Reviewerly/exHarmony huggingface dataset:
Learning Complementary Representations of the Past using Auxiliary Tasks in Partially Observable Reinforcement Learning

Partially observable Markov decision processes (POMDPs) define discrete-time sequential control problems [3, 11, 20]. In partially observable reinforcement learning (RL), an agent lacks access to the system state or domain model, and has to rely on the observable past (aka history-state) for decision making [20]. History-states are intrinsically complex, and extracting more appropriate representations is very challenging albeit necessary for general POMDPs. We refer to this as the history representation learning problem.
Stochastic Neural Network with Kronecker Flow.

Recent advances in variational inference enable the modelling of highly structured joint distributions, but are limited in their capacity to scale to the high-dimensional setting of stochastic neural networks. This limitation motivates a need for scalable parameterizations of the noise generation process, in a manner that adequately captures the dependencies among the various parameters. In this work, we address this need and present the Kronecker Flow, a generalization of the Kronecker product to invertible mappings designed for stochastic neural networks. We apply our method to variational Bayesian neural networks on predictive tasks, PAC-Bayes generalization bound estimation, and approximate Thompson sampling in contextual bandits. In all setups, our methods prove to be competitive with existing methods and better than the baselines.
An automatic discourse relation alignment experiment on TED-MDB

This paper describes an automatic discourse relation alignment experiment as an empirical justification of the planned annotation projection approach to enlarge the 3600-word multilingual corpus of TED Multilingual Discourse Bank (TED-MDB). The experiment is carried out on a single language pair (English-Turkish) included in TED-MDB. The paper first describes the creation of a large corpus of English-Turkish bi-sentences, then it presents a sense-based experiment that automatically aligns the relations in the English sentences of TED-MDB with the Turkish sentences. The results are very close to the results obtained from an earlier semi-automatic post-annotation alignment experiment validated by human annotators and are encouraging for future annotation projection tasks.
The Excitation Switching Control Method of Tidal Generator Based on T-S Fuzzy Weighting

Jiang, Y. and Luo, J., 2020. The excitation switching control method of tidal generator based on T-S fuzzy weighting. In: Yang, Y.; Mi, C.; Zhao, L., and Lam, S. (eds.), Global Topics and New Trends in Coastal Research: Port, Coastal and Ocean Engineering. Journal of Coastal Research, Special Issue No. 103, pp. 1010–1013. Coconut Creek (Florida), ISSN 0749-0208.In view of the continuous development of power system, this paper proposes a T-S fuzzy weighting based excitation switching control method for tidal generator set, which can solve the dynamic and static performance defects of excitation control of tidal generator set and improve the operation performance of generator set. Combining the advantages of T-S model fuzzy controller and fuzzy PID controller, a dual control switching control exciter is constructed. The research results show that this control method has stronger damping capacity for small disturbance, at the same time, it completely suppresses the voltage fluctuation at the end of the tidal generator, makes the voltage amplitude at the end of the generator almost unaffected by small disturbance, realizes zero dynamic, and can more stably control the overshoot of the control of the tidal excitation synchronous power generation, has low control error and high control accuracy for the tidal excitation synchronous power generation, improves the excitation switching control efficiency of the generator set, and suppresses the excitation switching control oscillation of the tidal generator.
Personal Information Privacy: What's Next?

In recent events, user-privacy has been a main focus for all technological and data-holding companies, due to the global interest in protecting personal information. Regulations like the General Data Protection Regulation (GDPR) set firm laws and penalties around the handling and misuse of user data. Theseprivacy rules apply regardless of the data structure, whether it being structured or unstructured. In this work, we perform a summary of the available algorithms for providing privacy in structured data, and analyze the popular tools that handle privacy in textual data; namely medical data. We found that although these tools provide adequate results in terms of de-identifying medical records by removing personal identifyers (HIPAA PHI), they fall short in terms of being generalizable to satisfy nonmedical fields. In addition, the metricsused to measure the performance of these privacy algorithms don't take into account the differences in significance that every identifier has. Finally, we propose the concept of a domain-independent adaptable system that learns the significance of terms in a given text, in terms of person identifiability and text utility, and is then able to provide metrics to help find a balance between user privacy and data usability.
Robust guarantees for learning an autoregressive filter

