Reviewerly/exHarmony huggingface dataset:
Hierarchical Lov\'asz Embeddings for Proposal-free Panoptic Segmentation

Panoptic segmentation brings together two separate tasks: instance and semantic segmentation. Although they are related, unifying them faces an apparent paradox: how to learn simultaneously instance-specific and category-specific (i.e. instance-agnostic) representations jointly. Hence, state-of-the-art panoptic segmentation methods use complex models with a distinct stream for each task. In contrast, we propose Hierarchical Lovasz Embeddings, per pixel feature vectors that simultaneously encode instance- and category-level discriminative information. We use a hierarchical Lovasz hinge loss to learn a low-dimensional embedding space structured into a unified semantic and instance hierarchy without requiring separate network branches or object proposals. Besides modeling instances precisely in a proposal-free manner, our Hierarchical Lovasz Embeddings generalize to categories by using a simple Nearest-Class-Mean classifier, including for non-instance stuff classes where instance segmentation methods are not applicable. Our simple model achieves state-of-the-art results compared to existing proposal-free panoptic segmentation methods on Cityscapes, COCO, and Mapillary Vistas. Furthermore, our model demonstrates temporal stability between video frames.
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Efficient Training of Robust Decision Trees Against Adversarial Examples

In the present day we use machine learning for sensitive tasks that require models to be both understandable and robust. Although traditional models such as decision trees are understandable, they suffer from adversarial attacks. When a decision tree is used to differentiate between a user's benign and malicious behavior, an adversarial attack allows the user to effectively evade the model by perturbing the inputs the model receives. We can use algorithms that take adversarial attacks into account to fit trees that are more robust. In this work we propose an algorithm, GROOT, that is two orders of magnitude faster than the state-of-the-art-work while scoring competitively on accuracy against adversaries. GROOT accepts an intuitive and permissible threat model. Where previous threat models were limited to distance norms, we allow each feature to be perturbed with a user-specified parameter: either a maximum distance or constraints on the direction of perturbation. Previous works assumed that both benign and malicious users attempt model evasion but we allow the user to select which classes perform adversarial attacks. Additionally, we introduce a hyperparameter rho that allows GROOT to trade off performance in the regular and adversarial settings.
Predicting Fraudulent Motor Vehicle Insurance Claims Using Data Mining Model

In recent years, insurance fraud detection has attracted a great deal of concern and attention as the insurance industry has witnessed an increase in the number of fraudulent claims. The aim of this research was to develop a data mining model that that would predict fraudulent insurance claims. The research also seeks to establish the variables with the most predictive power. From a data set with 1,000 claims, 70 percent were used for training the machine using Python Programming Language and the remainder being used to test the accuracy of the algorithms used. Twenty-nine attributes were observed to have influence in predicting the potentially fraudulent behavior of the claims and variables such as policyholder’s hobbies and the extent of damage on the motor vehicle were found to have the most predictive influence. As for the predictive influence, the Decision Tree had the highest accuracy level compared to the other algorithms.
El aula invertida como estrategia de aprendizaje

El presente articulo de investigacion tiene como objetivo sistematizar fundamentos teoricos basicos relacionados con el aula invertida como estrategia de aprendizaje. El estudio se desarrollo en base a una metodologia bibliografica documental que permitio obtener informacion relevante y criterios conceptuales trascendentes sobre el tema, contemplando la revision de diferentes datos de naturaleza cientifica de veinte expertos, que contribuyeron al logro del objetivo planteado. Se establecio los factores que favorecen el aprendizaje utilizando el aula invertida, asimismo se reconocio el soporte de la clase al reves a la labor que realiza el docente y se resalto la importancia del aula invertida para el aprendizaje como ayuda al docente.Palabras clave: Aula invertida, aprendizaje, labor docente, TIC. ABSTRACTThis research article aims to systematize basic theoretical foundations related to the inverted classroom as a learning strategy. The study was developed on the basis of a documentary bibliographic methodology that allowed relevant information and transcendental conceptual criteria on the subject to be obtained, contemplating the review of different data of a scientific nature by twenty experts, who contributed to the achievement of the proposed objective. The factors that favour learning using the inverted classroom were established, and the support of the class was also recognised as being the opposite of the work carried out by the teacher, and the importance of the inverted classroom for learning was highlighted as an aid to the teacher. Keywords: Inverted classroom, learning, teaching work, ICT.
Construction of complete minimal test set for single intra-level bridging and stuck-at faults in reversible circuits

