Reviewerly/exHarmony huggingface dataset:
Increasing Oversampling Diversity for Long-Tailed Visual Recognition

The long-tailed data distribution in real-world greatly increases the difficulty of training deep neural networks. Oversampling minority classes is one of the commonly used techniques to tackle this problem. In this paper, we first analyze that the commonly used oversampling technique tends to distort the representation learning and harm the network’s generalizability. Then we propose two novel methods to increase the minority feature’s diversity to alleviate such issue. Specifically, from the data perspective, we propose a mixup-based Synthetic Minority Over-sampling TEchnique called mixSMOTE, where tail class samples are synthesized from head classes so that a balanced training distribution can be obtained. Then from the model perspective, we propose Gradient Re-weighting Module (GRM) to re-distribute each instance’s gradient contribution to the representation learning network. Extensive experiments on the long-tailed benchmark CIFAR10-LT, CIFAR100-LT and ImageNet-LT demonstrate the effectiveness of our proposed method.
Intelligent Distributed Method to Secure Stored Data in Cloud Computing

Computing using cloud services is a new and different paradigm that is manufacturing nice changes to enterprise hardware and code style additionally opening a massive path to the web-based computing services for meeting the varied wants because the cloud is gaining huge advancement cloud knowledge security and privacy of information is turning into an essential issue. If we have a tendency to take into account all the safety problems associated with the cloud then one amongst the main issues is that cloud operators have an opportunity to succeed in the cloud user’s sensitive knowledge. This concern dramatically decreases the usability of cloud computing in several areas, like monetary organizations. This paper concentrates on the difficulty that cloud operators cannot reach the sensitive info of cloud users and thus proposes a new cryptography method by which cloud administrators cannot gain access to the entire information. The proposed approach divides the data into three parts and thus the data is stored in three different distributed clouds due to which cloud operators cannot reach the complete data, they can only gain access to the partial data which is of no use. In this research we will present a solution to the above- stated problem and will try to develop a model which focuses on secure cloud data model with acceptable computation time.
Head Pose Tracking Method Based on Face Detection And Stereo Visual SLAM

For purpose of solving the fine estimation and real time problems of existing head pose tracking methods, we propose a method based on face detection and stereo visual SLAM algorithm. Firstly, the stereo image is pre-processed by Gaussian filter and the face region is localized using adaptive Haar+Adaboost algorithm. Secondly, we use the improved ORB algorithm to extract the feature points in the image grids and match them through stereo vision technology. The invalid 3D points are excluded according to the depth threshold. Thirdly, we obtain 3D-2D matching relations through projecting mappoints from last frame to current frame. Finally, we obtain the optimized head pose through the Bundle Adjustment and the coordinate system transformation relation. The experiments show that the average error of the method in this paper is about 0.5°, indicating that the method has high precision.
Correction to: Short Text Clustering with a Deep Multi-embedded Self-supervised Model

Due to an oversight, the second affiliation of three co-authors was omitted in the originally published version. The revised version has the correct affiliations of all co-authors.
Social media and communications

The regulation of technology is an important and topical area of law, relevant to almost all aspects of society. Technology Law: Australian and International Perspectives presents a thorough exploration of the new legal challenges created by evolving technologies, from the use of facial recognition technology in criminal investigations to the rise and regulation of cryptocurrencies. A well-written and fascinating introduction to technology law in Australia and internationally, Technology Law provides thorough coverage of the theoretical perspectives, legislation, cases and developing issues where technology and the law interact. The text covers data protection and privacy, healthcare technology, criminal justice technology, commercial transactions, cybercrime, social media and intellectual property, and canvasses the future of technology and technology law. Written by leading experts in the field, Technology Law is an excellent resource for law students and legal professionals with an interest in the area.
Eigenfunction rules

It is well known that eigenfunctions have to be continuous at each space point of the structure in which they are localized. This is not the only rule they have to fulfill. Rules involving eigenfunction derivatives are also used in the bulk and at the boundary of all physical systems. The aim of this section is to try and reach a general formulation of the eigenfunction rules. At each space point of this network, it is found that the eigenfunctions are continuous and the sum of their outgoing first derivatives is equal to zero. These rules fix the values of the discrete eigenvalues.
ARGUMENT BAR MOVEMENT IN RELATIVE CLAUSES PRODUCED BY BIPA STUDENTS: AN ANALYSIS OF NOAM CHOMSKY’S GENERATIVE TRANSFORMATION

