Reviewerly/exHarmony huggingface dataset:
Semantic-Based Duplicate Web Page Detection

The Internet search has become a regular activity for billions of web users to find information. Users typically rely on search engines for information retrieval. Thus, it has become increasingly important for users to find the best results for their queries. There are nevertheless challenges to provide the most efficient, appropriate, and trustworthy results to the user in every web search environment. But there exist numerous unwanted repetitive web pages that escalate time complexity and indexing space issues; hence, identifying and eliminating such pages become a necessity for the communities responsible for information retrieval and web mining. The main aim for web content mining is to identify the duplicate web page content in web search engine. The literature shows the lack of a complete and time efficient duplicate detection model for web search optimization. The present study has identified this need for an enhanced duplicate web page detection technique to improve web search. Increasing the Web site usability and user satisfaction is the most crucial factors in web page detection scenario.
Self-marketing as a way of boost global competitiveness of a teacher

Digital transformation in modern society incessantly increases the growth rate of investment in the cutting-edge information technologies, which greatly affects the quality of products and services provided. The Russian education system, with the priority goal of modernizing it being to update the teaching staff and reconstruct the system of advanced professional training of educators, is also undergoing radical changes. The process of integrating distance technologies into the structure of pedagogical activity makes significant adjustments to the strategy of teaching students, which leads to re-evaluation of professionally and socially meaningful qualities of a teacher for building effective business relations with consumers of educational services and improving self-competitiveness in the labor market. This requires a fundamentally new approach to selecting an individual educational trajectory that will contribute to the successful development of professional competence of a teacher, which, according to the author, can be achieved by implementing self-marketing.&#x0D; The article considers the author’s scheme of self-marketing of a foreign language teacher developed to assess self-effectiveness – competitive advantages (professionally and socially meaningful qualities) – and provide useful guidelines to fight off competition in the [international] educational industry.
Location YardStick: Calculation of the Location Data Value Depending on the Users’ Context

These days, many apps acquire location data as a way of estimating the user's behavior. As such, there are privacy concerns in using location data. In particular, users who are concerned about privacy may reduce the frequency of location acquisition or turn off the function, even though it degrades the quality of service. On the other hand, the only options available to users are yes-no or either-or ones such as "Always permit background acquisition" or "Permit only while using the app". For example, users who give permission to "Permit only while using the app" are themselves unable to understand how far their own veil of privacy will be lifted. That is, there are no metrics that can help users to understand the value of their own location data. How should the value of location data be determined? This study attempts to answer that question. The difficulty is that the value of a single point of location data depends on the context, such as how much other location data the app holds or when the location data was obtained. We propose a "Location YardStick" (LYS) that calculates the value of location information fairly in context. We confirmed that the LYS score is close to the user's expectations by comparing its results with those of a large online survey of 1300 people, and we conducted case studies in which we calculated LYS on location data acquired in various actual contexts.
Individual Cloud

It will be thought for sure that any kinds of knowledge will be accumulated and enhanced as Unique Cloud and Smart Cloud. And as a result of this phenomenon, the related space for the world will be able to be indulged in the world of getting processed information as a final use of data for a daily life. This is a very comfortable world to live, but, on the other hand, there might be a possibility which there will be many or some who live only under the offered information and knowledge from intelligent computer systems (Mini Cloud, Unique Cloud, Smart Cloud). So, it is very important to have knowledge of us in investigating whether or not Unique Cloud and Individual Cloud are useful enough to use by inspecting from the outside world even though we are to live in the hypothetical world. And here the authors propose a method to resolve some of the problems under these situations by an idea of “Individual Cloud.”
The Weight Distributions of the (256, &lt;i&gt;k&lt;/i&gt;) Extended Binary Primitive BCH Codes with &lt;i&gt;k&lt;/i&gt;≤71 and &lt;i&gt;k&lt;/i&gt;≥187

Computing the weight distribution of a code is a challenging problem in coding theory. In this paper, the weight distributions of (256, k) extended binary primitive BCH codes with k≤71 and k≥187 are given. The weight distributions of the codes with k≤63 and k≥207 have already been obtained in our previous work. Affine permutation and trellis structure are used to reduce the computing time. Computer programs in C language which use recent CPU instructions, such as SIMD, are developed. These programs can be deployed even on an entry model workstation to obtain the new results in this paper.
Probing the limits of quantum theory with quantum information at subnuclear scales

