Reviewerly/exHarmony huggingface dataset:
Elliptic divisibility sequences over the Edwards model of elliptic curves

In this work, we use division polynomials on Edwards elliptic curves to construct elliptic nets of rank one called elliptic divisibility sequence on this curve. Introduced by Morgan Ward, elliptic divisibility sequence on elliptic curve are used for solving the elliptic curve discrete logarithm problem (ECDLP). Moved on rank 2, Elliptic Nets algorithm via elliptic nets associated to Weierstrass elliptic curves are useful for the computation of bilinear maps (called pairings) defined on the groups of points of elliptic curves and very useful to the construction of cryptographic protocols.
Effectiveness of Contact Tracing to Reduce Fatality from COVID-19: Preliminary Evidence from Colombia

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Adaptive Enhancement Technology for Screen Content Photos

Recent years have witnessed the widespread applications of mobiles and other portable electronic devices, involving a variety of screen content photos. Different from natural scene photos, screen content photos are composed of more lines, fewer colors and unique text messages. Thus, it is difficult to realize the satisfactory enhancement effect of screen content photos using traditional image enhancement technology since they are designed for the natural scene. In this paper, we develop a novel enhancement model for screen content photos by considering text and picture separately. To be specific, we first use a fully convolutional network to divide a screen content photo into three independent parts: picture region, foreground text region, and background. Second, an optimal modification of histogram is used to automatically enhance the picture region’s contrast, and the guided image filter is used to enhance the foreground text region. Third, the enhanced picture region, the enhanced foreground text region, and background are fused to obtain the final enhanced image. Experimental results show that our model has produced less noise and derived outstanding enhancement effect than the popular enhancement techniques.
An Analysis of Dehazing Methods with Detail Fusion Combination Technique

The proposed Detail Fusion Combination Technique (DFC) has an objective to reduce the haze in a single image whilst preserving the image quality. The result of the proposed technique has been compared with other state-of-the-art dehazing approaches and evaluated with image quality assess- ment. Various image quality assessment methods such as the Mean Squared Er- ror (MSE), Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity Index (SSIM) have been used to test the veracity of the result. Each resultant image has been evaluated with its corresponding ground truth counterpart respectively. Additionally, auxiliary datasets without ground truth images have been used with the proposed dehazing method in order to show the image quality qualita- tively.
The distribution of the number of distinct values in a finite exchangeable sequence

Let Kn denote the number of distinct values among the first n terms of an infinite exchangeable sequence of random variables (X1,X2,…). We prove for n=3 that the extreme points of the convex set of all possible laws of K3 are those derived from i.i.d. sampling from discrete uniform distributions and the limit case with P(K3=3)=1. We also consider the problem in higher dimensions and variants of the problem for finite exchangeable sequences and exchangeable random partitions.
PHILOSOPHICAL CONNOTATIONS OF THE LEADERSHIP PHENOMENON

The article focuses on the phenomenon of leadership in philosophical discourse. Philosophical retrospection of the concept of "leadership" as a philosophical phenomenon and its systematic analysis is carried out. Philosophical connotations of the phenomenon of leadership in the dynamics of social and political processes of modern times are being defined. In modern society, the well-formed image of leaders of organizations, movements and etcetera an important role. Leadership is a universal phenomenon of social life. It is present in any sphere of human activity that requires stratification: the separation of leaders and subordinates, leaders and followers. In modern science, where there is a commonality of initial positions, leadership is characterized by ambiguity: as a social relationship of domination and subordination in a group or organization (sociology); as a characteristic of the figure of a leader and its impact on others (psychology); as effective and successful innovations in business, dominance in enterprise performance (economy); as developing vision, decision-making, empowerment and direction of people towards specific goals (management); as a process of human interaction in which authoritative people wield real power, exerting legitimate influence on a society that voluntarily gives them part of its political power and rights (political science). The essence of leadership reveals its numerous concepts and theories that have evolved in the history of philosophy and social philosophy. Classical theorists tried to understand and develop the ideal concepts of leadership. Modern researchers are not analyzing the ideal of leadership, but what it is. The philosophical understanding of leadership can be seen, first, as a form of power held by one individual or group of individuals; secondly, as a social position of decision-making; thirdly, as an influence on others.
A Low-Complexity End-to-End Stereo Matching Pipeline From Raw Bayer Pattern Images to Disparity Maps