The optimal predictor for a linear dynamical system (with hidden state and Gaussian noise) takes the form of an autoregressive linear filter, namely the Kalman filter. However, a fundamental problem in reinforcement learning and control theory is to make optimal predictions in an unknown dynamical system. To this end, we take the approach of directly learning an autoregressive filter for time-series prediction under unknown dynamics. Our analysis differs from previous statistical analyses in that we regress not only on the inputs to the dynamical system, but also the outputs, which is essential to dealing with process noise. The main challenge is to estimate the filter under worst case input (in $\mathcal H_\infty$ norm), for which we use an $L^\infty$-based objective rather than ordinary least-squares. For learning an autoregressive model, our algorithm has optimal sample complexity in terms of the rollout length, which does not seem to be attained by naive least-squares.
Construction Of Case-Based Oral English Mobile Teaching Platform Based On Mobile Virtual Technology

In view of the poor interactive performance, long response time and low user satisfaction of the traditional oral English teaching platform, this paper proposes a mobile oral English teaching case platform based on mobile virtual technology. Select B/S data frame. The subordinate patterns are all MVC patterns. The student user module applies the virtual technology to the mobile interaction and USES the data frame format transformation and reorganisation to improve the sense of interaction. The teacher module establishes the transmission path, improves the transmission rate. The administrator module connects to the back-end database and completes data maintenance and privilege replacement through multiple logical tables. The experimental results show that compared with the traditional mobile teaching platform, the designed mobile teaching platform has the advantages of short response time, high user satisfaction rate and convenient application.
Hitting Long Directed Cycles Is Fixed-Parameter Tractable

In the Directed Long Cycle Hitting Set problem we are given a directed graph G, and the task is to find a set S of at most k vertices/arcs such that G-S has no cycle of length longer than l. We show that the problem can be solved in time 2^O(l^6 + l k^3 log k + k^5 log k log l) ⋅ n^O(1), that is, it is fixed-parameter tractable (FPT) parameterized by k and l. This algorithm can be seen as a far-reaching generalization of the fixed-parameter tractability of Mixed Graph Feedback Vertex Set [Bonsma and Lokshtanov WADS 2011], which is already a common generalization of the fixed-parameter tractability of (undirected) Feedback Vertex Set and the Directed Feedback Vertex Set problems, two classic results in parameterized algorithms. The algorithm requires significant insights into the structure of graphs without directed cycles of length longer than l and can be seen as an exact version of the approximation algorithm following from the Erdős-Posa property for long cycles in directed graphs proved by Kreutzer and Kawarabayashi [STOC 2015].
Design of Key Data Integration System for Interactive English Teaching based on the Internet of Things

In order to solve the problems that the integration of key data in the traditional interactive English education system of the internet of things generally takes too long and has low accuracy, the key data integration system of interactive English teaching based on the internet of things is designed. Hardware design process configuration in order to achieve the integration of teaching objectives, integrating teaching contents, the integration of teaching process and the integration of teaching evaluation module, in the process of the system software design installation system configuration server, realise the remote desktop email management and system configuration, the PHP configuration, content management configuration, key data integration to realise English interactive teaching. Results show that the integration completion time of the designed system varies in the range of 62 s-95 s, and the accuracy is always above 90%. The integration completion time of the system is short and the accuracy is high.
Textbooks for the New Ukrainian School as a Means of Effective Educational Communication: Discourse Analysis and Problems of the Culture of the Edition

The purpose of the study, which we started in October 2018 with the support of the Ministry of Education and Science of Ukraine and the intergovernmental Ukrainian-Finnish project “Learning together”, is to analyze the quality of modern textbooks for the first grade of the New Ukrainian School, to identify outdated scientific paradigms, to identify and systematize cultural problems of textbook publication, which should be taken into account during the editorial and publishing of textbooks for the second and third grades. Methodology. At the initial stage of the study, a bibliographic method was used for the identification and systematization of scientific sources, normative legal documents on the problems of textbook creation. The use of methods of discourse analysis, logical, semantic, context analysis of text and visual components of textbooks for the first grade of the New Ukrainian School made it possible to identify the problematic aspects of the textbook publication culture. Typical flaws in the culture of textbook publication for the New Ukrainian School are systematized using methods of scientific generalization and classification. The results of the research showed a number of problems: visualization of outdated Soviet discourse, systematic errors, consistency and logic of presentation of the material, fairly low linguistic culture of publications, and sometimes unsatisfactory quality of artistic design. The solution of these problems requires a complex, systemic and integrative approaches. This includes the training of editors, publishers, authors, the formation of their high social responsibility, the creation of a single scientific and informational space for authors, reviewers and editors based on the leading publishing houses and academic departments of publishing and editing, the organization of seminars, trainings, summer/winter schools, etc. Such work has already begun within the preparatory stage of the international project “Finnish support for a New Ukrainian School”. The results of the research were used during the All-Ukrainian scientific and practical seminar “New textbook for the New Ukrainian School: Requirements, criteria for evaluation, registration” organized by the Institute for the modernization of the content of education for publishers who worked on textbooks for the second grade of the New Ukrainian School (November 22, 2018), training for experts who assessed the textbook for the second grade of the New Ukrainian School (January 21-23, 2019) and training sessions for publishers of textbooks for the New Ukrainian School (March 12-15, 2019), prepared by using experts from the Ukrainian- Finnish project “Learning together.”
A Coverage Path Planning Method Based on Multiple Solar Powered Unmanned Aerial Vehicles

