Reviewerly/exHarmony huggingface dataset:
Helmholtz: A Verifier for Tezos Smart Contracts Based on Refinement Types

Abstract A smart contract is a program executed on a blockchain, based on which many cryptocurrencies are implemented, and is being used for automating transactions. Due to the large amount of money that smart contracts deal with, there is a surging demand for a method that can statically and formally verify them. This tool paper describes our type-based static verification tool Helmholtz for Michelson, which is a statically typed stack-based language for writing smart contracts that are executed on the blockchain platform Tezos. Helmholtz is designed on top of our extension of Michelson’s type system with refinement types. Helmholtz takes a Michelson program annotated with a user-defined specification written in the form of a refinement type as input; it then typechecks the program against the specification based on the refinement type system, discharging the generated verification conditions with the SMT solver Z3. We briefly introduce our refinement type system for the core calculus Mini-Michelson of Michelson, which incorporates the characteristic features such as compound datatypes (e.g., lists and pairs), higher-order functions, and invocation of another contract. Helmholtz successfully verifies several practical Michelson programs, including one that transfers money to an account and that checks a digital signature.
Learning framework with joint task optimization applied to consumer health applications with behavioral nudges

We consider a consumer-facing healthcare mobile app that recommends optimal user behaviors based on the user's current and historical engagement with the application, including both inferred and explicit preferences. The app separately pushes intermittent behavioral nudges to elicit specific optimal user health behaviors like messaging a healthcare provider or recording one's meals after extended disengagement. We propose applying a reinforcement learning approach, and jointly optimizing the recommendation of a menu of items and sending the user behavioral nudges in a multi-stage paradigm. We propose this as an alternative to optimizing the recommendations and nudges separately or in sequence, as is the prevailing approach across different but analogous e-commerce recommender system settings. We argue that this solution approach optimizes user welfare in the short- and long-term across generalized reward functions.
Development of 3D models for faculty of education database system via monitor’s graphical user interface interactive for perception and utilization

This study is a research and development study that used systematic approaches as an operational concept. The objectives of the study included: (1) To study the usage demands of an on-screen interactive Graphical User Interface (GUI) for the Faculty of Education database. (2) To create 3D models and study their efficiency in the usage of an on-screen interactive GUI for the Faculty of Education database. (3) To evaluate the perception and utilization of 3D models in the usage of an on-screen interactive GUI for the Faculty of Education database. The population in this study included; (1) 100 staff and students in the Faculty of Education – who were selected using Purposive Sampling to study usage demands of an on-screen interactive GUI for the Faculty of Education database. (2) 5 experts and 40 staff and students of the Faculty of Education – who were selected using Purposive Sampling to study the efficiency of 3D models in the usage of an on-screen interactive GUI for the Faculty of Education database. (3) 300 staff and students of Ramkhamhaeng University who used 3D models with the on-screen interactive GUI of the Faculty of Education database within the 1-month test period of the study. The research instruments used in this study were: (1) a questionnaire about usage demands of an on-screen interactive GUI for the Faculty of Education database, (2) an expert opinion evaluation form, and (3) an assessment form for perception and utilization of 3D models in the usage of an on-screen interactive GUI for the Faculty of Education database – all of which were found with .930 reliability and item discrimination values between .71 - .85.
Optimization-Based Tone Mapping Evaluation

In recent years, increasing attention has been paid to devising tone mapping operators, which convert specialized high dynamic range (HDR) images to standard low dynamic range (LDR) ones for visualization on daily monitors. However, there lacks a reliable evaluation criterion for comparing distinct tone mapping operators, which is of great significance to the design and optimization of tone mapping methods. In this paper we propose an effective tone mapping evaluation system (TMES) based on a two-stage framework. In the first stage, features are extracted in view of the observations that luminance information, color saturation, statistical naturalness, structural fidelity and visual saliency have different and determinate influences on the perceptual quality of tone-mapped LDR images. In the second stage, the extracted features are integrated with a data-driven optimization strategy, which iteratively learns the parameters by applying thousands of collected tone-mapped LDR and natural images. Our TMES evaluation system can be implemented with or without reference HDR images, serving for the optimization and monitoring of tone mapping methods. Experiments conducted on three databases prove the superiority of our quality evaluation system.
Validation Feedback based Image Transfer Network for Data Augmentation