Conventional computer vision algorithms, including stereo matching algorithms, take finely rendered color images as input. However, existing image signal processing (ISP) pipelines for color image generation are designed for photography with a goal of generating pleasing images for human eyes. This paper describes a new end-to-end pipeline for stereo matching from raw Bayer pattern images to disparity maps with customized ISP. Unlike conventional stereo matching systems which need a complete ISP module to render full-size standard RGB (sRGB) images, a subsampling-based demosaicing-downsampling (SDD) operation is introduced in the proposed pipeline to demosaic and downsample the Bayer pattern images. The resultant half-size color image pairs are processed with simple denoising and tone mapping algorithms to generate the final input images of stereo matching algorithms. It is found that the simple nearest neighbor upsampling method is good enough to generate the final full-size disparity maps. Experimental results show that the proposed pipeline is capable of generating comparable or even better stereo matching results than the conventional pipeline. By skipping most of the unnecessary ISP steps and reducing the size of input images, the computational complexity of the end-to-end stereo matching pipeline is significantly reduced.
Marketplace-Level Domain Ontologies

Abstract To enable semantic interoperability with external services and platforms, the Virtual Materials Marketplace (VIMMP) project has developed a system of marketplace-level domain ontologies, supporting the ingest and retrieval of data and metadata at the VIMMP marketplace front end; these ontologies are expressed in OWL2 using TTL notation [1]. Internally, VIMMP uses the marketplace-level domain ontologies as a part of its approach to data management, underlying the interactions with users. This chapter and the subsequent two chapters present ontologies from the VIMMP project and their relation to other work, including other ontologies.
SAFE – Secure Aggregated Frequency Estimates

We propose a system for privacy-aware machine learning. The data provider encodes each record in way that avoids revealing information about the record's field values or about the ordering of values from different records. A service provider stores the encoded records and uses them to perform classification on queries consisting of encoded input field values. The encoding provides privacy for the data provider from the service provider and from a third party issuing unauthorized queries. But the encoding makes regression-based and many tree-based classifiers impossible to implement. It does allow histogram-type classifiers that are based on category membership, and we present one such classification method that ensures data sufficiency on a per-classification basis.
Deep Learning Model for Recognizing Text in Complex Images

Recognition of text from complex background images is a challenging task due to the large variations in background, texture, font, and illumination conditions. Text can be detected easily from those images containing less background complexity. There are a few applications that detect the text from images. The accuracy obtained is low for the complex background images. To improve the accuracy, convolutional neural network is implemented. Basically, the proposed approach consists of three parts. At first, the text is detected from a complex background. Then the text is extracted from the image using Tesseract. Finally, all the detected words are stored in a text file. Then the text is converted into an audio file. The proposed system reads the text from the image with the aim to provide assistance for visually impaired persons.
OntoBelliniLetters: A Formal Ontology for a Corpus of Letters of Vincenzo Bellini

In this paper the formal OntoBelliniLetters ontology is described concerning the corpus of Vincenzo Bellini’s correspondence letters kept at the Belliniano Civic Museum of Catania. This ontology is part of a wider project - the BellinInRete project - one of whose aims is the development of a more general and complete ontology for the whole Vincenzo Bellini’s legacy preserved in the Museum. The main concepts and relations building up the ontology knowledge base are described and discussed and hints for their implementation by means of the standard OWL-2 description language are presented. The ontology schema is inspired by the CIDOC Conceptual Reference Model (CIDOC CRM).
The Role of Transcreation in Corporate Communication

In a globalized world, companies need to have their online information linguistically and culturally adapted to access international markets. Transcreation is an interlingual creative re-interpretation of a text made considering the linguistic and cultural differences between the target and the original audiences. One of the main sources of corporate information is the corporate website. The US healthcare sector is one of the major industries in the world. Hence, studying the characteristics of their dissemination of corporate information is relevant to know the keys of a fruitful corporate communication. The main objective of this chapter is to identify the keys of a web transcreation process. It is divided in 1) to elaborate a set of indicators for evaluating web transcreation strategies and 2) to apply these indicators to a corporate website to exemplify their functioning through a case-study. The website of the company Pfizer is analyzed. The original US-English and the Spain-Spanish websites are compared. The analysis provides the keys to a successful transcreation process.
Geologic Modelling Using Augmented Reality

