Reviewerly/exHarmony huggingface dataset:
CAT: Cross-Attention Transformer for One-Shot Object Detection

Given a query patch from a novel class, one-shot object detection aims to detect all instances of that class in a target image through the semantic similarity comparison. However, due to the extremely limited guidance in the novel class as well as the unseen appearance difference between query and target instances, it is difficult to appropriately exploit their semantic similarity and generalize well. To mitigate this problem, we present a universal Cross-Attention Transformer (CAT) module for accurate and efficient semantic similarity comparison in one-shot object detection. The proposed CAT utilizes transformer mechanism to comprehensively capture bi-directional correspondence between any paired pixels from the query and the target image, which empowers us to sufficiently exploit their semantic characteristics for accurate similarity comparison. In addition, the proposed CAT enables feature dimensionality compression for inference speedup without performance loss. Extensive experiments on COCO, VOC, and FSOD under one-shot settings demonstrate the effectiveness and efficiency of our method, e.g., it surpasses CoAE, a major baseline in this task by 1.0% in AP on COCO and runs nearly 2.5 times faster. Code will be available in the future.
Quantum Simulation of the Agassi Model in Trapped Ions

This work was partially supported by the Consejeria de Economia, Conocimiento, Empresas y Universidad de la Junta de Andalucia (Spain) under Groups FQM-160, FQM-177, and FQM-370, by the Spanish Ministerio de Ciencia e Innovacion, FIS2017-88410-P, PGC2018-095113-B-I00, PID2019-104002GB-C21 and PID2019-104002GB-C22, as well as by the European Commission, H2020-INFRAIA-2014-2015 (ENSAR2) and by European Regional Development Fund (ERDF), ref. SOMM17/6105/UGR. Resources supporting this work were provided by the CEAFMC and Universidad de Huelva High Performance Computer (HPC@UHU) funded by ERDF/MINECO project UNHU-15CE-2848
Contrastive learning of strong-mixing continuous-time stochastic processes

Contrastive learning is a family of self-supervised methods where a model is trained to solve a classification task constructed from unlabeled data. It has recently emerged as one of the leading learning paradigms in the absence of labels across many different domains (e.g. brain imaging, text, images). However, theoretical understanding of many aspects of training, both statistical and algorithmic, remain fairly elusive. In this work, we study the setting of time series -- more precisely, when we get data from a strong-mixing continuous-time stochastic process. We show that a properly constructed contrastive learning task can be used to estimate the transition kernel for small-to-mid-range intervals in the diffusion case. Moreover, we give sample complexity bounds for solving this task and quantitatively characterize what the value of the contrastive loss implies for distributional closeness of the learned kernel. As a byproduct, we illuminate the appropriate settings for the contrastive distribution, as well as other hyperparameters in this setup.
Library Guides: Resources for graduates and alumni: Business, Economics, Law

This guide is for University of Queensland graduates, alumni and future higher degree by research students. It outlines how you might access books, journal articles and other resources after graduation to re-skill, upskill or continue learning.
Boolean Functions with Affine Annihilators

In the article we study boolean functions with affine annihilators. We have obtained results in both, estimating the number of functions under study and defining the relationship between Walsh-Hadamard coefficients of an arbitrary boolean function and its affine annihilator available. The second section of this article focuses on estimating the number of boolean functions with affine annihilators. The value has top and bottom bound. Besides, we have obtained the asymptotic estimate of the number of boolean functions with affine annihilators. The third section studies the Walsh-Hadamard coefficients of boolean functions with affine annihilators. First, we have derived the dependence of the Walsh-Hadamard coefficient on the distance between an arbitrary boolean function and a vector space of the affine function’s annihilators. Based on this result, we have obtained the dependence of distance between an arbitrary boolean function and a set of functions with affine annihilators on the spectrum of given function. Also we have defined the necessary and sufficient condition for the arbitrary boolean function to be with an affine annihilator available. Using the results obtained we bounded an absolute value of Walsh-Hadamard coefficients. Also we suggested a method for boolean equations analysis, which is based on two known methods. Namely, we used an analysis using annihilators and an analysis using linear analogs. We have obtained an estimate of the success probability of the suggested method for an arbitrary boolean function. Also we proved that bent functions are the most resistant to this analysis. The results obtained can be used in analysis of boolean equations. Also obtained dependences can be used, for instance, to study bent functions and algebraic immunity of boolean functions.
Ethics and humanities education in the era of global processes

