Reviewerly/exHarmony huggingface dataset:
RUBRICS AND FEATURES OF INFORMATION PRESENTATION IN THE INTERNET MEDIA “UKRAINSKYI TYZHDEN’”

The article describes the features of the selection of headings in the internet media of the “Ukrainskyi tyzhden’”. Today, for modern journalists, the issue of not only the diversity of rubrics in internet publications, but also the compliance of rubrics with the needs of readers is relevant. To do this, the article analyzes which rubrics journalists prefer in the first place. What names of headings do they choose. How they prepare materials for a specific heading. Some journalists like to repeat the names of columns, like to take these names from other media. But it is not right to do like this. Each media must be unique. It doesn’t mean that journalists can not cover the same information. Of course, the information will always be the same, because all the media write about the same things, according to events. But no matter which information, because the main is how it is presented. First of all, it should be the most important information that people need. This should not be plagiarism from another publication. This must be a unique presentation of the material not in a short form. The material should be presented clearly and distinctly, at the same time, interestingly. Every journalist must remember that important skills that a modern journalist should possess are first and foremost literary ability, language and style of the author, the ability to express their thoughts and reveal the position of another, the ability to accurately and vividly tell about the event, to convey the fact, evaluate and explain. Also it is necessary to notice that the internet media “Ukrainskyi tyzhden’” were taken to study the materials. “Ukrainskyi tyzhden’” has a special approach to the selection of headings. During this research we noticed that there are only five headings in this internet media, including: “Articles”, “Columns”, “Photo Report”, “Magazine”, “Press Releases”. The brightest rubric is “Articles”. It has many subheadings. One of the most interesting is “Pandemic”. Also it is worth to notice that all materials from “Articles” rubric are suitable for the names of headings. Very good subheadings are “Politics” and ”Economy”, a good subheading also is “World”.
Pembuatan Motion Comic Perjalanan Hidup Ir. Sukarno

Ir.Sukarno was an important figure in Indonesia. He was not only the first president in Indonesia, but he also the founder of Pancasila. Unfortunately, the fifth graders interest in learning his biography is so weak. It is because the media used in teaching-learning process is full of texts and visualization in the explanation is not provided. To enhance student interests in learning Ir.Sukarno’s biography, it is necessary to apply an alternative media which is fascinating for students. Getting to know the problem, the researcher did analysis toward a certain media and particular needs of system, so the researcher designed Motion Comic Application dealing with the biography of Ir. Sukarno for fifth graders of Elementary school. The phases from designing characters to designing pages were implemented through this final project. The Motion Comic application regarding to Ir.Sukarno’s biography has several optional menu such as chosen stories, synopsis, figures, and credits. The menu of chosen storiesconsists of four motion comic videos while the menu of synopsis composes four summaries of each video. Further, the menu of figures talks about characters involved in the stories. The menu of credits consists of creator’s information two advisors, and the sources of audios applied in the Motion Comic of Ir.Sukarno’s biography. This application was implemented by using Adobe Illustrators CS6, Adobe Flash Professional CS6, Adobe Effect CS6, and Garage Band. After conducting the implementation of the application, the researcher employed an experiment and evaluation. The result shows that Motion Comic application of Ir.Sukarno’s biography is appealing and can trigger young learners to recognize the life stories of Ir. Sukarno.
Opinion Targets and Sentiment Terms Extraction based on Self-Attention

Opinion targets and sentiment terms extraction is a key task in aspect-level sentiment analysis. Existing researches have shown that using the dependency structures of reviews helps to complete the task. In this paper, we present a novel opinion targets and sentiment terms extraction model based on self-attention. The proposed model learns the contextual feature of each token in a review through a LSTM network, and a self-attention mechanism is used to directly capture the relations between any two tokens in a review, thus the global dependencies and internal structure of reviews can be modeled better. Experiments results on two benchmark datasets show that the proposed model achieves a better performance than current state-of-the-art in opinion targets and sentiment terms extraction task.
Future Teachers Training to Use the Internet Network for Developing High School Students’ Scientific Capabilities

