Reviewerly/exHarmony huggingface dataset:
Text Mining and Data Information Analysis for Network Public Opinion

Network public opinion information is massive and complex, and it is difficult to make effective use of manual means. In this paper, a method based on pattern matching and machine learning (PMML) was proposed to analyze the emotional tendencies of network public opinion. Firstly, the key words in public opinion were extracted, then the patterns were extracted and matched, and the emotional tendencies of words were calculated to obtain the pattern sequence vectors. Support vector machine (SVM) classifier was used to classify emotional tendencies. The Internet reviews of Meituan hotel were taken as the experimental subject. PMML method was found to have a high classification performance, with a maximum accuracy of 86.75%. It suggested the effectiveness of the proposed method. Then PMML method was used to classify the emotional tendencies of the collected reviews, and the results showed that the negative emotional tendency was greater than the positive tendency, which showed the inadequacy of Meituan hotel. The experiments in this paper provide some basis for the application of PMML in sentiment analysis of Internet public opinion.
Proof Verification Technology and Elementary Physics

Software technology that can be used to validate the logical correctness of mathematical proofs has attained a high degree of power and sophistication; extremely difficult and complex mathematical theorems have been verified. This paper discusses the prospects of doing something comparable for elementary physics: what it would mean, the challenges that would have to be overcome; and the potential impact, both practical and theoretical.
LBP-Motivated Colour Texture Classification

In this paper we investigate extensions of Local Binary Patterns (LBP), Improved Local Binary Patterns (ILBP) and Extended Local Binary Patterns (ELBP) to colour textures via two different strategies: intra-/inter-channel features and colour orderings. We experimentally evaluate the proposed methods over 15 datasets of general and biomedical colour textures. Intra- and inter-channel features from the RGB space emerged as the best descriptors and we found that the best accuracy was achieved by combining multi-resolution intra-channel features with single-resolution inter-channel features.
Instantaneous in‐band radio frequency interference suppression using non‐linear folders

A front-end adaptive folder with a filter is presented to instantaneously push jammers to higher frequencies while preserving the integrity of small signals of interest. A programmable filter is utilised to further suppress folded jammers for achieving a widely scalable dynamic range over a large frequency range. To achieve maximum programmability with a minimal increase of power and area, combinatorial intrinsic device characteristics are exploited to tune folding points for rapid adaptation to a changing electromagnetic environment.
Parallel Feature Network For Saliency Detection

Saliency detection is widely used in many vision tasks like image retrieval, compression and person re-identification. The deep-learning methods have got great results but most of them focused more on the performance ignored the efficiency of models, which were hard to transplant into other applications. So how to design a efficient model has became the main problem. In this letter, we propose parallel feature network, a saliency model which is built on convolution neural network (CNN) by a parallel method. Parallel dilation blocks are first used to extract features from different layers of CNN, then a parallel upsampling structure is adopted to upsample feature maps. Finally saliency maps are obtained by fusing summations and concatenations of feature maps. Our final model built on VGG-16 is much smaller and faster than existing saliency models and also achieves state-of-the-art performance.
Self-instructed Distance e-Learning of Foreign Languages in the Far North of the Russian Federation

In this paper, we describe the concept “self-development” in a context of philosophical, psychological and pedagogical science. The essence of the process of self-development appears in different philosophical and psychological scientific schools. Definition of self-development of the personality in distance learning of a foreign language is given. Efficiency of distance education technologies for self-development of the personality is shown by practical consideration. Vast territory, distant locality, undeveloped infrastructure and seasonal character of transport lines of communication are the most common features of foreign language teaching in the Far North regions of the Russian Federation, particularly in the Sakha Republic. In these circumstances, we consider Distance e-Learning to be one of the most optimal form of foreign language learning. The article considers Distance e-Learning as a combination of Distance Education and e-Learning which is characterized by the extensive use of Information and Communications Technologies (ICT) in the delivery of education and instruction as well as the use of synchronous and asynchronous online communication in an interactive learning environment or virtual communities, instead of a physical classroom, to bridge the gap in temporal or spatial constraints.
Development of a robust high-speed videogrammetric technique for the measurement of large-scale shaking table tests