The article shows the importance of teaching ethics for the development of humanitarian education, as well as reveals the problematic issues of contemporary ethical knowledge. The authors consider the issue of the influence of digital technologies on remote communication of people, analyzing in this regard the network communications. It is shown that they correspond to morality, in which the communication of people is supposed to be unlimited by formal institutions, and is characterized by a broad discourse. The used methodology is based on the ethics of discourse, works on virtue ethics, modern brain research, neurophilosophy, and evolutionary ethics. Besides, the authors show the importance of virtue ethics and demonstrate that neurophilosophy and evolutionary ethics are unable to explain the entire variety of human behavior, in particular, to explain why a person is able to set himself supertasks. The article analyzes the development specifics of global processes that often cause the transformation of moral behavior motives. The novelty of the research consists in demonstrating the combination of ethical (humanitarian) and natural science knowledge, which corresponds to the development stage of contemporary science, which is characterized as post-nonclassical.
Interaction of models with real objects as a way to improve augmented reality

Unlike a purely virtual world, it is much more difficult for the user to believe in the reality of augmented reality objects. Due to the lack of proper lighting or shadows, the object may appear to be floating in the air, detached from the real objects around it. One obvious problem with augmented reality is that a virtual object appears remote from the real object, but it still appears in front of it. An approach is proposed that will allow the interaction of real and virtual objects. Both real and virtual objects can be moved and rotated in the scene, preserving overlaps. A virtual object can also be placed in front of or behind a real object relative to the camera, which decides whether or not to overlap. The proposed algorithm consists of five stages and the system architecture. The evaluation is based on five defined criteria. Results and ways of improvement for the future research are presented.
Optimizing Transformations of Dynamic Languages Compiled to Intermediate Representations

Compiling dynamic languages to stack-based intermediate representations used in platforms such as. NET and Java proved to be useful, mainly due to the enhanced interoperability and security. To produce the best intermediate code possible, current approaches perform a detailed flow-sensitive type analysis of the original code and utilize its results to choose the most efficient operations of the target platform. As known from the traditional compilers, the standard way to further increase program performance is using a set of transformations, which increase its efficiency while preserving its semantics. However, these transformations are not directly usable in the compilers of dynamic languages, because these operate on a higher level of abstraction; moreover, dynamic languages pose specific challenges, such as those stemming from weak typing. In this paper we propose a set of transformations which fit into the architecture of a dynamic language compiler, fitting well together with the type analysis. For evaluation purposes, we implemented them to Peachpie, a compiler of PHP to. NET. Applying the transformations during compilation of WordPress resulted in improvement of 0.6 % in the generated assembly size, 1.8% in CPU time and 0.8% in memory consumption.
An Explosion Based Algorithm to Solve the Optimization Problem in Quadcopter Control

This paper presents an optimization algorithm named Random Explosion Algorithm (REA). The fundamental idea of this algorithm is based on a simple concept of the explosion of an object. This object is commonly known as a particle: when exploded, it will randomly disperse fragments around the particle within the explosion radius. The fragment that will be considered as a search agent will fill the local space and search that particular region for the best fitness solution. The proposed algorithm was tested on 23 benchmark test functions, and the results are validated by a comparative study with eight well-known algorithms, which are Particle Swarm Optimization (PSO), Artificial Bee Colony (ABC), Genetic Algorithm (GA), Differential Evolution (DE), Multi-Verse Optimizer (MVO), Moth Flame Optimizer (MFO), Firefly Algorithm (FA), and Sooty Tern Optimization Algorithm (STOA). After that, the algorithm was implemented and analyzed for a quadrotor control application. Similarly, a comparative study with the other algorithms stated was done. The findings reveal that the REA can yield very competitive results. It also shows that the convergence analysis has proved that the REA can converge more quickly toward the global optimum than the other metaheuristic algorithms. For the control application result, the REA controller can better track the desired reference input with shorter rise time and settling time, lower percentage overshoot, and minimal steady-state error and root mean square error (RMSE).
Technology in the educational field before COVID: a commitment to MOOCs as a training strategy in the university context

Although the development of technology in the educational field has been promoting progressive changes in teaching methodology, especially at the university level, in the last quarter century, it is due to the pandemic that plagues humanity (COVID-19) when from the academic context there has been the urgent need to rethink all the operation and non-contact possibilities based on the Internet through synchronous or asynchronous teaching. Thus, with the development of MOOCs, great possibilities have been seen to meet educational demands in a non-face-to-face way, enabling individualized and open attention to the group of students who present cases and varied needs. In the present work, we intend to carry out an approach to MOCCs in terms of conceptualization, characteristics, elements and typologies, deepening their relationship with educational care in the pandemic moment that surrounds us. To finish, we will make a tour of various MOCC aggregators / search engines and we will copy several of them to demonstrate their educational potential.
Optimal Designs for Parameter Estimation and Model Tests

