Reviewerly/exHarmony huggingface dataset:
Analysis Methods in Neural Language Processing: A Survey.

The field of natural language processing has seen impressive progress in recent years, with neural network models replacing many of the traditional systems. A plethora of new models have been proposed, many of which are thought to be opaque compared to their feature-rich counterparts. This has led researchers to analyze, interpret, and evaluate neural networks in novel and more fine-grained ways. In this survey paper, we review analysis methods in neural language processing, categorize them according to prominent research trends, highlight existing limitations, and point to potential directions for future work.
EverSSDI: blockchain-based framework for verification, authorisation and recovery of self-sovereign identity using smart contracts

In the current identity management process, the problems such as increasing differentiation of digital identities, fragmentation and centralisation of identity information have been exposed. In this paper, a framework, named EverSSDI, using smart contracts in an Ethereum-based blockchain is constructed, which provides a unique identifier to normalise differentiated user identities. A fine-grained authorisation mechanism is designed based on the Hierarchical Deterministic protocol (HD protocol) to solve the fragmentation problem of identity information. Besides, a reliable information verification mechanism is elaborated to enhance the credibility of the digital information. In addition, two novel methods are proposed for identity recovery, one of which is based on Social Networking Services (SNS) authorisation and the other Ethereum Oracles. The final implementation and discussion show that the user has self-sovereign management authority, which enables the user to become the real dominant of his/her identity rather than only a prover of digital identity.
Revolutionary Change in Cryptography

From Ancient periods the secure communication is required for that cryptography is invented. Cryptography provides users the various types of functionalities for encrypting the data and authenticates the users who use the encrypted data. More formally, Cryptography is a science of protecting data. This study represents a timeline of the evolution of cryptography from early Egyptian cryptography to modern cryptography encryption technique. This study explains why encryption is needed why every world's leader used encryption and why we still needed it. The different techniques used during 1899 BCE and till now for the secure communication which is an important part of the digital world. This Study will let know what different types of cryptography techniques used in the different period of times. Also, this study will help peoples to know in details about the different cryptographic machines and their work and efficiency of encrypting and decrypting data of those machines.
Ordinal Logistic Regression Analysis of Factors Affecting the Length of Student Study

The length of time a student completes the study period is a measure of the student's achievement and the success of his study program. Because the duration of the study period is quite influential on the quality of a study program and the learning process in it, it is necessary to do a more in-depth study of the factors that influence the duration of student studies. This study aims to model the factors that influence the length of the study period of students using ordinal logistic regression. These factors are the student's GPA and gender. Data on the length of study, GPA and gender were taken for students of the Mathematics Education Department, IKIP Mataram, who graduated in 2017 and 2018. The results of the study showed that the two factors had a significant effect on the length of the study period.
Decimal Selection Functions

When we take a decimal form of a number in the unit interval [0,1], we can form a new number by selecting certain digits and discarding the others. We analyze the properties of this process, particularly in relationship to a recent Monthly article.
Mac OS Forensics

Mac is very popular among professionals and enthusiasts of fields such as Photography, Music production and editing, Video processing, and Web development. Mac comes with Apple Inc.’s voice assistant Siri, which enhances user experiences.
Extreme Speech| Extreme Speech and Global Digital Cultures — Introduction

In this article, we introduce the Special Section on Extreme Speech and Global Digital Cultures by developing the concept of “extreme speech.” In addressing the growing cultures of online vitriol and extremism, this concept advances a critical ethnographic sensibility to situated online speech cultures and a comparative global conversation that moves beyond the legal-normative debates that have been dominant in North America and Europe. We demonstrate this intervention by highlighting three interlinked arguments: Extreme speech inhabits a spectrum of practices rather than a binary opposition between acceptable and unacceptable speech; the sociotechnological aspects of new media embody a context in itself; and the violence of extreme speech acts is productive of identity in historically specific ways. This approach entails a methodological move that takes account of the meanings online users attach to vitriol as historical actors. It thus allows for critical frameworks to emerge from emic terms of action rather than moral concepts superimposed from the outside. Ethnographic explorations of extreme speech, we suggest, open up a new avenue to critique the contemporary global conjuncture of exclusionary politics.
The Multimedia in Physics Teaching and Learning community

