Reviewerly/exHarmony huggingface dataset:
VOLUTION OF SPATIAL-TIME PARAMETERS OF AUDIOVISUAL IMAGES IN THE PROCESS OF CREATING THE SCREEN MASTERPIECES (ON THE FACTS OF PHOTOGRAPHY, FILM, TELEVISION, VIDEO)

On-screen creativity is a single cultural-aesthetic system, operating with the language of visual and audiovisual images, the basic source of which is inseparably linked with such categories of reality as space and time. Their special position is determined by the fact that they are attributes of the existence of life forms and without their reflection any on-screen creativity becomes impossible. At certain stages of its historical evolution, screen creativity grew by new typical formations. The photography appeared first, then the cinema, and later on television, in the depths of which, after a while, the video was parted. Each new type at the level of space-time relations with the reality preceeding the camera formed its own special principles of screen narration. At the same time, they depended on the features of the new technological system, and on the dominant modes of visuality on an individual and collective levels. In this process, the cultural-aesthetic progress in on-screen creativity was reflected. The general logic of the relationship of the author of the screen work and the displayed reality in terms of its on-screen chronotope organization has evolved from a single, instantaneous discretization of it, to a total space-time continuity. From the author’s point of view, the more speculative picture of this process looked as follows: the photographic chronotope is characterized by a single spatial appearance of the displayed object and its temporary immobility (static); the cinematic chronotope is characterized by an editorial multiplicity of forms of the displayed object, which recreates conditional space and conditional time on the screen; the television chronotope is characterized by a simultaneous multiplicity of forms of the displayed object, which recreates the conditional space and real time on the screen; the video chronotype is characterized by a continual multiplicity of shapes of the displayed object, which recreates real space and real time on the screen. It is obvious that the evolution of screen creativity stimulated the development of new creative possibilities in terms of the spatial and temporal organization of audiovisual images, which in turn contributed to the establishment and enrichment of specific cultural aesthetic formations. Their common aspiration was focused on achieving natural integrity and authenticity in presenting life forms on the screen.
Image Compression for Telemedicine using New Wavelets and Modified EZW

With the invent of better signal processing operations unveiled by the research community of both communication and signal processing, the Telemedicine is becoming more and more prominent all over the world. Communicating the data captured from the patient to the clinicians in non-recognizable seconds of time is crucial in many cases so as to take a right decision at right time. Then the processing of the data sent to clinicians is the second part of telemedicine where extensive processing capabilities are required. In this paper, the first part of telemedicine is answered by devising diversified schemes using wavelet and modification of standard coding scheme embedded zero tree wavelet (EZW). First, coding by EZW and Set partitioning in Hierarchical tree (SPIHT) was implemented. Then, new wavelets and their lifting versions are designed. Finally, two variations of standard EZW scheme were proposed. The simulation results suggest that the techniques presented in this paper provide better compression performance at different levels of compression ratio (CR) and peak signal to noise ratio (PSNR). In addition to CR and PSNR, bit error rate and output bandwidths are calculated.
INVESTIGATING READING COMPREHENSION PROCESSES IN ESP EDUCATION

Reading is regarded as a cognitive process of meaning construction, or an interactive process that comprises low-level processes of word recognition and high-level processing of ideas. Schema theory implies the meaning of а text is not embedded in the text itself; it is actually created in an active manner through interaction between the reader and the text, in which readers use their world knowledge to decode text meaning. Accordingly, readers bring their ideas, experience and previously gained knowledge into reading comprehension processes. The attainment of specific reading goals, including main idea comprehension and extracting specific information from the text, requires the employment of various reading strategies. In that sense, strategic behavior is deployed by proficient readers; it enables them to facilitate and improve text comprehension, which is the ultimate aim of the reading skill. 10 ESP students of the College of Applied Professional Studies in Vranje took part in this research as respondents. After completing their reading comprehension assignments, students reported on those tasks by virtue of think-aloud protocols. This type of research may provide an insight into specific problems students encounter during text processing activities, as well as strategies they employ to resolve them, which would facilitate the evaluation of reading performance and progress monitoring. The results imply that strategic training would enable ESP students to efficiently attain both general and specific reading goals.
On Orderings in Security Models