Reversible logic computing is gaining enough interest in the field of low-power circuit design technology. Moreover, the concept of reversible computing is widely used in quantum circuit computation. Therefore, it has motivated researchers to explore reversible logic as a circuit design alternative. Several problems of synthesis and optimisation of the reversible circuits have been reported in the present literature. In this context, the testing plays an important role in the effective performance of these circuits. For detecting all possible faults in the reversible circuits, numerous fault models have been proposed, where many of the proposed fault models common to conventional logic circuits. In this paper, we consider the problem of testing in the NCT or GT library-based reversible circuits with respect to an efficient test set generation for single intra-level bridging faults and single stuck-at faults. The proposed test generation method has been developed based on the concept of one-to-one mapping mechanism (reversible circuit property). Finally, experimental results show that the generated test is capable of 100% fault coverage for both the fault models and also the results are compared with the existing methods for analysing the test set size.
A Case Study on Cloud Computing Architecture Design for Bank Industry

Technology makes life easy. People contact banks in their day to day life activity. And also the banks are committed to serve their customers with the help of currently advanced technology. The aim of a bank is to give consistent and satisfactory banking services for the customers. The use of advanced technology in banking requires sophisticated knowledge of the technology and expertise and a large number of employees are required for implementation and management of that system.Cloud computing makes easy the management of IT infrastructure and the bank sector systems. Cloud service providers provide three basic types of services: infrastructure as a service, software as a service and platform as a service. In a cloud environment, there are concerns in the security and confidentiality of the data placed at the cloud.The main purpose of the study is design the cloud computing architecture for Dashen bank, which will reduce the labor need for managing IT infrastructure and system and enhance the use of technology with the required security verification.The study focused on designing aspects of cloud computing. The study used interview, observation and document analysis to gather the data. The interview was conducted on the selected department and employee of the bank. The observation was at the data center of the Dashen bank using a checklist. All the required data was collected from the head quarter of Dashen bank.The study revealed the management of the bank recognized the potential benefit of cloud computing and has started dealing with companies like Microsoft and IBM to adopt the technology. However, because of the absence of regulatory framework and security concerns, immediate adoption of cloud computing tend to difficult.Future researcher needs to focus on assessing and developing an appropriate security system for bank sector. In addition, appropriate policy and procedure needs to be crafted by the regulatory body like NBE and MICT
Sample-Optimal PAC Learning of Halfspaces with Malicious Noise

We study efficient PAC learning of homogeneous halfspaces in $\mathbb{R}^d$ in the presence of malicious noise of Valiant~(1985). This is a challenging noise model and only until recently has near-optimal noise tolerance bound been established under the mild condition that the unlabeled data distribution is isotropic log-concave. However, it remains unsettled how to obtain the optimal sample complexity simultaneously. In this work, we present a new analysis for the algorithm of Awasthi~et~al.~(2017) and show that it essentially achieves the near-optimal sample complexity bound of $\tilde{O}(d)$, improving the best known result of $\tilde{O}(d^2)$. Our main ingredient is a novel incorporation of a matrix Chernoff-type inequality to bound the spectrum of an empirical covariance matrix for well-behaved distributions, in conjunction with a careful exploration of the localization schemes of Awasthi~et~al.~(2017). We further extend the algorithm and analysis to the more general and stronger nasty noise model of Bshouty~et~al.~(2002), showing that it is still possible to achieve near-optimal noise tolerance and sample complexity in polynomial time.
VALUE SELF-DETERMINATION OF YOUNG PEOPLE IN ONLINE LEARNING CONDITIONS

The article defines the formulation of the problem of the quality of online education and how it affects to the value self-determination of the personality among young people. Referring to the regulatory legal documents of the Republic of Kazakhstan on education, the authors draw attention to the need to develop a full-fledged comprehensively developed personality, which is determined by value attitudes. The data of systematized observations from personal experience of working with youth are presented. The rationale is given for revising the training system in a pandemic and the need for the development of terminal values ​​in students is expressed. With this type of value orientations, students are able to show high-quality knowledge, interest in learning new, systematic and detailed study of lecture material, active involvement in the learning process. As a solution to the problem, it is planned to introduce changes in the systems of rules and traditions in schools and universities. One of the conditions for the effective management of the educational process in an educational institution is the ability and desire of a teacher to be a mentor for students. It also emphasizes the importance of harmonizing the value system of teachers and students and their relationship with the strategic goals of the educational organization.
Introductory lectures to the course of mechanics given by professor S.E. Khaykin in 30-s and 40-s of XX-th century (retrospective pedagogic analysis)

