Reviewerly/exHarmony huggingface dataset:
Term Rewriting that Preserves Models in KR-Logic

In human proofs of mathematical problems, such as proofs in a group theory, term rewriting is usually used. When we consider Herbrand semantics for the first-order logic with constraints ( $$\text {FOL}_\mathrm{c}$$ ), correct representation of evaluable terms cannot be obtained due to lack of representation power of the logic. In place of $$\text {FOL}_\mathrm{c}$$ with Herbrand semantics, we use $$\text {KRL}_\mathrm{c}$$ (KR-Logic with built-in constraints). We propose a class of term rewriting rules, and prove that they preserve the sets of all models in KR-Logic. Representation and computation by the rewriting rules in KR-Logic is well established in the space of $$\text {KRL}_\mathrm{c}$$ . This paper opens a new method of logical problem solving, with $$\text {KRL}_\mathrm{c}$$ being the representation space and $$\text {ECLS}_\mathrm{N}$$ being the computation space. This theory integrates logical inference and functional rewriting under the broader concept of equivalent transformation.
Equational Theories and Monads from Polynomial Cayley Representations

Abstract We generalise Cayley’s theorem for monoids by providing an explicit formula for a (multi-sorted) equational theory represented by the type $$PX \rightarrow X$$ , where $$P$$ is an arbitrary polynomial endofunctor with natural coefficients. From the computational perspective, examples of effects given by such theories include backtracking nondeterminism (obtained with the original Cayley representation $$X \rightarrow X$$ ), finite mutable state (obtained with $$n \rightarrow X$$ , for a constant n ), and their different combinations (via $$n \times X \rightarrow X$$ or $$X^n \rightarrow X$$ ). Moreover, we show that monads induced by such theories are implementable using the type formers available in programming languages based on a polymorphic $$\lambda $$ -calculus, both as compositions of algebraic datatypes and as continuation-like monads. We give a set-theoretic model of the latter in terms of Barr-dinatural transformations. We also introduce , a tool that takes a polynomial as an input and generates the corresponding equational theory together with the two implementations of the induced monad in Haskell.
Application of the Web Data Mining Technology in the English Translation Platform

The global economic integration makes the trade between China and other countries in the world more and more frequent. English translation naturally becomes the primary language used by all countries. At the same time, with the continuous development of the modern information technologies, the ways and means of our English learning are becoming more diverse. Especially with the emergence of the English electronic dictionaries, English learning has become more and more simple. However, with the changes of the users’ habits and the development of the mobile smart phones, the English translation platform based on the Web data mining technology has become the focus of the current applications, and it has attracted people’s attention and welcome, so that English lovers can complete their English learning through their mobile phones.
Text Feature Extraction and Selection Based on Attention Mechanism

Selecting features that represent a particular corpus is important to the success of many machine learning and text mining applications. However, the previous attention-based work only focused on feature augmentation in the lexical level, lacking the exploration of feature enhancement in the sentence level. In this paper, we exploit a novel feature extraction and selection model for information retrieval, denoted by Dynamic Feature Generation Network (DFGN). In sentence dimension, features are firstly extracted by a variety of different attention mechanisms, then dynamically filtered by thresholds automatically learned. Different kinds of characteristics are distilled according to specific tasks, enhancing the practicability and robustness of the model. DFGN relies solely on the text itself, requires no external feature engineering. Our approach outperforms previous work on multiple well-known answer selection datasets. Through the analysis of the experiments, we prove that DFGN provides excellent retrieval and interpretative abilities.
Proposal of Control Education Curriculum in University of Education

In this paper, A student in the teacher training course learns the basic theory and principle of operation in the field of control, and through basic experiments and practices, basic concepts related to sequence control and feedback control, which are the main handling items within the course of electronic measurement control and mechanism. It aims to propose a lesson curriculum that can be learned experientially with respect to properties. Lecture on the proposed curriculum. Also, conduct a questionnaire to students. As a result, we analyze students' understanding of measurement and control from questionnaire data and verify effectiveness.
A Study on the Education of Data Analysing Technology for the Urban Planning in the New Data Environment

The evolution of the internet and data technologies has formed the new impetus for rapid development of the architecture and urban planning, more broadly, for relative industries and educations.New paradigms and research methodologies are established for the urban planning and designing in this new environment and spatial quantitative analysis has become an indispensable part of the designing process.Using internet thinking to explore possible innovations in teaching methods has become a hotspot of the educators in Urban Planning.This paper has attempted to propose new teaching methods, which is essential in the new environment for the education of Architecture and Urban Planning, from the perspectives of quantitative cognitions on the architectures and city layouts.The outcomes of this research could be considered as a reference for the featured professional education in Architecture.
Learning User and Item Representations for Recommender Systems

