Reviewerly/exHarmony huggingface dataset:
SOrT-ing VQA Models : Contrastive Gradient Learning for Improved Consistency

Recent research in Visual Question Answering (VQA) has revealed state-of-the-art models to be inconsistent in their understanding of the world -they answer seemingly difficult questions requiring reasoning correctly but get simpler associated sub-questions wrong.These sub-questions pertain to lower level visual concepts in the image that models ideally should understand to be able to answer the reasoning question correctly.To address this, we first present a gradient-based interpretability approach to determine the questions most strongly correlated with the reasoning question on an image, and use this to evaluate VQA models on their ability to identify the relevant sub-questions needed to answer a reasoning question.Next, we propose a contrastive gradient learning based approach called Sub-question Oriented Tuning (SOrT) which encourages models to rank relevant subquestions higher than irrelevant questions for an <image, reasoning-question> pair.We show that SOrT improves model consistency by up to 6.5% points over existing approaches, while also improving visual grounding and robustness to rephrasings of questions.
Open-Domain Question Answering with Pre-Constructed Question Spaces

Open-domain question answering aims at locating the answers to user-generated questions in massive collections of documents.Retriever-readers and knowledge graph approaches are two big families of solutions to this task.A retriever-reader first applies information retrieval techniques to locate a few passages that are likely to be relevant, and then feeds the retrieved text to a neural network reader to extract the answer.Alternatively, knowledge graphs can be constructed and queried to answer users' questions.We propose an algorithm with a novel readerretriever design that differs from both families.Our reader-retriever first uses an offline reader to read the corpus and generate collections of all answerable questions associated with their answers, and then uses an online retriever to respond to user queries by searching the pre-constructed question spaces for answers that are most likely to be asked in the given way.We further combine one retriever-reader and two reader-retrievers into a hybrid model called R 6 for the best performance.Experiments with large-scale public datasets show that R 6 achieves state-of-the-art accuracy.
Proposal for a common categorisation of IT incidents

This paper presents the proposal for a common categorisation of malicious cyber incidents (cyberâ€‘attacks) and other information technology (IT) incidents formulated by ten financial authorities that are members of the G-7 Cyber Expert Group (CEG) and that represent six of the G-7 jurisdictions. The aim of the proposal is to promote the harmonisation of the various incident reports that authorities require from financial institutions by defining common principles and developing a common taxonomy for incident reporting. The adoption of these common principles and taxonomy should make incident reporting more robust and effective by facilitating a common understanding of incidents, the sharing of information, and the joint management of IT cross-border crises.
RELAYVIO: MOBILE APPLICATION FOR DOCUMENTING DOMESTIC VIOLENCE

RelayVio is designed and developed as android based mobile applications for all users, particularly users of domestic violence victims and their families in Malaysia. The main function of this app is to encourage domestic violence victims to document evidence of violence by way of writing notes, capturing images and recording dates and times of the occurrence. The app also allows victims to sending messages to a domestic violence hotline (Talian Nur), or can directly connect to 999 in the event of an emergency. The app also aims to educate the general public on the signs, dangers and help they can get relating to domestic violence abuse, through the use of animation (3D stop motion). getting information about the act of domestic violence. The method used in the development of mobile applications is ADDIE, which consists of analysis, design, system development, implementation and evaluation. An interview with a sociologist was conducted as an expert review, as well as a usability study of the app. Results show that the majority of the participants agreed that RelayVio app will be able to facilitate victims of domestic violence to gather information and keep documentation of the abuse as a form of evidence against their abusers.
Rooftop layout optimization for PV installation using GIS

In this work, we develop a new modelling process to optimize the PV installation layout on industrial building rooftops; the model searches for maximizing the number of installed PV panels in a defined spot area, characterized by its shape, size, tilt and orientation. The study focuses on areas of latitude between tropics, but is useful for other latitudes. The method is applied to an industrial conglomerate of reference, made up of 34 industries, whose geographical characteristics have been provided by the GIS technique. The proposed model reduces the area of the spot to a very small size (5m x 5m), thanks to the use of the GIS tools, thus increasing the precision of results and making the solution more reliable. The accuracy of the method is over 98.5%. The model takes into account not only the shape and size of the PV panel but also the tilt angle. The model predicts the number of panels as a function of the tilt angle of the panel and the azimuth of the rooftop. The modelling process has allowed obtaining the surface coverage factor of the PV layout for panels facing to the Equator in rooftops with a specific azimuth. The results of the modelling shows that coverage factor increases with the rooftop’s azimuth, having a minimum value of 75% for a rooftop azimuth of 45º and a maximum of 92% for angles of 5º and 85º.
Content Providers’ Secondary Liability: A Social Network Perspective

