Reviewerly/exHarmony huggingface dataset:
Teaching Bachelors of Mathematics with Graphical Representation of Functions in the Context of Digitalization of Education

The article discusses the teaching of mathematics bachelors to functions in the form of a graphical representation in the conditions of digitalization of education. The theoretical significance of the formation and development of graphic culture is shown, the possibility of depicting the necessary information through its graph by constructing a mathematical model of the process defined by a mathematical formula. In addition, methods of application of modern information and communication technologies have been developed. The efficiency of using Maple mathematical packages in teaching university students to display functions in the form of a graphic image in the conditions of digitalization of mathematical education is determined. It is shown that the activity of studying the graph of a function using a computer mathematics system plays an important role in the formation of opportunities for the manifestation of students' creative abilities, the development of knowledge and research abilities, active independent work, work planning. Classes based on the use of digital technologies are characterized by adaptability, manageability, interactivity, a combination of individual and group work, as well as temporary unlimited learning. In addition, digital technologies provide a number of new opportunities for both teachers and students, which allows you to automate most of the academic work, save time, quickly find the necessary information, socialize, improve yourself, freeing up time for individual work with students.
Application of the Virtual Museum Method in the Process of Analyzing Applied Art and Creative Works

The article presents the results of the research and the art history, educational possibilities of the virtual museum method. The exhibits of art in the museum are classified depending on consumer, technical, form, machine-tool features. For residents and students living away from the centers of the Museum of Art, the art history opportunities and needs of the virtual museum are open. The features of the art exhibits in the museum, criteria and methods of their analysis, content, program, methods of presentation of works of art to future teachers are presented. The virtual museum is recognized as an art criticism method, an innovative phenomenon in modern research. The advantage of the virtual museum method, as opposed to traditional methods, is revealed for students. The theoretical and practical significance of using the museum method in universities is described. The study substantiates the process of ensuring the introduction of a virtual museum to national cultural values as an art criticism opportunity, consistency, art criticism and methodology. Artistic analysis and art history demonstration by the virtual museum method includes the direction of: analysis of the idea of the work, composition, color, volume of space, technique of execution. During the analysis of the artistic features of applied art products, students are provided with information about the product such as: consumer goods, shaping, material processing, technology, ergonomics, decorative design of the product, year of manufacture, region and master. In the course of the study of the effectiveness of the application of this method in practice, the proposed content, model, program, methods of preparing a future teacher to use the virtual museum method is determined by the expertise of prepared esperts, based on the results of experimental verification. Conclusions are presented on indicators, signs with the content of the formation of a new quality in the training of future teachers by the virtual museum method.
CONTESTING TECHNOCOLONIALISM? THE 'ORDINARY TRANSCRIPTS' OF EVERYDAY RESISTANCE

This paper investigates the extent to which marginalized communities contest practices of datafication and technological experimentation which are becoming increasingly ubiquitous in the aid sector. Drawing on seven years of research in the humanitarian and development sectors, the paper explores forms of resistance to digital aid practices. The paper is divided into two parts. The first section observes how datafication and digital innovation in the aid sector rework the colonial genealogies of humanitarianism and digital technology. I then theorize resistance in situations of asymmetrical power. The second section discusses empirical examples of everyday contestation. Drawing on Scott’s notion of the ‘hidden transcripts’ (1985), the paper develops the term ‘ordinary transcripts’ to illustrate the modest critique of digital power through everyday life practices such as non-participation and the oppositional appropriation of digital aid projects. Listening to the ‘ordinary transcripts’ of everyday resistance is also partly a methodological argument as it is only through ethnographic encounters that these small acts of contestation can be noticed. The paper concludes that the arguments about digital power and the persistence of colonial legacies do not preclude the acknowledgement of human agency. However, the ordinary transcripts of everyday resistance do not equal decolonization which requires a radical restructuring of power relations. Still, ordinary resistance needs to be recognized for it may contain the seeds of future decolonial struggle.
Components and Psychological Characteristics of Soft Skills

The development of soft skills is in the focus of attention of the world's largest companies and organizations, in particular, the Organization for Economic Development and Cooperation (OECD), the World Economic Forum (WEF). This is due to the fact that geopolitical and technological trends determine the skills that future specialists need to meet the requirements of the labor market. In the conditions of technological development of a dynamically developing modern society, radical changes in world education, expressed in the formation of a single educational space, the needs of the subjects of education have strengthened the requirements for higher education. As part of this process, new educational standards, a new system for assessing the quality of education are being introduced, modules of educational programs integrated with production are being developed. This, in turn, contributes to the search for the closest and optimal ways to form soft skills of graduates of higher educational institutions to real working conditions. Interdisciplinary direction plays a crucial role in almost all professional fields. The problem of the development of soft skills since the middle of the last century has been dealt with at various times by many scientists who consider and study the concept of soft skills in various aspects. This article, presented in this regard, substantiates the relevance of the formation of soft skills in future specialists. The definitions of the concepts of skill, soft skill, which have been studied and formulated in the fundamental research works of research scientists, are given. Classifications of scientists from far and near abroad by components of soft skills and their psychological component are systematized in the form of tables. As a result of the theoretical analysis, the authors identified the main components of soft skills, such as emotional intelligence, communication skills, critical thinking skills and leadership. The psychological features of the components of soft skills and their relationship are determined. The most important factors of the information and communication technologies (ICT) market are defined as technological development, continuous expansion of the ICT space, the need for a high level of soft skills. The importance of the formation of soft skills among graduates of higher educational institutions is shown.
A cross-age face generation method based on CGAN and LSTM