Modern quantum engineering techniques enabled successful foundational tests of quantum mechanics. Yet, the universal validity of quantum postulates is an open question. Here we propose a new theoretical framework of Q-data tests, which recognises the established validity of quantum theory, but allows for more general -- 'post-quantum' -- scenarios in certain physical regimes. It can accommodate a large class of models with modified quantum wave dynamics, correlations beyond entanglement or general probabilistic postulates. We discuss its experimental implementation suited to probe the nature of strong nuclear interactions. In contrast to the present accelerator experiments, it shifts the focus from high-luminosity beam physics to individual particle coherent control.
Introduction. Inquiries in Philosophical Pragmatics: Linguistic and Theoretical Issues

Together with the volume “Inquiries in philosophical pragmatics: Theoretical developments,” this book collects selected contributions to the conference Pragmasophia II held in Lisbon in 2018. The eleven essays of this volume focus on how a linguistic structure or expression manifests a pragmatic phenomenon, and are ordered considering their relationship with the specificity of the context. The first three papers, devoted to the topics of prototype-based generalizations, scalar implicatures, and temporal ordering, propose new insights into pragmatic phenomena considering linguistic behavior independent of the social activity in which it is placed. In the last papers, the analytical and empirical goal becomes predominant. Here, the theoretical advances are considered as instruments for analyzing specific texts, such as marketplace interactions, courtroom speech, schizophrenic discourse, narratives of literary texts for children or deception in movies. In between, three papers devoted to emotive or loaded words bridge the passage from more theoretical to more empirical and context-oriented works.
Integrated Spatio-temporal Storyline Visualization with Low Crossover

A story is a chain of events. Each event has multiple dimensions, including time, location, characters, actions, and context. Storyline visualizations attempt to visually present the many dimensions of a story's events and their relationships. Integrating the temporal and spatial dimension in a single visualization view is often desirable but highly challenging. One of the main reasons is that spatial data is inherently 2D while temporal data is inherently 1D. We propose a storyline visualization technique that integrate both time and location information in a single view. We have developed a timeline-based visualization method that maintains regular ordering of temporal and spatial dimensions. We also developed a heuristic method to reduce excessive line crossovers for large data sets. Through case studies, we show that this visualization method provide a good balance in integrating temporal and spatial dimensions.
Activization of Cognitive Activity of Students in Higher Education Institutions

The article discusses options for enhancing the cognitive activity of students. As a method of enhancing cognitive activity, the proposed method of projects. The analysis of the main provisions of the technology for enhancing cognitive activity through the introduction of project training. It is proposed to use group methods of enhancing the cognitive activity of students. The ways of stimulating cognitive activity are considered. It has been determined that the use of the project method in teaching, as the activation of cognitive activity, gives high positive, emotional satisfaction, develops curiosity, intelligence, speech, logical and imaginative thinking, makes it possible to expand and deepen the level of cognitive activity, to awaken students' desire for in-depth study of educational material, develop the creative abilities of students and is an essential condition for improving the quality of education.
‘’t is ça va dan he’

Abstract This article discusses the adjectivization of the Dutch interjections ça va and ok . argues that this adjectivization process was driven by analogical relations based on broad syntactic categories. A corpus investigation and acceptability judgements show (i) that the adjectival use of ça va and ok has become more frequent since Lemmens’s research, but that their adjectivization is not (yet) completed, (ii) that not only abstract generalizations, but also lower-level generalizations and specific constructions play a crucial role in the adjectivization of both interjections, and, (iii) that ça va and ok already as interjections showed limited grammatical behaviour, making them more susceptible to adjectivization. We argue – contra – that not (only) reinterpretation has led to the adjectivization of both interjections, buth rather their lexical and horizontal links in the constructional network.
Neural Network Weight Compression with NNW-BDI

Memory is a scarce resource and increasingly so in the age of deep neural networks. Memory compression is a solution to the memory scarcity problem. This work proposes NNW-BDI, a scheme for compressing pretrained neural network weights. NNW-BDI is a variation to standard Base-Delta-Immediate [13] compression technique to make it a better fit for neural network weights, using techniques such as quantization, downscaling, randomized base selection, and base-delta-configuration adjustment. We evaluate our algorithm by compressing the weights of a MNIST classification network. Our evaluation shows that NNW-BDI reduces memory usage by up to 85% percent without any reduction in inference accuracy.
Intelligent Cross-Well Sandstone Prediction Based on Convolutional Neural Network

