Reviewerly/exHarmony huggingface dataset:
APPLICATION OF SMARTPHONE BASED QUIZIZZ APPLICATIONS AS A LEARNING MEDIA IN THE ENVIRONMENT OF UNIVERSITAS PGRI MADIUN

This research stems from the learning that is applied to the accounting and economic education environment of PGRI Madiun University which tends to be still content transmission and teacher centered. These learning activities resulted in students being limited in developing creativity, understanding the concepts, and students still using their cellphones for learning while in class so that student learning outcomes are still not optimal. The main objective of this research is to apply smartphone-based quizizz applications as learning media in the PGRI Madiun University environment. The method used in this research is descriptive-qualitative. This research was conducted at the University of PGRI Madiun. The subject of this study is a study program in accounting education and economic education. The results showed that in general students were positive about the application of smartphone-based quizizz applications as learning media. The application of smartphone-based quizizz applications as a learning media as a learning media has increased the effectiveness and efficiency of time in learning and improved information technology skills, discipline in completing lecture tasks, and facilitates communication with lecturers supporting the courses concerned
Providing Uncertainty-Based Advice for Deep Reinforcement Learning Agents (Student Abstract)

The sample-complexity of Reinforcement Learning (RL) techniques still represents a challenge for scaling up RL to unsolved domains. One way to alleviate this problem is to leverage samples from the policy of a demonstrator to learn faster. However, advice is normally limited, hence advice should ideally be directed to states where the agent is uncertain on the best action to be applied. In this work, we propose Requesting Confidence-Moderated Policy advice (RCMP), an action-advising framework where the agent asks for advice when its uncertainty is high. We describe a technique to estimate the agent uncertainty with minor modifications in standard value-based RL methods. RCMP is shown to perform better than several baselines in the Atari Pong domain.
Database Reconstruction from Noisy Volumes: A Cache Side-Channel Attack on SQLite

We demonstrate the feasibility of database reconstruction under a cache side-channel attack on SQLite. Specifically, we present a Flush+Reload attack on SQLite that obtains approximate (or "noisy") volumes of range queries made to a private database. We then present several algorithms that, taken together, reconstruct nearly the exact database in varied experimental conditions, given these approximate volumes. Our reconstruction algorithms employ novel techniques for the approximate/noisy setting, including a noise-tolerant clique-finding algorithm, a "Match &amp; Extend" algorithm for extrapolating volumes that are omitted from the clique, and a "Noise Reduction Step" that makes use of a closest vector problem (CVP) solver to improve the overall accuracy of the reconstructed database. The time complexity of our attacks grows quickly with the size of the range of the queried attribute, but scales well to large databases. Experimental results show that we can reconstruct databases of size 100,000 and ranges of size 12 with error percentage of 0.11 % in under 12 hours on a personal laptop.
Gambling, the sure way of getting nothing for something : A study of mixed methods

Date:                        2019-06-11 Level: Master’s thesis in Business Administration, 15 cr Institution: School of Business, Society and Engineering, Mala ...
Corrigendum: Corrigendum to ‘Learning manual assembly through real-time motion capture for operator training with augmented reality”

The authors regret that <The co-author Riccardo Tronconi is not included in the author list. Please add his name as co-author of this paper> The authors would like to apologise for any inconvenience caused.
Privacy-Preserving Dark Pools

A dark pool is a private forum for trading financial instruments such as equities and derivatives. The service is offered to traders, often representing large financial institutions, who aim to make large trades without telegraphing their intentions in a public venue such as the New York Stock Exchange or NASDAQ. Internally, the dark pool operates just like a public exchange, but the order book, a list of offers to buy and sell, is not visible to any of the participants. Only when matching orders are found the trade is executed and reported externally. Because the large orders are not visible to others, the risk of significant price moves is reduced. The operators of dark pools are trustworthy, but traders are notoriously suspicious. Traders are concerned about any leakage'' of information that might alert others to their intentions and cause price moves against them. The operator sees all orders posted by all participants, including sensitive information such as the volume of the order and the bid or ask price. Because the operator of the dark pool is usually a large financial institution with its own investments in the assets being traded, it may have conflicts of interest with the clients it serves in the dark pool. While such conflicts are mitigated by law and regulation, they continue to exist. We propose a new mechanism that reduce the need of traders to trust the operator of the dark pool. By adopting cryptographic techniques, we achieve a fully private and secure marketplace where sellers and buyers interact with the operator without exposing the volumes or prices of their orders to the operator or to any other counter party. These values remain secret until a matching order is found, and only afterward it will be revealed publicly.
Implementasi XML Encryption Pada Data Kursus English Communitative