Nowadays the Professional Standard of a Teacher is being implemented in the Russian higher education. Special importance is acquired to formation of scientific and methodological readiness of pedagogical specialties students to use the Internet network. Acquired skills will prove useful in a teacher’s career to develop high school students’ scientific capabilities when teaching at school. The development of indicators of scientific and methodological readiness of teachers for the above-mentioned activity and research culture of high school students as well as the design and implementation of pedagogical conditions of formation of scientific and methodological readiness of future teachers in the considered context is based on the culturological approach. The research methods include survey methods, assessment of the measure of coherence between the manifestations of the indicators of the investigated scientific and methodological readiness with the help of K. Pearson criterion. A survey of Russian teachers working in profile classes of high schools showed the following items: 53% of teachers have a reproductive or adaptive level of scientific and methodological readiness to use the Internet network for the development of scientific capabilities of their high school students which were evaluated according to three criteria: motivation, technological readiness and creative activity. The article presents materials revealing the essence of pedagogical conditions for the formation of scientific and methodological readiness of students to use the Internet for developing scientific capabilities of high school students. The authors emphasize the importance of implementing the results of pedagogical research in university practice and using them in the work of students of pedagogical specialties. The identified pedagogical conditions of formation of future teachers’ scientific and methodological readiness to use the Internet network in the development of scientific capabilities of high school students serve as the basis for the emergence of new pedagogical technologies.
The effects of pattern screen surface deformation on deflectometric measurements: a simulation study

Phase-measuring deflectometry (PMD) is an optical inspection technique for full-field topography measurements of reflective sample surfaces. The measurement principle relies on the analysis of specific patterns, reflected at the sample surface. Evaluation algorithms often model the respective pattern screen as a planar light source. However, the 3200 pattern screen in our inspection setup exhibits a central bulge of its surface of about 2–3mm. This paper presents a simulation framework for PMD to evaluate the effects of a deformed screen surface. The idea is to simulate image data acquired with screen surface deformations and to examine the effects on the PMD evaluation results. The simulated setup consists of a 3200 pattern screen with an adjustable central bulge height of 0–3mm and two cameras with a field of view (FOV) of approximately 225mm by 172mm on the sample surface. A first experiment examines the reconstruction errors for a planar sample surface if the reconstruction algorithm uses perfect calibration data (i.e. the same parameters used for the simulated image acquisition). The reconstructed surfaces exhibit a tilt with a maximum height difference of 174 μm across the FOV. A second experiment repeats the reconstruction process of the same sample surface, using camera parameters determined in a simulated calibration process. The resulting surfaces possess irregular, wave-like errors with amplitudes of up to 9 μm in the FOV. The presented simulation results reveal the accuracy limits if a deformation model of the pattern screen is not explicitly included in the reconstruction process.
The genesis of IT tools in making management decisions of the university admission committee

The article discusses the issue of the dynamics of changes in IT tools that have been and are used to make management decisions in the work of the university admission committee. The main directions of the work of the admission committee are highlighted: organizational and methodological, technological, the actual admission campaign and generalization, as the final stage at which the results of the admission campaign are summed up. The features of each of the directions are highlighted and the IT tools that were used for them are indicated. It is shown that over the past two decades, IT tools have undergone drastic changes, which are associated with an increase in the functionality of the admission committee. Arguments are given in support of the thesis that the solution for automating the management activities of the university, in particular for the admission campaign, over the past years has been a domestic software on the 1C:Enterprise platform — the 1C:University system. The article presents the stage-by-stage coordination of the admission campaign — from planning and forming the required list of documents (application of the applicant, receipt, examination sheets) to processing information about entrance examinations and USE results, forming enrollment orders. It is shown that the 1C:University system occupies an important place in the automation of many processes taking place in the admission office of the university. Online services that are important for the organization of the admission campaign are described.
VFep: 3D Graphic Face Representation Based on Voice-based Emotion Recognition

Human communication on the Internet is increasing as a substitute to direct human interaction in a physical space. This trend is expanding particularly with the COVID-19 pandemic. Furthermore, presenting the face expressed in 3D graphics to the communication partner is preferred owing to the discomfort felt in showing the actual face of the communicating person. However, showing emotional expressions with a 3D graphic face is difficult. To overcome this problem, we design and implement Voice to Face Expression (VFep) that analyzes the speaker's voice signal, recognizes the emotion of the speaker, and reflects it in the 3D model of the face in real time. In this paper, the design and implementation of VFep and the preliminary evaluation results are described.
Cloud-enabaled Multimodal Knowledge Modeling and Acquisition for Education and Learning (KaaS)

