Reviewerly/exHarmony huggingface dataset:
Feature Distillation With Guided Adversarial Contrastive Learning.

Deep learning models are shown to be vulnerable to adversarial examples. Though adversarial training can enhance model robustness, typical approaches are computationally expensive. Recent works proposed to transfer the robustness to adversarial attacks across different tasks or models with soft labels.Compared to soft labels, feature contains rich semantic information and holds the potential to be applied to different downstream tasks. In this paper, we propose a novel approach called Guided Adversarial Contrastive Distillation (GACD), to effectively transfer adversarial robustness from teacher to student with features. We first formulate this objective as contrastive learning and connect it with mutual information. With a well-trained teacher model as an anchor, students are expected to extract features similar to the teacher. Then considering the potential errors made by teachers, we propose sample reweighted estimation to eliminate the negative effects from teachers. With GACD, the student not only learns to extract robust features, but also captures structural knowledge from the teacher. By extensive experiments evaluating over popular datasets such as CIFAR-10, CIFAR-100 and STL-10, we demonstrate that our approach can effectively transfer robustness across different models and even different tasks, and achieve comparable or better results than existing methods. Besides, we provide a detailed analysis of various methods, showing that students produced by our approach capture more structural knowledge from teachers and learn more robust features under adversarial attacks.
The Far Eastern State Scientific library – a professional communication center

One of the system-forming elements in the library sphere are central libraries of the Russian Federation subjects (national, territorial, regional), which provide methodical maintenance of library activities in their region. The main task of methodical centers is to develop and improve methods of work performed by library specialists. The Far Eastern State Scientific Library is the methodical center for public libraries in the Khabarovsk Territory. There is a specialized division – the Department of Research and Methodical work – in its structure. In the course of scientific and methodical activities, the division is implementing information, organizational, research and pedagogical functions, so the structure of the department includes a group of methodical maintenance, a group of specialists engaged in research work, and a licensed center for additional professional training. Well-organized professional communication is the key to the successful development of the region library sector. Consideration of methodological support as an activity to organize and maintain professional communication of library professionals will reveal how effectively such communication is organized, what types, forms and channels of communication are used in the process of methodological support of the library institution activities in the region. The Library gives great attention to the communication formation at various levels (interpersonal, group, mass), and strives to use all available forms (written, spoken, visual) and channels (spoken, document, electronic) of communication. The article objective is to elucidate the Library experience of methodical support of public libraries in the Khabarovsk Territory.
Music schools and schools of arts Libraries – the place for study and work ("second place")

In contrast to Oldenburg’s concept of «library – the “third place”» the article presents its role as the «second place», i.e. the place for study and work, on the examples of music and art schools libraries, (music schools/CAS) of St. Petersburg. These establishments meet the specific needs of library users (students and teachers) that occur in the process of educational activities on pre-service programs in various types of art. The peculiarity of these libraries permit them to preserve their own niche in the general library and information space and in each concrete institution of additional education. The article examines social functions, goals and tasks of DMSH/DSHI libraries, their normative-legislative regulations, financial and acquisition questions, work of referencesearch apparatus, forms of servicing users. Possible ways of their development are designated: creation of the special Model standard; transformation of libraries into educational information centers on art in the educational environment of schools with the appropriate technical and technological equipment and the Internet access; active mastering of social networks. All this will allow DMSH/DSHI libraries to develop and implement additional forms of service.
Shimon the Rapper: A Real-Time System for Human-Robot Interactive Rap Battles

We present a system for real-time lyrical improvisation between a human and a robot in the style of hip hop. Our system takes vocal input from a human rapper, analyzes the semantic meaning, and generates a response that is rapped back by a robot over a musical groove. Previous work with real-time interactive music systems has largely focused on instrumental output, and vocal interactions with robots have been explored, but not in a musical context. Our generative system includes custom methods for censorship, voice, rhythm, rhyming and a novel deep learning pipeline based on phoneme embeddings. The rap performances are accompanied by synchronized robotic gestures and mouth movements. Key technical challenges that were overcome in the system are developing rhymes, performing with low-latency and dataset censorship. We evaluated several aspects of the system through a survey of videos and sample text output. Analysis of comments showed that the overall perception of the system was positive. The model trained on our hip hop dataset was rated significantly higher than our metal dataset in coherence, rhyme quality, and enjoyment. Participants preferred outputs generated by a given input phrase over outputs generated from unknown keywords, indicating that the system successfully relates its output to its input.
Semi-supervised Multi-task Network For Image Aesthetic Assessment