Modern image classifiers are often suffering over-fitting problems because of the insufficient number of images in the dataset. Data augmentation is a strategy to increase the number of training samples. However, recent data augmentation methods are designed manually and cannot generate real-like images. Some neural network-based image generation methods such as GAN and VAE can also be used for data augmentation, but they are usually applied to unbalanced datasets. Since the generated images cannot be guaranteed to be from the same label, using them to extend a balanced dataset may lead to decreasing the accuracy of the classifier. In this paper, we propose an image transfer network to produce images that automatically adapt to a specific dataset and classifier. The image transfer network will search for the output images which can maximize the validation accuracy and help the classifier to overcome the over-fitting problems. Through the experiments, our method achieves high accuracy on CIFAR-10 and CIFAR-100 datasets. Moreover, since it could combine with other data augmentation methods, we show that using our method can push the state-of-the-art results furthermore.
SmartFund: Predicting Research Outcomes with Machine Learning and Natural Language Processing

The mission of the National Science Foundation (NSF) is to promote progress of science. It supports fundamental research and education in science and engineering. It provides funding for researchers to explore a variety of disciplines in thousands of institutions across the United States. The outcomes of such research projects vary widely and with much funding being funneled into these projects, it would be efficient and cost-effective to be able to predict these outcomes so the NSF can make informed decisions on the amount of funding they allocate to future projects. We consider a variety of factors that point to general trends and use a combination of natural language processing techniques (such as topic models and phrase mining) and neural networks to predict how many papers and citations will come from potential research projects seeking funding.
Opposite Information Annotation on ‘Word List by Semantic Principles’

本論文ではシソーラス『分類語彙表』に対する反対語情報付与作業について示す．分類語彙表上では反対語対に対しても同じ分類番号が付与されている．この同じ分類番号が付与されている単語群から反対語対を抽出し，分類作業を行った．まず，人手により反対語候補となる単語対を網羅的に収集した．次に，一般的な日本語話者が反対語と感じるかをクラウドソーシングにより収集し，50% 以上の方が反対語とみなしたものを反対語と定義した．最後に，得られた反対語リストに対して，村木の「対義語」の分類を精緻化したものを付与した．分析にあたっては，反対語認識の非対称性・分類語彙表ラベル・分類・コーパス頻度・単語埋め込みなどの観点から検討を行った．言語学的な分析においては，閉じた反対語対に対してより反対語らしさを感じる傾向が確認された．言語処理的な分析においては，単語埋め込み上で反対語対の置き換え可能性の評定とコサイン類似度に中程度の相関があることが確認された．
Publicly Verifiable Outsourcing Computation for QR Decomposition Based on Blockchain

In the Big Data Era, outsourcing computation has become increasingly significant as it supplies computation resources for clients with limited resources. However, there are still many security challenges such as payment fairness, privacy protection, and verification. In this paper, we propose a secure publicly verifiable outsourcing computation scheme for the large-scale matrix QR decomposition. In the proposed scheme, client can pay for outsourcing services through blockchain-based payment system which achieves the payment fairness. Moreover, to protect privacy, both permutation matrix and block diagonal matrix are applied in encryption process. Meanwhile, to achieve the public verification, the computational complexity is reduced by using the matrix digest technology. It is worth mentioning that our scheme is provable and secure under the co-CDH assumption.
A Construction of Robustly Reusable Fuzzy Extractors over Blockchains

Fuzzy extractors (FEs) turn a noisy source of high entropy, such as biometric information, into a uniformly distributed key. FEs can extract cryptographically desirable keys without storing the keys. FE was first proposed by Dodis et al. [1], and it has been studied actively since. Moreover, a robust FE to achieve higher security and a reusable FE to achieve more functionality were proposed. Wen et al. constructed a robustly reusable FE (rrFE) that satisfies robustness and reusability simultaneously [2]. However, only few rrFEs have been proposed and all are based on the Common Reference String (CRS) model.Recently, Goyal and Goyal [3] defined blockchain formally as a model for use as components of cryptographic protocols. In this paper, we introduce an rrFE based on the blockchain proposed by Goyal et al. instead of the CRS model. In contrast to the CRS model, a blockchain trusts not a specific third party but a distributed system. Therefore, a protocol based on CRS may lose security by a betrayal of TTP. Meanwhile, our protocol tolerates malicious acts of parties as long as the majority are honest.
An Illumination Modulation-Based Adversarial Attack Against Automated Face Recognition System

In recent years, physical adversarial attacks have been placed an increasing emphasis. However, previous studies usually use a printer to physically realize adversarial perturbations, and such an attack scheme will meet inevitable disadvantages of perturbation distortion and low concealment. In this paper, we propose a novel attack scheme based on illumination modulation. Because of the rolling shutter effect of CMOS sensor, the created perturbation will not be distorted and completely invisible. According to the attack scheme, we have proposed two novel attack methods, denial of service attack (DoS attack) and escape attack, and offered a real scene to apply the attack methods. The experimental results show that both of two attack methods have a good performance against AFR. DoS attack has an attack success rate of 92.13% and escape attack has an attack success rate of 82%.
Evolutionary Stable Solution Concepts for Initial Play

