Reviewerly/exHarmony huggingface dataset:
PODC 2020 Review

Rachid Guerraoui was the rst keynote speaker, and he got things o to a great start by discussing the broad relevance of the research done in our community relative to both industry and academia. He rst argued that, in some sense, the fact that distributed computing is so pervasive nowadays could end up sti ing progress in our community by inducing people to work on marginal problems, and becoming isolated. His rst suggestion was to try to understand and incorporate new ideas coming from applied elds into our research, and argued that this has been historically very successful. He illustrated this point via the distributed payment problem, which appears in the context of blockchains, in particular Bitcoin, but then turned out to be very theoretically interesting; furthermore, the theoretical understanding of the problem inspired new practical protocols. He then went further to discuss new directions in distributed computing, such as the COVID tracing problem, and new challenges in Byzantine-resilient distributed machine learning. Another source of innovation Rachid suggested was hardware innovations, which he illustrated with work studying the impact of RDMA-based primitives on fundamental problems in distributed computing. The talk concluded with a very lively discussion.
LibGuides: Permalinks: Proquest

Learn how to create permanent URLs for the library's electronic resources: databases, journals, articles, ebooks, etc
Dicto-Comp: A technique in reducing high school students� errors in writing

This study investigated the use of dicto-comp in minimizing errors in students writing. The study concerned the type of errors frequently made by the students after the implementation of dicto-comp and the effectiveness of dicto-comp in reducing the students errors in writing. The study used the quantitative approach using the quasi-experimental research design. The instrument of the study was writing tests. The study took place at a senior high school in Banda Aceh, Aceh Province, Indonesia. Findings showed that after the implementation of dicto-comp, the students frequently made grammatical errors at 46.42% and mechanical errors at 40.66%. Further, the t-test results showed that t-test = 2.12 and t-table = 1.70. This indicated that t-test score was higher than t-table, and thus, the alternative hypothesis (Ha) was accepted and the null hypothesis (Ho) was rejected. Therefore, it can be concluded that dicto-comp decreased the errors in the students writing. It is suggested that teachers of English apply dicto-comp technique and/or combine it with another method/ strategy in teaching writing in classroom
A Deep Learning Generative Approach for Speech-to-Scene Generation

Visualization can enhance the power of our subconscious mind. Research has proven that visualization is a very effective medium for communication since it enables humans to remember insights for a longer duration. A speech input visualizer would thus be of utmost importance because of its wide-ranging applications in areas such as Education, Engineering, Defence, Art, Game Development, Architecture, and so on. This paper introduces a real-time efficient “Speech-to-Scene” Generator using a deep learning approach. A novel combination of HTML speech recognition API and Text Conditioned Auxiliary Classifier Generative Adversarial Network has been proposed to overcome this problem. This model has been trained on a car’s data set consisting of 16 distinct classes. Additionally, this model can also adapt to various other data sets. The generated images were evaluated with Inception Score and Multi-Scale Structural Similarity Index (MS-SSIM) to compare with state-of-the-art image generation technologies.
PENINGKATAN KEMAMPUAN PENGELOLAAN WEBLOG DENGAN KONTEN INTERNET SEHAT SEBAGAI SARANA PUBLIKASI DAN INFORMASI PADA SISWA SMA NEGERI 2 SEMARANG

Community Service Activities (PkM) Increasing the Capability of Management of Healthy Weblogs with Internet Content as a Means of Publication and Information for Students of Semarang 2 High involving partners of High School Middle School students in the city of Semarang. Many school students have not used the weblog to provide information and publications about activities related to learning, school organization activities and other activities. In this activity, partners will be given training in making weblogs with healthy internet content by the PKM team tailored to the level of needs and resources of each partner. At the end of this activity, it is expected that all students who take part in the training can create a weblog by filling out healthy internet content for the better so that it will improve  the  ability  of  publications  and  information  to  internet  users  as  a  form  of  community  service. The purpose of this service is to increase the ability of weblogs to share knowledge, publications and information of  students by creating a healthy internet on the weblog.
Identification of Extended Objects of Geoinformation Space by Semantic Triangulation

Development refers to management in socio-economic systems and can be used in systems for collecting, converting, processing information and making decisions when the source information is incomplete or unclear.
There Is a Third Condition Aside from Survival and Death that Affects Outcome Statistics: Terminal Discharge