Cross-age face generation refers to generating face images of other age groups by using images of known ages. It is widely used in public safety, entertainment, etc. As to the problem that the existing methods based on GANs only use age information as the generation condition and ignore the sequence of age information, we present a cross-age face generation method based on CGAN and LSTM. This method consists of four modules. The first module is a generator, which is used to generate face images of different age groups. The second module is a discriminator, whose main task is to determine whether the generated image is real or forged. The third module is a pre-trained ResNet, which is responsible for extracting the features of real images. Finally, LSTM provides age groups classification constraints for the generator by the sequence of age information.
Peer Review Statement

All papers published in this volume have been 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 Anonymous • Conference submission management system : Morressier • Number of submissions received : 85 • Number of submissions sent for review : 72 • Number of submissions accepted : 45 • Acceptance Rate (Submissions Accepted / Submissions Received × 100) : 52.9 • Average number of reviews per paper : 1 • Total number of reviewers involved : 19 • Contact person for queries : Name : Dr. M. SURENDAR Email : surendar.m@nitpy.ac.in Affiliation : Assistant Professor, National Institute of Technology Puducherry
Things We Could Design: For More Than Human-Centered Worlds by Ron Wakkary

Ron Wakkary’s Things We Could Design: For More Than Human-Centered Worlds (MIT Press, 2021) aims to rethink the direction of design practice using a posthumanist approach. This book is the result of years of professional and theoretical experience gained by the author in both academia and practice (Everyday Design Studio). Posthumanist exploration of design stands in opposition to the prevailing “art of human design of the last thirty years,” in which human values have been in the service of a “behavioral understanding of what is human” (p. 1). It represents an exploration of the possibilities for a new understanding of human-technology relations and posthumanism, while also addressing issues of accountability, sustainability, and equality.
Anticipating Consumer Demand using ML

Abstract: Demand forecasting is essential for every growing online business. Without efficient demand forecasting systems in place, it might be next to impossible to always have the right amount of stock on hand. Because a food delivery service deals with a high volume of perishable raw materials, it is critical for the company to accurately forecast daily and weekly demand. If a warehouse has too much inventory, there is a greater likelihood of wastage, and if it has too little, there may be shortages, which would encourage customers to turn to your competitors. Therefore, predicting demand is one of the important tasks to be done. The project represents a food delivery company that operates in multiple cities. This particular company has various fulfillment centres in these cities for dispatching meal orders to their customers. Its objective is to anticipate consumer demand and the goal is to build a predictive regression model to assist the client in projecting demand for the following weeks so that these centres can organize their raw material stock properly, with the usage of various Machine Learning and Deep Learning Models and Techniques. For that purpose, there are various tools, techniques and methods are proposed. Linear regression model, Random Forest, XG Boosting, Decision tree is some of the models performed for getting the highest accuracy.
A Two-Stage Image Frame Extraction Model -ISLKE for Live Gesture Analysis on Indian Sign Language

The new industry revolution focused on Smart and interconnected technologies along with the Robotics and Artificial Intelligence, Machine Learning, Data analytics etc. on the real time data to produce the value-added products. The ways the goods are being produced are aligned with the people’s life style which is witnessed in terms of wearable smart devices, digital assistants, self-driving cars etc. Over the last few years, an evident capturing of the true potential of Industry 4.0 in health service domain is also observed. In the same context, Sign Language Recognition- a breakthrough in the live video processing domain, helps the deaf and mute communities grab the attention of many researchers. From the research insights, it is clearly evident that precise extraction and interpretation of the gesture data along with an addressal of the prevailing limitations is a crucial task. This has driven the work to come out with a unique keyframe extraction model focusing on the preciseness of the interpretation. The proposed model ISLKE deals with a clustering-based two stage keyframe extraction process. It has experimented on daily usage vocabulary of Indian Sign Language (ISL) and attained an average accuracy of 96% in comparison to the ground-truth facts. It is also observed that with the two-stage approach, filtering of uninformative frames has reduced complexity and computational efforts. These key leads, help in the further development of commercial communication applications in order to reach the speech and hearing disorder communities.
Loss-tolerant architecture for quantum computing with quantum emitters

We develop an architecture for measurement-based quantum computing using photonic quantum emitters. The architecture exploits spin-photon entanglement as resource states and standard Bell measurements of photons for fusing them into a large spin-qubit cluster state. The scheme is tailored to emitters with limited memory capabilities since it only uses an initial non-adaptive (ballistic) fusion process to construct a fully percolated graph state of multiple emitters. By exploring various geometrical constructions for fusing entangled photons from deterministic emitters, we improve the photon loss tolerance significantly compared to similar all-photonic schemes.
ASPEST: Bridging the Gap Between Active Learning and Selective Prediction

