Reviewerly/exHarmony huggingface dataset:
The History of Systematic Catalogue of the Russian Academy of Sciences Library. The Initial Stage of Creation, 1924—1929

The article, based on the results of planned research carried out in the Department of scientific systematization of literature (DSSL) of the Russian Academy of Sciences Library (RASL), considers the poorly studied period in the history of the RASL systematic catalogue — the second half of the 1920s. The purpose of this article is to reconstruct the initial stage of creation of systematic card catalogue of RASL, basing on archival documents. The author presents the history of the first functional Department of the Library — Systematization Department of the II (Foreign) Branch of the Russian Academy of Sciences Library, organized to complete the systematic card catalogue. The article describes the circumstances of the formation of the Department: existence of two branches of the library (I — Russian and II — Foreign), domestic difficulties, acute shortage personnel, the presence of an array of items without shelf marks, the use of outdated classification. The author presents a number of persons who started to work in the Department in 1924—1925: S.S. Abramovich-Baranovsky, A.A. Arnoldi, N.A. Burov, G.G. Geld, A.A. Gizetti, V.S. Zolotilov, S.V. Melikova-Tolstaya, V.S. Serebrenikov, etc. The article considers the main functional responsibilities assigned to the Department: systematization of the book collections, organization of systematic card catalogue, foreign books acquisition, composing and reviewing of the rules and instructions, preparation of scientific conclusions on books, participation in the organization of exhibitions, compilation of bibliography. The author describes in detail the results of work in 1924—1925: the restored method of book systematization according to K.M. Baer system, preparation of the instructional and methodical apparatus, and compilation of the card catalogue of publications up to 1914. The article presents the brief observation of the proposals to improve the classification of K.M Baer. The improvement included expansion of the classification, destruction of completely outdated units, transfer of some units of the system in the relevant modern scientific classification departments and subsections, and updating of the scientific terminology. The author highlighted and marked the traditions established in the 1920s, which later became the basis for human, organizational and methodological policy of the RASL Department, existing now for 95 years: reflection in the systematic catalogue of all types of publications coming to the library, involvement in the Department of specialists of certain branches of knowledge and activities, assignment to specialists of the relevant sections of catalogue. The refusal of K.M. Baer classification in 1930 marked the entry of RASL into the next stage of the history, during which the restructuring of the entire library was carried out on the functional basis, and the development of its own classification schedules began.
A Dimensionality Reduction Model for Complex Data Grouping

Abstract Given the existing packet dimensionality reduction model, the simple distance hypothesis is only used as a simple assumption that there is a certain relationship between packet data. This document proposes to share information between packet data with relevant random measures as a priori. We explicitly calculated the Lévy measure of the mixed random measure and offered the inference steps of detailed parameter a posteriori. Compared with the traditional method, the grouping dimensionality reduction model can achieve faster convergence and can well maintain the original information of data. The experimental results on the public dataset show that the grouping dimensionality reduction model is an effective dimensionality reduction algorithm and can be employed to extract characteristics on big data.
Work-in-Progress: QUASS —A Dynamic Knowledge Sharing System

In the field of formal education, knowledge bases are associated with courses. The learning offered by a course is best enabled when the knowledge base is fully and easily accessible to its students. However, the means and channels whereby the knowledge are captured and shared vary and they mostly require multistep and non-routine. In this paper, we will elaborate on an in-progress work we are working on to enable a more efficient way of capturing knowledge and at the same time, enable easy access and sharing of the content for students.
HDR in Consideration of the Abilities of the Human Visual System

In recent years, high dynamic range (HDR) has been improved enormously. The capability of cameras and displays to reproduce small differences in luminance levels is constantly growing. However, we are still dealing with a limitation of the human visual system (HVS) known as the simultaneous contrast range (SCR). Compared to earlier studies, this paper focuses on real-world scenarios for evaluating the SCR. In natural images, bright highlights, especially in HDR, can limit the eyes' sensitivity to small differences in surrounding dark areas. This paper describes a test-image set developed as part of current research activities by the authors to measure the relation between the perceived SCR and the following four significant parameters: the distance, or rather, the viewing angle; the size of the bright highlight; the luminance of the highlight; and the ambient light. As a result, a mathematical formula is given that can help to evaluate and improve HDR viewing experiences as well as standard dynamic range downconversions.
Vocabulary Trees with OSS Detectors

