are useful in business decision makings. In this 21st century, primarily data is available in online mode. Users follow the reviews of the products, share opinions to the public. Reviews are free-form and unstructured text format. Sentiment analysis is used to extract the opinions from the unstructured textual reviews. Forecasting is a process of future assessment. The machine learning supports the forecasting in two approaches, regression and time series models. One is extracting the daily sentiment scores from the tweets, the daily sentiment scores in the form of numerical type. Second one is applying the regression models and time series models on the daily sentiment scores. These regression algorithms are linear regression; random forest regression, Poisson regression and super vector regression with different kernels like linear, polynomial and radial are used in this paper. Quality metrics for regression techniques MSE and R-square are verified. Linear regression, and SVR with kernels like linear, and radial attain more than 97% of R-square. Finally two time series methods applied, these are EWMA and Esmoothing approaches. The optimal EWMA is achieved by smoothing parameter and optimal Esmoothing is achieved by reducing the RMSE using optimal parameter, which performs good results in forecasting.
A Robust Approach to Authentication of Handwritten Signature Using Voting Classifier

This research paper’s main motive is to improve the recognition rate of Offline Signature Verification system. In our research, decisions of three classifiers i.e., Multilayer Perceptron, Random Forest Classifier and Naive Bayes are combined using voting classifier to determine the output. The softwares used for this research are WEKA and Matlab. Performance of this approach is tested on CEDAR dataset for writer dependent model. Overall recognition rate of whole dataset of 55 users is 91.25%. Out of the dataset, the recognition rate of 45 users is above 85%.
Bot or Not? A Case Study on Bot Recognition from Web Session Logs.

This work reports on a study of web usage logs to verify whether it is possible to achieve good recognition rates in the task of distinguishing between human users and automated bots using computational intelligence techniques. Two problem statements are given, offline (for completed sessions) and on-line (for sequences of individual HTTP requests). The former is solved with several standard computational intelligence tools. For the second, a learning version of Wald’s sequential probability ratio test is used.
Detection and Tracking Cows by Computer Vision and Image Classification Methods

In this paper, the cow recognition and traction in video sequences is studied. In the recognition phase, this paper does some discussion and analysis which aim at different classification algorithms and feature extraction algorithms, and cow's detection is transformed into a binary classification problem. The detection method extracts cow's features using a method of multiple feature fusion. These features include edge characters which reflects the cow body contour, grey value, and spatial position relationship. In addition, the algorithm detects the cow body through the classifier which is trained by Gentle Adaboost algorithm. Experiments show that the method has good detection performance when the target has deformation or the contrast between target and background is low. Compared with the general target detection algorithm, this method reduces the miss rate and the detection precision is improved. Detection rate can reach 97.3%. In traction phase, the popular compressive tracking (CT) algorithm is proposed. The learning rate is changed through adaptively calculating the pap distance of image block. Moreover, the update for target model is stopped to avoid introducing error and noise when the classification response values are negative. The experiment results show that the improved tracking algorithm can effectively solve the target model update by mistaken when there are large covers or the attitude is changed frequently. For the detection and tracking of cow body, a detection and tracking framework for the image of cow is built and the detector is combined with the tracking framework. The algorithm test for some video sequences under the complex environment indicates the detection algorithm based on improved compressed perception shows good tracking effect in the changing and complicated background.
C.G. HEMPEL’S PHILOSOPHY: DEDUCTIVE-NOMOLOGICAL MODEL OF HISTORICAL EXPLANATION

The article is devoted to the deductive-nomological model of explanation, which emphasized the most important aspect of scientific explanation – the connection with scientific laws. It is demonstrated thatthe peculiarity of the historical explanation lies in the fact that general laws are not formulated in an explicit form due to their triviality and obviousness.
SPANISH EFL TEACHERS AND ICT TOOLS. A SURVEY-BASED ANALYSIS

In the last few years, teachers in Spain have experienced numerous changes in their methodology due to the implementation of ICT (Information and Communication Technologies) in education. This research provides a survey-based analysis of EFL (English as a Foreign Language) teachers that assesses their attitude towards digital resources and the current state of affairs in Spain concerning digital tools. Results indicate that despite receiving training in digital skills, teachers still need more support from their educational centres and that the technical equipment available is limited. Besides, they use more often ICT tools for practicing listening and evaluate favourably collaboration among teaching staff and the figure of the ICT coordinator.
AVAILABILITY EVALUATION OF DIFFERENT PLANNING AND SCHEDULING ALGORITHMS IN HYBRID CLOUD SYSTEM

The importance of hybrid cloud computing has become a reality in recent years for large and medium enterprises and even at the individual level, which increases the need for many improvements in its availability level. One of the most important things that affects availability is the task scheduling process. Task scheduling is subject to many scheduling algorithms and these algorithms differ in terms of performance and purpose, the most important aspects being improved by using an appropriate scheduling algorithm is the total execution time(makespane) and also the success rate and downtime live migration. Because working on a cloud computing environment is costly and complex, we have simulated a hybrid cloud environment using reliable and accurate simulation and used Directed acyclic graph(DAG) as a workflow application. In this paper we will compare scheduling and planning algorithms for cloud computing environment by implementing a framework using (workflowsim) based on (cloudsim) simulator in order to choose the best algorithm to verify the possibility of improving availability.
ANALYSIS NEEDED FOR PREPARATION OF TEACHING MATERIALS IN ENGLISH FOR MEDICAL PERSONNEL IN BATAM CITY

This study aimed to find out the needs, functions, and problems faced by medical personnel in Batam city in using English for the medical field. Research is useful for developing language training and courses for special needs through analysis used to map the concrete needs of users. This research uses quantitative methods where the use of quantitative methods and data. Instruments and techniques of data collection is the way how the author uses strategies and instruments to collect data, in this case the authors collected data with questionnaires and asked respondents to fill it out and use the data processor. Based on the research results, it was found that the most needed English language skill was speaking. Therefore, the teaching materials that will be compiled are those that support speaking skills. As a learning direction, the teaching materials that are prepared also need to include elements of the function of English which are considered important for medical personnel in Batam City, namely to provide information. Finally, in compiling English teaching materials for medical personnel, it is necessary to include English grammar skills in order to support the confidence of medical personnel in Batam City.
An Effective Optimization Method for Neural Machine Translation: The Case of English-Persian Bilingually Low-Resource Scenario.

In this paper, we propose a useful optimization method for low-resource Neural Machine Translation (NMT) by investigating the effectiveness of multiple neural network optimization algorithms. Our results confirm that applying the proposed optimization method on English-Persian translation can exceed translation quality compared to the English-Persian Statistical Machine Translation (SMT) paradigm.