The fields of Recommender Systems (RS) and Information Retrieval (IR) are closely related. A Recommender System can usually be seen as a specialized Information Retrieval system where the information need is implicit in the user profile. This parallelism has been exploited in the past to transfer methods between fields. One popular approach is to put the standard bag-of-words representation of queries and documents in IR at the same level as the user and item representations obtained from the user-item matrix in RS. Furthermore, in the last years, new ways of representing words and documents as densely distributed representations have risen. These embeddings show the ability to capture the syntactic and semantic relationships of words and have been applied both in IR and natural language processing. It is our objective to study ways to adapt those techniques to produce user/item representations, evaluate their quality and find ways to exploit them to make useful recommendations. Moreover, we will study ways to generate those representations leveraging properties particular to collaborative filtering data.
Research and Application of Comprehensive Survey Technology for Transmission Engineering in Shallow Sea Area

To carry out seabed engineering geological survey is one of the important technical measures to ensure the safety of submarine electric transmission lines. Firstly, the characteristics, principles and application scope of several kinds of geotechnical engineering survey techniques were analyzed. On this basis, a comprehensive survey technique for seabed engineering geology is proposed. By applying the comprehensive survey technology to the engineering geological survey of the submarine transmission line routing area in a certain sea area, the engineering geological characteristics of the area and the unfavorable geology and obstacles affecting the line safety are found out, which provides technical guidance for ensuring the transmission line safety. The rationality and applicability of the comprehensive survey technology are verified by practical examples, which can provide reference for other submarine geotechnical engineering survey and promote the development of marine survey technology in China.
Multi-indicators Multi-objective Evolutionary Algorithm with Q-Learning for Real-world Network Optimization

Aiming at the deployment optimization of complex Internet of Things (IoT) systems, we propose a new multi-objective optimization algorithm using multiple indicators with reinforcement learning, called MIEA-RL. In MIEA-RL, a set of evaluation indicators are employed to guide the evolution of population, while a Q-learning method is designed to manage these indicators in an efficient way during the search. To be specific, each candidate indicator is determined by the performance improvement of the population selected by the current indicator. Moreover, the search biases of different indicators can be adaptively balanced according to a Q-learning table. Accordingly, the convergence and diversity can be maintained effectively while the algorithm complexity is not increased. Finally, the MIEA-RL is applied to resolve the real-world IoT optimization instances in the experiment. Results show the proposed algorithm is effective and efficient to handle with these problems.
A Study About Configuration Management Process for Safety DCS Software V&amp;V in Nuclear Power Plant

Software verification and validation (V&V) is the key technology to improve the quality of software in nuclear power plant and ensure the safe operation of DCS. The configuration management (CM) is an important mean to standardize the software V&V process and improve the efficiency and quality of the software V&V. However, in the current configuration management process for safety DCS software V&V in nuclear power plant, the baseline management of input files has some deficiencies. The paper proposes a method for input file baseline management through research standards and combined practical experience, which can provide reference for the CM in subsequent software V&V project.
Model of Forming Mathematical Notional-Terminological Apparatus in Elementary School Children

Terminology is one of the constituents of the scientific knowledge system. Mastering terminology means to learn the extent and content of notions, and also to use these terms in work. The problems of terminology formation were studied by Bogoyavlensky, Galperin, Talyzina. In the studies of Vygodsky, the inner speech derives from conversational speech in a way of changing its function and consequently its structure. Though there has not been developed complete methodic conception of forming terminology apparatus in children, the chapter is intended to describe a model that forms mathematical terminology apparatus in the process of teaching. The main methods of studies were psychology literature analysis, educational process analysis (teaching mathematics), watching and testing elementary school children in Russia.
Comment on “Tyler Warchola, Stefan V. Lalonde, Ernesto Pecoits, Konstantin von Gunten, Leslie J. Robbins, Daniel S. Alessi, Pascal Philippot, Kurt O. Konhauser. Petrology and geochemistry of the Boolgeeda Iron Formation, Hamersley Basin, Western Australia. Precambrian Research, (2018) 316: 155–173”

Reconstruction of the Neoproterozoic to Early Cambrian paleogeography of northeast Asia proposed by Lee et al. (2016, Palaeogeography, Palaeoclimatology, Palaeoecology, 441, 770–786) is based on miscalculated statistical values and/or some radiometric data ignored without rationale. The Gondwana linkage between the Korean Peninsula and the Sino-Korean (North China) Block in their model should be reconsidered.
Construction and Integration of a Quadcopter in a Simulation Platform for Multi-vehicle Missions