Security decisions are often made on the basis of a comparison of two or more alternatives. Is it better go with design A or design B? Which security policy is best for my needs? What combination of defensive mitigations provide the best protection from attack? Implicit in such comparisons are ordering relations \(\preceq \) among the alternatives. Such ordering relations crop up in numerous security formalisms. This paper studies preorders that arise in three formalisms for very different domains of security: attack trees, Copland specifications of layered attestations, and cryptographic protocols. While these three areas of study appear to be very different in subject matter and form, we identify a common construction for defining preorders that arise in them. This new perspective unlocks novel connections that should allow insights in one domain to bear fruit in the others as well.
Introduction

The concept underlying measurement invariance is often introduced using a metaphoric example via physical measurements such as length or weight (Millsap, 2011). Suppose I developed an instrument to estimate the perimeter of any object. My instrument is invariant if it produces the same estimate of the object’s perimeter, regardless of the object’s shape. For example, if my instrument provides the same estimate of the perimeter for a circle and a rectangle that have the same true perimeter, then it is invariant. However, if for a circle and a rectangle of the same true perimeter my measure systematically overestimates the perimeters of rectangles, then my measure is not invariant across objects. The object’s shape should be an irrelevant factor in that my instrument is expected to provide an accurate estimate of the perimeter, regardless of the object’s shape. However, when we have a lack of measurement invariance, the estimated perimeter provided by my instrument is influenced not only by the true perimeter but also by the object’s shape. When we lack measurement invariance, irrelevant factors systematically influence the estimates our instruments are designed to produce.
Is Expressiveness the Future of Software?

We explore what potentially may happen to software by 2033, taking views from across the industry. Our central premise is that, by increasing problem-domain expressiveness, more real-world experiences can be captured and converted into digital simulators, which can form shareable models of knowledge.
Supporting decision-makers in healthcare domain. A comparative study of two interpretative proposals for Random Forests

The growing success of Machine Learning (ML) is making significant improvements to predictive models, facilitating their integration in various application fields, especially the healthcare context. However, it still has limitations and drawbacks, such as the lack of interpretability which does not allow users to understand how certain decisions are made. This drawback is identified with the term "Black-Box", as well as models that do not allow to interpret the internal work of certain ML techniques, thus discouraging their use. In a highly regulated and risk-averse context such as healthcare, although "trust" is not synonymous with decision and adoption, trusting an ML model is essential for its adoption. Many clinicians and health researchers feel uncomfortable with black box ML models, even if they achieve high degrees of diagnostic or prognostic accuracy. Therefore more and more research is being conducted on the functioning of these models. Our study focuses on the Random Forest (RF) model. It is one of the most performing and used methodologies in the context of ML approaches, in all fields of research from hard sciences to humanities. In the health context and in the evaluation of health policies, their use is limited by the impossibility of obtaining an interpretation of the causal links between predictors and response. This explains why we need to develop new techniques, tools, and approaches for reconstructing the causal relationships and interactions between predictors and response used in a RF model. Our research aims to perform a machine learning experiment on several medical datasets through a comparison between two methodologies, which are inTrees and NodeHarvest. They are the main approaches in the rules extraction framework. The contribution of our study is to identify, among the approaches to rule extraction, the best proposal for suggesting the appropriate choice to decision-makers in the health domain.
Statistical Literacy as a Way to Achieve Social Consensus

The maintenance of civil peace and harmony in the Russian state from time immemorial has been defined as a priority that allows maintaining the integrity of both state and territorial. Global processes taking place in the world, epidemic waves of viruses, incessant local wars, diligent attempts to separate people and peoples bring to the fore the need to consolidate society in order to ensure the national security of the country. In this context, the importance of statistics increases, which significantly affects the perception of the dominant values by society, forms the attitude of people to the state policy being pursued. At the same time, the understanding of statistical information (figures, data) in a number of cases does not correspond to reality, making it difficult to adequately assess the existing situation, which is associated with an insufficient level of statistical literacy of the population, officials and specialists in various fields of activity.
Augmented Reality based Online Shopping

Online shopping constitutes a huge market in today’s world. But still hasn’t reached to its maximum potential. Sales companies in online mode encounter a lot of crises when a large number of products are returned, possibly due to improper fit, improper visual, many more such reasons. Hence online shopping is in constant need of upgrades to improve its sales and reduce the return rates. In this paper, a possible solution is proposed. The webcam of a device is used to view a customer wearing an outfit on the web portal on a real-time basis in the most efficient manner with characteristics of the 3D model depicting a real fabric. So, a study on different approaches and methods that are required to render 3D objects in real-time was carried out. Subsequently, two of the implementation methods offered by the Vuforia package to augment 3D models of objects in real-time, i.e., image target and model target was studied. As compared to the traditional method of shopping, this proposed system provided an add-on feature to online shopping, hence giving a realistic approach to it.
Examination of operating range based on maneuverability and operability of wheelchair-mounted robot arm