The recent years have witnessed a great success of artificial intelligence applications in geological prospecting, so that the traditional manual work, which is time-consuming and labor-intensive, could be accomplished automatically or at least in a human–machine cooperation way. This letter presents a first attempt in proposing an automatic way to predict the cross-well sandstone that plays a crucial role in formation characterization and reservoir exploration. Such a two-stage framework is composed of i) a convolution neural network (CNN)-based coarse prediction module and ii) a geological experience-based error correction (EC) module. Experiments demonstrate that our proposed module can achieve comparable accuracy as experts.
A Locally Weighted Metric for Measuring the Perceptual Quality of 3D Objects

The increasing use of 3D models in many areas lead us to think about the impact of the different distortions that can affect the 3D object during the rendering process. These deformations are usually evaluated using geometric metrics, which have not a good correlation with human judgment, while the visual perceptual quality of 3D models is necessary. In this context, a new full-reference metric denoted LWRMS is defined in this work. It can predict the distortion score between the original object and its damaged version without taking into account the constraint of connectivity. The proposed metric is defined in order to get a good correlation with the human visual perception coming from a subjective measurement. The numerical experiments are carried out on a known database LIRIS/EPFL General-Purpose database. The quantitative results show a good performance of the proposed metric in comparison with methods from the literature.
A Vital Approach for Smart Home System Using OWL Ontology

Software product line (SPL) features, both variant and reusable ones, have been depicted through numerous ways. Several studies have portrayed the different approaches to model the features of software products. In our paper, we have chosen smart home as the domain to explain the features and characteristics of product line. Our paper has adopted Web ontology approach to propose the relationship between software product line conformations. The dynamic interpretation of different software product line features has been depicted using variants. Feature tree, also called the feature diagram, has been exercised as comprehensive model to model software product line variants. Thus, presenting a graphical way is to represent the feature model using Web ontology approach. The design, analyzation and verification of feature model have evolved over the years. This paper focuses on OWL-DL as a reliable language for showcasing the variant features of SPL. Our paper discusses these essential variant components of smart home domain using Web semantics.
Underwater Image Enhancement Based on Double Pyramid Feature Fusion Mode

The exponential attenuation of propagated light underwater results in unsatisfactory image features, including color distortion, low contrast and blur. To solve these problems, advantages and disadvantages of image histogram equalization and white balance methods were investigated in this study based on an underwater model, and the method of using the original image to attain the first and second images through histogram equalization and white balance, respectively, was proposed. Laplacian pyramid was introduced to decomposite each image and obtain its layered structure, and the Gaussian pyramid mapping to each weight was formed according to normalized weights. At the end of this study, images were reconstructed by pyramid-based fusion under the guidance of image measurement model and normalized weight mapping model. The experimental results demonstrate that this method integrates the advantages of histogram equalization and white balance methods, providing modified image colors and improved color contrast.
Automatic Test Case Generation for Prime Field Elliptic Curve Cryptographic Circuits

Elliptic curve is a major area of research due to its application in elliptic curve cryptography. Due to their small key sizes, they offer the twofold advantage of reduced storage and transmission requirements. This also results in faster execution times. The authors propose an architecture to automatically generate test cases, for verification of elliptic curve operational circuits, based on user-defined prime field and the parameters used in the circuit to be tested. The ECC test case generations are based on the Galois field arithmetic operations which were the subject of previous work by the authors. One of the strengths of elliptic curve mathematics is its simplicity, which involves just three points (P, Q, and R), which pass through a line on the curve. The test cases generate points for a user-defined prime field which sequentially selects the input vector points (P and/or Q), to calculate the resultant output vector (R) easily. The testbench proposed here targets field programmable gate array (FPGAs) platforms and experimental results for ECC test case generation on different prime fields are presented, while ModelSim is used to validate the correctness of the ECC operations.
Perceptual visual security assessment by fusing local and global feature similarity

Selective encryption is an effective technique for multimedia big data encryption. A perceptual metric that takes the human visual system (HVS) into account is necessary for evaluating the visual security degrees of selectively encrypted images. Existing metrics are mainly based on the similarity of structural information which is represented by local spatial contrast features. However, visual security is concerned with not only the distortion of structural information but also the leakage of important visual information. The local features cannot exactly express the leakage of important visual information. This paper presents a perceptual visual security assessment metric by fusing local and global feature similarity. Considering the HVS response, the proposed metric measures in three aspects: the distortion of structural information, the leakage of important visual information, and the changes of frequency components. To measure the distortion of structure information, local pattern similarity is calculated based on the normalized Hamming distance between the local binary pattern (LBP) binary codes. The similarity of the global LBP histogram is computed to evaluate the leakage of important visual information. A lowpass weighted discrete cosine transform (DCT) frequency similarity is presented to detect the changes of various frequency components. Experimental results demonstrate that the proposed metric achieves significantly higher performance and stronger robustness than the state-of-the-art metrics.
Reading tea leaves differently?