High-speed videogrammetry has gradually become the important measurement technique in civil engineering material testing and structure monitoring. This paper presents a robust videogrammetric approach to monitor and analyse the spatial deformations of structures in large-scale shaking table tests, which consists of three main parts as follows. (1) A videogrammetry system with multiple high-speed cameras is established to measure three-dimensional (3D) morphological changes of large structures. (2) An accurate target recognition algorithm is introduced into the measurement scheme, and then the target tracking and matching strategy is proposed in our scheme to calculate the sequential image coordinates of the target points in the high-speed image sequences. (3) The 3D coordinates of the target points can be obtained by the videogrammetric analysis algorithms, and the key structural deformation parameters can be further calculated through the spatiotemporal analysis of the sequential point coordinates. The shaking table test of largescale wooden pagoda as an empirical test is performed to demonstrate the feasibility and reliability of the whole highspeed videogrammetric technique. The experimental results show that the proposed approach can achieve sub-millimeter positioning accuracy of the artificial targets with comparison of high-accuracy total station. Moreover, the credibility of the measured displacement results is further verified by comparison with the results of the high-accuracy displacement sensor.
Adaptation and Implementation of the ISO42010 Standard to Software Design and Modeling Tools

Model cantered software development practices adoption remains limited to small niche domains. The broad development practices remain code centric. Modeling tool complexity is often cited as a significant factor limiting the adoption and negatively affecting user experience. Modeling and design tools complexity are due to multiple factors including complexity of the underlying language, weak support for methodologies, and insensitivity to users’ concerns. This results in modeling and design tools that expose all or most of their capabilities and elements at once, often overwhelming users and negatively affecting user experience. The problem is further exacerbated when a tool supports multiple domain-specific modeling languages that are defined on top of a base language such as UML. In this case, the tool customizations and visual elements necessary to support each language often interfere with each other and further exacerbate the modeling tool complexity. In this paper, we present a novel and systematic approach to reduce the complexity of design and modeling tools by introducing an interpretation and adaptation of the ISO42010 standard on architecture description specific to the software domain. We demonstrate this approach by providing a working implementation as part of the Papyrus opensource modeling framework. In this approach, we leverage the notions of Architecture Contexts and Architecture Viewpoints to enable heterogeneous UML-based languages to be independently supported and help contextualize the exposed tool capabilities. This paper presents the ISO42010 interpretation and adaptation to software design and architecture and a case study with several definitions of architecture contexts. The implementation of this novel approach demonstrates the ability for multiple modeling languages and notations to coexist without interference and provides significant reduction in the exposed capabilities in the UI. Reducing design and modeling tool complexity has a potential to significantly broaden the adoption of modeling and design practices in the software engineering sphere.
sFEA: A Secure Finite Element Analysis Technique

Designers need a way to overcome information-related risks, including information leakage and misuse by their own collaborators during collaborative product realization. Existing cryptographic techniques aimed at overcoming these information-related risks are computationally expensive and impractical even for moderate problem sizes, and legal approaches such as nondisclosure agreements are not effective. The computational practicality problem is particularly pronounced for computational techniques, such as the finite element analysis (FEA). In this paper, we propose a technique that enables designers to perform simulations, such as FEA computations, without the need for revealing their information to anyone, including their design collaborators. We present a new approach, the secure finite element analysis approach, which enables designers to perform FEA without having to reveal structural/material information to their counterparts even though the computed answer depends on all the collaborators' confidential information. We build secure finite element analysis (sFEA) using computationally efficient protocols implementing a secure codesign (SCD) framework. One of our findings is that the direct implementation of using SCD framework (termed as naïve sFEA) suffers from lack of scalability. To overcome these limitations, we propose hybrid sFEA that implements performance improvement strategies. We document and discuss the experiments we conducted to determine the computational overhead imposed by both naïve and hybrid sFEA. The results indicate that the computational burden imposed by hybrid sFEA makes it challenging for large-scale FEA—our scheme significantly increases the problem sizes that can be handled when compared to implementations using previous algorithms and protocols, but large enough problem sizes will swamp our scheme as well (in some sense this is unavoidable because of the cubic nature of the FEA time complexity).
Encryption Principles and Techniques for the Internet of Things

This chapter explores the encryption techniques used for the internet of things (IoT). The security algorithm used for IoT should follow many constraints of an embedded system. Hence, lightweight cryptography is an optimum security solution for IoT devices. This chapter mainly describes the need for security in IoT, the concept of lightweight cryptography, and various cryptographic algorithms along with their shortcomings given IoT. This chapter also describes the principle of operation of all the above algorithms along with their security analysis. Moreover, based on the algorithm size (i.e., the required number of gate equivalent, block size, key size, throughput, and execution speed of the algorithm), the chapter reports the comparative analysis of their performance. The chapter discusses the merits and demerits of these algorithms along with their use in the IoT system.
Exact results for the anisotropic honeycomb lattice Green function with applications to three-step Pearson random walks