This study was intended to describe (1) the characteristics of the argument bar movement in relative clauses, (2) the characteristics of the relative clause structure, and (3) the suitability of the relative clause structure produced by BIPA students. This research was a qualitative descriptive case study. This research data were relative clauses sourced from BIPA students' speeches at the beginner and intermediate levels at the University of Muhammadiyah Malang. The data collection method used was the listening method with tapping, recording, note-taking, and hidden fishing techniques. Data analysis was carried out by identifying the predication-argument relationship with theta theory, identifying the deep structure and surface structure, analyzing movement objectives, movement traces, and movement consequences by utilizing the subjacency condition theory. The results showed that the characteristics of the argument bar movement in the relative clauses generated by 92% of BIPA students were in the form of short movements and did not exceed one bounding node. Based on the Indonesian language rules, most of the relative clauses produced by BIPA students were appropriate (75%). It shows that BIPA students have fully understood the relative clause structure.
NEW FORMS OF PUBLIC PARTICIPATION IN SCIENCE AND TECHNOLOGY : REVIEW OF FOREIGN STUDIES

In the 21st century, the relationship between science and society takes on a new character. Today, public participation is required not only in the discussion and decision-making concerning important scientific and technical issues, but also in the production of innovations and scientific knowledge. Citizens and the public are seen as important participants in the research process and consumers of new technologies. In this regard, new forms of involving non-specialists in joint research projects are emerging. This is largely facilitated by the rapid development of information and communication technologies, which greatly simplify and expand the interaction of scientists and volunteers. Citizen Science projects cover all areas of science and serve as an important complement to scientific research.
Why Infrastructure as Code?

In this chapter, we will cover how organizations have deployed applications in their datacenters and the evolution of the software-defined datacenter approach. We’ll also cover why it’s now more important than ever to master the skills of infrastructure as code (IaC), as well as the current state of IaC.
Introduction

With a machine learning approach and less focus on linguistic details, this gentle introduction to natural language processing develops fundamental mathematical and deep learning models for NLP under a unified framework. NLP problems are systematically organised by their machine learning nature, including classification, sequence labelling, and sequence-to-sequence problems. Topics covered include statistical machine learning and deep learning models, text classification and structured prediction models, generative and discriminative models, supervised and unsupervised learning with latent variables, neural networks, and transition-based methods. Rich connections are drawn between concepts throughout the book, equipping students with the tools needed to establish a deep understanding of NLP solutions, adapt existing models, and confidently develop innovative models of their own. Featuring a host of examples, intuition, and end of chapter exercises, plus sample code available as an online resource, this textbook is an invaluable tool for the upper undergraduate and graduate student.
Event Cube for Suicidal Event Analysis: A Case Study

The publicly available data, such as the massive and dynamically updated news and social media data streams (a.k.a. big data), cover a wide range of social activities, personal views, and expressions. Effective research and application rely heavily on the ability of comprehending and discovering the knowledgepatterns underlying this big data, from which the notion of an event serves as a cornerstone in building up more complex knowledge structures. Establishing methodologies and techniques for discovering real-world events from such large amounts of data, as well as for managing and analyzing such events in an efficient and aesthetic manner, is crucial and challenging. In this paper, we present an event cube framework devised to support various collection, consolidation, fusion, and analysis tasks for suicidal events. More specifically, we present a mechanism for data collection over multiple data sources in both passive and active manners, and promote the mappings constructed from various representation spaces for data consolidation. Furthermore, multimodal fusion is devised to integrate multiple data intrinsic structures and learn discriminative data representations so as to process heterogeneous multimodal data efficiently. Finally, the event cube model is developed to support event organization and contextualization with hierarchical and analytical operations. A case study is provided to demonstrate the capabilities and benefits of our event cube facilities supporting on-line analytical processing of suicidal events and their relationships.
Models for assessing the effectiveness of higher education export development in the Russian Federation

Models for assessing the effectiveness of the development of exports of higher education in the Russian Federation as the activity of educational institutions of higher education to create and develop a channel and method of supplying educational services to foreign consumers are considered.
Formalizing Predicates for Discovery Under the Lexicon Grammar Framework

This text proposes a method for automatic analysis of predicates for discovery (PD) in Spanish. A PD is a predicative unit that projects an argument structure (AS) whose meaning alludes to ‘something that is found by someone -or something- somewhere’ (e.g., ‘encontrar’, ‘hallar’). This type of task is useful in fields such as medicine, since it offers the possibility of automatically identifying findings of interest (diseases, test results, etc.) in large text corpora. The present work is based on Lexicon Grammar (LG), which proposes a formalization from the nature of arguments (object classes) and transformational possibilities. The methodology is carried out as follows: (i) manual identification of PDs from a corpus of gynecology and obstetrics; (ii) elaboration of LG tables for each PD, where object classes are categorized and possible transformations are listed; and (iii) computational modeling. For the last stage, electronic dictionaries and computer-generated grammars were built in NooJ. The algorithm with automatically detected and generated ASs from PDs (325 grammatical sentences) was evaluated against an annotated corpus (1000 manually-annotated sentences, randomly extracted from a corpus of 5 million words). Results gave 98% accuracy, 88% coverage, and 92% F-measure.
Adaptive Enhancement for Scanned Historical Document Images