In today’s diversified world, with every person having their own idiosyncratic identity, the field of face detection and recognition has received significant scope. Since birth, humans develop and harvest similar facial features, making their recognition a challenging problem. Thus, the development of faster, more accurate and robust algorithms is of prime importance. The most critical requirements in developing a reliable face recognition algorithm is a large database of facial images and a well-developed systematic procedure to evaluate the system. In this paper, we bring out an approach to implement quick facial recognition using the concept of vocabulary trees in accordance with ORB, SIFT and SURF detectors and compare their performance. The model is trained using the Grimace, Face95 and ORL databases. The experiments are conducted by employing various state-of-the-art clustering algorithms and the results are compared for accuracy. The results and comparisons obtained on the databases show that the ORB detector clustered using Spectral clustering algorithm to construct the Vocabulary Tree outperforms the other techniques.
DEVELOPMENT OF DIDACTIC PRINCIPLES IN THE SYSTEM OF INFORMATIVE TRAINING TECHNOLOGY TEACHER AT USE TECHNOLOGIES OF COMPUTER MODELING

The characteristic features of computer modelling technology in the process of informatics training of future technology teachers are realized due to the approach of the educational process to the real conditions of future professional activity. The systematic implementation of the didactic principles of teaching informatics disciplines creates an effective environment for gaining knowledge and forming informatical competences of students, ensuring the creative nature of informatical training aimed at developing technological thinking, a meaningful manifestation of the professionaloriented position and development of the personal professional potential of future teachers of technology.
The application of statistic image analysis for classification of breast cancer based on mammograms

Abstract Cancer is a disease characterized by the ability of abnormal cells to grow uncontrollably. In the medical field, detection of breast cancer is done using a mammogram. Examination of the mammogram image is still done manually by the doctor / radiologist, so it is necessary to use technology as supporting information. In this research, mammogram image classification based on gray-level co-occurrence (GLCM) matrix and gray-tone difference matrix (GTDM) has been done with backpropagation method. The stages of the mammogram image classification process include the process of image acquisition, pre-processing, feature extraction with GLCM and GTDM and classification using backpropagation. The preprocessing process carried out is gray-scalling, contrast enhancement, image segmentation with Otsu thresholding, edge detection process, and image thickening process with widening morphology method. The highest performance results for accuracy are 85% and precision is 85.7%. This result was obtained when using the GLCM and GTDM feature extraction methods.
A New Improved Boosting for Imbalanced Data Classification

As one of the most important component of artificial intelligence, machine learning is getting more and more attention. AdaBoost, a classic machine learning algorithm, is widely used. However, when faced with imbalanced data classification, AdaBoost's recognition rate of minority samples is low due to ignoring class imbalance. In many cases, minority samples are of high value. For this shortage, combining the theory of margin and cost-sensitive idea, a new Boosting algorithm called CMBoost is proposed based on cost-sensitive margin statistical characteristics, which is firstly through optimizing margin statistical characteristics to improve formal algorithm and then extended by cost-sensitive. Experimental results on the UCI dataset show that the CMBoost algorithm is superior to AdaBoost for imbalanced data classification problem.
Normalized Sprint Estimation

Accurate estimation of software projects is quintessential for overall success of the project. Estimation of agile projects adopted in most of the modern software projects is challenging due to lack of historical data and due to dynamic characteristics of the agile projects. In this paper we introduce “Normalized Sprint Estimation” method which factors in dynamic characteristics of the agile projects such as non-functional requirements, sprint success factors and such. The author applied the normalized sprint estimation method to 14 sprints from three digital projects and the predicted estimation values had Pred (0.3), more than 80%. Though the normalized sprint estimation model is tested for digital projects, the same methodology can be applied for software projects from other domains as well.
Green Cloud Framework For Reducing Carbon Dioxide Emissions in Cloud Infrastructure

The increasing deployment of datacenters and cloud resources around the globe escalated by higher electricity prices advanced energy cost, cooling and communication cost, and carbon dioxide consumption. To curb such ever-increasing problem complexity, we have formulated a scientific workflow-based cost-effective paradigm based on rigorous mathematical model. Multiple techniques have been considered to increase system utilization rate within acceptable performance bounds. First, we have applied Dynamic Voltage and Frequency Scaling (DVFS) approach to scale down the power consumption by cloud servers via calculating the best near-optimal frequency. Then, we have reused cloud-based VMs to execute as many scientific workflows as possible using fewer cloud servers which conserves a tremendous amount of energy cost including carbon dioxide emission consumption and electricity cost. This has been done through eliminating the overhead of sharing multiple VMs the same server's capacity. Moreover, the aforementioned objectives have been achieved without degrading the Quality of Service (QoS) specified in Service Level Agreement (SLA). However, we have simulated our heuristic using open source CloudSim and compared with algorithms such as the Rank and EARES-D. The results have showed that our paradigm model is better than other heuristics with an average energy reduction of 70%.
Multi-models Dynamic Recommendation for Offline Clothing Sales