This paper proposes a solution to solve the coverage path planning (CPP) problem of multi-solar unmanned aerial vehicles (UAVs), and the research content of this paper is as follows. First, the energy production model and consumption model of the solar UAV are established, and according to this model, the flying speed of the solar UAV are determined. Besides, the energy flow efficiency is defined to evaluate the energy utilization efficiency of this operation. After that, transform the CPP problem into vehicle routing problem (VRP), and a mixed integer linear programming (MILP) model is established to determine the flight path of each UAV with the objective of minimizing operation time. In this method, the solar UAV is used for CPP, which solves the problem of short flight time of traditional UAV. Operation time is used as the objective function to solve the CPP, so that the task can be completed as soon as possible. And the calculation of energy flow efficiency can be used to evaluate the operation efficiency of solar UAV.
Diameter-based Interactive Structure Discovery

We introduce interactive structure discovery, a generic framework that encompasses many interactive learning settings, including active learning, top-k item identification, interactive drug discovery, and others. We adapt a recently developed active learning algorithm of Tosh and Dasgupta (2017) for interactive structure discovery, and show that the new algorithm can be made noise-tolerant and enjoys favorable query complexity bounds.
Security Enhancement Using Modified AES and Diffie–Hellman Key Exchange

In today’s world, providing data security is a primary concern. For this purpose, many researchers have introduced asymmetric and symmetric algorithms to ensure security. But they are not resistant to many attacks. In this paper, we combine symmetric and asymmetric techniques to provide more security. Advanced Encryption Standard algorithm is modified by generating Dynamic S-Boxes (DS-Boxes) to provide a better attack-resistant algorithm. In our approach, Diffie–Hellman is used to generate and exchange both keys and random numbers. These random numbers create DS-Boxes used in Modified AES. The proposed algorithm is resistant to timing attacks, linear, and differential cryptanalysis attacks due to the usage of DS-Boxes.
Based on Censydiam Model and Characters in Contemporary TV Series to Create Persona

Persona has been widely applied in software interaction design, product design and service design. It is a huge challenge to create persona accurately in design projects. The Censydiam model is often applied in creating personas for its own knack in analyzing the personalities and pursuits of users. This paper found that roles with their personalities, emotional expression and behavior patterns built in TV series have practical value in creating personas. To improve the accuracy of personas, some roles in TV series are analyzed and classified based on the Censydiam model. The result is a diagram which is a new Censydiam model with rich labels of roles. This method as an innovative application of the Censydiam model can improve accuracy and efficiency of creating personas and enhance practicality of application after the experiment and practice of the new diagram in design project of electronic products. This paper reports the basic framework of model (Censydiam Model), the principle of this method and the process of applying this method to build personas and proposes the selection principles of TV series.
Health Disaster Preparedness Using Android Mobile Based Application Case Mount Bromo Eruption

Introduction: In the last 10 years, Mount Bromo has erupted four times; 2004, 2010, 2015 and 2019. However, it is unique that people at Tengger are reluctant to evacuate even though Mount Bromo is erupting and releasing volcanic material such as stones and dust.Methods: This research is a quantitative study, using correlative analytic observational design and cross sectional approach with pourposife sample of 120 taken from online questionare results of bivariate analysis using gamma correlation test obtained the results of knowledge factors (p=0.005; r=0.27) attitude (p=0.000; r=0.45), means of infrastructure (p=0.000; r=0.58), and android application (p=0.000; r=0.59) for health preparedness. Results: Knowledge, attitude, infrastructure and android application factors can influence health preparedness in disaster risk reduction in Bromo area.Using the smartphone application as the Mount Bromo information facilities are one of an effort so that people and tourists can activate if an eruption occurs. There is important health preparedness about features made in the application such as distribution shelters, evacuation routes, health centres, photos, videos, and primary health care information.Conclusion: Assessment results to the application interface, the information conveyed, and the features offered showed that the application was very useful and gives a new perspective in conveying accurate information to the public and also tourists. The health preparedness community level is also quite good with the services provided by the Bromo alert application.
METHOD OF TEACHING STUDENTS TO INNOVATIVE ENGINEERING ACTIVITIES IN THE OLYMPIAD ENVIRONMENT