The mathematical properties of the lattice Green function for the anisotropic honeycomb lattice are studied, where is a complex variable which lies in a plane, and is a real anisotropy parameter with . This double integral defines a single-valued analytic function provided that a cut is made along the real axis from to . In order to analyse the behaviour of along the edges of the cut it is convenient to define the limit function where . It is proved that the limit functions and can be sectionally evaluated exactly for all , in terms of various elliptic integrals of the first kind , where is a rational function of and u.
Generalized Semimodularity: Order Statistics

A notion of generalized n-semimodularity is introduced, which extends that of (sub/super)modularity in four ways at once. The main result of this paper, stating that every generalized -semimodular function on the nth Cartesian power of a distributive lattice is generalized n-semimodular, may be considered a multi/infinite-dimensional analogue of the well-known Muirhead lemma in the theory of Schur majorization. This result is also similar to a discretized version of the well-known theorem due to Lorentz, which latter was given only for additive-type functions. Illustrations of our main result are presented for counts of combinations of faces of a polytope; one-sided potentials; multiadditive forms, including multilinear ones—in particular, permanents of rectangular matrices and elementary symmetric functions; and association inequalities for order statistics. Based on an extension of the FKG inequality due to Rinott & Saks and Aharoni & Keich, applications to correlation inequalities for order statistics are given as well.
Combining Ultrasound and X-Ray Imaging for Mammography

This study aims at the combination of 3D breast ultrasound and 2D mammography images to improve the accuracy of diagnosis of breast cancer. It was shown that ultrasound breast imaging has advantages for differentiating cysts and solid masses which are not visible in an X-ray image. Moreover, the specificity in X-ray imaging decreases with an increasing breast thickness, so that ultrasound is usually used as an adjunct to X-ray breast imaging. A fully automatic system to obtain both 2D mammography and 3D ultrasound images is used. The alignment of a 2D mammography image in the cone-beam coordinate system and 3D ultrasound image in a Cartesian coordinate system is the essential task in this study. We have shown that deviations up to 23 mm caused by the cone-beam system can be calculated and corrected utilizing the geometry information of the hardware. The multimodal image reading tool is presented in a GUI for clinical diagnosis. The presented setup might lead to a distinct improvement in effciency and add diagnostic value to the acquisition.
Special issue on just-in-time requirements engineering for software integration

This special issue tackles specific challenges of requirements engineering (RE) in agile and interconnected settings. Compared to traditional upfront RE, the practices in agile or open-source software projects tend to be just-in-time, characterized by lightweight representation and continuous refinement of requirements. The special issue features six articles, ranging from conceptual views through analytic reasonings to empirical studies. Altogether, the collection offers important and timely contributions toward advancing our understanding of RE in industrial information integration and Industry 4.0.
Task Intelligence Workshop @ WSDM 2019

The task intelligence workshop at the 2019 ACM Web Search and Data Mining (WSDM) conference comprised a mixture of research paper presentations, reports from data challenge participants, invited keynote(s) on broad topics related to tasks, and a workshop-wide discussion about task intelligence and its implications for system development.
Email Authorship Attribution

Email correspondence is regularly manhandled for directing social designing assaults including spamming, phishing, data fraud, and circulating malware. This is to a great extent credited to the issue of obscurity intrinsic. Finding the authorship of email which can be stated as attribution problem is contemplated as content classification issue where the styles of writing of people are displayed in view of their already composed documents. In this paper, Multiple Association Rules for Authorship Attribution (CMARAA) is proposed to solve the problem of authorship attribution. The proposed method makes the remarkable composition style of features of a person. The experimental evaluation shows that CMARAA classifies with 92% of accuracy being the most accurate algorithm when compared to other classification algorithms for different combinations of authors.
The conference on the global ecological problems held on the occasion of the 155-th anniversary of Vladimir Vernadsky within the framework of the Fourth World Professional Forum “The book. Culture. Education. Innovations”