Realization of a cloud enabled Knowledge modeling as a Service (KaaS) supports acquiring, managing and sharing knowledge through different types of sources. Cloud computing enables its users to access and edit their data easily without any administration and software development expenses and difficulties. In this paper, an overview and implementation results of the concept called Knowledge Forge is described. The proposed concept of this research is successfully tested and applied in the representation and management of job knowledge (competences) towards the assessment of talent's proficiency. This can also be used for modeling of graduates and students proficiency in order to identify their competence gaps and assign proper learning sources to them in order to improve their competitiveness. The Knowledge Forge can be extended easily to a wide variety of applications in order to enable further knowledge formats and application areas. Thereby, new formats use their own graphical interface and methods, while no changes in the system itself are required. The main goal of this research is to enable skilled workers and knowledge engineers to search for, modify and connect different formats of knowledge(e.g. unstructured knowledge). Neither users nor administrators have to care about the data format, so a search may show better results out of all stored data along with external search results provided by web search engines. The result of this work is a framework for all KaaS purposes. Although its use is limited at the moment it creates a basis for new applications in several areas. Further work can enhance the functionality or simplify the enhancement process to enable even the users to create their own applications.
Privilege-Escalation Vulnerability Discovery for Large-scale RPC Services

RPCs are fundamental to our large-scale distributed system. From a security perspective, the blast radius of RPCs is worryingly big since each RPC often interacts with tens of internal system components. Thus, discovering RPC vulnerabilities is often a top priority in the software quality assurance process for production systems. In this paper, we present the design, implementation, and deployment experiences of PAIR, a fully automated system for privilege-escalation vulnerability discovery in Ant Group's large-scale RPC system. The design of PAIR centers around the live replay design principle where the vulnerability discovery is driven by the live RPC requests collected from production, rather than relying on any engineered testing requests. This ensures that PAIR is able to provide complete coverage to our production RPC requests in a privacy-preserving manner, despite the manifest of scale (billions of daily requests), complexity (hundreds of system-services involved) and heterogeneity (RPC protocols are highly customized). However, the live replay design principle is not a panacea. We made a couple of critical design decisions (and addressed their corresponding challenges) along the way to realize the principle in production. First, to avoid inspecting the responses of user-facing RPCs (due to privacy concerns), PAIR designs a universal and privacy-preserving mechanism, via profiling the end-to-end system invocation, to represent the RPC handling logic. Second, to ensure that PAIR provides proactive defense (rather than reactive defense that is often limited by known vulnerabilities), PAIR designs an empirical vulnerability labeling mechanism to effectively identify a group of potentially insecure RPCs while safely excluding other RPCs. During the course of three-year production development, PAIR in total helped locate 133 truly insecure RPCs, from billions of requests, while maintaining a zero false negative rate per our production observations.
PCRec: A Private Coding Computation Scheme Based on Edge Computing for Recommendation System

Coding distributed computing (CDC) has been widely used in many fields, such as recommendation systems, image classification, etc.. In the process of applying CDC to the recommendation systems, the user's privacy protection and stragglers (computation latency) should be taken into consideration. Although many solutions have been proposed to address these two considerations, they require additional computation resources that may result in higher communication load. In this paper, we propose PCRec, a Private Coding computation scheme based on edge computing, which solves the problem of the stragglers and the privacy protection in Recommendation systems and further reduces the communication load. Specifically, PCRec aims to protect the privacy and mitigate the impact of the stragglers by utilizing the coding method and obfuscating the data involved in the calculation. Secondly, PCRec uses specific task allocation scheme and coding computation scheme to further reduce the communication load. To evaluate the performance of PCRec, we compare the PCRec with the three related schemes, such as PCMM, PC, UNMDS, in terms of communication load and computation latency. The experimental results demonstrate that the PCRec scheme can reduce the communication load up to 50% and the computation latency by at least 39% compared with other schemes. Therefore, PCRec not only protects the user's privacy and mitigates the impact of stragglers, but also reduces the communication load efficiently.
A Shape Optimization Technique for Medical Images

Abstract Segmentation and restoration are among the primary objectives in the field of medical image processing. Among many methods available today, derivative method specifically domain based derivative method helps immensely in this field of medical imaging. There was a time-based improvement in the aspects of establishing results in a medical image with the aid of topological derivative. Advantage of this method lies in establishing a link between that of the perturbed domain and that of the original domain and solving for the required metrics in the problem. Treating the original domain as the original image and the diseased image to be the perturbed domain, topological derivative helps to solve the problem. Asymptotic analysis also helps in handling both large and small amount of data based on the big-O notation and small-o notation. It also establishes the supremacy of topological derived image metrics to that of other metrics. Here attempts are made for solving problems in medical images with the help of topological derivative method by adapting minimization procedure. Also, the end results are arrived in an outstanding way with help of the receiver operating characteristic curve.
Implementation of quantum gates on quantum dot register

