Reviewerly/exHarmony huggingface dataset:
Exploring the impact of Artificial Intelligence and robots on higher education through literature-based design fictions

Abstract Artificial Intelligence (AI) and robotics are likely to have a significant long-term impact on higher education (HE). The scope of this impact is hard to grasp partly because the literature is siloed, as well as the changing meaning of the concepts themselves. But developments are surrounded by controversies in terms of what is technically possible, what is practical to implement and what is desirable, pedagogically or for the good of society. Design fictions that vividly imagine future scenarios of AI or robotics in use offer a means both to explain and query the technological possibilities. The paper describes the use of a wide-ranging narrative literature review to develop eight such design fictions that capture the range of potential use of AI and robots in learning, administration and research. They prompt wider discussion by instantiating such issues as how they might enable teaching of high order skills or change staff roles, as well as exploring the impact on human agency and the nature of datafication.
AI4VIS: Survey on Artificial Intelligence Approaches for Data Visualization

Visualizations themselves have become a data format. Akin to other data formats such as text and images, visualizations are increasingly created, stored, shared, and (re-)used with artificial intelligence (AI) techniques. In this survey, we probe the underlying vision of formalizing visualizations as an emerging data format and review the recent advance in applying AI techniques to visualization data (AI4VIS). We define visualization data as the digital representations of visualizations in computers and focus on data visualization (e.g., charts and infographics). We build our survey upon a corpus spanning ten different fields in computer science with an eye toward identifying important common interests. Our resulting taxonomy is organized around WHAT is visualization data and its representation, WHY and HOW to apply AI to visualization data. We highlight a set of common tasks that researchers apply to the visualization data and present a detailed discussion of AI approaches developed to accomplish those tasks. Drawing upon our literature review, we discuss several important research questions surrounding the management and exploitation of visualization data, as well as the role of AI in support of those processes. We make the list of surveyed papers and related material available online at.
GraphMAE: Self-Supervised Masked Graph Autoencoders

Self-supervised learning (SSL) has been extensively explored in recent years. Particularly, generative SSL has seen emerging success in natural language processing and other fields, such as the wide adoption of BERT and GPT. Despite this, contrastive learning---which heavily relies on structural data augmentation and complicated training strategies---has been the dominant approach in graph SSL, while the progress of generative SSL on graphs, especially graph autoencoders (GAEs), has thus far not reached the potential as promised in other fields. In this paper, we identify and examine the issues that negatively impact the development of GAEs, including their reconstruction objective, training robustness, and error metric. We present a masked graph autoencoder GraphMAE (code is publicly available at https://github.com/THUDM/GraphMAE) that mitigates these issues for generative self-supervised graph learning. Instead of reconstructing structures, we propose to focus on feature reconstruction with both a masking strategy and scaled cosine error that benefit the robust training of GraphMAE. We conduct extensive experiments on 21 public datasets for three different graph learning tasks. The results manifest that GraphMAE---a simple graph autoencoder with our careful designs---can consistently generate outperformance over both contrastive and generative state-of-the-art baselines. This study provides an understanding of graph autoencoders and demonstrates the potential of generative self-supervised learning on graphs.
Machine translation for Arabic dialects (survey)

Arabic dialects also called colloquial Arabic or vernaculars are spoken varieties of Standard Arabic. These dialects have mixed form with many variations due to the influence of ancient local tongues and other languages like European ones. Many of these dialects are mutually incomprehensible. Arabic dialects were not written until recently and were used only in a speech form. Nowadays, with the advent of the internet and mobile telephony technologies, these dialects are increasingly used in a written form. Indeed, this kind of communication brought everyday conversations to a written format. This allows Arab people to use their dialects, which are their actual native languages for expressing their opinion on social media, for chatting, texting, etc. This growing use opens new research direction for Arabic natural language processing (NLP). We focus, in this paper, on machine translation in the context of Arabic dialects. We provide a survey of recent research in this area. We report for each study a detailed description of the adopted approach and we give its most relevant contribution.
INFORMATION RETRIEVAL SYSTEM PADA FILE PENCARIAN DOKUMEN TESIS BERBASIS TEXT MENGGUNAKAN METODE VECTOR SPACE MODEL

Speed and density in the process of finding documents and information has become mandatory, contained in information systems, to facilitate the search process or find documents and information needed, it is called information retrieval or information retrieval system, implementation of the theory applied in this study using the model method vector space, the purpose of this study is to provide general exposure to the process of finding digital documents. With the token and indexing process so that the results of the masses are found in the database using keywords, so the system will search according to the keywords input into the system, and will be compared with the data contained in the database, so that it can produce the correct information.
Respect Human Value to Control Software Development Failure