We study one-shot play in the set of all bimatrix games by a large population of agents. The agents never see the same game twice, but they can learn `across games' by developing solution concepts that tell them how to play new games. Each agent's individual solution concept is represented by a computer program, and natural selection is applied to derive a stochastically stable solution concept. Our aim is to develop a theory predicting how experienced agents would play in one-shot games. To use the theory, visit https://gplab.nhh.no/gamesolver.php.
Building Knowledge-Based Economies in Africa: A Systematic Review of Policies and Strategies

Compared to other regions of the world, Africa is lagging in its drive toward knowledge-based economies. This study systematically reviews the literature in order to highlight the policies and strategies with which African countries can accelerate their current drive towards building knowledge-based economies. These are discussed in terms of three pillars of the World Bank’s knowledge economy framework. They are the indices for: (i) education and skilled population, (ii) information and communication technology and (iii) economic incentives and institutional regime.
Aprendizaje colaborativo: una aproximación a la animación sociocultural

espanolMuchas de las teorias del aprendizaje que conocemos actualmente reconocen lo importante que son las relaciones sociales y la interaccion con otras personas a la hora de adquirir conocimiento. Saber trabajar en grupo para lograr objetivos comunes, es reconocido por muchos autores como una competencia transversal de aprendizaje en todos los niveles de ensenanza. A su vez, las nuevas tecnologias actuales nos permiten la comunicacion entre varios sujetos del aprendizaje, contribuyendo a la creacion de entornos sociales para la interaccion, ideales para explorar nuevos enfoques metodologicos y favorecer los ya existentes. La crisis sanitaria del COVID 19 nos ha mostrado como las metodologias de aprendizaje colaborativo y a traves de las TIC, estan cobrando cada vez mayor auge y proyeccion en la innovacion educativa. Gracias a la metodologia del trabajo colaborativo, el alumnado no solo mejora sus conocimientos academicos, tambien aprenden a trabajar otras destrezas y habilidades que tan importantes son para su futuro laboral. De ahi discurrir la importancia que tiene el hecho de interaccionar con las demas personas a la hora de que se adquiera conocimiento y como muchas de las caracteristicas, funciones, estrategias y herramientas del aprendizaje colaborativo emanan de un concepto como es la Animacion Sociocultural EnglishMany of the learning theories that we know today recognize how important social relationships and interaction with other people are when it comes to acquiring knowledge. Knowing how to work in groups to achieve common objectives is recognized as a transversal learning competence at all levels of teaching. Interacting with other people is a key process when it comes to acquiring new knowledge. In turn, the new current digital technologies allow us to communicate between both subjects of learning, contributing to the creation of social environments for interaction, being ideal for exploring new methodological approaches and favoring existing ones. The health crisis of COVID 19 has shown us how collaborative learning methodologies and especially through ICTs, are gaining a growing boom and projection in educational innovation. Hence the importance of interacting with other people when it comes to acquiring knowledge and like many of the characteristics, functions, strategies, tools … of collaborative learning and that are carried out in it. , are extracted from a concept nowadays not as fashionable as it was in other times, but preserving the same essence of then, such as Sociocultural Animation.
V-WorkGen: Virtual Workload Generation Tool for Connected Automotive Services

Connected car is one of the major trends in the auto-motive industry to provide users with advanced services to improve driving quality and safety. For example, a predictive maintenance service identifies any malfunction of vehicles by analyzing sensor data sent from them; High-Definition (HD) map can be constructed by collecting sensor data from multiple vehicles, and distributed to them to enhance the quality of any autonomous features.
Comparison of Augmented Reality Apps and Their Ability to Develop Communication Skills

The paper is aimed at augmented reality mobile apps that could be used to help students develop their communication skills. Such apps could serve as both a main and support tool for developing these competencies. The paper aims to provide a detailed comparison of iOS and Android apps. The first part of the paper provides a theoretical background. The second part of the paper is centered on the mobile application market, with 5 Android and 5 iOS apps being analyzed in detail, focusing on key criteria for selecting an appropriate app. This paper may be used as the basis for further research into augmented reality mobile apps and the development of communication skills.
Learning to Play Imperfect-Information Games by Imitating an Oracle Planner