The Multimedia in Physics Teaching and Learning community share a keen interest in pedagogical approaches to physics education. A major part of this concerns the development of software and hardware tools to enhance the experience of students and teachers. In September 2017 around 60 colleagues from across the globe came to The Open University campus for three days of networking and sharing of ideas. In plenary sessions John Belcher spoke about the MIT’s TEAL project on learning environments for electromagnetism, Eileen scanlon spoke on Learning and Teaching physics ‘in the open’ and Bruce Mason reviewed Mobile technology. There were general contributions by participants in sessions on Virtual and remote labs, Developments in schools, Simulations and representation, IT/arduino projects, Game based learning, and Use of smart phone technology. There were also workshop activities on Jupyter Notebooks, Remote and Robotic Observatories and on the OpenSTEM labs facilities of the Open University. The abstracts of contributions are archived at this URL https://bit.ly/2SKtoKF. Formal reports based on some of the presentations are included here for future reference. These have been edited together to form a coherent record of those contributions that were ready for publication in a print format. Robert Lambourne and Nicholas Braithwaite
Straightness metric for warping strength in atmospheric turbulence affected images

Reliable no-reference image quality metrics are indispensable in many research areas. In this paper, a metric for image warping due to atmospheric turbulence is presented. Its main mechanism is the quantification of “straightness” in distorted images.
LITERASI MULTIMODAL BERMUATAN KEARIFAN LOKAL SERTA IMPLEMENTASINYA DALAM PEMBELAJARAN

Abstract : This article aims to place and position multimodal literacy by using text containing local wisdom as a learning medium. This presentation is based on three things, namely (1) the context of multimodal literacy in learning, (2) multimodal literacy in learning, and (3) positioning multimodal texts with local wisdom. These problems are related to the pedagogical aspects of multimodal learning in the view of constructivism. Learning is directed at preparing students in the industrial revolution 4.0 era that requires competent students to take part in society by strengthening socio-cultural local wisdom in the formation of personal identity. This problem then inspired the development of student multimodal literacy by utilizing local wisdom-filled texts. Keywords : Multimodal Literacy, Local Wisdom, Learning
ANALISIS DAN PERANCANGAN SISTEM INFORMASI ADMINISTRASI PEMBAYARAN BIAYA PENDIDIKAN BERBASIS WEB DAN SMS GATEWAY PADA PONDOK PESANTREN NURUL IMAN MUARO SEBAPO

Pondok Pesantren Nurul Iman is a religious education institution that has a number of santri as 621people. In the administrative activities of the payment education fees at Pondok Pesantren Nurul Imanstill use manual recording system that experienced various obstacles such as the length of time required toget information on payment of education fee and often the information is not up to the parents of thesantri. Therefore, need a tool in the form of Information Administration System Payments Education Feethat work in computerized, so that can be a solution of the problem. In this research, system design usingUML modeling that produce use case diagram, activity diagram and class diagram. The results of thisresearch is a prototype of the Information System Administration Payment Education Fees based web andSMS Gateway in the hope to help overcome the problems that occur
S&CNet: A Enhanced Coarse-to-fine Framework For Monocular Depth Completion.

Dense depth completion is essential for autonomous systems and 3D reconstruction. In this paper, a lightweight yet efficient network (S\&CNet) is proposed to obtain a good trade-off between efficiency and accuracy for the dense depth completion. A dual-stream attention module (S\&C enhancer) is introduced to measure both spatial-wise and the channel-wise global-range relationship of extracted features so as to improve the performance. A coarse-to-fine network is designed and the proposed S\&C enhancer is plugged into the coarse estimation network between its encoder and decoder network. Experimental results demonstrate that our approach achieves competitive performance with existing works on KITTI dataset but almost four times faster. The proposed S\&C enhancer can be plugged into other existing works and boost their performance significantly with a negligible additional computational cost.
Introduction to Cyber Forensics

The rise and growth of cyberspace have led to a chain of events that has shaped the world we live in. We have seen the rise of IT industries, which created millions of jobs all over the world either directly or indirectly. The start of e-commerce has revolutionized the shopping and retail industry. E-governance was adopted by nations all around the globe as it provided a better platform for administration and promoted transparent and efficient working practices. With the development of computer systems, the world has also witnessed the emergence of cybercrime. As computer-related crimes and incidents have increased, investigations have demanded the services of experts with knowledge of computer systems and law enforcement protocols. The pioneers of cyber forensics were computer hobbyists and law enforcement officers who would share their knowledge to investigate computer-related crimes. Over the past years, the world has witnessed computer-related crimes, which have directly or indirectly harmed people or organizations; a term was coined for them – cybercrime.
Realization of Optimal Identification Tasks for Dynamic Systems in Real Time Scale

The article describes a technical complex for solving problems of D-optimal sequential identification of a wide class of dynamic regression models in real time scale. As an example of an identifiable system, the technological process of formaldehyde production is given.
A Holistic Registration Approach to Fusion of Interpolated Frames

The Fusion of Interpolated Frames Super-Resolution (FIF SR) method has successfully been used restore turbulent aliased imagery with the aid of only a global affine registration routine. This paper examines an extension of this method that employs both a global affine registration and a local block-matching optical flow registration to better address local warping in turbulent imagery. Results are presented from simulated datasets that have varying levels of optical turbulence.
Blockchain's Potential to Combat Procurement Frauds