People learn and define their own values to interact in different situations. It is important to know the human values (HV) for dealing humans in better ways. HV can also be helpful for software development managers to make right decisions for managing their teams well. Unfortunately, to a great extent, the very factor is ignored in software engineering (SE). This study aims to provide a basic motivation of the topic to SE researchers to carry out some empirical evidences to control software development failures through respecting software developers’ HV. In order to operationalize the study, few disciplines, in which the HV are empirically discussed, are considered to replicate the impacts on software development. The factor HVs is well connected with satisfaction and improvement outcomes in sociology, education and management studies. Likewise, this study also literates the importance of HVs for successful software project development. This study concludes that HV can form strong correlations with software development roles and can be used to minimize the software failure.
Smart Online Transactions Using Voice Recognition for Elderly People

The work in this paper targets creating voice based financial framework.In the realm of present day innovation where we use web and advanced mobile phones to modify the effect by building up an function that may really help the individuals who need it the most.We are discussing the provincial pieces of our nation, which makes the greater part of the India.The significant motivation behind why a large portion of these individuals are not yet adjust with this cutting edge innovation is on the grounds that they think that its hard to utilize and don't have a thought of utilizing these advanced cells.This application causes them access the fundamental financial administrations in the manner they are most agreeable.That is letting them utilize the telephones with voice order control, accessible in their own local language.Particularly the approach of versatile banking, it tackled the issue of going from their town to close by city simply realize the bank balance.This spares their time, additionally telling them about the better offers accessible just on one order.
MEDIA

Africa Research Bulletin: Political, Social and Cultural SeriesVolume 57, Issue 6 p. 22784B-22785C Social and Cultural MEDIA First published: 20 July 2020 https://doi.org/10.1111/j.1467-825X.2020.09546.xRead the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onEmailFacebookTwitterLinked InRedditWechat No abstract is available for this article. Volume57, Issue6July 2020Pages 22784B-22785C RelatedInformation
A Novel Object Detection Algorithm in Video

Deep learning technology performs effect in feature extraction of images.Nowadays, with the development of video monitoring, the application of deep learning technology to surveillance video has profound implications.The effects of traditional video recognition are not satisfactory, but deep learning methods perform effect in many scenes of image classification.This paper proposed a novel object detection algorithm in video.It combined the traditional methods of extracting feature and deep learning algorithm to realize vehicle identification based on surveillance video.The method used the frame difference method and background subtraction to preprocess the image, and then trained a network model based on YOLO to perform object detection and obtain the categories and location information of the monitored vehicle.Compared with the existing object detection algorithms faster RNN, our method can achieve higher accuracy and can significantly shorten the time for detection, which can recognize the object of vehicle video quickly and efficiently.The method can meet the requirements of real-time detection.
PROGRAMA MESA BRASIL: FORTALECIMENTO DA REDE FRENTE À PANDEMIA DO CORONAVÍRUS

Aiming to reduce hunger, food waste and to promote food and nutritional security, the Mesa Brasil Program operates nationally with the redistribution of food, products of low commercial value but of great nutritional value, delivering for social entities registered in the Program.This is a situation analysis study, which the objective is to assess the change in behavior of the Mesa Brasil from Sesc (Social Service of Comerce) Santa Maria donations.The methodology consists of quantifying the information contained in the Program's databases by separately filtering the information from 2019 and 2020.There was a big change in donations after the start of the pandemic.In 2020, the donations were 144% bigger compared to the previous year.It is believed that this increase is, primarily, due to donations to Mesa Brasil's Lives Campaigns and also the beginning of the Food Acquisition Program (PAA).
Using a service blueprint and the service catalogue concept to plan a smart governance system: the case study of the southern Taiwan science park

To improve the Southern Taiwan Science Park efficiency, the administration of the park used the smart city concept to transform it into a smart science park. Beyond the information and communication technology (ICT), the key to the development of a smart science park was to consider the requirements of the park's relevant stakeholders. Hence, this study applied the concept of persona, a service blueprint, and the service catalogue concept as the planning methodology and used smart governance as an example to demonstrate our planning process. We held focus group meetings with each persona, used a service blueprint to visualise the group's requirements, and utilised a service catalogue to present the service contents of the related smart governance systems. The study suggested that the relevant authority should implement the smart governance data centre, a public equipment management monitoring platform, and a disaster management platform to improve the efficiency and effectiveness of the public service of the park.
Automatic and Efficient Allocation for Examination Seats using Android Application