Some patients discharged automatically are classified as terminal discharge, while their clinical outcome is survival, disrupting the results of clinical research.The data of this study were taken from inpatients admitted to the ICU of the First Medical Center of the People's Liberation Army General Hospital, Beijing, China from 2008-2017. We collected the data regarding medications used over the three days before discharge from the group of patients who survived and the group of patients who died, and the outcomes of all patients were recalculated by three classification algorithms (AdaBoosting, Pearson correlation coefficient, observed to expected ratio-weighted cosine similarity). Our basic assumption is that if the classification result is death but the actual in-hospital outcome is survival, the associated patient was likely terminally discharged.The coincidence rate of the outcomes calculated by the AdaBoosting algorithm was 98.1%, the coincidence rate calculated by the Pearson correlation coefficient was 61.1%, and the coincidence rate calculated by the observed to expected ratio-weighted cosine similarity was 93.4%. When the three classification methods were combined, the accuracy reached 98.56%.The combination of clinical rules and classification methods has a synergistic effect on judgments of patients' discharge outcomes, greatly saving time on manual retrieval and reducing the negative influence of statistics or rules.
Direct wavefront sensing from extended objects: a general sensor

Wavefront sensing from an extended object is a challenging task since the phase to be sensed is disturbed by the one generated from the structure of the extended object. To address this problem, a general wavefront sensor is proposed. The configuration of the proposed sensor consists of a field lens, a collimating lens, a lenslet array, and a camera. The field lens, the first element of this sensor, ensures that each lenslet collects the same information of the extended object, which is a basis for the reconstruction of the distorted wavefront from the extended object using the proposed sensor. The fundamental strategy of the sensor is converting the scenario of wavefront sensing from an extended object into the traditional one from a point source by eliminating the Fourier spatial spectrum of the extended object in the frequency domain. As a result, the distorted wavefront can be reconstructed using the algorithm of the Shack–Hartmann wavefront sensor. Numerical simulations and experiments both verify the feasibility and accuracy of the proposed sensor for direct wavefront sensing from any types of extended objects.
LibGuides: Music: Online Resources

This Library Guide will help students find the resources they need for their music research.
VilNMN: A Neural Module Network approach to Video-Grounded Language Tasks

Neural module networks (NMN) have achieved success in image-grounded tasks such as question answering (QA) on synthetic images. However, very limited work on NMN has been studied in the video-grounded language tasks. These tasks extend the complexity of traditional visual tasks with the additional visual temporal variance. Motivated by recent NMN approaches on image-grounded tasks, we introduce Visio-Linguistic Neural Module Network (VilNMN) to model the information retrieval process in video-grounded language tasks as a pipeline of neural modules. VilNMN first decomposes all language components to explicitly resolves entity references and detect corresponding action-based inputs from the question. Detected entities and actions are used as parameters to instantiate neural module networks and extract visual cues from the video. Our experiments show that VilNMN can achieve promising performance on two video-grounded language tasks: video QA and video-grounded dialogues.
Registering Unmanned Aerial Vehicle Videos in the Long Term

Unmanned aerial vehicles (UAVs) have become a very popular way of acquiring video within contexts such as remote data acquisition or surveillance. Unfortunately, their viewpoint is often unstable, which tends to impact the automatic processing of their video flux negatively. To counteract the effects of an inconsistent viewpoint, two video processing strategies are classically adopted, namely registration and stabilization, which tend to be affected by distinct issues, namely jitter and drifting. Following our prior work, we suggest that the motion estimators used in both situations can be modeled to take into account their inherent errors. By acknowledging that drifting and jittery errors are of a different nature, we propose a combination that is able to limit their influence and build a hybrid solution for jitter-free video registration. In this work, however, our modeling was restricted to 2D-rigid transforms, which are rather limited in the case of airborne videos. In the present paper, we extend and refine the theoretical ground of our previous work. This addition allows us to show how to practically adapt our previous work to perspective transforms, which our study shows to be much more accurate for this problem. A lightweight implementation enables us to automatically register stationary UAV videos in real time. Our evaluation includes traffic surveillance recordings of up to 2 h and shows the potential of the proposed approach when paired with background subtraction tasks.
Vital Records: Uncover the past from historical handwritten records

We present Vital Records, a demonstrator based on deep-learning approaches to handwritten-text recognition, table processing and information extraction, which enables data from century-old documents to be parsed and analysed, making it possible to explore death records in space and time. This demonstrator provides a user interface for browsing and visualising data extracted from 80,000 handwritten pages of tabular data.
Correction to: MobiEye: turning your smartphones into a ubiquitous unobtrusive vital sign monitoring system

The original article can be found online.
Quiet book - interactive book - learning tool