Innovative engineering activity (IEA), as a creative productive activity, is the basis for ensuring the technological progress of the society, and innovative training is one of the priority tasks of universities. The author proposes solving this problem by forming creative, activity, motivational, psychological, and other components of competence in innovative engineering (CIEA) when studying in the olympiad environment. The study aims at the improvement of the efficiency of training students for innovative engineering activity. The author updated the idea of the educational environment prevailing in pedagogical practice and formulated the concept of the innovation-oriented olympiad educational environment (OEE) as the system of interacting subjects and objects of educational activity in the conditions of the olympiad movement. The author developed the OEE model, which includes motivational-targeted, structural, organizational, and content-related, process-technological, and reflective-evaluative components. A single olympiad cycle, the object of which is an olympiad task, acts as a substrate of this model. To implement a cycle in the OOS, the author developed a sub-model of the IEA training methodology within one such cycle. It includes all of the listed components of the OEE model, relies on their content, uses its scientific and methodological approaches to learning, methods, and didactic principles; is implemented through 10 intra-stage and 5 inter-stage steps. The paper presents the main learning outcomes in the described environment confirming its high efficiency.
Domain Adversarial Training for Infrared-colour Person Re-Identification

Person re-identification (re-ID) is a very active area of research in computer vision, due to the role it plays in video surveillance. Currently, most methods only address the task of matching between colour images. However, in poorly-lit environments CCTV cameras switch to infrared imaging, hence developing a system which can correctly perform matching between infrared and colour images is a necessity. In this paper, we propose a part-feature extraction network to better focus on subtle, unique signatures on the person which are visible across both infrared and colour modalities. To train the model we propose a novel variant of the domain adversarial feature-learning framework. Through extensive experimentation, we show that our approach outperforms state-of-the-art methods.
USE OF SONGS IN TEACHING SIMPLE TOBE AND PAST TENSE TEACHING

The purpose of this study was to see whether the use of English songs can improve students' understanding and mastery of Simple and Past Tense in affirmative sentences, denying and questioning sentences. And to prove that songs are also effective in increasing students' abilities in mastery ‘To Be’ Benefits of research. The results of the study are expected to be useful for researchers, students, lecturers and academics: Firstly, This research is expected to be useful for researchers to know precisely the conditions of the field, the problem of the learning process so that it becomes a reference in preparing before facing the actual conditions. Secondly, For students, the use of this method is expected to help them understand the lesson more easily and make them like English because the use of this method is fun. Thirdly, for readers, you will get information about the method of teaching English using English songs. Finally, Students can learn and understand the use of tobe in the present tense form and past tense and get new vocabulary through the song. Not only knowing the meaning of the words in the song. However, students can also understand the true meaning of the song they are listening to. Through question and answer that is done after students listen to the song, students are also asked to dare to say the answer according to the questions given. Besides that songs as authentic material can make classes interesting and fun, increase students' interest in learning, provide everyday language exposure that is generally not displayed in textbooks, and integrate several language skills at once. One thing that teachers also need to pay attention to is the discussion of cultural aspects when instructors use songs in the classroom. In this study we can conclude. Keywords: Songs; Teaching; Simple Tobe; Simple Past Tense.
Research on ECDSA-Based Signature Algorithm in Blockchain

&lt;p&gt;This paper mainly discusses the use of signature in the transaction process under the background of Bitcoin blockchain. At the beginning, the paper presents the way and principle of Bitcoin transaction. In order for receiver B to trust the source of the transaction, the message needs to be signed. ECDSA algorithm is applied to the signature in the process of transaction. Then it describes the introduction of ECDSA signature, the process of signature generation and verification, and the application of ECDSA in Bitcoin blockchain. Finally, the advantages of ECDSA are analysed. The weak random number problem of ECDSA still exists in the current blockchain development, which needs the attention of developers.&lt;/p&gt;
The Development of Traditional Thai Massage Chatbot Application for Hypertension Treatment

Hypertension is one of the significant health problems from chronic health conditions, which may cause serious health issues and sudden death. Thai massage or Nuad Thai, which is a Thai traditional healing practice and a well-known therapy, can be applied as a treatment for some chronic health conditions. There are various Thai massage courses available for people who are interested, but the problems of participation schedules, massage therapy techniques, and how to practice it correctly are difficult for non-experts to follow and improve the knowledge and skills by themselves. Thus, we would like to develop computer instructional lessons of Thai massage for high blood pressure treatment by giving basic information through a media service or an application, which is a chatbot application. Then, we evaluated the quality of graphics and video content as well as the chatbot application using an online survey. The results showed that the media was easy to follow and understandable. The users mentioned that after they used the chatbot application and saw the Thai massage video clips, they were able to perform the massage by themselves.