In the era of data-drive-productivity, the effective use of data will lead to higher conversion rates and turnover for offline clothing sales. This paper proposes a dynamic recommendation algorithm that combines multi-models such as collaborative filtering, content-based recommendation, visual-based recommendation, and hot sales models. According to the purchase records in the different period of a certain season, the weights in different recommendation models were dynamically adjusted to get a better recommendation result. Experiments proved our algorithm would achieve an excellent recommend performance, the generated results were rich and complex, the recommended results for new customers were as smart as for regular customers.
A Machine Learning Application for Latency Prediction in Operational 4G Networks

Measuring performance on Internet is always challenging. When it comes to the mobile networks, the variety of technology characteristics coupled with the opaque network configuration make the performance evaluation even a more difficult task. Latency is one of the aspects having the largest impact on the performance and on the end users’ Quality of Experience. In this paper, we present a machine learning approach that, exploiting real mobile network data on the end user, try to predict the latency in a real operational network. We consider a large-scale dataset with more than 238 million latency measurements coming from 3 different commercial mobile operators. The presented methodology flattens the RTT values into several bins, turning the latency prediction problem to a multi-label classification problem. Then, three well-known supervised algorithms are exploited to predict the latency. The obtained results highlight the importance of representative dataset from operational network. It calls for further improvements on the algorithm selection, tuning, and their predictive capabilities.
Results: Selected Individual Journey Experiences

This chapter proposes a second-by-second analysis of individual journey experiences. The physical, sensory, social and emotional features of two motorcyclists’ and three cyclists’ journeys are presented, with the aim at identifying commonalities and differences, and to reflect upon the connections between the tangible and intangible elements of tourist travel. Journey experiences are confirmed to be eudaimonic, emotionally rich escapist experiences, where individuals, modes and contextual conditions are combined to form a unique and composite space-time mix. Based on the evidence collected, the personas methodology helps to transform the thick descriptions at individual level into fictitious characters—the personas—to enable future tourism and transport planning.
Standardization of Handwritten Words to Improve Readability

Everyone has different handwriting, and this is a difficulty since not everyone can discern the handwriting of different people. The described technique converts unstructured handwriting into a structured type. To resolve the problem, the authors want to separate every letter of the words so as to converting the alphabet into a commonplace type. This is to simplify the written language for everyone. This article presents a piece of text identification from image. OCR is enforced to convert electronic kind of image into machine-editable text.
The dual code of any <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" overflow="scroll" id="d1e336" altimg="si16.gif"><mml:mrow><mml:mo>(</mml:mo><mml:mi>δ</mml:mi><mml:mo>+</mml:mo><mml:mi>α</mml:mi><mml:msup><mml:mrow><mml:mi>u</mml:mi></mml:mrow><mml:mrow><mml:mn>2</mml:mn></mml:mrow></mml:msup><mml:mo>)</mml:mo></mml:mrow></mml:math>-constacyclic code over <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" overflow="scroll" id="d1e357" altimg…

Let F 2 m be a finite field of cardinality 2 m , R = F 2 m [ u ] ∕ 〈 u 4 〉 = F 2 m + u F 2 m + u 2 F 2 m + u 3 F 2 m ( u 4 = 0 ) which is a finite chain ring, and n is an odd positive integer. For any δ , α ∈ F 2 m × , an explicit representation for the dual code of any ( δ + α u 2 ) -constacyclic code over R of length 2 n is given. And some dual codes of ( 1 + u 2 ) -constacyclic codes over R of length 14 are constructed. For the case of δ = 1 , all distinct self-dual ( 1 + α u 2 ) -constacyclic codes over R of length 2 n are determined.
Designing embodied interactions for informal learning

Interactive installations that are controlled with gestures and body movements have been widely used in museums due to their tremendous educational potential. The design of such systems, however, remains problematic. In this paper, we reflect on two open research challenges that we observed when crafting a Kinect-based prototype installation for data exploration at a science museum: (1) making the user aware that the system is interactive; and, (2) increasing the discoverability of hand gestures and body movements.
Control Method Based on Deep Reinforcement Learning for Robotic Follower with Monocular Vision