Along with the automation of our electronic equipment life, security problems become a lot of important and necessary. There square measure queries asked in our existence like “is this the correct person to be allowed to access the system?”, “is this the licensed person to perform such action?”, and “does this person belong to the current country?” there have been 2 strategies for responsive this questions: 1st one supported “what you have” and referred to as (knowledge factors), like ID cards, and therefore the other supported “what you know” and referred to as (ownership factors), but each strategies will be borrowed or traced or purloined, therefore users have to be compelled to carry several IDs and study loads of passwords.
Fuzzy Logic Support for Requirements Engineering

As software projects are getting more and more complicated, the greatest risks in software engineering are most probably emanating from the limitations of an inexperienced developer in imagining the boundaries of an abstract artefact that does not even exist yet. Requirement engineering is extremely important in a software development project, yet inherently difficult. Requirements can be redundant, optional, overlapping and even contradictory. They come from different sources and often are represented in an informal way. Requirements also are followed throughout the development process and can be partially met in different degrees in various stages of the process. In this work we advocate a fuzzy logical model for following the requirements and their fulfillment. We also present the logical design of a requirements knowledge base manager that we are building in order to facilitate requirement-aware rapid development tools.
PBL과 메이커 교육을 적용한 가정과 예비교사를 위한 의류학 실습 수업 개발

The aim of this research is to develop a clothing and textiles studio course for preservice home economics teachers applying principles of Project-Based Learning (PBL) and maker education to equip future teachers with the ability to nurture creativity among adolescents. The studio course was developed in the following stages: analysis, design, development, implementation, and evaluation. We concluded that the resulting course met the following objectives extracted from the 2015 revised curriculum of home economics subjects: to promote creative and environmentally-friendly fashion design and styling abilities, gain the ability to use makerspace tools, understand flat pattern making and sewing processes, and develop creative thinking, aesthetic sense, and communication skills. Furthermore, the educational effects of PBL and maker education were confirmed through student comments on the course. Students mentioned the practicality of the material in their actual lives along with their enhanced integration of the subject material, self-directedness, aesthetic sense, ability to learn through trial and error, collaboration and communication, and sharing. Based on results from the implementation and evaluation stages, a clothing and textiles studio course should include the following modules: introduction of terms and tools, submission and sharing of clothing reformation and upcycling techniques, introduction to hand sewing, pouch making, heat-transfer printing, 3D printing, mask making, hat making, vest making, and the final team project on fashion styling. It is important for instructors to provide detailed guidelines on selecting personas for styling, looking for available materials, and selecting materials online.
Invariants for EA- and CCZ-equivalence of APN and AB functions.

An (n,m)-function is a mapping from ${\mathbb {F}_{2}^{n}}$ to ${\mathbb {F}_{2}^{m}}$ . Such functions have numerous applications across mathematics and computer science, and in particular are used as building blocks of block ciphers in symmetric cryptography. The classes of APN and AB functions have been identified as cryptographically optimal with respect to the resistance against two of the most powerful known cryptanalytic attacks, namely differential and linear cryptanalysis. The classes of APN and AB functions are directly related to optimal objects in many other branches of mathematics, and have been a subject of intense study since at least the early 90’s. Finding new constructions of these functions is hard; one of the most significant practical issues is that any tentatively new function must be proven inequivalent to all the known ones. Testing equivalence can be significantly simplified by computing invariants, i.e. properties that are preserved by the respective equivalence relation. In this paper, we survey the known invariants for CCZ- and EA-equivalence, with a particular focus on their utility in distinguishing between inequivalent instances of APN and AB functions. We evaluate each invariant with respect to how easy it is to implement in practice, how efficiently it can be calculated on a computer, and how well it can distinguish between distinct EA- and CCZ-equivalence classes.
A SURVEY ON MEASURING REUSABILITY, MODULARITY AND EXTENSIBILITY ON COUPLING AND COHESION

This paper presents a research study on how to enhance performance of a system by using extensibility, reusability and modularity. It also describes how they support to increase the system’s quality by applying reusability concept and how the changes are adapted by using modularity and extensibility. It also explains elaborately how to measure reusability, modularity and extensibility in coupling and cohesion and how to increase Cohesion and decrease Coupling.
COVID-19 School Closures and the Principles of Proportionality and Balancing

Abstract Even though COVID-19 has an extremely low crude mortality rate among children, drastic measures to combat the disease significantly infringed the fundamental human rights of millions of children to education and protection. This article examines whether COVID-19-related school closures and the suspension of necessary measures of protection for special needs and vulnerable children were justifiable derogations from covenant obligations and international human rights law. The researcher assessed relevant treaty and covenant obligations of state parties and affirms what international human rights law determines regarding the justifiable limitation of human rights. The article centers on whether the regulations to combat the COVID-19 pandemic are inter alia legitimate, adequate, necessary and proportionate stricto sensu . It argues that the limitation of fundamental human rights must achieve benefits that are proportional to the cost of the limitation, and that the infringement will not be considered proportional if there are less restrictive but equally effective means to achieve the same purpose. Ultimately, it highlights that education and the necessary measures of protection for all children – but specifically those children with special needs and children belonging to vulnerable groups – should be one of the highest priorities in any national strategy to reopen society.
Role of Libraries in Teacher Education of Manipur