Recent technological developments allow Internet users to disseminate ideas to a large audience. These technological advances empower individuals and promote important social objectives. However, they also create a setting for speech-related torts, harm, and abuse.One legal path to deal with online defamation turns to the liability of online content providers who facilitate the harmful exchanges. The possibility of bringing them to remove defamatory content and collecting damages from them attracted a great deal of attention in scholarly work, court decisions, and regulations. Different countries established different legal regimes. The United States allows an extensive shield—an overall immunity, as it exempts the liability of content providers in speech torts. This policy is not adopted worldwide. The EU directive outlines a “notice-and-takedown” safe haven. Other countries, such as Canada, use common tort law practices. This article criticizes all of these policy models for being either over or under inclusive.This article makes the case for a context-specific regulatory regime. It identifies specific characteristics of different content providers with their own unique settings, which call for nuanced legal rules that shall provide an optimal liability regime. To that end, the article sets forth an innovative taxonomy: it relies on sociological studies premised on network theory and analysis, which is neutral to technological advances. This framework distinguishes between different technological settings based on the strength of social ties formed in each context. The article explains that the strength of such ties influences the social context of online interactions and flow of information. The strength of ties is the best tool for designing different liability regimes; such ties serve as a proxy for the severity of harm that defamatory online speech might cause, and the social norms that might mitigate or exacerbate speech-related harm.The proposed taxonomy makes it possible to apply a sociological analysis to legal policy and to outline modular rules for content providers’ liability at every juncture. This article does so while taking into account basic principles of tort law, as well as freedom of speech, reputation, fairness, efficiency, and the importance of promoting innovation.
Automatic Graph Generation for E-learning Systems

The subject of the research is one of the ways of updating modern training systems for solving problems of graph theory, namely, automatic generation of graphs. This approach will reduce the load on the training system database and generate tasks for the user in real-time without updating the bank of tasks. In the course of the work, the advantages and disadvantages of this approach were identified. The most suitable method for the implementation of the research was chosen to represent graphs in electronic computers. The requirements for generated graphs and possible ways of implementing these requirements are identified and substantiated. Namely: in the implemented program, simple connected undirected graphs will be generated. We considered an important detail in working with graphs — graph traversal using the “Depth (width) search” algorithm, which in this task is used to check the graph for connectivity. The result of the work is presented — a software implementation of the graph generation algorithm in the C# programming language. In it, graphs are represented by an adjacency list, generated randomly, and checked for connectivity using the DFS (Depth First Search) function. DFS is a software implementation of the Depth First Search algorithm.
PENGARUH MODEL PEMBELAJARAN KOOPERATIF TIPE JIGSAW TEHADAP PRESTASI BELAJAR SISWA KELAS VII PADA MATA PELAJARAN IPS DI SMP NEGERI 2 KEDUNGADEM TAHUN 2019/2020

Abstrak: This study aims to determine whether there is an influence of the use of Jigsaw Cooperative learning models on the learning achievement of social studies subjects on the subject of human activity in meeting the needs of class VII in SMP Negeri 2 Kedungadem in the academic year 2019/2020. The design of this study uses quantitative research methods. Data collection in this study used a test model. The test model used is the pree test and post test given to the experimental group and the control group. The data analysis used is the statistical method t test (t-test). Hypothesis testing results on calculations performed using t test. from testing the results of the hypothesis test, the value of t arithmetic = 5.960 with DK = 48 results obtained ttable = 2.068 with DK = {t | t 2.068} results from Thitung € DK so that H0 is rejected, it can be concluded that the learning model cooperative jigsaw type has a positive influence on student learning outcomes of class VII on social studies subjects the subject of human activity in meeting the needs of SMP Negeri 2 Kedungadem in the academic year 2019/2020.Keyword: Cooperative Model Jigsaw, Learning Achievement
Efficient Search Method for IoT Entities with Similarity Adaptive Estimation