Abstract Robotic follower is receiving attention widely in recent years. Aiming at the problems of low sample collection efficiency, high training cost and difficult design of reward function in the real world, we propose a control method based on deep reinforcement learning. Different depth layers are adopted to attain the end-to-end control of the robotic follower through pre-trained. Then, we design a reward function mechanism to judge whether the robot follower follow falsely. Then the appropriate pre-trained network is transferred to reinforcement learning, and a deep reinforcement learning system for monocular vision robot following tasks is established. According to the experimental results, the proposed deep reinforcement learning method can efficiently collect a large number of data sets, shorten the training period and reduce the number of times that the robot follower loses its target.
Facial Expressions Analysis for Applications in the Study of Sign Language

Elements of information technology for analysis of facial expressions to apply in interactive study of sign language are described.The main elements of information technology, its structure and experimental implementation has been discussed.Analysis was carried out in order to identify how the classifier error rate depends on type of classifier, number of feature and teach set.Optimal constructs of classifiers were proposed, giving appreciable improvement of existing algorithms.
An NC Algorithm for Sorting Real Numbers in &lt;em&gt;O&lt;/em&gt;(nlogn/√&lt;span style=&quot;margin-left:-4px;margin-right:2px;border-top:2px solid black&quot;&gt;loglogn&lt;/span&gt;) Operations

We apply the recent important result of serial sorting of n real numbers in ( ) log O n n time to the design of a parallel algorithm for sorting real num- bers in ( ) 1 log O n ε + time and log log log n n O n         operations.This is the first NC algorithm known to take ( ) log o n n operations for sorting real numbers.
Proposal for CAPTCHA that Makes Use of the Human Ability to Understand Context

For the visually impaired, it is difficult to use CAPTCHA that was generated using visual information. The only way is to install a browser add-on and, by eliminating CAPTCHA, to collect information from the internet. However, it is not easy for visually impaired people to install an add-on, and there will also be disadvantages for general users if anyone is able to eliminate the CAPTCHA function. As such, using text that can be converted into voice, we proposed a sentence rearranging format of CAPTCHA that makes use of the human ability to understand context. Through experiments, we examined the kind of sentences, number of Japanese characters, number of sentences, and special characteristics of sentences that the sentence rearranging format could accommodate. Our conclusion was that, primarily, humans find it easy to understand context to the extent that the subject of the sentence is clearly indicated and is linked to the content of the sentence, that it is appropriate to use four sentences or fewer as multiple-choice options in problem sentences, and that less than 100 Japanese characters is ideal for the number of characters.
Computing isomorphisms and embeddings of finite fields

Let q be a prime power and let F q be a field with q elements. Let f and g be irreducible polynomials in F q [ X ], with deg f dividing deg g. Define k = F q [ X ]/ f and K = F q [ X ]/ g , then there is an embedding ϕ : k [EQUATION] K , unique up to F q -automorphisms of k. Our goal is to describe algorithms to efficiently represent and evaluate one such embedding.
Performance Measurements of Sobel Edge Detection Implemented in an FPGA Architecture and Software

This paper presents an implementation of Sobel edge detection in static images for the FPGA, described in Verilog, and for the respective software: Mathematica, MATLAB, OpenCV and in-house C++ written program. Comparisons in performance were made between the different applications. The results concluded that the FPGA was faster.
Psychological Correctation Opportunities of the Tendency for Machiavellianism in Pedagogue’s Personality

The article deals with the psychological correctation opportunities of the tendency towards the machiavellianism in the pedagogue’s personality. In today's global education system, the issue of increasing the professional training of teachers is an urgent issue for the students to create the best educational, social and cultural conditions. Improving the professional skills of teachers in bringing the quality of education up to world standards is also a key international experience. Research on modern requirements for improving the quality of education in the world focuses on the issues of diagnostics and correctation of the tendency towards the machiavellianism in the pedagogue’s personality. Despite the fact that there is a unanimous consensus on the interpretation of the general essence of Machiavellianism, there are still debates about some aspects related to its practical expression. Describing Machiavellianism as a n attribute of an individual , specific person ality type and behavioral strategy is vital both scientifically and practical ly .
The Business Transformation Framework and Enterprise Architecture Framework for Managers in Business Innovation

The KMGSE offers a real-life case for detecting and processing an enterprise knowledge management model for global business transformation, knowledge management systems, global software engineering, global business engineering and enterprise architecture recurrent problems solving. This global software engineering (GSE) subsystem is a driven development model that offers a set of possible solutions in the form of architecture, method, patterns, managerial and technical recommendations, coupled with an applicable framework. The proposed executive and technical recommendations are to be applied by the business environment's knowledge officers, architects, analysts and engineers to enable solutions to knowledge-based, global software engineering paradigms' development and maintenance.