In this paper we propose, a novel adaptative histogram matching method to remove low contrast, smeared ink, bleed-through and uneven illumination artefacts from scanned images of historical documents. The goal is to provide a better representation of document images and therefore improve readability and the source images for Optical Character Recognition (OCR). Unlike other methods that are designed for single artefacts, our proposed method enhances multiple (low-contrast, smeared-ink, bleed-through and uneven illumination). The method starts by taking the bimodal peaks of the original grayscale image and multiplying them to generated gaussian windows to create an ideal histogram with weights of importance to distribution. This histogram becomes the reference histogram to be matched to the original image for a more optimized image. Median filtering is also incorporated in the method to remove salt and pepper noise. We demonstrate the technique on the European Newspapers project (ENP) dataset chosen from the Pattern recognition and image analysis research lab (PRImA) and establish from the results that, the proposed method significantly reduces background noise and improves image quality on multiple artefacts as compared to other enhancement methods tested. To evaluate the efficiency of the proposed method, we make use of several performance criteria. These include Signal to Noise Ratio (SNR), Mean opinion score (MOS), and visual document image quality assessment (VDIQA) metric. The proposed method performs best in all the evaluation metrics having a 42.6 % increment on the average score of the other methods for MOS, 44.3% increment on average score of other methods for SNR and 61.11% better in VDIQA compared to other methods.
Trace Car Based on Super Capacitor

Take the msp430f5529 single chip of TI company as the control chip and the wireless charging device as the core to coordinate the other modules. The system consists of transmitting module, receiving module, energy storage module, motor driving module, and sampling module. The transmission module adopts voltage type single-phase half bridge inverter circuit, and uses Faraday electromagnetic induction law at the output end to transfer the energy to the secondary coil, and generates series resonance by adjusting PWM wave frequency; the induction current generated by the secondary coil changes into DC through the rectifier circuit to charge the supercapacitor, and the capacitor connects the tps63020 voltage stabilizing module to supply power to the motor; through msp430f5529 the single chip microcomputer samples the voltage to decide whether to control the car to start moving.
Superunification: Pure Mathematics &amp; Theoretical Physics

In case if we complete the Gaussian type classical pure mathematics with cardinally new discoveries, then the problem of the super unified field theory as smoothly continued from the Standard model becomes just technical. This article is intended to demonstrate the quintessence of what is happening to theoretical physics because of the completion of pure mathematics. A comprehensive rendition of the superunification theory, please, find on the website: finaltheory.net.
Japanese Kana and Brazilian Portuguese Manuscript Database

This work introduces a Japanese Kana and Brazilian Portuguese database (JKBP), a novel database made freely available aimed at supporting the development of manuscript-based recognition tasks. As far as we know, this is the first database created and made available to the research community composed of Portuguese and Japanese manuscripts. The samples were collected from 57 volunteers. Each volunteer provided five manuscript samples written in Brazilian Portuguese, and five more samples written in Japanese Kana. We also describe baseline experiments accomplished on JKBP exploring some of its different possibilities of classification tasks, such as syllabary and writer classification. We conducted the experiments using Speed Up Robust Features (SURF), a texture descriptor which has been successfully used to capture the textural content in this application domain. Support Vector Machine (SVM) was used for classification, given its good performance in other works available in the literature involving similar tasks. The obtained results showed that the zoning process and use of late fusion provide a meaningful increase of the performance in some scenarios. The best accuracy rates achieved were 97.98% and 83.77% on writer identification task using Portuguese and Japanese manuscripts respectively, and 100% in syllabary classification.
THE FUTURE OF ICT TECHNOLOGY IN THE TEACHING OF SPECIALIZED DISCIPLINES FOR CHEFS

THE FUTURE OF ICT TECHNOLOGY IN THE TEACHING OF SPECIALIZED DISCIPLINES FOR CHEFS Assel Akhmetova PhD, Uralsk technological college &laquo;Service&raquo;, Kazakhstan, Uralsk &nbsp; Improving the effectiveness of education is impossib
Classification of Handwritten Indic Scripts Using Deep Learning