Image aesthetic assessment has always been regarded as a challenging task because of the variability of subjective preference. Besides, the assessment of a photo is also related to its style, semantic content, etc. Conventionally, the estimations of aesthetic score and style for an image are treated as separate problems. In this paper, we explore the inter-relatedness between the aesthetics and image style, and design a neural network that can jointly categorize image by styles and give an aesthetic score distribution. To this end, we propose a multi-task network (MTNet) with an aesthetic column serving as a score predictor and a style column serving as a style classifier. The angular-softmax loss is applied in training primary style classifiers to maximize the margin among classes in single-label training data; the semi-supervised method is applied to improve the network&#x2019;s generalization ability iteratively. We combine the regression loss and classification loss in training aesthetic score. Experiments on the AVA dataset show the superiority of our network in both image attributes classification and aesthetic ranking tasks.
On the Equivalence between Positional Node Embeddings and Structural Graph Representations

This work provides the first unifying theoretical framework for node (positional) embeddings and structural graph representations, bridging methods like matrix factorization and graph neural networks. Using invariant theory, we show that the relationship between structural representations and node embeddings is analogous to that of a distribution and its samples. We prove that all tasks that can be performed by node embeddings can also be performed by structural representations and vice-versa. We also show that the concept of transductive and inductive learning is unrelated to node embeddings and graph representations, clearing another source of confusion in the literature. Finally, we introduce new practical guidelines to generating and using node embeddings, which fixes significant shortcomings of standard operating procedures used today.
Conflict Generalisation in ASP: Learning Correct and Effective Non-Ground Constraints

Abstract Generalising and re-using knowledge learned while solving one problem instance has been neglected by state-of-the-art answer set solvers. We suggest a new approach that generalises learned nogoods for re-use to speed-up the solving of future problem instances. Our solution combines well-known ASP solving techniques with deductive logic-based machine learning. Solving performance can be improved by adding learned non-ground constraints to the original program. We demonstrate the effects of our method by means of realistic examples, showing that our approach requires low computational cost to learn constraints that yield significant performance benefits in our test cases. These benefits can be seen with ground-and-solve systems as well as lazy-grounding systems. However, ground-and-solve systems suffer from additional grounding overheads, induced by the additional constraints in some cases. By means of conflict minimization, non-minimal learned constraints can be reduced. This can result in significant reductions of grounding and solving efforts, as our experiments show.
Impact of Blockchain Applications on Trust in Business

Blockchain applications are considered as "trustless" machines, because they reduce business's needs of trust in others.The "trustless" nature draws researchers' attention on investigating the implications of blockchain in a business environment.From a view of business ethics, this paper aims at evaluating the impacts of blockchain applications on trust and business.After expounding the relations between trust in blockchain and trust in business partners, I evaluate the impacts based on a framework of competence trust, contractual trust, and goodwill trust.My conclusion is that full acceptance of trust in blockchain over trust in others is not good and will cause several risks that cannot be neglected.The main contribution of this paper is investigating and summarizing ethical and commercial risks of blockchain applications including disintermediation fallacy, centralization of trust, ambiguous contract, noncognitive trust in untrustworthy partners, and more actions guided by moral minimum.
Understanding Library Users via Surveys and Other Methods—Best Practices for Evidence-Based Library Development

A survey was performed over all university libraries within the Association of European Research Libraries (LIBER) in order to study how different methods of user input are utilized. Libraries using analysis based on explorative methods—such as UX and process mapping—report significantly increased user knowledge and perceived well-function. Over three-fourths of the respondents reported performing general user surveys. Surveys offer ease of collection, effectively gather researcher user group input and generate data suitable for communicating library value to stakeholders. However, it is resource-demanding to transfer findings into service changes, especially for smaller libraries, and results often support stepwise improvements rather than discovery of new services.
Revealing the Myth of Higher-Order Inference in Coreference Resolution