Communitative English is the first non-language institution in the city of Pontianak, which was founded in 1975. Communitative English has a variety of classes starting from the beginner class, classes specifically for employees used for the TOEFL class. Communitative English has not implemented web technology in the process of information dissemination and registration making it felt inefficient. The research that I use and in this study is a case study using Research and Development methods. Data collection techniques used were interviews, observation and literature studies. In addition, primary data is also used from interviews and observations and secondary data obtained from data and journals from previous research. The design method used is Rapid Application Development (RAD) with Unified Modeling Language (UML) system modeling tools obtained based on data from using case diagrams, activity diagrams, sequence diagrams and class diagrams. The programming language used is PHP and MySQL as a database. The results of this study will produce a data security system using xml encryption that can be used to manage selective communicative English data distributed online.
Viktiga telefonnummer i coronapademin - Lerums Kommun

Har har vi samlat viktiga telefonnummer som du kan ringa om du har fragor om coronaviruset eller ar orolig for dig sjalv eller nagon annan.
Online-Efficient Interval Test via Secure Empty-Set Check

In the age of information and communications technology (ICT), not only collecting data but also using such data is provided in various services. It is necessary to ensure data privacy in such services while providing efficient computation and communication complexity. In this paper, we propose the first interval test designed according to the notion of online and offline phases by executing our new empty-set check. Our protocol is proved to ensure both server and client privacy. Furthermore, neither the computational complexity of a client in the online phase nor the communicational complexity from a server to a client depends on the size of the set. As a result, even in a practical situation in which one server receives requests from numerous clients, the waiting time for a client to obtain the result of an interval test can be minimized.
Equational Reasoning for MTL Type Classes

Ability to use definitions occurring in the code directly in equational reasoning is one of the key strengths of functional programming. This is impossible in the case of Haskell type class methods unless a particular instance type is specified, since class methods can be defined differently for different instances. To allow uniform reasoning for all instances, many type classes in the Haskell library come along with laws (axioms), specified in comments, that all instances are expected to follow (albeit Haskell is unable to force it). For the type classes introduced in the Monad Transformer Library (MTL), such laws have not been specified; nevertheless, some sets of axioms have occurred in the literature and the Haskell mailing lists. This paper investigates sets of laws usable for equational reasoning about methods of the type classes MonadReader and MonadWriter and also reviews analogous earlier proposals for the classes MonadError and MonadState. For both MonadReader and MonadWriter, an equivalence result of two alternative axiomatizations in terms of different sets of operations is established. As a sideline, patterns in the choice of methods of different classes are noticed which may inspire new developments in MTL.
Deep End-to-end Network for 3D Object Detection in the Context of Autonomous Driving

Nowadays, autonomous driving is a trending topic in the automotive ﬁeld. One of the most crucial challenges of autonomous driving research is environment perception. Currently, many techniques achieve satisfactory performance in 2D object detection using camera images. Nevertheless, such 2D object detection might be not suﬃcient for autonomous driving applications as the vehicle is operating in a 3D world where all the dimensions have to be considered. In this thesis a new method for 3D object detection, using deep learning approach is presented. The proposed architecture is able to detect cars using data from images and point clouds. The proposed network does not use any hand-crafted features and is trained in an end-to-end manner. The network is trained and evaluated with the widely used KITTI dataset. The proposed method achieves an average precision of 81.38%, 67.02%, and 65.30% on the easy, moderate, and hard subsets of the KITTI validation dataset, respectively. The average inference time per scene is 0.2 seconds.
The Conversational Strategies between a Korean-American Beauty Vlogger and Beauty Enthusiasts about Beauty Tutorial

YouTube vlogs are commonly known as a one-way communication platform since they are featured by a single speaker who talks to the camera individually. However, this study analyzes the conversation within two beauty vlogs which have two speakers respectively which are the YouTube channel’s owner and her guests. The study aimed to identify what and how the conversational strategies used by the beauty vloggers. The findings showed that all of the strategies, except swearing and taboo language, were used by all beauty vloggers. By focusing on two vlogs, this qualitative study applied the theory of conversational strategies that are proposed by Coates (2013). These strategies are minimal responses, hedges, tag questions, question, command and directives, swearing and taboo language, and also compliments. Moreover, the study concluded the fact that the usage of these strategies is related closely to the context of the conversation.
Interactive methods for teaching russian

Modernization of education requires not only the active saturation of educational institutions with technology, but also fundamentally changes educational priorities, changes approaches to building a paradigm in general, and building individual educational trajectories, in particular. Significant changes in education are associated with the active introduction of interactive teaching methods in the educational process.
Distinguishing Black Hole and Naked Singularity in MOG via Inertial Frame Dragging Effect