Unmanned Aerial Vehicles or UAVs have been growing at a rapid pace due to the huge range of operations they can perform on the field. These vehicles are currently present in military applications, agricultural, rescue missions or telecommunications, among many other fields. However, some of the existing UAV solutions in the market are quite costly, not only monetarily but also in the complexity they entail. The objective of this work is to build a low-cost quadcopter (a type of UAV) and integrate it in a multi-vehicle mission simulation platform. The quadcopter is built with the help of a mounting guide and must be able to perform all basic flight operations. The simulation platform provides a flexible configuration of missions and test scenarios that allows to study the performance of the UAVs. After the integration, we will be able to analyze the interactions between real and simulated UAVs. Several tests (individual and collective) on the components used and interaction with the simulation platform are taken into account to evaluate the performance of the flight and integration with the simulation platform. With the tuning and testing done, it was possible to perform a brief flight and the virtual quadcopter managed to follow the real quadcopter’s movement. With these experiments, we can conclude that it is possible to mount a low-cost quadcopter without sacrificing flight or integration in other systems.
On the Security of Secret Sharing Over a Ring and the Fast Implementation

Secret sharing is the method to share secrets among a group of shares, and the secret can be reconstructed if one obtains a predefined number of shares. The polynomial secret sharing is usually constructed over a field. In this letter, a novel polynomial secret sharing over a ring is proposed. In particular, by choosing a certain ring, the fast Fourier transform can be applied on the encoding of secret sharing. The analysis shows that the proposed secret sharing scheme requires O(N log <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> N) Boolean operations per secret bit, which improves the prior result O(8 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">log* N</sup> N log <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> N) Boolean operations per secret bit. The simulation shows that the proposed scheme is in average four times faster than the conventional approach.
FPGA based out-of-band encryption module with key management system

Security is most important part in data communication systems. Today technologies have introduced different methods and schemes to secure data, financial transactions and other modes of data exchange. Out-of-band is one such mode where authenticity of user is determined by using concept of what you have. This concept can be witnessed in one form by receiving pin codes on registered cell phones to enable financial transaction making it truly out-of-band authentication. This work is about the development of one such device which allows the users to perform out-of-band encryption of sensitive data or documents on Laptop/PC which is running AES-256 algorithm using user controlled keys. The device is used to encrypt sensitive data or documents within the Laptop/PC and output encrypted data back to the Laptop/PC. The same device is used for decrypting the data. The key management system (KMS) is also designed that is responsible for secure distribution of keys.
Multi-Agent Planning under Uncertainty with Monte Carlo Q-Value Function

Decentralized partially observable Markov decision processes (Dec-POMDPs) are general multi-agent models for planning under uncertainty, but are intractable to solve. Doubly exponential growth of the search space as the horizon increases makes a brute-force search impossible. Heuristic methods can guide the search towards the right direction quickly and have been successful in different domains. In this paper, we propose a new Q-value function representation—Monte Carlo Q-value function , which is proved to be an upper bound of the optimal Q-value function . We introduce two Monte Carlo tree search enhancements—heavy playout for a simulation policy and adaptive samples—to speed up computation of . Then, we present a clustering and expansion with Monte-Carlo algorithm (CEMC)—an offline planning algorithm using as Q-value function, which is based on the generalized multi-agent A* with incremental clustering and expansion (GMAA*-ICE or ICE). CEMC calculates Q-value functions as required, without computing and storing all Q-value functions. An extended policy pruning strategy is used in CEMC. Finally, we present empirical results demonstrating that CEMC outperforms the best heuristic algorithm with a compact Q-value presentation in term of runtime for the same horizon, and has less memory usage for larger problems.
Capability‐Maturity Assessment as Performance Improvement: A case study

A capability-maturity assessment (CMA) answers the following two questions: (1) What are the characteristics that high-functioning organizations share? (2) How can those processes be leveraged for a maturing organization? As a process-improvement tool, a CMA provides a standard against which an organization targeted for improvement can be compared. For organizations just beginning the CMA journey, an internal and informal assessment is a low-resource alternative to a formal assessment. This case study details the CMA informal methodology that we adapted from the Software Engineering Institute (2010) for use with the Military Pay and Personnel department of the U.S. Navy. Results of repeated assessments over three years show gradual improvement in organizational maturity along with a simultaneous increase in performance and a decrease in overall resources expended.
EMT: A Tail-Oriented Method for Specific Domain Knowledge Graph Completion