This paper analyzes the impact of higher-order inference (HOI) on the task of coreference resolution. HOI has been adapted by almost all recent coreference resolution models without taking much investigation on its true effectiveness over representation learning. To make a comprehensive analysis, we implement an end-to-end coreference system as well as four HOI approaches, attended antecedent, entity equalization, span clustering, and cluster merging, where the latter two are our original methods. We find that given a high-performing encoder such as SpanBERT, the impact of HOI is negative to marginal, providing a new perspective of HOI to this task. Our best model using cluster merging shows the Avg-F1 of 80.2 on the CoNLL 2012 shared task dataset in English.
Coffee Farms as Design Labs: Manifesting Equity x Design Principles in Practice

Recent years have seen a rise in inclusive and participatory principles in design, co-design practices, and community-driven exercises.From "alternative spring breaks" in colleges, to Corporate Social Responsibility (CSR) initiatives at companies, to community development projects led by NGOs, there is growing awareness of the importance of co-design.However, many of these initiatives operate at the expense of communities, inevitability re-creating the power hierarchies they had hoped to level.Gardner, in Discordant Development, articulates the extent to which multinational corporations leverage the narratives of "community engagement" to further disenfranchise the rural poor of Bangladesh (Gardner, 2012).This paper offers a reflection on the role of academics and practitioners during the implementation of a community-based co-design experience at two coffee farms in rural Colombia.It aims to examine an ongoing co-design collaboration across 4 groups:
A Unified Plug-and-Play Framework for Effective Data Denoising and Robust Abstention

The success of Deep Neural Networks (DNNs) highly depends on data quality. Moreover, predictive uncertainty makes high performing DNNs risky for real-world deployment. In this paper, we aim to address these two issues by proposing a unified filtering framework leveraging underlying data density, that can effectively denoise training data as well as avoid predicting uncertain test data points. Our proposed framework leverages underlying data distribution to differentiate between noise and clean data samples without requiring any modification to existing DNN architectures or loss functions. Extensive experiments on multiple image classification datasets and multiple CNN architectures demonstrate that our simple yet effective framework can outperform the state-of-the-art techniques in denoising training data and abstaining uncertain test data.
Efficient Construction of Structured Argumentation Systems

We address the problem of efficient generation of structured argumentation systems. We consider a simplified variant of an ASPIC argumentation system and provide a backward chaining mechanism for the generation of structured argumentation graphs. We empirically compare the efficiency of this new approach with existing approaches (based on forward chaining) and characterise the benefits of using backward chaining for argumentation-based query answering.
A Smart Reminder for Social Purposes Using a Deep Learning‐Based Face Recognition Technique

This paper presents a deep learning‐based face recognition device. It aims to instantly remind users of the identities of those who they met before in parties or conferences. When greeted, one, who is correctly identified, may frequently feel more respected than another who is mistaken for someone else in the first place. The golden rule suggests one to treat others with respect, and then others will treat the one with respect in return. Empirically, making others feel respected can definitely facilitate communication among people for social and particularly business purposes. For this sake, this paper employed a pair of smart glasses as a hardware platform into which a deep learning‐based multi‐task cascaded convolutional networks and a FaceNet algorithm were integrated. This move provided a high face recognition accuracy and a strong robustness. In the end, this smart device as intended recognized captured images and displayed the identities of matched contacts in a face image database. Hopefully, this proposal can be applied to a wide diversity of fields. © 2020 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC.
Decision Support System Nutritional Supplement Receipt Determination Method Using Simple Additive Weighting (SAW)

Nutrition is a component of body builders in order to maintain and repair the tissues so that the function of the body can function properly. Currently in the village broke promontory has run a program providing nutrition food additive in which the program is based as a growth pattern in the village communities are uneven due to the lack of ancestry in consuming foods that are healthy and nutritious. Until now there has been the way of effective work to determine the acceptance of additional nutrients in the village broke headland. This study aims to assist the village in determiningNutritional Supplement acceptance in the village of Tanjung Disconnect. This system is built using a simple method that perogram Additvive weighting that can be done more effectively. Additvive simple weighting method is one method used in decision support seistem prosesperhitungnya by finding the weight values ??for each attribute.
THEORETICAL AND METHODOLOGICAL FUNDAMENTALS OF INTEGRATION OF HIGHER SCHOOL