This paper is resolved to streamline the errand of manual seating game plan of understudies in an examination lobby. The main goal is to develop an android app for automatic examination seating arrangement in addition to reducing the manual work of staff. A PDF containing student exam number with subject code and subject name will be sent by the university and will be received by the admin staff which will be converted into suitable format. Then an algorithm will be used to involuntarily allocate the students to the suitable block according to their strength. Then the staff will be randomly allocated to particular block. Alternating staff allocation will be done according to department. The students and the staff will receive a message regarding the block where they have been assigned. In this paper we can further add features to improve the flexibility.
Decoupling Model Checking from Object-Oriented Languages in Internet QoS

Agents and model checking, while technical in theory, have not until recently been considered appropriate. In this work, we verify the synthe-sis of SCSI disks, which embodies the confus-ing principles of cryptoanalysis. SMUTCH, our new methodology for distributed symmetries, is the solution to all of these issues
Incorrect Data in Text

at time of DOAC initiation or a PPI prescription filled up to 1 month after DOAC initiation.Among 82 625 users of warfarin, 20 124 (24%) had an active PPI prescription, while for 31 647 users of dabigatran it was 6769 (21%), for 35 252 users of rivaroxaban it was 8591 (24%), and for 17 751 users of apixaban it was 4615 (26%). 1 Estimates of the risk of fracture, with adjustment for PPI use, were virtually identical to those reported in our article. 1The hazard ratio (HR) for risk of hip fracture comparing DOACs with warfarin was 0.91 (95% CI, 0.78-1.07);after adjustment for PPIs it was 0.92 (95% CI, 0.78-1.07).Adjustment for PPI use was not associated with inpatient fractures (without PPI adjustment: HR, 0.87; 95% CI, 0.79-0.96;with PPI adjustment: HR, 0.87; 95% CI 0.78-0.97)or all fractures (without PPI adjustment: HR 0.93; 95% CI, 0.88-0.98;with PPI adjustment: HR 0.93; 95% CI, 0.89-0.98). 1 Adjustment for PPI use also did not attenuate the findings when we compared individual DOACs vs warfarin.In summary, although a hypothesis worthy of consideration, we found no evidence that our findings were explained by differential use of PPIs.
Development of Reading Comprehension System for Kannada Text Documents

Reading Comprehension (RC) plays an important role in Natural Language Processing (NLP) as it reads and understands text written in Natural Language. Reading Comprehension systems comprehend the given document and answer questions in the context of the given document. This paper proposes a Reading Comprehension System for Kannada documents. The RC system analyses text in the Kannada script and allows users to pose questions to It in Kannada. This system is aimed at masses whose primary language is Kannada - who would otherwise have difficulties in parsing through vast Kannada documents for the information they require. This paper discusses the proposed model built using Term Frequency - Inverse Document Frequency (TF-IDF) and its performance in extracting the answers from the context document. The proposed model captures the grammatical structure of Kannada to provide the most accurate answers to the user
UPA'19

Advancements in ubiquitous technologies and artificial intelligence have paved the way for the recent rise of digital personal assistants in everyday life. The Fourth International Workshop on Ubiquitous Personal Assistance (UPA'19) aims to continue discussing the latest research developments and outcomes on digital personal assistants. UPA'19 builds on the success of our three previous workshops, organized in conjunction with UbiComp'16-18. We welcome contributions focusing on the advancements toward digital assistants that provide a high level of personalization, through proactive and effective support of users' activities, in an unobtrusive manner. All workshop contributions will be published in the supplemental proceedings of the Ubicomp/ISWC 2019 conference and included in the ACM Digital Library.
The Urgency of Digital Media Literacy in Youth Scavengers in Bintara Jaya Environment, Bekasi City, West Java

The purpose of this research is to find out and describe the conditions of teenagers in the scavenger environment regarding their ability to select, filter, sort, understand and evaluate digital media content after they were exposed to current communication technology that transcend the boundaries of social economic status.On the basis that no matter how limited their economic reach are, teenagers in this environment are still exposed to digital media content through their uses of second-hand cellular phones that they bought.This qualitative research approach used a case study method that wants to describe in detail and comprehensively the conditions of this reality.The informants of this research were 4 teenagers who were accommodated by the study group of Sekolah Kami led by Mrs. Irina.These 4 teenagers are part of the 27 youth who are studying in the Sekolah Kami about various skills informally.The research was taken using a purposive sampling technique (as much as it needs), using cellphones.The data was collected using observation and in-depth interviews with informants as well as conducting documentation studies through various documents related to the research theme.The results were analyzed using the qualitative data analysis model from Miles and Huberman.Analysis of the data used stages from this model until there were categories related to the research theme and a conclusion was finally drawn
Incremental Feature Selection Method for Software Defect Prediction