The article is aimed at the retrospective pedagogic analysis of introductory lectures to the course of Mechanics given in 1934, 1937 and 1945 at the department of Physics in MSU by an outstanding educator professor Semen E. Khaykin. It is the frst attempt to carry out academic research of the author’s introductory lectures to the course of Mechanics by professor Khaykin from the Science Museum at the Department of Physics in MSU. The article provides an overview of the contents of each leсture, examines their major peculiarities and reveals specifc educational objectives professor Khaykin addressed in his course. The author of the article analyses the physical phenomena introduced in the lectures and studies the way material arrangement changed with the time. The author compares the series of introductory lectures to reveal the differences and makes an attempt to explain them by the social and political processes that took place in the country in the 30-s and the 40-s of the XXth century and affected the life and academic career of S. E. Khaykin.
Dash Sylvereye: A WebGL-powered Library for Dashboard-driven Visualization of Large Street Networks.

State-of-the-art open network visualization tools like Gephi, KeyLines, and Cytoscape are not suitable for studying street networks with thousands of roads since they do not support simultaneously polylines for edges, navigable maps, GPU-accelerated rendering, interactivity, and the means for visualizing multivariate data. The present paper presents Dash Sylvereye: a new Python library to produce interactive visualizations of primal street networks on top of tiled web maps to fill this gap. Dash Sylvereye can render large street graphs in commodity computers by exploiting WebGL for GPU acceleration. Dash Sylvereye also provides convenient functions to easily import OpenStreetMap street topologies obtained with the OSMnx library. Thanks to its integration with the Dash framework, Dash Sylvereye can be used to develop web dashboards around temporal and multivariate street data by coordinating the various elements of a Dash Sylvereye visualization with other plotting and UI components provided by Dash. We conduct experiments to assess the performance of Dash Sylvereye on a commodity computer in terms of animation CPU time and frames per second. To further illustrate the features of Dash Sylvereye, we also describe a web dashboard application that exploits Dash Sylvereye for the analysis of a SUMO vehicle traffic simulation.
Short-Lived Item Recommendation

In highly dynamic markets (e.g., online news, short videos, and flash sales), new items continuously flow into the markets and fade out quickly. Also, users' preferences shift as they interact with a fast-evolving item pool. These two characteristics of short-lived items make personalized recommendation an essential but challenging task. The absence of user-item interactions for new items brings in the cold-start problem. Recommender systems also need to promptly update user and item representations to incorporate new interactions, so that the systems immediately yield improved recommendations for users throughout the short life-circle of items. To address these challenges, we propose Attention Initialized Dual Recurrent Neural Network (AI-DRNN), a holistic deep learning model that learns effective initial representations of new items via Attention Mechanism, and efficiently updates users/items representations via Dual Recurrent Neural Network to improve recommendation accuracy. We evaluate the proposed model with clickstream data from an online flash sale platform and report its performance in predicting consumer behavior regarding which product a consumer will interact with next and the type of interaction (placing an order or continuing to search). Empirical experiments show that the proposed AI-DRNN performs significantly better in prediction accuracy on cold-started items and overall, compared with the state-of-the-art benchmarks. We further explore the item representations to understand the dynamic updating process of AI-DRNN. We find that AI-DRNN demonstrates interpretability regarding how the algorithm works. Interestingly, we find the proposed AI-DRNN shares the key property of collaborative filtering theory (i.e., predicting a user’s interests by pooling preference information from other users).
New deep learning approaches to domain adaptation and their applications in 3D hand pose estimation

This study investigates several methods for using artificial intelligence to give machines the ability to see. It introduced several methods for image recognition that are more accurate and efficient compared to the existing approaches.
Educational Technology - Concept,Importance and Approaches

Just as the field of education is wide and includes everything from learning, teaching, instructionand training, similarly, educational technical behavior technology instruction, technical audiovisualtechnical system, method of teaching, technology  oriented learning instructionframework and training communication psychology, etc. are included in this way. The field ofeducation technology has become very wide, from clear and school educational processes to thevery information broadcasting and philosophical processes and the field of education technologyhas spread, according to the registry, to identify these objectives and characteristics in the field ofeducation technology, planning the learning environment. The construction of content andorganization of teaching selection of teaching skills, selection of learning tools and learningassessment include future improvement in the development of trends. Educational technologyparticularly affected the teaching process, in which the principles of teaching are being givenmore importance, the role of educational technology need and importance are very useful andeffective in the following areas of work  Teaching theory ,Audio visual equipment selection,Analysis of teaching, Determination of educational objectives, Teaching  learning array selection of compositions, Curriculum development, Analysis of the behavior of thelearner, Assisted in nurturing, Teaching paradigm and Appropriate control by assessmentetc.
TARA: Tracking with Aspect Ratio Adaptability