Abstract An augmented reality (AR) system is presented which enhances the real-time collaboration of domain experts involved in the geologic modeling of complex reservoirs. An evaluation of traditional techniques is compared with this new approach. The objective of geologic modeling is to describe the subsurface as accurately and in as much detail as possible given the available data. This is necessarily an iterative process since as new wells are drilled more data becomes available which either validates current assumptions or forces a re-evaluation of the model. As the speed of reservoir development increases there is a need for expeditious updates of the subsurface model as working with an outdated model can lead to costly mistakes. Common practice is for a geologist to maintain the geologic model while working closely with other domain experts who are frequently not co-located with the geologist. Time-critical analysis can be hampered by the fact that reservoirs, which are inherently 3D objects, are traditionally viewed with 2D screens. The system presented here allows the geologic model to be rendered as a hologram in multiple locations to allow domain experts to collaborate and analyze the reservoir in real-time. Collaboration on 3D models has not changed significantly in a generation. For co-located personnel the approach is to gather around a 2D screen. For remote personnel the approach has been sharing a model through a 2D screen along with video chat. These approaches are not optimal for many reasons. Over the years various attempts have been tried to enhance the collaboration experience and have all fallen short. In particular virtual reality (VR) has been seen as a solution to this problem. However, we have found that augmented reality (AR) is a much better solution for many subtle reasons which are explored in the paper. AR has already acquired an impressive track record in various industries. AR will have applications in nearly all industries. For various historical reasons, the uptake for AR is much faster in some industries than others. It is too early to tell whether the use of augmented reality in geological applications will be transformative, however the results of this initial work are promising.
Motion Recognition System of Physical Aggression Behavior in Classroom

In order to detect the physical aggressive behavior of students in the classroom early, a motion recognition system is proposed in this paper. This motion recognition system can detect some physical aggression to provide teachers with early resolution of disputes to reduce greater harm. The system first uses monitors to monitor the movements of the students in the classroom and obtains the image of the body by background removal and saliency map technologies. Secondly, the velocity of the body movement is detected, and the velocity value is used as a judgment to determine whether it is physical aggressive behavior. Finally, a machine learning based confusion matrix is used to verify the accuracy of the proposed method. The experimental results confirm that the system can accurately detect the physical aggressive behavior of the collected clips.
Automotive Big Data Pipeline: Disaggregated Hyper-Converged Infrastructure vs Hyper-Converged Infrastructure

Big data disrupts everything it touches, but automotive is probably one of the top industries that enjoy and leverage the benefits. The Automotive Big Data Pipeline (ABDP) is a Big Data pipeline base on the automotive use case and is required to scale up agile and high performance in real-time or in batch. Nonetheless, there're many alternative infrastructure designs but lack of knowledge, which fits the best for the automotive domain. It leads this paper into a question: What kinds of infrastructure design could provide better performance for the ABDP?In this paper, we introduce two well-known infrastructure designs called Hyper-Converged infrastructure (HCI) and Disaggregated Hyper-Converged infrastructure (DHCI). HCI combines standard data center hardware using locally attached storage resources to create fast, common building blocks. However, does single standard hardware fit all the requirements? DHCI scale independently from compute and storage provides an option. It provides a more cost-efficient and flexible solution; however, there is no comparison from the performance point of view. Therefore, to address it, our objective is to conduct an empirical performance comparison to see which one performs better.The experiment result shows that DHCI performs almost the same as HCI on CPU utilization, memory, and network consumption. However, regarding storage and running time metrics, DHCI performs slightly higher storage throughput, IOPs, and less running time than HCI.
Courts and the mediation of public resource (AB) use during elections in Malawi

The (ab)use of public resources during elections in Malawi is a recurrent phenomenon. The judicial mediation of the (ab)use of public resources has, however, not been extensive. In instances where courts have intervened, their pronouncements have done little to stem the practice, especially by incumbents. This paper interrogates the judicial regulation of the (ab)use of public resources during elections in Malawi. Among other things, it establishes that state media remains one of the most highly contested resources during elections. The paper demonstrates that the judicial understanding of public resources is narrow and may shield politicians from censure. In addition, political actors in Malawi seem interested in questioning the (ab)use of public resources only in the period immediately preceding polling without concern about any (ab)use during the rest of the electoral cycle.
LET-Decoder: A WFST-Based Lazy-Evaluation Token-Group Decoder With Exact Lattice Generation