Software defect prediction models are essential for understanding quality attributes relevant for software organization to deliver better software reliability. This paper focuses mainly based on the selection of attributes in the perspective of software quality estimation for incremental database. A new dimensionality reduction method Wilk’s Lambda Average Threshold (WLAT) is presented for selection of optimal features which are used for classifying modules as fault prone or not. This paper uses software metrics and defect data collected from benchmark data sets. The comparative results confirm that the statistical search algorithm (WLAT) outperforms the other relevant feature selection methods for most classifiers. The main advantage of the proposed WLAT method is: The selected features can be reused when there is increase or decrease in database size, without the need of extracting features afresh. In addition, performances of the defect prediction models either remains unchanged or improved even after eliminating 85% of the software metrics.
Preface

This Conference Proceedings volume contains the written versions of most of the contributions presented during the 1st International Conference of SNIKOM (1st ICoSNIKOM) 2018 is an international conference of computer science and information technology. This conference is joint collaboration of APTIKOM Wilayah I Sumatera Utara and Politeknik Negeri Medan, and supported by Universitas Sumatera Utara, Universitas Methodist Indonesia, Universitas Prima Indonesia Medan, Universitas Harapan Medan, Universitas Malikussaleh, ATKP Medan, Universitas Potensi Utama, Politeknik Palcomtech Palembang and Telkom University. It took place at the Hotel Madani, Medan, Indonesia, on November 23-24, 2018. The theme is “Data Intelligence and IIoT on Cloude Era ”. The event will be held with presentations delivered by researchers from the international community, including presentations from keynote speakers, invited speaker and scientific parallel session presentations. The Conference has been a good opportunity for participants coming from any countries to present and discuss topics in their respective research areas. We would like to thank Director of Politeknik Negeri Medan, Rector of Universitas Sumatera Utara, to all participants for their contributions to the conference program and for their contributions to these proceedings. Many thanks go as well to our Keynote Speakers Prof. Dr. Jasni Mohammad Zain and Prof Dr. Opim Salin Sitompul, for their thought. Also many thanks to Coordinator APTIKOM Sumatera Utara, the Indonesian participants for their support and hospitality, which allowed all foreign participants to feel more at home. Our special thanks go to our colleagues Rahmat Widia Sembiring, Ph.D, Dr. Roslina, Mr. Friendly, all of the committes, for their devoted assistance in the overall organization of the conference. The Editors
Reduction based Histogram Equalization Technique for Image Enhancement

Here the proposed scheme mainly emphasizes the procedure of histogram equalization of images in more efficient way. Histogram equalization is required for image enhancement. Histogram spreads or flattens the histogram of an image and due to this the pixels with lower intensity values appear darker and the pixels with higher intensity values appear lighter. So the contrast of the input image is improved. For human interpretation various techniques of image enhancement have been widely used in different applications areas of image processing as the subjective quality of images is mainly important
Order Statistics

In this chapter we represent the power Poisson processes $$\mathcal {E}_{+}$$ and $$\mathcal {E}_{-}$$ as monotone sequences of order statistics, and explore the statistical behavior of these sequences. As we shall see, this order-statistics analysis will give rise to: the Zipf law and its inverse counterpart; the Weibull law and its inverse counterpart, the Fréchet law; and the Pareto law and its inverse counterpart.
Exact Cover with Color Codes and Intersection Graphs

A. Enlarging the set of items with new type of color coded items in a generalized exact cover problem, that is, proposing the so-called exact cover problem with color codes greatly enhances the modeling power of the generalized exact cover problem.It was pointed out that the new type of exact cover problem with color codes can be reduced to back the generalized exact cover problem without color codes.The reduction is accomplished by introducing tactically chosen new secondary items.This paper will show that the number of newly introduced secondary items is related to the chromatic number of a suitably defined auxiliary graph.The arguments are constructive.Carrying out the construction of the auxiliary graph and coloring its nodes in a greedy manner gives a practical algorithm for the above reduction.Since the number of colors provided by the greedy coloring procedure is not equal to the chromatic number of the auxiliary graph the number of the introduced secondary items in the reduction exceeds the necessary optimal minimum.