A two-qubit register is simulated using a graph of four quantum dots, each of which has a point contact.One-qubit Pauli gates and two-qubit gates CNOT •CZ and CP(π) were implemented, the effect of dephasing created by point contacts on the accuracy of two-qubit gates was calculated numerically, and this system was calculated using the model potential.
Digits Reverse Order Based Approach for Symmetric Encryption/Decryption of Digital Images

Information transmission from one point to another point has become play an important role In the new era, where information security is utmost important. Due to having more application of multimedia transfer through wireless communication, art of cryptography provides a security of information which is mathematical algorithm to convert messages into an unreadable form. In this manuscript, an encryption/decryption technique is proposed for color image based on pixel shuffling and Arnold transform. The parameter of Arnold transform utilized during encryption process is considered a secret key for the whole process.
In-depth Informatization of Technology Management of Dateng Gorge Water Conservancy Project

As a large-scale livelihood project, the Dateng Gorge water conservancy project needs to consider many factors such as safety, resettlement, environment, energy, and flood control, which involve all aspects of technical problems. Effective management of the technologies can improve the construction efficiency of the project. With the development of science and technology, informatization of technology management becomes an inevitable trend. Especially in the current information sharing era, only with multi-dimensional and in-depth informatization can the increasing needs for technology management be met. In the present study, a multi-dimensional technology management system was established for the Dateng Gorge water conservancy project, featuring full-cycle tracking, information sharing and interdepartmental collaboration. Innovative solutions based on the investment systems, BIM management, three-dimensional application, data certificate CA and mobile office were employed to realize informatized management of technologies in the water conservancy project.
A Novel Framework for Deep Learning from Pairwise Constraints

We consider the problem of deep semi-supervised classification, where label information is obtained in the form of pairwise constraints. Existing approaches to this problem begin with a clustering network and utilize custom loss functions to encourage the learned representations to conform to the obtained constraints. We present a novel framework that seamlessly integrates pairwise constrained clustering, semi-supervised classification, and supervised classification. This approach leverages advances in unsupervised learning by jointly training a Siamese network and autoencoder to learn a representation that is amenable for both clustering and classification. The resulting framework outperforms existing approaches on common image recognition datasets.
Network Space Search for Pareto-Efficient Spaces

Network spaces have been known as a critical factor in both handcrafted network designs or defining search spaces for Neural Architecture Search (NAS). However, an effective space involves tremendous prior knowledge and/or manual effort, and additional constraints are required to discover efficiency-aware architectures. In this paper, we define a new problem, Network Space Search (NSS), as searching for favorable network spaces instead of a single architecture. We propose an NSS method to directly search for efficient-aware network spaces automatically, reducing the manual effort and immense cost in discovering satisfactory ones. The resultant network spaces, named Elite Spaces, are discovered from Expanded Search Space with minimal human expertise imposed. The Pareto-efficient Elite Spaces are aligned with the Pareto front under various complexity constraints and can be further served as NAS search spaces, benefiting differentiable NAS approaches (e.g. In CIFAR-100, an averagely 2.3% lower error rate and 3.7% closer to target constraint than the baseline with around 90% fewer samples required to find satisfactory networks). Moreover, our NSS approach is capable of searching for superior spaces in future unexplored spaces, revealing great potential in searching for network spaces automatically.
Relative Position Representation over Interaction Space for Natural Language Inference

In natural language inference (NLI), attention mechanism has achieved great success, but it does not explicitly model order information between sequential elements. Besides, existing models for NLI tend to neglect positional information of inter-sentence words. In this paper, we propose a novel relative position representation over interaction space, which is called Distance and Direction based Relative Position Presentation (D <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> RPR). It can capture relative distance and relative direction information simultaneously, but also establish potential correlations between non-central words while representing the position of the central word. We incorporate D <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> RPR into self-attention over space to enhance intra-sentence contextual connections. Moreover, D <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> RPR is used to capture relative position relationships between inter-sentence words. In this way, our model can strengthen the semantic connection be-tween sentences. Experiment results show the effectiveness of D <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> RPR and our model achieves competitive performance on SNLI dataset and Quora dataset.