One of the big issue in procurement is fraud, and many companies go through deep investigation before offering a job for the right candidate as the job is very sensitive as large budgets allocated to procure goods and services for business. Procurement fraud, thus,  is likely to occur in the procurement department  since they deal with money, through dealing with vendors for material, goods, services, transportation, logistics, distribution of products, warehousing, or other benefits in exchange for awarding the contract, and frauds are then possible based on quid pro quo, whereby an  advantage is given in exchange for awarding the contract. To this end, using the traditional methods to control such frauds are not easy and could be faded away very soon,  especially with existing and emerging digital technologies such as Blockchain.  The paper reviewed how Blockchain is able to eradicate procurement frauds through focusing on the usability and functionality of the technology in procurement. The study uses the experiment research method to measure procurement frauds as the independent variable and the power of Blockchain to control such frauds as the dependent variables, using the nonexperimental research method. The study tries to highlight the challenges and possible directions of Blockchain research in protecting procurement from any types of frauds that could be happening, which are impossible through the traditional methods. Finally, this paper points out the future directions in the Blockchain technology in procurement.
Os Sistemas de Organização do Conhecimento e os desafios frente a geração Google

Information Science (IS) faces an interesting paradox in the current context.On the one hand we have a big boom of information and on the other hand the immense challenge that can consolidate IS and Knowledge Organization Systems (KOS) through this scenario.This article seeks to point out ways that KOS can follow to counter web searchers such as Google, widely used tools that increasingly lead people to question library systems and why they exist.The web searchers have given a great contribution to the search for information in the digital environment.However, they are immersed in visions of large corporations and limited to stereotypes, sometimes prejudiced.Such systems still lack skills that can be found in KOS which follow ethical values and construction parameters that seek to know their users and their socio-historical-cultural reality.
Thematic Progression in Students’ Descriptive Texts

Thematic progression is important in coherence to be considered as good text. So, it needs the element of thematic progression or it can be called theme and rheme. Theme and rheme constitutes the main part of clause, because comprehending the thematic progression may help to understand whole clause. The coherence text should also be necessary written by students in senior high school in Batujajar. This investigation is conducted to consider the thematic progression and coherence in descriptive text. The purpose of this research is to identify types of thematic progression in students’ descriptive text and the levels of coherence in students’ descriptive text. The researchers use descriptive quantitative method.. The data are all clauses from paragraphs on text. The result of the result shows that there are two of three models of thematic progression found, namely zig-zag theme and re-iteretion. In addition, the finding also found that there are three level coherence in every students’ descriptive text such as a good, fair, and less levels coherence.
Exploring the Potential of Metaheuristics-Based Clustering in Load Profiling Applications

The clustering tool is ideal for scientific and engineering problems where no information about the data structure is available. Usually, in load profiling applications no sufficient information is a priori given for the consumers' classes, their consumption patterns and other attributes that will aid on building a descriptive model for the consumption trends. Many clustering algorithms of different type have been proposed. However, no attention has been placed so far in the utilization of metaheuristics for building robust clustering tools. The scope of this study is to develop a hybrid algorithm that combines partitional clustering and Particle Swarm Optimization (PSO). Simulation results indicate the superiority of the proposed algorithm over conventional clustering approaches.
DEVELOPMENT OF NEW PROGRAMMING WITH STICKERS FOR ELEMENTARY SCHOOL PROGRAMMING EDUCATION

1 Electrical and Electronic Engineering / International College of Technology, Kanazawa (JAPAN)2 Global Information and Management / International College of Technology, Kanazawa (JAPAN)
User experience in the aspect of threats to digital security

AimCharacterization of user experience as a threat to cyber security and determination of the level of awareness of users of social networks in the aspect of sharing their data in the network are the goal of the research presented in the article. MethodsIn order to investigate the indicated problem, we applied one of the qualitative research methods -an individual in-depth interview based on the original scenario.Th e motivation to use this method is the need to receive the most detailed information from users.Th e research group includes 12 people aged between 19 and 25, who use social media on a daily basis. ResultsFrom the interviews we have obtained information about the respondents' knowledge about the data they provide and we have determined which data is actually made available by them in the network.On this basis, we have determined the level of awareness of users in the examined aspect.In addition, we obtained information about the motivation of the respondents to share data on portals of User experience in the aspect of threats to digital security User experience w aspekcie zagrożenia dla bezpieczeństwa cyfrowego
ARSNOVA.CARDS: HOW TO SUSTAINABLY PROMOTE MOBILE LEARNING WITH A FLASHCARD APP