This chapter discusses the use of interpretive techniques by the US Supreme Court and by the European Court of Justice in copyright cases. The method of systematic content analysis is used to code the entire body of these cases for the use of any of ten interpretive techniques (or topoi) as identified by MacCormick, Summers and Taruffo. The introductory part discusses the methods used, followed by a brief overview of the particularities of both courts as all readers are not necessarily equally familiar with the workings of both courts. The first part consists of a descriptive overview of both case law corpuses. In the second part, the rationale behind copyright law in both systems are discussed. The third and main part of the analysis consists of a presentation and discussion of the statistical analysis performed on the coding of the cases. It will be shown that both courts use six of the ten interpretive techniques similarly, and four differently: the main differences are to be found in the interpretation techniques that go back to the legislator’s intent. This leads to the conclusion that the interpretation techniques used by both courts fit the underlying, philosophical and thus substantive differences in both systems of copyright law. This insight can contribute to a better mutual understanding of the respective systems across both sides of the Atlantic.
A drawing by Leonardo da Vinci and the shaping of D. Merezhkovsky’s literary reputation

The article considers the background of the little-known letter written by D. Merezhkovsky to Novoe Vremya in 1901 with regard to the novel Resurrected Gods. Leonardo da Vinci [Voskresshie bogi. Leonardo da Vinchi] and establishes the circumstances that prompted such a reaction to V. Burenin’s feuilleton. The novel was written during the period of bitter competition with A. Volynsky, who had authored a study of Leonardo da Vinci’s life. Merezhkovsky’s suspicion that the latter may have plagiarised his original plot resulted in an acrimonious rivalry. In his letter, Merezhkovsky chooses to focus on the author’s ‘scholarly scrupulosity’ and the authoritative opinion of European audiences, who had long acknowledged his writing talent, rather than on prejudiced reviews of his novels penned by newspaper-employed critics. The article argues that what really provoked Merezhkovsky to approach the newspaper was his resentment of unfair allegations, rather than an attempt to defend the authenticity of Leonardo’s drawing. Hostile reviews of his novel in the periodicals contradicted Merezhkovsky’s efforts to create his own reputation as a writer.
Prediction of Covid-19 Infection in Indonesia Using Machine Learning Methods

Abstract Currently, the world is experiencing a prolonged pandemic known as Covid-19. Many prediction models of Covid-19 have been developed by the governments to make the right decisions to control the outbreak. In Indonesia, there is also much research on the prediction of Covid-19 using machine learning methods, which provide the statistics to predict the total cases, the total deaths, the peak and the end of the pandemic. This paper investigates three prediction models: Gaussian Naive Bayes (GNB), and Support Vector Machine (SVM), and Decision Tree (DT) in predicting total cases and total deaths of Covid-19 in Indonesia. First, a preprocessing is applied to change the string data to the numerical dataset using a label encoder. Second, the models are trained using the Covid-19 Indonesia Time Series All Dataset (CITSAD) with 90% and 10% train/test split. The three models are then investigated to predict new cases and new deaths. The evaluation using the CITSAD of ten provinces in Indonesia shows that DT gives the highest accuracy of 93% and provides the fastest processing time of 48.4 seconds.
Development and Research of a Strategic Data Center Management Model

Energy efficiency is one of the most important issues in the design and operation of data centers. Energy efficiency implies efficient and environmentally friendly use of energy, namely heat recovery, flexible cooling management, use of terrain climate to beneData centers should not have transit communications (heating, water, sewer). However, for rooms containing servers, there are requirements for the level of humidity, so the presence of water is necessary at all times. The risk of flooding can be reduced by waterproofing. Y Servers require constant, round-the-clock cooling and heat removal, even if the data center is located on a pole. Therefore, the room must be equipped with an artificial climate system. Temperature and humidity must be monitored. Cabinets and racks should be arranged in an alternating pattern, so that the front side of the cabinets/racks in each row faces the front side of the other row, creating “hot” and “cold” passages. Cold air comes from under the raised floor, hot air goes to the ceiling: this is how air circulation occurs.fit infrastructure, carbon reduction, solar panels, etc.