The article identifies the theoretical and methodological foundations of integration of information and communication pedagogy in the space of higher education; the concept of “information and communication pedagogy” is defined as the basis of a quality educational process in the development of the information society; an attempt is made to explore the theoretical foundations of the process of information management in the field of education by studying the features of the concept of ”information“ as a set of external messages that are received, transformed or stored in the internal system. The author proposes an understanding of the structure and elements of information and communication pedagogy as a complex science. The general nature of informatization of modern society reveals new challenges and gives rise to new trends in the development of pedagogical science. Recently, teachers’ attention has been drawn to the study of various problems related to the information approach to learning, education, school management, because there are powerful information processes of transmission, storage, use, transformation of information. And although the study of various aspects of the connection of information processes with teaching and education is just beginning, nevertheless, information pedagogy is formed as a new branch of pedagogical science that studies information processes in pedagogical phenomen. Characterizing the information approach in pedagogy, we define the conceptual apparatus of information pedagogy. The concept of ”information“ is complex and multifaceted. Analysis of the above general scientific concept showed that with its help it was possible to find common ground in such different, at first glance, processes as cognition of the world by the human brain and adaptation of a living organism to changing living conditions. In this respect, the concept of ”information“ is similar to the concept of ”energy“, which allowed us to consider common views on many processes that previously seemed incompatible
Social media as platforms for information sharing among librarians in Anambra State, Nigeria

The global trend on the use of social mediahas enhanced professional information sharing andnetworking. This development has created spaces forgroupsthat determine who gets informed, updated, inspiredand connectedas members. The librarians in Nigeria are not left out in this strategic phenomenon. This paper evaluated the different social media platformsused by librarians in Nigeria, thebenefits and the challenges. It was an expository researchthat employedfocus group discussion. A total of 12librarians from different institutionsparticipated in the discussion.Interview was also used to elicit data.The findings revealed that WhatsAppwas rated 100% as the number one social media platform used by librarians, followed by Facebookwith 80%, twitter 50%, Instagramand LinkedIn41.7%, respectively while Skype rated 33% and blog 25%. It was also discovered that 50% of the respondents belonged to 6-10 professional groups while 33% and 25% belonged to over 11 professional groups on WhatsAppand Facebook, respectively. Benefits that werederived through the social media platforms are awards, sponsorships, collaboration, updates, networking,supports,exchange of ideas and professional relationship.However,unwanted copy and paste,inactive participation,personal and business advertisements, information explosion anddisregardsto rules and regulations of the platformsaffect their use ofthe social mediagroups.It was therefore, recommended that strict sanctions should be placed on unwanted posts as well as punishment onmembers that err. The implication is that if decorum was not placed on social media platforms, there would be nomeaningful sharing of information and full participation of members.
Unsupervised Transfer Learning for Spatiotemporal Predictive Networks

This paper explores a new research problem of unsupervised transfer learning across multiple spatiotemporal prediction tasks. Unlike most existing transfer learning methods that focus on fixing the discrepancy between supervised tasks, we study how to transfer knowledge from a zoo of unsupervisedly learned models towards another predictive network. Our motivation is that models from different sources are expected to understand the complex spatiotemporal dynamics from different perspectives, thereby effectively supplementing the new task, even if the task has sufficient training samples. Technically, we propose a differentiable framework named transferable memory. It adaptively distills knowledge from a bank of memory states of multiple pretrained RNNs, and applies it to the target network via a novel recurrent structure called the Transferable Memory Unit (TMU). Compared with finetuning, our approach yields significant improvements on three benchmarks for spatiotemporal prediction, and benefits the target task even from less relevant pretext ones.
A hyperlocal mobile web for the next 3 billion users

Despite increasing mobile Internet penetration in developing regions, growing web page complexity and the lack of optimization from remote content providers make the web experience poor in these areas. The high relative bandwidth cost, poor network performance, and lack of relevant local content combine to dampen the demand for the Internet and services it enables. In this paper we propose GAIUS, a content ecosystem enabling efficient creation and dissemination of locally relevant web content. At its core, GAIUS consists of the following innovations: a locally sustainable content ecosystem, and MAML, a web specification language that simplifies web pages to reduce costs and lower barriers for content creation.