The author reviews the work of the international conference on the global ecological problems held on the occasion of the 155-th anniversary of Vladimir Vernadsky within the framework of the Fourth World Professional Forum “The book. Culture. Education. Innovations” (“Crimea”). About 40 papers dedicated to VladimirVernadsky, his contribution to the modern science, his ideas and their transformation in the modern world, as well as to the practical experience of the libraries, museums, universities, advanced training organizations, were presented. The contents of the key papers is discussed, the links to the full texts on the RNPLS&amp;T’s www-site are given. Within the conference framework, special events oriented towards teenagers and young adults, the graduates’ session “Solutions for ecological problems”, interactive ecological game, and podium discussion “Do we have the ecological future?”, etc., were held. The author emphasizes that the main conference result is the collaboration plans made between researchers, libraries, museums, universities, non-government organizations to spread Vernadsky’s ideas, as well as the establishment RNPLS&amp;T — V. I. Vernadsky Foundation the joint site to promote new projects and to engage the interested parties.
Development of a dynamic surface shape measurement for magnetic fluid

Traditional measurement techniques such as fringe and stereo projection can hardly measure the black surface shape of magnetic liquid in revolving container which has a cover to prevent the liquid spilling out. To solve this problem, a multi-step measurement method based on linear laser projection is proposed. Modulated laser by synchronous revolving chopper is introduced to obtain the steady projection light curve on the measured location of the magnetic fluid surface. In order to capture the instantaneous reflected light of the projection light curve, a camera used a long exposure time of shooting is used. Taking the advantages of multiple exposure luminance enhancement effect of long exposure time, pictures with high brightness and contrast projection light are obtained. The overall surface shape of the fluid can be reconstructed by many laser projection lines extracted from the pictures captured at different angles of revolving container. A high transparency acrylic cover is adopted to provide good sealing performance and light transmission quality in the experiment. On the base of correction of influence of refractive index of the acrylic cover, the height formula of magnetic fluid surface is derived. The camera installation angle and distance between the camera and the container are not required as the size of container are utilized to calibrate the camera. The relationship between image coordinates and world coordinates is also obtained. According to the height curves of the projection lines and their measuring angles on the container, 3-D surface shape of magnetic fluid is reconstructed. The surface shape is verified indirectly by using the imbalance of the container, and the relative unbalance errors between the measurement results and the results by Shenk dynamic balancing machine under different conditions are between 0.8% and 11%. Another performance experiment on measuring the surface shape of an rubber block indicates that the measurement range of the proposed method is that the slope of the measured surface must be less than 3.94, and the sensitivity is 0.18 mm. All performance of the proposed method is acceptable, so such a complex industrial problem is solved only by a daily digital camera.
A Textual Notation for Modeling and Generating Code for Composite Structure

Models of the composite structure of a software system describe its components, how they are connected or contain each other, and how they communicate using ports and connectors. Although composite structure is one of the UML diagram types, it tends to be complex to use, or requires particular library support, or suffers from weak code generation, particularly in open source tools. Our previous work has shown that software modelers can benefit from a textual notation for UML concepts as well as from high-quality code generation, both of which we have implemented in Umple. This paper explains our extensions to Umple in order create a simple textual notation and comprehensive code generation for composite structure. A particular feature of our approach is that developers do not always need to explicitly encode protocols as they can be in many cases inferred. We present case studies of the composite structure of several systems designed using Umple, and demonstrate how the volume of code and cyclomatic complexity faced by developers is far lower than if they tried to program such systems directly in C++.
Approximate Backbone Subsection Optimization Algorithm for the Traveling Salesman Problem

Approximate backbone subsection optimization algorithm is proposed to solve the traveling salesman problem, for the precision accuracy of the basic ant colony algorithm for solving the larger traveling salesman problem is low. First, traveling salesman problem approximate backbone is obtained by the ant colony algorithm, and then the original traveling salesman problem is sectioned based on the approximate backbone. Then the ant colony optimization algorithm is applied to solve the subsections to improve the precision accuracy of the global optimal solution. The experimental results show that the algorithm is more precision accuracy than the basic ant colony algorithms in the solution of the typical traveling salesman problem.
Feature Based Multivariate Data Imputation

We investigate a new multivariate data imputation approach for dealing with variety of types of missingness. The proposed approach relies on the aggregation of the most suitable methods from a multitude of imputation techniques, adjusted to each feature of the dataset. We report results from comparison with two single imputation techniques (Random Guessing and Median Imputation) and four state-of-the-art multivariate methods (K-Nearest Neighbour Imputation, Bagged Tree Imputation, Missing Imputation Chained Equations, and Bayesian Principal Component Analysis Imputation) on several datasets from the public domain, demonstrating favorable performance for our model. The proposed method, namely Feature Guided Data Imputation is compared with the other tested methods in three different experimental settings: Missing Completely at Random, Missing at Random and Missing Not at Random with 25% missing data in the test set over five-fold cross validation. Furthermore, the proposed model has straightforward implementation and can easily incorporate other imputation techniques.