We propose a novel lazy-evaluation token-group decoding algorithm with on-the-fly composition of weighted finite-state transducers (WFSTs) for large vocabulary continuous speech recognition. In the standard on-the-fly composition decoder, a base WFST and one or more incremental WFSTs are composed during decoding, and then token passing algorithm is employed to generate the lattice on the composed search space, resulting in substantial computation overhead. To improve speed, the proposed algorithm adopts 1) a token-group method, which groups tokens with the same state in the base WFST on each frame and limits the capacity of the group and 2) a lazy-evaluation method, which does not expand a token group and its source token groups until it processes a word label during decoding. Experiments show that the proposed decoder works notably up to 3 times faster than the standard on-the-fly composition decoder.
Text Image Deconvolution Using Re-blurry Process And $L_{0}$ Norm

For single image blind deblurring issue, we need to estimate the kernel and the latent image from an observed blurry image. It is well known that the statistical results of clear text image with re-blurring process is very different with that of blurry text image. Furthermore, according to the prosperity of text image, the L0 norm has been proofed effectively in text image deblurring. Therefore, inspired by observing distinct properties of text image with or without re-blurring process, we propose a new deblurring method to process text image by using the re-blurry process and L0 norm. First, we employ the proposed regularization terms to the image deblurring framework. Then, we propose an effectively optimized method to estimate kernel and latent image. Finally, comparing with the state-of-the-art methods are evaluated quantitatively and qualitatively. In conclusion, the proposed method performs favorably against the state-of-the-art methods on processing blurry text images.
Data-to-text Generation via Planning

Abstract Planning based text generation from structural data is an emerging approach that manages to plan for “what to say.” Existing methods can not dynamically adjust the planning, because they generate complete plans statically without considering the result of surface realization. To address this issue, we propose a model that conducts dynamic text planning and surface realization alternately. In each sentence’s generation, our model first plans the records according to the generated text and the plan history, then realizes the sentence conditioned on the corresponding plan. Experimental results demonstrate that our model performs better on both text planning and text generation. Our model with the dynamic planner achieves impressive results on the E2E dataset.
Approaches to the application of homomorphic encryption in sensor networks

Abstract This paper describes the basic principles of the sensor network. The article characterizes the most common types of attacks on wireless sensor networks. The most commonly used protocols of sensor networks are presented. Special attention is paid to schemes of partially homomorphic encryption and fully homomorphic encryption schemes. An approach to the implementation of sensor network protection using the joint use of a fully homomorphic encryption algorithm and a symmetric block encryption algorithm is proposed.
Payroll System Design With SDLC (System Development Life Cycle) Approac: Payroll System Design With SDLC (System Development Life Cycle) Approac

The HR technologies are predominantly used for HR administrative applications, including payroll and benefits administration, this research has profound implications on the evaluation of their effectiveness. A failure to pay people on time and the right amount can cause immense employee dissatisfaction and distress which in turn can severely dent the employer branding.By adopting the system development life cycle (SDLC), this study captures the key factors that should have been taken into account in designing, implementing and rolling out the new payroll system at PT. Faramiga Sindo Energi. The factors that contribute to the success or failure of project implementation are the same which reinforce their reliability and validity.By using the payroll system, the resulting payroll information is more complete, efficient, fast and precise than the previous system which always experiences delays in presenting payroll report information. With the implementation of the program that has been designed, the system can provide convenience in the process of calculating salaries and can find out the salary report quickly and can be requested at any time when needed.
The Extending the Knowledge Base of the Intelligent CAD of a Design Organization Using Semantic Analysis of Wiki-Resources

This article describes the proposed model of the domain ontology core domain using the products of the FSPC Mars as an example. The article presents an algorithm for automatically extending the core of the OWL ontology using the semantic analysis of the enterprise’s internal wiki resources. The statistical algorithms TF-IDF and C-VALUE are used to extract single-word and verbose terms from wiki pages. Relationships between objects embedded in wiki pages and resulting semantic relationships between terms located on the same wiki page are retrieved when extending the knowledge base. A feature of the proposed algorithm is the solution of the problem of terms ambiguity. This problem was solved by comparing the context sets of terms of homonyms wiki-pages. The software was developed to create an organization’s semantic network based on the ontology core to evaluate the effectiveness of the developed model and algorithm. An extended ontology is created automatically based on user parameters. The accuracy of the generated semantic network was 70%.
INFORMATION TECHNOLOGY (ENGAGEMENT, HYPE) - A VOLUNTARY ROAD LEADING TO CONTROL ON THE INTERNET...?!

The article presents a study of new information technologies (engagement and hype). The forms and methods of involving people in the Internet space are presented, in which some people are offered new technologies for development, self-improvement, study, business, communication, and others are offered an "information prison". The options that allow everyone to determine their own way in the Internet space are presented either.