When supporting the independence of a physically handicapped person using a wheelchair-mounted robot arm, it is expected that it will be extremely difficult to grasp a falling object, which is one of the daily activities, without assistance. By tilting the mounting portion forward at an arbitrary angle, it is expected that the operating area near the floor will be expanded, but there is a problem that the operating direction of the operating device and the operating direction of the robot arm wrist position do not match. Therefore, in this paper, when an arbitrary rotation angle is given to the mounting part of the wheelchair-mounted robot arm, the control direction by the operation device and the operation direction of the robot arm are matched, and the improvement in maneuverability is evaluated.
Architecture Design of Emergency Rehabilitation Management System for Large-scale Public Health Events Based on Machine Learning

Our country is in the transitional period of economic transition society, facing complex contradictions, coupled with natural disasters, accidents and disasters, public health and social security exposure of the inharmonious issues, there is the possibility of various public emergencies anytime and anywhere. Therefore, no matter from the perspective of field, frequency, scale, organization, etc., my country is in a period of frequent public emergencies at this stage. This paper studies the architecture design of a large-scale public health incident emergency rehabilitation management system based on machine learning.
Peer review declaration

Abstract All papers published in this volume of Journal of Physics: Conference Series have been peer reviewed through processes administered by the Editors. Reviews were conducted by expert referees to the professional and scientific standards expected of a proceedings journal published by IOP Publishing. • Type of peer review: Single-blind / Double-blind / Triple-blind / Open / Other (please describe) An international scientific committee selected papers corresponding to the following criteria: a paper should have more than 8 pages and contain new scientific results, which are in the thematic area of the conference. Next, each selected paper underwent scientific peer review and technical check. The type of peer review was double-blind scientific peer review. At least 3 reviewers from different scientific organizations participated in the review of one paper. In case of disagreement between the reviewers, additional reviewers were involved. All papers are also checked for plagiarism, image quality and quality of the English language. • Conference submission management system: Open Journal System • Number of submissions received: 1240 • Number of submissions sent for review: 1157 • Number of submissions accepted: 493 Acceptance Rate (Number of Submissions Accepted / Number of Submissions Received X 100): 39.75 • Average number of reviews per paper: 3 reviewers per paper • Total number of reviewers involved: 132 • Any additional info on review process: Contact person for queries: Name: Vera Murgul Affiliation: Peter the Great St.Petersburg Polytechnic University, St. Petersburg, Russia Email: vera.murgul@mail.ru
Attacks on hospitals increase as criminals exploit pandemic

Interpol's Cybercrime Threat Response (CTR) team has warned that cyber criminals have stepped up ransomware attacks against hospitals and other medical facilities.
Clothing retrieval based by image and text combination

Image text combination retrieval is a new direction in multimodal retrieval, in which query is composed of image and modified text. The retrieved target image should not only be similar to the query image, but also have the change specified by the modified text. The traditional clothing retrieval adopts the single-mode retrieval method of image search or text search, which is lack of retrieval flexibility. To solve the problem of feature fusion caused by semantic differences between clothing image and text, this paper proposes a multi-dimensional feature fusion model, which constructs a high-dimensional visual feature and semantic feature fusion model based on the scaling point product attention mechanism to extract high-dimensional fusion features, then the low dimension visual semantic fusion features are used as the residual of high dimension fusion features for target image retrieval. Compared with the previous feature fusion methods, the recall rate of Top1 on Fashion200k data set is increased by 15.4%, which is obviously superior to most of the existing graph and text feature fusion models, which shows that the model is advanced and effective.
Features of the course "Business english" for engineering masters’ students

The article presents a content analysis of the «Business English» for future engineers at the master’s level. Studying the «Business English» contributes to the competencies formation in accordance with the requirements of the Federal State Educational Standard of Higher Education 3 ++. The methods and forms of Business English were determined taking into account the features of teaching masters’ students, the motives for studying in the magistracy. The selection of training materials for Business English is based on the authenticity of training materials, real tasks, pragmatic orientation and adaptability of materials to changing the labor market conditions in order to develop cross-cultural and business communication of future engineers.
Neural Structured Prediction