Jaisswal, Aaditree Ghalsasi, Prachi Jain, Aabha Batra, Misha Arora, SandhyaOld handwritten documents written in regional languages are difficult to interpret. It is also hard to identify the script that the characters are conforming to. Script recognition is an integral part of researching the anthropology of a region and understanding its geography and culture. Current research in handwritten script recognition focuses on character level recognition of at most two or three languages. It is also a lot harder to identify scripts in Indian languages due to the similarity between their characters. The aim of this paper is to be able to create a deep learning model that can classify up to twelve different languages, at document level and display the output based on the result by performing line-level segmentation, followed by word-level segmentation and finally with character recognition of the document.
Examining attitudes towards cybersecurity compliance through the lens of the psychological contract

This research proposal defines the aim to explore the perceptions and experiences of employees through a global pandemic. In an exploratory qualitative study, utilising thematic analysis, the intention is to take an interpretivist position to examine participants&apos; accounts of working from home during a pandemic, by looking through the psychological contract (Rousseau, 1996a) lens to better understand this phenomenon. This research serves to offer a potential line of enquiry when it comes to the human factors of cyber and information security behaviour and any themes which may overlap with psychological contract breaches (PCB). Previous research has suggested that the psychological contract can impact on employee commitment towards their organisations (Jabeen, Behery and Hossam, 2015), and employees&apos; attitudes towards cyber security affect the frequency in engaging in risky online behaviours, (Hadlington, 2018), this study aims to draw out any themes around these areas through semi-structured interviews with employees in a global law firm.
Privacy and data protection

The regulation of technology is an important and topical area of law, relevant to almost all aspects of society. Technology Law: Australian and International Perspectives presents a thorough exploration of the new legal challenges created by evolving technologies, from the use of facial recognition technology in criminal investigations to the rise and regulation of cryptocurrencies. A well-written and fascinating introduction to technology law in Australia and internationally, Technology Law provides thorough coverage of the theoretical perspectives, legislation, cases and developing issues where technology and the law interact. The text covers data protection and privacy, healthcare technology, criminal justice technology, commercial transactions, cybercrime, social media and intellectual property, and canvasses the future of technology and technology law. Written by leading experts in the field, Technology Law is an excellent resource for law students and legal professionals with an interest in the area.
From quest to quill

In this session, the team behind the Immersive Best-in-Show winner (Bonfire) at Siggraph 2019 reveals creative and technical insights from their two recent award winning VR projects: Baba Yaga and Namoo.
A materialidade e a institucionalidade da informação possíveis contribuições para a noção de documento na Arquivologia

We will discuss in the article the notion of document in Archivology and Information Science. To this end, this study aims to describe the possible contributions that the materiality and institutionality of information can offer to the archival document. The methodology was based on a literature review and analysis of it in the field of archivology, making the exploratory research critical and reflective.Thus, in a preliminary way, the article sought to present the perspectives and contributions of the materiality and institutionality of the information to the documentand to relate it to the notionof document in archivology.
Load Balancing Synchronized Brownout Oriented Approach for Safeguarding Cloud Services Sustainability

Efficient global networking demands proficient data centres, to cater cloud computing of par excellence. The attainment of this goal is infringed by unexpected events like flash crowds and hardware failures. It degrades the users experience since applications exhibit an unpredictable unresponsive behaviour. This challenge can be negotiated by brownout-enabled cloud applications to control response times and by incorporating replicas which are mirror image facsimile of applications with same functionalities to address redundancy factor. The induction of a load balancer to address direct incoming traffic revamps the objective of curbing this aforesaid challenging problem further. But the load balancers are not reckoned as a good indicator to decipher the replicas-related performance since their functionalities are response time-dependent. Response times themselves are subjugated to self-adaptive features of applications hence unable to express replica-related performance with full authenticity. Therefore, load balancing strategies are needed to be synchronous with brownout applications to address user experience degradation with prime importance with respect to response time. It can be achieved by deactivating application optional components in a dynamic and selective manner to contain response time as close as possible to a set point under a scenario of stress during phase of high resource utilization.
Intellectual property

The regulation of technology is an important and topical area of law, relevant to almost all aspects of society. Technology Law: Australian and International Perspectives presents a thorough exploration of the new legal challenges created by evolving technologies, from the use of facial recognition technology in criminal investigations to the rise and regulation of cryptocurrencies. A well-written and fascinating introduction to technology law in Australia and internationally, Technology Law provides thorough coverage of the theoretical perspectives, legislation, cases and developing issues where technology and the law interact. The text covers data protection and privacy, healthcare technology, criminal justice technology, commercial transactions, cybercrime, social media and intellectual property, and canvasses the future of technology and technology law. Written by leading experts in the field, Technology Law is an excellent resource for law students and legal professionals with an interest in the area.