Education of teacher is considered as a significant input for quality improvement of education system. Teacher is the backbone of delivery system of an educational enterprise. For this reason, pre-service and in-service teacher education programmes are conducted for orientation and reorientation of teachers to become efficient and competent ones. In this 21st Century of Digital Era the role of libraries in teacher education is tremendous. Application of ICT, library automation and wide range of services provided by libraries in teacher education will bring another revolution in nearby future in learning and teaching process. Lack of finance, resource and aware of library services are big challenges in giving proper library services to the teacher educational institutional in Manipur.
NILAI MORAL DALAM NOVEL MATA DI TANAH MELUS KARYA OKKY MADASARI DAN IMPLIKASINYA PADA PEMBELAJARAN SASTRA DISEKOLAH DASAR

This study aims to determine the moral values contained in the Novel Mata di Tanah Melus by OkkyMadasary. The method used in this study is data analysis with concentrated data collectiontechniques in the form of quotations containing moral values. The validity check of this research datauses source triangulation. Data is analyzed through the steps of data collection, data reduction, datapresentation, and data collection.The results of this study indicate that in the novel Mata di TanahMelus byOkky Maddasary there are three types of moral values namely, individual moralvalues,social moral values, and religious moral values. The dominant moral values in the novel Mata diTanah Melus are social moral values with an percentage of individual values 37%, social moralvalues 46%, and religious moral values 17%. The contents of the story in the novel Mata di TanahMelus illustrate the interaction of the characters with other characters who are only known in an areaof the island outside Indonesia, namely in Tanah Melus. Moral values in the novel can be replicatedin the teaching of elementary school literature. Teachers can teach moral values contained in novelsaccording to the lesson plans in school. Through novels and other story books children will find iteasier to capture what they learn
An Examination of Fairness of AI Models for Deepfake Detection

Recent studies have demonstrated that deep learning models can discriminate based on protected classes like race and gender. In this work, we evaluate bias present in deepfake datasets and detection models across protected subgroups. Using facial datasets balanced by race and gender, we examine three popular deepfake detectors and find large disparities in predictive performances across races, with up to 10.7% difference in error rate between subgroups. A closer look reveals that the widely used FaceForensics++ dataset is overwhelmingly composed of Caucasian subjects, with the majority being female Caucasians. Our investigation of the racial distribution of deepfakes reveals that the methods used to create deepfakes as positive training signals tend to produce "irregular" faces - when a person's face is swapped onto another person of a different race or gender. This causes detectors to learn spurious correlations between the foreground faces and fakeness. Moreover, when detectors are trained with the Blended Image (BI) dataset from Face X-Rays, we find that those detectors develop systematic discrimination towards certain racial subgroups, primarily female Asians.
Weakly Supervised Action Selection Learning in Video

Localizing actions in video is a core task in computer vision. The weakly supervised temporal localization problem investigates whether this task can be adequately solved with only video-level labels, significantly reducing the amount of expensive and error-prone annotation that is required. A common approach is to train a frame-level classifier where frames with the highest class probability are selected to make a video-level prediction. Frame level activations are then used for localization. However, the absence of frame-level annotations cause the classifier to impart class bias on every frame. To address this, we propose the Action Selection Learning (ASL) approach to capture the general concept of action, a property we refer to as "actionness". Under ASL, the model is trained with a novel class-agnostic task to predict which frames will be selected by the classifier. Empirically, we show that ASL outperforms leading baselines on two popular benchmarks THUMOS-14 and ActivityNet-1.2, with 10.3% and 5.7% relative improvement respectively. We further analyze the properties of ASL and demonstrate the importance of actionness. Full code for this work is available here: https://github.com/layer6ai-labs/ASL.
LITERATURE SURVEY OF VARIOUS CHATBOTS

A chatbot is AI computer software that can act as a conversation through textual or auditory methods. The core of chatbots analyses a customer’s data using the artificial intelligence which integrates the response with them. Different tasks can be replaced with AI-powered bots as they are much more powerful—and are capable of performing multiple tasks at once. Machine Learning techniques are basically used in the process of understanding the input that we get from the user and replying to the user. Natural language processing allows a bot to have a conversation as naturally as possible. The ideal interaction between user and chatbot is a balanced mix of Innovative technology and human Intervention