We consider learning to play multiplayer imperfect-information games with simultaneous moves and large state-action spaces. Previous attempts to tackle such challenging games have largely focused on model-free learning methods, often requiring hundreds of years of experience to produce competitive agents. Our approach is based on model-based planning. We tackle the problem of partial observability by first building an (oracle) planner that has access to the full state of the environment and then distilling the knowledge of the oracle to a (follower) agent which is trained to play the imperfect-information game by imitating the oracle’s choices. We experimentally show that planning with naive Monte Carlo tree search does not perform very well in large combinatorial action spaces. We, therefore, propose planning with a fixed-depth tree search and decoupled TS for action selection. We show that the planner is able to discover efficient playing strategies in the games of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Clash Royale</i> and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Pommerman</i> and the follower policy successfully learns to implement them by training on a few hundred battles.
FAIRising Pedagogical Documentation for the Research Lifecycle

How can pedagogical research complement academic research and vice versa? This case study revisits two research projects on curricular resources: the first, in 2019, analyzes partially structured syllabi data in digital humanities, and the second, in 2021, focuses on unstructured course titles and descriptions in LIS course catalogs. Findings reexamine data collection and analysis processes in which the lack of linked semantic metadata and persistent digital objects in curricular resources impedes fruitful research on how (inter)disciplinary topics are taught and future researchers trained. Consequently, the case study locates a gap: the role of pedagogical documentation in the research lifecycle has not been considered. As suggested by the emergence of FAIR principles, metadata expertise is a foundation for establishing the findability, accessibility, interoperability, and reuse of persistent digital objects in research outputs. FAIRising pedagogical documentation for the research lifecycle holds potential to link curricular resources with other research outputs. Information professionals have a leadership role in assisting faculty to create FAIRised pedagogical documentation, and curricular resources so prepared address the gap for integrating pedagogical documentation with the research lifecycle. Benefits include recognition of curricular resources as vital research outputs and facilitating longitudinal research on (inter)disciplinary pedagogical practices in the FAIR ecosystem.
e-Commerce Site Pricing and Review Analysis

Nowadays, people only prefer to buy products by online means as they feel it is easy but on the other hand, they get low-quality products. Online purchasers get confused for considering which e-commerce site to buy a product. There are many strategies that can be considered to buy a product online by seeing offers and reviews. There are many e-commerce sites that provide fake reviews and unrealistic offers that work for attracting customers. In this paper, we suggest a method by which every customer gets an option of comparison between two sites dynamically which helps them to see through customer reports of the particular product bought from the particular e-commerce Web site in a transparent way.
System-Integral Interdisciplinary Methodology - Qualitatively New Tools of General and Professional Education in the Context of the Second Industrialization of Russia

The education system is a key element in the progress or degradation of the country's population and economy. Formed in the present education system of Russia according to the Bologna models and the patterns aimed at stupefying the total population, a sharp decline of scientific progress in social production and increased dependence on foreign manufacturers and managers of the domestic financial and resource wealth. The way out of this deadlock circle of problems is in the revival of the advanced positions of the former soviet education system on a qualitatively new scientific basis, theory and system-holistic methodology, providing a full knowledge of the phenomena of nature and society in conditions of certainty. Existing methodologies of partial cognition in conditions of high degree of uncertainty and subjectivity of representation are based on outdated and inadequate theories. &#x0D; System-holistic interdisciplinary methodology is characterized by a set of necessary and sufficient for objective and complete knowledge of the conceptual tools that allow you to accurately, fully and adequately understand the socio-economic processes, to lead the knowledge immediately from the general to the specific, thereby reducing the multiple time and resources for the process of knowledge. It is based on a qualitatively new scientific basis, objective theory, uses objective units of dimensions of physical quantities (kWh and the like), takes into account in the knowledge and management of the action of an expanded set of universal and socio-economic laws of human development-society in nature. A deeper analysis of the set of laws allowed us to identify the main goal of human development-society and the main socio-economic forms of manifestation of the laws: useful costs-results, useless, harmful, loss of cost-results in the structure of the budget of social time. There are no other socio-economic forms of human activity. Therefore, the main goal of human development-society in nature is to increase the share of useful and reduce the share of useless, harmful, loss of cost-results in the structure of the budget of social time. This is the basis for the preservation of civilization on Earth. The technique, technology, organization, education system used serve only as forms of manifestation of life that contribute to or hinder the progress of mankind. The implementation of the Second industrialization of Russia is aimed at a radical solution to the ever-increasing complex of internal and external problems in modern conditions. A key element of the successful implementation of this large-scale strategic program is the immediate introduction of a fundamentally new education system that ensures high rates of economic growth and well-being of the entire population of Russia.