We analyze the generalized spin precession of a test gyroscope around a stationary spacetime i.e. for Kerr-MOG black hole~(BH) in scalar-tensor-vector gravity or modified gravity~(MOG). A detailed study of generalized spin frequency has been done for \emph{non} extremal Kerr-MOG BH, \emph{extremal} Kerr-MOG BH and \emph{naked singularity~(NS)} in comparison to non-extremal BH, extremal BH, and NS of Kerr spacetime. The generalized spin frequency that {we have} computed could be expressed in terms of {the} BH mass parameter, the angular momentum parameter, and the MOG parameter. Moreover, we differentiate the non-extremal BH, extremal BH, and NS via computation of the said precession frequency. The Lense-Thirring~(LT) frequency {can} obtain from generalized spin frequency by taking the limit as $Ω=0$ i. e. {when the} angular frequency is set to zero limit. Furthermore, we compute the LT frequency for various {values of} angular coordinates i.e. starting from polar to {the} equatorial plane. We show that the LT frequency diverges at the horizon for extremal BH. Finally, we study the accretion disk physics by computing three epicyclic frequencies namely the Keplerian frequency, {the} radial epicyclic frequency and {the} vertical epicyclic frequency. We also compute the periastron frequency and nodal frequency. With the aid of these frequency profiles, {one} can distinguish three compact objects i. e. \emph{non-extremal BH, extremal BH} {and} \emph{NS}.
IMPORTANCE OF MATHEMATICAL DISCIPLINES IN THE STRUCTURE OF EDUCATIONAL PROGRAMS OF HIGHER EDUCATION WITH INTRODUCTION OF FSES 3++

The analysis of the importance of mathematical disciplines in the structure of the main professional educational programs of higher education was carried out on the example of undergraduate programs implemented in SSUGT in the frames of FSES 3++.
The importance of monitoring vergence eye movements for solutions using virtual technologies

Eyesight monitoring systems are of particular interest to virtual technology research teams and concern mainly three key aspects: physiological, technical and functional. The first one is to solve the so-called conflict of vergence and accommodation. In contrast to typical gaming applications, e.g. vision therapy requires the ability to smoothly transfer attention between the points of near and far. The technical aspect is primarily the search for new measurement methods, which is particularly important in the case of mobile goggles with limited computing capabilities of the processor. The last aspect concerns the possibility of creating effective HMI (Human Machine Interface) solutions. Full Text: PDF ReferencesJ. D. Bayliss et. al., "Lazy Eye Shooter: a Novel Game Therapy for Visual Recovery in Adult Amblyopia", 2012 IEEE International Games Innovation Conference CrossRef Y. L. Chen., L. Shi, J. W. L. Lewis, M. Wang, "Infrared Retinoscopy", Photonics 2014, 1, 303-322. CrossRef W. Fuhl, M. Tonsen, A. Bulling, and E. Kasneci, "Pupil detection for head-mounted eye tracking in the wild: an evaluation of the state of the art," Mach. Vis. Appl., vol. 27, no. 8, pp. 1275-1288, 2016 CrossRef N. Sarkar, D. Strathearn, G. Lee, M. Olfat, A. Rohani and R. R. Mansour, "A large angle, low voltage, small footprint micromirror for eye tracking and near-eye display applications", 2015 Transducers - 2015 18th International Conference on Solid-State Sensors, Actuators and Microsystems (TRANSDUCERS), Anchorage, AK, 2015, pp. 855-858, CrossRef
The LoCA Regret: A Consistent Metric to Evaluate Model-Based Behavior in Reinforcement Learning

Deep model-based Reinforcement Learning (RL) has the potential to substantially improve the sample-efficiency of deep RL. While various challenges have long held it back, a number of papers have recently come out reporting success with deep model-based methods. This is a great development, but the lack of a consistent metric to evaluate such methods makes it difficult to compare various approaches. For example, the common single-task sample-efficiency metric conflates improvements due to model-based learning with various other aspects, such as representation learning, making it difficult to assess true progress on model-based RL. To address this, we introduce an experimental setup to evaluate model-based behavior of RL methods, inspired by work from neuroscience on detecting model-based behavior in humans and animals. Our metric based on this setup, the Local Change Adaptation (LoCA) regret, measures how quickly an RL method adapts to a local change in the environment. Our metric can identify model-based behavior, even if the method uses a poor representation and provides insight in how close a method's behavior is from optimal model-based behavior. We use our setup to evaluate the model-based behavior of MuZero on a variation of the classic Mountain Car task.
QPSO-CD: Quantum-behaved Particle Swarm Optimization Algorithm with Cauchy Distribution