With a machine learning approach and less focus on linguistic details, this gentle introduction to natural language processing develops fundamental mathematical and deep learning models for NLP under a unified framework. NLP problems are systematically organised by their machine learning nature, including classification, sequence labelling, and sequence-to-sequence problems. Topics covered include statistical machine learning and deep learning models, text classification and structured prediction models, generative and discriminative models, supervised and unsupervised learning with latent variables, neural networks, and transition-based methods. Rich connections are drawn between concepts throughout the book, equipping students with the tools needed to establish a deep understanding of NLP solutions, adapt existing models, and confidently develop innovative models of their own. Featuring a host of examples, intuition, and end of chapter exercises, plus sample code available as an online resource, this textbook is an invaluable tool for the upper undergraduate and graduate student.
Peer review declaration

All conference organisers/editors are required to declare details about their peer review. Therefore, please provide the following information: • Type of peer review: Double-blind There were total 229 submissions, and only 197 papers have been send to the reviewers. The rest of papers were out of the scopes. All the accepted papers have been submitted to strict peer-review by 2-3 expert referees. • Conference submission management system: http://www.chairin.cn/login?conf=msee2021 • Number of submissions received: 229 • Number of submissions sent for review: 197 (submitted for publication) • Number of submissions accepted: 96 • Acceptance Rate (Number of Submissions Accepted/Number of Submissions Received X 100): 41% • Average number of reviews per paper: 2 • Total number of reviewers involved: 98 • Any additional info on review process: Reviewers will be asked to provide numerical ratings for the submissions on a scale from 1-5 on criteria such as relevance, reviewer’s confidence, technical soundness, originality of the presented work, paper organization, overall evaluation. In addition, reviewers will be asked to provide 2 sets of comments for each submission they review: (1) Comments for the Authors (2) Comments for the Technical Program Committee. • Contact person for queries: Ms Kun Zhang, Email: 2792810276@qq.com, Tel: 18163305570
Smart Community Construction System Architecture Based on Five-viewing Demands

Community intelligence is one of the important development directions of modern urban construction and governance. Combined with the demands of the owners and property management of the smart community, this paper sorts out the service demands of the owners and property management in five aspects: viewing the personnel access, viewing the vehicle parking, viewing the video surveillance, viewing the intercom and viewing the equipment. Based on these demands, the general system architecture of the construction of the smart community with the concept of five-viewing is proposed. Then the case of Zhonghaihuating smart community is analyzed on the concept and effect of five-viewings.
E-Government Service Demand Prediction and Forecasting during COVID-19 Pandemic: SARIMA Model based Exploration

COVID-19 proved the relevance of digital infrastructure and services globally. Regular ranking each nation globally on E-Government provides the seriousness of the UN and global leaders in shaping the future strategically. Channelizing E-Government services through an agent-based entrepreneurship model is not new. Like any digital business, E-Government services mature globally with technology. The scope for delivering these services is also on the rise leading to attracting entrepreneurs to set up E-Government outlets. The real challenge remains to predict the demand of E-Government services to make the business sustainable. Indian E-Government framework, NeGP and Digital India policy dwell on the business model driven policy through CSC framework. This article examines the citizen demand of E-Government services and predicts the demand behavior of the citizens during the COVID-19 pandemic for the entrepreneurs using SARIMA model. The actual demand scenario during a pandemic is as per the forecast and predictions of the model.
Control of Non-Linear Systems using Fuzzy PI-PD Controller

This paper gives the relationship of control performance of various types of fuzzy controllers, fuzzy (PI-PD) controller, combination of fuzzy PI and PD controller and fuzzy PI-PD controller. The analytical structures of Fuzzy PI-PD controller is deciphered through triangular memebership functions by using mamdani row interference technique and zadeh fuzzy logic and center of gravity defuzzification method. In simulation the control performance of non linear systems for various controllers by taking triangular, Gaussian g bell, trapezoidal memebership functions
Image-Based rendering

Over the last fewdecades, image-based rendering has emerged as one of the most exciting applications of computer vision (Kang, Li et al. 2006; Shum, Chan, and Kang 2007; Gallo, Troccoli et al. 2020). In image-based rendering, 3D reconstruction techniques from computer vision are combined with computer graphics rendering techniques that use multiple views of a scene to create interactive photo-realistic experiences such as the Photo Tourism system shown in Figure 14.1a. Commercial versions of such systems include immersive street-level navigation in online mapping systems such as Google Maps and the creation of 3D Photosynths from large collections of casually acquired photographs.
Depth Estimation

Stereo matching is the process of taking two or more images and building a 3D model of the scene by finding matching pixels in the images and converting their 2D positions into 3D depths.