Appears in: EDULEARN19 Proceedings Publication year: 2019Pages: 2067-2077ISBN: 978-84-09-12031-4ISSN: 2340-1117doi: 10.21125/edulearn.2019.0561Conference name: 11th International Conference on Education and New Learning TechnologiesDates: 1-3 July, 2019Location: Palma, Spain
Implementation of Data Mining to Predict Food Sales Rate Method using Apriori

Fonzu Premium restaurant management has had difficulty in knowing the which menus are most in demand by consumers and still uses manual methods, and sometimes customers can not order the desired order Because some of the menus on the menu list are up or some raw material supplies are not available.Apriori algorithm is one algorithm that searches frequent itemset by using the association rule technique.Based on the results of implementing the association rule method using a priori algorithm to find the linkages between the level of sales menu Fonzu Premium ordered at restaurants.With this association rule, it is expected to help the managerial parties to find out the which menus are most in demand by consumers, so a system can be used the which can be used as a prediction system using data mining association rule Apriori algorithm using.
SAR 3D sparse imaging based on CLA

A novel method for synthetic aperture radar (SAR) three-dimensional (3D) sparse imaging based on a coprime linear array (CLA) is proposed. To reduce the geometric resolution loss caused by under-sampled sparse SAR, a jointed sparse imaging approach is used. In this scheme, the coprime sampled data of CLA is separately processed via the iterative reweight least-squares approach, and their recovered results are combined to cancel the false targets and grating-lobes to improve the imaging quality. Both simulated and experimented results demonstrate the effectiveness of the method. It shows that the exploiting of CLA and sparse recovery can significantly reduce the linear array antenna amount and the geometric resolution loss compared with the conventional uniform linear array SAR.
Conditional Linear Regression

Work in machine learning and statistics commonly focuses on building models that capture the vast majority of data, possibly ignoring a segment of the population as outliers. However, there may not exist a good, simple model for the distribution, so we seek to find a small subset where there exists such a model. We give a computationally efficient algorithm with theoretical analysis for the conditional linear regression task, which is the joint task of identifying a significant portion of the data distribution, described by a k-DNF, along with a linear predictor on that portion with a small loss. In contrast to work in robust statistics on small subsets, our loss bounds do not feature a dependence on the density of the portion we fit, and compared to previous work on conditional linear regression, our algorithm’s running time scales polynomially with the sparsity of the linear predictor. We also demonstrate empirically that our algorithm can leverage this advantage to obtain a k-DNF with a better linear predictor in practice.
Efficient mask expansion for green-screen keying using color distributions

Masks are heavily used in image and video processing, particularly in the context of green screen keying. Designing good masks is a difficult task that involves painting over small details of images. Usually, only a rough mask is created. We propose an algorithm to expand such a mask, using color similarity. Our approach is fast, even on 4K images, and compares favorably with standard tools used in keying.
TOWARDS REFLECTION AND ACTION ON THE DEVELOPMENT OF A HYBRID LEARNING MODEL TO PROMOTE THE ADOPTION OF MOBILE DEVICES IN SCHOOLS

TOWARDS REFLECTION AND ACTION ON THE DEVELOPMENT OF A HYBRID LEARNING MODEL TO PROMOTE THE ADOPTION OF MOBILE DEVICES IN SCHOOLS
Association Rule Mining for Career Choices Among Fresh Graduates

Nowadays, an increasing number of colleges have built information systems to manage masses of educational data, but actually most data is in an idle state and fails to create any value.As an efficient data analysis method, association rule mining can precisely make good use of these disordered data and extract useful but latent information from them.In this paper, an example of 228 students, who graduated from the School of Information of Zhejiang University of Finance and Economics, China in 2017, is taken to discover the association rules between their career choices and academic performance using Apriori algorithm.The main purpose of this paper is to offer fresh graduates a reference to future career choices and help teachers guide them in better career planning.The experimental results indicate that the courses students are good at largely affect their career choices, although their overall career scope is not narrow.
CAN A SOLUTION BE FOUND USING INFORMATION AND COMMUNICATION TECHNOLOGY GADGETS IN HIGHER EDUCATION? A CASE OF A RURAL UNIVERSITY

CAN A SOLUTION BE FOUND USING INFORMATION AND COMMUNICATION TECHNOLOGY GADGETS IN HIGHER EDUCATION? A CASE OF A RURAL UNIVERSITY
TEKNOLOGI AKSARA LONTARA DI ERA INFORMASI TEKNOLOGI 4.0

The aim of this paper is to show the development of number and marking of Lontara’s script. The development is to provide and make a specific and additional marking character of Lontara. Those characters developed furthermore in the form of electronically program that able to be run at word office, both under windows and opensource (linux). The program used in making of Lontara’s number and its additional marking character is Fontmonger program. The obtained result of this development is a file program that available to be run properly either at word office or opensource and the file is called ltrunhas.ttf.