Motivated by particle swarm optimization (PSO) and quantum computing theory, we have presented a quantum variant of PSO (QPSO) mutated with Cauchy operator and natural selection mechanism (QPSO-CD) from evolutionary computations. The performance of proposed hybrid quantum-behaved particle swarm optimization with Cauchy distribution (QPSO-CD) is investigated and compared with its counterparts based on a set of benchmark problems. Moreover, QPSO-CD is employed in well-studied constrained engineering problems to investigate its applicability. Further, the correctness and time complexity of QPSO-CD are analysed and compared with the classical PSO. It has been proven that QPSO-CD handles such real-life problems efficiently and can attain superior solutions in most of the problems. The experimental results showed that QPSO associated with Cauchy distribution and natural selection strategy outperforms other variants in the context of stability and convergence.
FORMING OF A PROFESSIONAL IDEAL WHEN TRAINING LIBRARIANS

An ideal is a significant component of the processes of self-education and professional formation, constituting the basis of an individual’s value consciousness and determining the life strategy of a student – the future specialist. Professional ideals form the student’s worldview and professional orientation, which is expressed in his behavior and attitude to reality. In psychological and pedagogical literature, the professional ideal is interpreted today as an image of professional excellence, as the supreme desired goal, idea and dream. Recently, we have witnessed a significantly increased interest of the foreign and domestic scientific community in the problem of the professional ideal and the features of its formation, which is associated with the general vectors of social development – modernization and democratization of all its spheres. Empirical studies of students’ professional values – that are engaged in the library field of preparation – show that traditionally the book is considered as the main value object, and often many of them explain their professional choice by the fact that they love the book, they cannot imagine their lives without it. Moreover, the undoubted general cultural value – the book – for the student – the future librarian is not only an object of reading, but also an important object of professional activity around which communication with the reader takes place, the meaning and purpose of the library. Reading is, in most cases, the necessary element of the student’s professional ideal. The future librarian should be an active, qualified reader, involved in book culture since his childhood, who cannot imagine his life without a home library, probably collected by his parents or, quite the reverse, begun to be formed by him. Broad reading interests, good literary taste, knowledge of literature and bibliography are the main characteristics of the future specialist in the library field. Students’ awareness of the essence of professional values, formation of their set and certainty in professional ideals contribute to the valuebased behavior and professional orientation, which lead to adequate ideas about the kernel and specifics of professional activities.
Instruction Filters for Mitigating Attacks on Instruction Emulation in Hypervisors

Vulnerabilities in hypervisors are crucial in multi-tenant clouds and attractive for attackers because a vulnerability in the hypervisor can undermine all the virtual machine (VM) security. This paper focuses on vulnerabilities in instruction emulators inside hypervisors. Vulnerabilities in instruction emulators are not rare; CVE-2017-2583, CVE-2016-9756, CVE-2015-0239, CVE-2014-3647, to name a few. For backward compatibility with legacy x86 CPUs, conventional hypervisors emulate arbitrary instructions at any time if requested. This design leads to a large attack surface, making it hard to get rid of vulnerabilities in the emulator.
Reading Between the Demographic Lines: Resolving Sources of Bias in Toxicity Classifiers

The censorship of toxic comments is often left to the judgment of imperfect models. Perspective API, a creation of Google technology incubator Jigsaw, is perhaps the most widely used toxicity classifier in industry; the model is employed by several online communities including The New York Times to identify and filter out toxic comments with the goal of preserving online safety. Unfortunately, Google's model tends to unfairly assign higher toxicity scores to comments containing words referring to the identities of commonly targeted groups (e.g., "woman,'' "gay,'' etc.) because these identities are frequently referenced in a disrespectful manner in the training data. As a result, comments generated by marginalized groups referencing their identities are often mistakenly censored. It is important to be cognizant of this unintended bias and strive to mitigate its effects. To address this issue, we have constructed several toxicity classifiers with the intention of reducing unintended bias while maintaining strong classification performance.
BOOK INDUSTRY OF SIBERIA PROGRESS IN THE XX – THE BEGINNING OF THE XXI CENT.: OVERVIEW OF RESEARCHES

Socio-economic transformations taking place in the XXI century affect all spheres of science, education, culture and production, including book industry. The article substantiates the necessity of studying the innovative potential of book industry of Siberia, the dynamics of its main industries development – book publishing and printing. The innovative potential of book industry is defined as the ability of book production institutions to implement effectively the specific tasks of preparing, producing and replicating print and electronic publications with the maximum use of available resources. Conception of current processes of regional publishing business functioning is impossible without studying the history of regional book publishing, Siberian printing industry, specifics of publishing houses activities in the XX cent. and in the first decades of the XXI cent. for to accentuate attention on the book industry innovative component, perspectives of material, technical, infrastructural, human, financial and other resources development under the conditions of impending global economic crisis, provoked as well by pandemia entailed by coronavirus infection spreading. Further study, analysis and characteristics of each resource individually are necessary for to actualize and mobilize all compensatory mechanisms of introducing innovations for the future regional book industry development.