The existing similar entity search method has poor adaptability to the length of the observed sequence, and the data storage overhead in the search process is too large, and the accuracy of the search result is insufficient. To this end, an efficient search method is proposed for the IoT Entity Search with Similarity Adaptive Estimation (SAEES). Firstly, in order to reduce the storage overhead of the entity observation sequence, a lightweight method of segmentation representation of the observation sequence is designed to perform a lightweight segmentation compression representation of the original observation sequence of the entity collected by the sensor. Then, in order to achieve an accurate estimation of the similarity of entities with different observation sequence lengths, an adaptive estimation method for observation sequence similarity is proposed. Finally, by exploiting the designed efficient similar entity search matching method, the exact search matching of the entity is completed according to the estimated entity similarity. The simulation results show that the proposed method can greatly improve the efficiency of similar entity search.
Learning disentangled representations via product manifold projection

We propose a novel approach to disentangle the generative factors of variation underlying a given set of observations. Our method builds upon the idea that the (unknown) low-dimensional manifold underlying the data space can be explicitly modeled as a product of submanifolds. This gives rise to a new definition of disentanglement, and to a novel weakly-supervised algorithm for recovering the unknown explanatory factors behind the data. At training time, our algorithm only requires pairs of non i.i.d. data samples whose elements share at least one, possibly multidimensional, generative factor of variation. We require no knowledge on the nature of these transformations, and do not make any limiting assumption on the properties of each subspace. Our approach is easy to implement, and can be successfully applied to different kinds of data (from images to 3D surfaces) undergoing arbitrary transformations. In addition to standard synthetic benchmarks, we showcase our method in challenging real-world applications, where we compare favorably with the state of the art.
Adversarial Robustness Guarantees for Random Deep Neural Networks

The reliability of deep learning algorithms is fundamentally challenged by the existence of adversarial examples, which are incorrectly classified inputs that are extremely close to a correctly classified input. We explore the properties of adversarial examples for deep neural networks with random weights and biases, and prove that for any $p\ge1$, the $\ell^p$ distance of any given input from the classification boundary scales as one over the square root of the dimension of the input times the $\ell^p$ norm of the input. The results are based on the recently proved equivalence between Gaussian processes and deep neural networks in the limit of infinite width of the hidden layers, and are validated with experiments on both random deep neural networks and deep neural networks trained on the MNIST and CIFAR10 datasets. The results constitute a fundamental advance in the theoretical understanding of adversarial examples, and open the way to a thorough theoretical characterization of the relation between network architecture and robustness to adversarial perturbations.
Creating Engaging Embodied Conversational Agents

Many factors go into creating an ECA that is engaging, appropriate for the intended purpose and educationally beneficial. The persona of the ECA is a major consideration and covers not only the appearance and voice of the ECA but also their responses and mannerisms. Another factor is perceived availability versus interference of the ECA—should it be a constant presence or just appear when needed? In which case, how do we know whether it is appearing often enough or too often, like the infamous Microsoft Clippit (Picard 2004)? Clearly, a range of issues must be considered, and what works for one learner does not necessarily work for everyone, however existing research in psychology and human–computer interaction can provide us with some guidelines.
custom: Implementation of Quality Control System Using Magnetic Image Sensor

This paper depicts an overview and special technique for the recognition, detection, and measuring of the quality of magnetic on materials. It is based on the Hall Effect principle of and signal converter. The board is small but it gives good results in addition to ease of use, less cost, and low power. The magnetic field emitted from the material to be checked is converted to a visual spectrum. This means that magnetic fields can now be seen in real-time, the magnetic sensors used on the tile are some of the most highly sensitive. Visualizing things that are very difficult to normally seen. Because there is so much around that just cannot easily perceive, and how much more important bits of science we would be able to get done if only could easily see them as naturally as seeing things like color. Magnetic field detection in an object into a two-dimensional image will make that important and very useful especially with low cost, power, and easy to use, unlike some costly sensors.
Developing One-Stop Intelligent and Interactive Library Service Systems in Universities

Being a world-class university is always the goal of a university in the world. A first-class university is usually characterized by the broadcasting of knowledge, developing knowledge, globally networked, academic freedom, intellectually stimulating environment, internal self-governance by academics, pursuit cultural and scientific activities and social and civil life. It is important to understand how the library changes its services influence the development of the broadcasting of knowledge, developing knowledge, globally networked, academic freedom, intellectually stimulating environment, internal selfgovernance by academics, pursuit cultural and scientific activities and social and civil life. The library should turn the traditional service to the discipline service and transform its services to support research and innovation, especially on the library service for developing knowledge into a world firstclass. The library services in universities that want to be a world-class should be centered on the establishment of first-class disciplines. And thus an interactive Library service system should be built for better developing firstclass discipline.
Password Protected Secret Sharing from Lattices