The basic unit of knowledge graph is triplet, including head entity, relation and tail entity. Centering on knowledge graph, knowledge graph completion has attracted more and more attention and made great progress. However, these models are all verified by open domain data sets. When applied in specific domain case, they will be challenged by practical data distributions. For example, due to poor presentation of tail entities caused by their relation-oriented feature, they can not deal with the completion of enzyme knowledge graph. Inspired by question answering and rectilinear propagation of lights, this paper puts forward a tail-oriented method - Embedding for Multi-Tails knowledge graph (EMT). Specifically, it first represents head and relation in question space; then, finishes projection to answer one by tail-related matrix; finally, gets tail entity via translating operation in answer space. To overcome time-space complexity of EMT, this paper includes two improved models: EMT$$^v$$ and EMT$$^s$$. Taking some optimal translation and composition models as baselines, link prediction and triplets classification on an enzyme knowledge graph sample and Kinship proved our performance improvements, especially in tails prediction.
FULLY AUTOMATIC DIGITAL FRINGE PROJECTION MEASUREMENT FOR 3D FACIAL SURFACE

Digital fringe projection technique is widely used in industrial applications with high accuracy and measurement speed. In this study, a fully automatic high-speed digital fringe projection technique is presented to profile 3D facial characteristics. The structured light with fringe pattern is used to be the light source in the measurement system and is projected by a digital light processing projector. The distorted fringe patterns from facial surface are captured by the digital camera. The absolute phase maps are calculated by using phase-shifting and quality guided path unwrapping algorithm. A complete, 3D facial feature is obtained by our measurement. We achieved simultaneous phase acquisition, reconstruction and three-dimensional (3D) exhibition at a speed of 0.5[Formula: see text]s. This technique may provide a high accuracy and real-time 3D facial measurement for biometric verification.
Research on Practice Teaching Reform of Editing and Publishing Major Under the Background of Media Convergence

With the continuous progress of digitalization and information technology, editing and publishing education is also facing changes. The current society needs a large number of modern digital publishing talents. Editorial and publishing education should adhere to the training of digital publishing talents as the center, constantly adjust and optimize the training objectives, training methods and curriculum settings, improve the professional quality of teachers, and cultivate high-quality digital publishing talents.
Analysis of Current Situation and Influencing Factors of Teaching Informationization in Colleges and Universities—Taking a University in Yunnan Province as an Example

This paper first expounds the meaning of teaching informationization in colleges and universities. On this basis, it analyzes the influencing factors of information-based teaching in colleges and universities, focusing on discussing issues existing in the process of teacher informationization and student informationization and their causes, and put forward some opinions and suggestions on how to improve the level of information-based teaching in colleges and universities.
Empirical Evaluation of Visual Graph Analytic Techniques

Visual Graph analytics is one of the best sources for creating its remarkable, distinct impact in the field of data science. In most new time graph analytics and big data has fascinated a wide range of attention from the researchers and scientists from all over the world. By using the most advanced tools for the graph, analytics can lead the most useful and productive results in various domains which include life sciences, business, computer sciences, engineering and so on. Biological data can be represented in interpretable form when exposed to graph analytic tools which may lead to meaningful insights. This research paper is aimed for the empirical evaluation of three tools MEME suite, DMINDA, and Neo4j. In this paper, we have various research objectives such as a collection of datasets from heterogeneous biological data sources, data integration, and formation of the new dataset (MYBIOGRID). Design the queries in Neo4j using Cypher Query Language in order to visualize MYBIOGRID using Property Graph Model. Determine the relationships in the dataset, based on path analysis and centrality analysis; uploading data in MEME suite and DMINDA for motif elicitation. The result from this study indicates that visualization of similarity matrix of repetitive patterns thus representing the most similar and least similar patterns in the sequence shown in a conclusion table. Neo4j graph databases play a vital role in graph analytics but in memory storage makes analysis very lime to consume for the massive bulk of data sets. Each tool has its specific parameters making it a good candidate for analysis.
Hand Gesture Detection and Its Application to Virtual Reality Systems

Detecting hand gestures can provide a useful non-contact interaction tool with machines and systems and it has been employed for a wide range of applications. Recently, smart glasses and Virtual Reality (VR) headsets become viable solutions for various training applications ranging from surgical training in medicine to operator training for heavy equipment. A major challenge in these systems is to interact with the training platform since user’s view is blocked. In this paper, we present hand gesture detection using deep learning as a means of interaction with the VR system. Real world images are streamed by a camera mounted on the VR headset. User’s hand gestures are detected and blended into the virtual images providing more immersive and interactive user experience.