This interactive cloth book is intended for children of preschool age. The activities were chosen and created so that they would allow for the child's versatile and diverse growth.Every activity in this book is created using snaps, velcro, hooks, buttons or zippers. Most of the sewing was done by hand which meant multiple stitch patterns and techniques were used. A sewing machine was used rarely, mainly for the page edges and frames, spine of the book and for attaching larger unmovable pieces onto the page. The pieces are made out of felt, as are the pages which were also stiffened with ronofix to improve the overall structure of the book.The activities in the book allow for the child's fine motor skills to improve - detaching and attaching snaps, interwinding strings, working with velcro and buttons and moving beads. However, it also develops their sense of time and space, visual perception, perception of color and background, visual analysis/synthesis, eye movement and numeral skills.
Identifying English Language Learning Strategies Used by Polytechnic Students

English is regarded as the second language (ESL) in Malaysia and is one of the compulsory subjects at Malaysian polytechnic. To master the language, students need to have their own language learning strategies. The application of language learning strategies is beneficial in helping students to improve their language skills. The current study aims to investigate the polytechnic students' use of English language learning strategies. Survey method was used to gather the data of this study. The respondents were among 151 students from a polytechnic in Malaysia. The 50 items from the Strategy Inventory for Language Learning (SILL) were adopted for the survey. The findings revealed that the polytechnic students have their own preferred English language learning strategies based on the six categories from SILL. It is hoped that the language educators could take the information gathered from this study to direct their efforts in promoting the English language learning activities which suit the students' English language learning strategies to help them in improving their English language skills.
Installing Packages and Using Libraries

You installed R and RStudio and are now familiar with them. Now it is time to discover another feature of R that will help you learn statistics.
Communication and Cooperation in Distance Learning

The article deals with the analysis of communication and collaboration; the criteria of their effectiveness are described. Special attention is paid to distance learning, in the context of pandemic in particular. The role of communication and collaboration in distance learning has been studied. The experience of distance learning implementation in Borys Grinchenko Kyiv University has been described and the results of the students’ survey on effectiveness of communication and collaboration with teachers and groupmates aimed at learning tasks fulfilment and problem solving during distance learning have been presented. IN addition, examples of communication and collaboration organization in distance learning have been provided.
ISIKUN at the FinCausal 2020: Linguistically informed Machine-learning Approach for Causality Identification in Financial Documents

This paper presents our participation to the FinCausal-2020 Shared Task whose ultimate aim is to extract cause-effect relations from a given financial text. Our participation includes two systems for the two sub-tasks of the FinCausal-2020 Shared Task. The first sub-task (Task-1) consists of the binary classification of the given sentences as causal meaningful (1) or causal meaningless (0). Our approach for the Task-1 includes applying linear support vector machines after transforming the input sentences into vector representations using term frequency-inverse document frequency scheme with 3-grams. The second sub-task (Task-2) consists of the identification of the cause-effect relations in the sentences, which are detected as causal meaningful. Our approach for the Task-2 is a CRF-based model which uses linguistically informed features. For the Task-1, the obtained results show that there is a small difference between the proposed approach based on linear support vector machines (F-score 94%) , which requires less time compared to the BERT-based baseline (F-score 95%). For the Task-2, although a minor modifications such as the learning algorithm type and the feature representations are made in the conditional random fields based baseline (F-score 52%), we have obtained better results (F-score 60%). The source codes for the both tasks are available online (https://github.com/ozenirgokberk/FinCausal2020.git/).
Fog horn sound Lindesnes lighthouse – Cornes de brume

The sound of the Lindesnes fog horn can be heard one in July every year - on the Fog horn day
Algoritma Penyelesaian Persamaan Fuzzy Non Linear dengan Metode Modifikasi Newton Raphson dan Implementasinya

Non-linear fuzzy equations are mathematical problems that can be solved. Non-linear fuzzy equations can be solved by numerical methods, namely the Newton Raphson modification method. The Newton Raphson modification method is shown in an algorithm to be implemented with a computer program using the Matlab application. So that the calculation process can be done easily and in a short time. In the non-linear fuzzy equation of a given case, a solution can be found efficiently using the given algorithm.
“Shakespeare in the Vectorian Age” – An evaluation of different word embeddings and NLP parameters for the detection of Shakespeare quotes

In this paper we describe an approach for the computer-aided identification of Shakespearean intertextuality in a corpus of contemporary fiction. We present the Vectorian, which is a framework that implements different word embeddings and various NLP parameters. The Vectorian works like a search engine, i.e. a Shakespeare phrase can be entered as a query, the underlying collection of fiction books is then searched for the phrase and the passages that are likely to contain the phrase, either verbatim or as a paraphrase, are presented in a ranked results list. While the Vectorian can be used via a GUI, in which many different parameters can be set and combined manually, in this paper we present an ablation study that automatically evaluates different embedding and NLP parameter combinations against a ground truth. We investigate the behavior of different parameters during the evaluation and discuss how our results may be used for future studies on the detection of Shakespearean intertextuality.
Evidencia de estrategias escriturales a partir de la implementación de una propuesta de práctica escritural con Traductor Google