In visual object tracking (VOT), accurate and robust scale estimation of a target object is a challenging task. The discriminative correlation filter (DCF) is widely employed in VOT due to its high efficiency and accuracy. However, DCF based trackers do not have inherent scale adaptability. Most existing scale estimation methods for DCF based trackers cannot accommodate aspect ratio variation and thus result in inferior performance. In this paper, we propose to address the scale estimation problem and enable aspect ratio adaptability by utilizing a group of DCFs to localize the boundaries of the target object. Deep hierarchical convolutional features are exploited to improve the accuracy and robustness. The resulting system is named TARA: tracking with aspect ratio adaptability. Extensive empirical evaluation using the publicly available tracking benchmark datasets demonstrates that TARA can meet the demand of scale variation challenges and obtains favorable performance compared to state-of-the-art trackers.
Due esempi di lessicografia bilingue in Inghilterra e in Italia a metà del diciannovesimo secolo

EnglishTarver’s Royal Phraseological French-English, English-French Dictionary (vol. 1, 1845; vol. 2, 1849) and Milhouse’s Dizionario Italiano-Inglese, Inglese-Italiano (vol. 1, 1849; vol. 2, 1853) were published at a short distance from each another, respectively in London and in Milan. They are both two-volume bilingual dictionaries which include English, and they partly share their didactic aims: they primarily address learners of French or English respectively as a foreign language. However, their structure and contents differ. Tarver’s dictionary is specialised, as the word ‘phraseology’ shows in the title itself, while Millhouse’s dictionary is a general-purpose one, though with a special focus on English pronunciation. Differences partly depend on their production situational contexts, with reference to French learning in England as opposed to English learning in Italy, and partly on the respective linguistic, lexical, and lexicographic traditions behind their approaches. A brief comparative analysis of the entries hand and main in Tarver’s dictionary and of hand and mano in Millhouse’s one is meant to show if and how their presentation modes and treatment meet their authors’ (and prospective users’) aims. italianoIl dizionario di Tarver, The Royal Phraseological English-French, French-English Dictionary, in due volumi (vol. 1, 1845; vol. 2, 1849), pubblicati a Londra, e quello di Millhouse, Dizionario Italiano-Inglese, Inglese-Italiano, anch’esso in due volumi (vol. 1, 1849; vol. 2, 1853), usciti a Milano, hanno visto la luce in anni molto vicini e con obiettivi didattici parzialmente comuni: sono entrambi dizionari bilingui, in entrambi e presente la lingua inglese e sono primariamente rivolti a chi studia, rispettivamente, il francese o l’inglese come lingua straniera. Al contempo sono diversi per struttura e contenuti: il dizionario di Tarver e specialistico, come evidenziato dalla parola ‘phraseological’ fin dal titolo, mentre quello di Millhouse ha scopi generali, anche se e incentrato sulla pronuncia dell’inglese. Le differenze sono in parte dovute ai contesti in cui sono stati prodotti, legati all’insegnamento del francese in Inghilterra e a quello dell’inglese in Italia, e in parte ad approcci linguistico-lessicali e lessicografici piu o meno legati alle rispettive tradizioni. La breve analisi delle voci hand e main in Tarver e di hand e mano in Millhouse evidenzia come le modalita di presentazione e di trattamento delle entrate rispondono ai rispettivi obiettivi.
Envisioning the Partnership of Human and AI in English Language Teaching and Learning

The perspective of emerging technology could be seen from two different lenses. The view that technology would threaten society as it could take offer some existing jobs, and the view that technology could create opportunities which offer new ways to learn, communicate, share, create, and collaborate (Winthrop, R., Barton, A. & McGivney, E. 2018). It is suggested that the education personnel start building a harmonious partnership with intelligent machines, in the attempt to transform and revolutionize the educational system. The focus of this presentation is to bring your attention to the uses of AI in the area of English Language Teaching (ELT). This topic is far too broad to cover in this short presentation, so I will narrow my focus to the partnership of AI with English teachers and students. Five schools of thought; dystopians, utopians, technology optimists, productivity skeptics and optimistic realists (Knickrehm, M. 2019) is going to be presented first and followed by how AI can be utilized in ELT. The second part, possible partnership of AI with English teachers will be discussed and elaborated. AI as “personal tutor” especially in the area of speaking and writing will be demonstrated and discussed. The last part of this presentation will focus on the possible changes in the process of teaching and learning by utilizing available AI.