A password protected secret sharing (\(\mathsf {PPSS}\)) allows a user to store shares of a secret on a set of L servers, and use a single password to authenticate itself to any subset of k servers at a later time to access the shares and reconstruct the secret. Security of \(\mathsf {PPSS}\) ensures that a coalition of up to \(k-1\) servers cannot reveal any information about the secret message or the password. A related primitive is threshold password authenticated key exchange protocol (\(\mathsf {TPAKE}\)) that allows a user to establish individual authenticated shared secret keys with members of a subset of k out of L servers, using a single password. These primitives are well motivated, with applications such as secure storage of secret keys, and secure group communication using passwords for authentication. In this paper, we give the first construction of these primitives that provide post-quantum security. We prove security of our constructions in concurrent setting, and in the standard model, reducing security to the decisional LWE problem.
Data sharing system describing the COVID-19 epidemic in the Czech Republic

At the time when the COVID-19 pandemic began to pose a dramatic threat to the Czech Republic, a team of experts from the Institute of Health Information and Statistics of the Czech Republic (IHIS CR) and the Institute of Biostatistics and Analyses at the Faculty of Medicine of the Masaryk University (IBA FM MU), under the methodical guidance of the Ministry of Health of the Czech Republic, focused on the design and development of conceptual processing and publication of data. With regard to characteristics of data on the COVID-19 epidemic, it is obviously not possible to publish primary records that are kept in central databases, mainly due to personal data protection as well as the provision of valid and correctly interpreted information. This contribution aims to introduce a comprehensive system of data preparation, processing and visualisation, which is intended for the general public, media, and academic institutions as well as for crisis management. A detailed knowledge of methodical processes employed in epidemiology and healthcare provision is of key importance, and the same applies for the know-how needed for an effective data analysis and the development of software tools. In practice, an interconnection of various teams and specialties has been achieved, namely regional and national methodology specialists in data collection from the Regional Public Health Authorities, specialists reporting positive records, developers of central registries, analysts, developers of web applications, the central management team of the COVID-19 epidemic, and the leadership of the healthcare department. All these efforts have led to regular reporting on the epidemiological situation in the Czech Republic, which consists of static presentations including data sources, online visualisation platforms, open data sets and a secure application programming interface for data distribution on the level of individual regions. All static and interactive reports have been built on the same data basis, which has been continuously developed according to current requirements and the changing epidemiological situation. Open data have indisputably the biggest potential for the future, as they offer a standardised way of either machine-based or manual processing. The entire system of publishing data on the COVID-19 epidemic strives to provide comprehensive and correct information to the above-mentioned target audience.
Pedagogizar la tecnología en tiempos de aislamiento

Living among lights and shadows, we are going through this time of exception, taking the pandemic and its digital educational practices as an excuse to do pedagogy to try to problematize them. It is not a time for balance or projections, we are only trying to think about education in times of confinement together, though respecting the obligatory social distance. The article shows the impact of the preventive protection measures of the pandemic in the educational system and its practices. Confinement poses discontinuities and breakdowns in the educational task when moving to another time / school space, predominantly digital. This scenario touched the educational practices and daily life of the subjects involved in them. The shock generates agreements, disagreements and tensions. The tensions challenge us today under the same terms but with different meanings about the public, the common, the law, equality, the distribution of wealth and knowledge, cultural capital. Finally, equality and rights continue to echo like a dream that yearns to wake up.
Research on the Empirical Study of Blended English Teaching Model Based on Network Platform Promoting Learning by Competition

Abstract With the popularity of the Internet, computer technology has been applied to college education, especially English teaching. Through the network platform (hereinafter referred to as NP), college students can compete in English, including listening, speaking, reading and writing. Through Promoting Learning by Competition (hereinafter referred to as PLBC), students can show their learning knowledge through skill competition, which will better integrate situational teaching and practical teaching. Through the NP, we can gather students from all over the country to participate in the competition, which has solved the basic problem of the number of participants for colleges and universities. By PLBCs, colleges and universities can cultivate practical professionals, which can increase the practicability of students’ English ability. Through blended English teaching model (hereinafter referred to as BETM), colleges and universities can form a teaching system of “teaching, learning, practice and competition”, which will strengthen students’ practical ability and learning efficiency. First of all, this paper analyzes the importance of PLBC. Then, this paper demonstrates the advantages of BETM. Finally, some suggestions are put forward.