One of the resources that can contribute, at a global level, to the development of writing processes is the Google Translate tool, which has generated several surveys with the aim of identifying its possible influences in the field of writing. In the context of the Javeriana university, regarding the TG, there is a skeptical view among professors and students of intermediate level I of English, which causes that the tool is not openly recommended in contexts of writing in English as a foreign language, and therefore it has not been possible to identify what possible writing strategies may emerge from the use of the tool in such contexts. For this reason, the implementation of a proposal of writing practice (in spanish, propuesta practica escritural PPE) with Google Translator, based on the needs analysis of intermediate English I students of the LLMM, was considered pertinent. It should be noted that the theoretical foundation of this research is based on the approaches of Williams (2003) and Bloom (2008) that describe the development of processes and writing strategies, considering the perspective of writing as a process. In addition to this, taking into consideration that the nature of the research was of a qualitative nature, different aspects of the grounded theory were taken into account. According to this analysis, the instruments that were used to carry out the data collection were screen recordings, field diaries, questionnaires and semi-structured interviews. The data revealed that, in agreement with the experience of the four participants, from the implementation of the GT tool different writing process and strategies can emerge, based on the theory such as: relation of prior knowledge based on the linguistic code, L1 incorporation, substitution, error correction and recombination. Similarly, it is possible to show that students can develop strategies in their foreign language writings, which have not been explored from the theory, such as rhetorical adjustment and confirmation of the meaning. Finally, the results obtained in the research showed that by implementing the TG in the PPE using consciously the written strategies, this one can represent a useful resource when writing academic texts.
Wearable Fall Detector for Elderly People

Now a days, most of the elderly person live in home alone. In their day to day living, some activities likely to have some accidents, such as fall. If the fall is unobserved for a longer period, it may lead to severe health trauma or even leads to death. According to the insights announced in National Safety Council, they are the subsequent driving reason for unexpected passing assessing 424000 passing worldwide. The objective of this paper is to develop a device that detects the fall event of the elderly person and intimate to the family members about the event. A call will be made automatically to the contact number provided in the fall detector application installed in the smart phone. It can accompany elderly people both indoors and outdoors in contrast to ambient devices. Computation of this method is simple and it is possible to implement in small size, so it can be easily carried by the elderly people. It can be afforded by
SOME RESULTS FROM A SURVEY ABOUT FORMING DIGITAL LITERACY OF 8 YEARS OLD STUDENTS

Contemporary children live in a digital era and it is almost impossible for them not to be tempted by technologies. This article presents some interesting results from Bulgarian project „Digital Competencies and Media Education at Pre-school and Primary School Age” (National Science Fund; Н05/8 14.12.2016). In 2018 there were interviewed 637 children from 13 Bulgarian towns. The focus in this article is only 8 years old students and their digital habits. The author is a Member of the team of the COST project ‘Digital literacy and multimodal practices of young children’ (Action IS1410) – DigiLitEY. In March 2019 in Manchester on the final project’s meeting of DigiLitEY were presented results connect ed with the key participants for this COST’s project – up to 8 years old students. This article analyses this aged group and their attitudes of digital technologies.
Texture Feature Technique for Security of Indian Currency

In recent years, security of currency has gain importance in the field of research. With the advent of digital technology, color printer, and color scanner are the cheapest way for counterfeiter to produce fake currency. Feature extraction is the most important technique in paper currency recognition. According to reviewer, texture feature plays an important role for paper currency detection. Texture feature is generally a statistical-based approach and in the present work, a new model is proposed for paper currency detection. The presented model is computing the texture properties like Gray Level Co-occurrence Matrix (GLCM) of Rs. 500 for real and fake currency. The Principle Component Analysis (PCA) is used for reduction of higher dimension of images. The proposed work provides better results with the collaboration of PCA and GLCM. The texture properties have been used and GLCM measured the variation in intensity at pixel of interest of the currency. The computed results have been presented in the form of table and graphs.
Chinese Grammatical Error Diagnosis with Graph Convolution Network and Multi-task Learning

This paper describes our participating system on the Chinese Grammatical Error Diagnosis (CGED) 2020 shared task. For the detection subtask, we propose two BERT-based approaches 1) with syntactic dependency trees enhancing the model performance and 2) under the multi-task learning framework to combine the sequence labeling and the sequence-to-sequence (seq2seq) models. For the correction subtask, we utilize the masked language model, the seq2seq model and the spelling check model to generate corrections based on the detection results. Finally, our system achieves the highest recall rate on the top-3 correction and the second best F1 score on identification level and position level.