Selective prediction aims to learn a reliable model that abstains from making predictions when uncertain. These predictions can then be deferred to humans for further evaluation. As an everlasting challenge for machine learning, in many real-world scenarios, the distribution of test data is different from the training data. This results in more inaccurate predictions, and often increased dependence on humans, which can be difficult and expensive. Active learning aims to lower the overall labeling effort, and hence human dependence, by querying the most informative examples. Selective prediction and active learning have been approached from different angles, with the connection between them missing. In this work, we introduce a new learning paradigm, active selective prediction, which aims to query more informative samples from the shifted target domain while increasing accuracy and coverage. For this new paradigm, we propose a simple yet effective approach, ASPEST, that utilizes ensembles of model snapshots with self-training with their aggregated outputs as pseudo labels. Extensive experiments on numerous image, text and structured datasets, which suffer from domain shifts, demonstrate that ASPEST can significantly outperform prior work on selective prediction and active learning (e.g. on the MNIST$\to$SVHN benchmark with the labeling budget of 100, ASPEST improves the AUACC metric from 79.36% to 88.84%) and achieves more optimal utilization of humans in the loop.
PENGARUH PEMBERIAN KOMBINASI AMPAS TAHU DAN LIMBAH ROTI AFKIR YANG DIFERMENTASI SEBAGAI NUTRISI TERHADAP PERTUMBUHAN DAN PRODUKSI MAGGOT (Hermetia illucens)

This study aims to determine the effect of giving a combination of tofu pulp and fermented bread on the growth and production of maggots. The method used is a complete Randomized Design (RAL) 5 treatments with 3 tests, namely, P1: Tofu dregs (100%), P2: tofu dregs (75%) + afkir bread (25%), P3: tofu dregs (50%) + afkir bread (50%), P4: tofu dregs (25%) + afkir bread (75%) and P5: afkir bread (100%). The results of the study obtained the best combination of nutrients, namely P3with a weight growth of 0.236 gr and a length growth of 2.00 cm. From the results of the protein content test, the highest maggot protein at P5 was obtained at 43.09%. While the measurement of maggot media obtained a temperature of 34-40oC and a pH of 4.5-7.
Monitoring of Video Surveillance

Abstract: The system gathers a sizable dataset of human faces during the data gathering phase in order to train the machine learning algorithms. In the face detection phase, computer vision algorithms are used to discover and recognise human faces in an image or video stream. You may accomplish this by using The deep convolutional neural network (CNN) architecture of the VGG16 algorithm is one of the most widely used algorithms for this job. The VGG16 algorithm has produced cutting-edge outcomes in a variety of computer vision applications, such as face recognition. Computer vision and machine learning algorithms that can detect and validate human faces. Access control, monitoring, and security systems are just a few examples of the many uses for the system. Data gathering, face detection, face recognition, and verification are a few of the processes that the project goes through. A personal identification method called face recognition analyzes a person's physical features to determine their identity to detect and extract facial features from the Image. The process for recognizing faces in humans consists of two phases: face detection, which occurs quickly in people unless the face is nearby, and introduction, which identifies faces as belonging to specific people
Hand Gesture Recognition using Anchor Points for Real Time Predictions, Integrated with Voice Over (Text to Speech)

Abstract: There are billions of people in the world who have hearing and speaking impairments. According to a survey roughly 1 billion people are born with hearing and speaking problems. Such disabled or challenged people struggle a lot to communicate with normal humans. A blessing to them is Sign Language, using which they can communicate efficiently with others and can express their ideas and feelings. Sign language is a procedure in which people communicate through making gestures with their hand which are globally recognized and have standard interpretation. Sign Language can be taught to everyone, but it requires a lot of trainers and experts to train everyone personally. Since technology has a lot of reach and resources in this modern era, imbibing such Mechanisms into technology increases the reach of Sign Language Exponentially
Haralick Texture Features based Syriac(Assyrian) and English or Arabic documents Classification

Script identification is very essential before running an individual OCR system. Automatic language script identification from document images facilitates many important applications such as sorting, transcription of multilingual documents and indexing of large collection of such images, or as a precursor to optical character recognition (OCR), in this paper the characterized are between Syriac and English documents or between Syriac and Arabic documents were the characterized is achieved by extracting Haralick texture Features. it is investigated a texture as a tool for determining the script of document image ,based on the observation that text has a distinct visual texture. Further, K nearest neighbour algorithm is used to classify 300 text blocks into one of the two scripts: Syriac, and English , or Syriac and Arabic based on Haralick texture Features . The script was inserted to the System with different rotation angles between 0Âº and 135Âº and the results of recognition were good.
A Survey of Resources and Methods for Natural Language Processing of Serbian Language

Abstract The Serbian language is a Slavic language spoken by over 12 million speakers and well understood by over 15 million people. In the area of natural language processing, it can be considered a low-resourced language. Also, Serbian is considered a high-inflectional language. The combination of many word inflections and low availability of language resources makes natural language processing of Serbian challenging. Nevertheless, over the past three decades, there have been a number of initiatives to develop resources and methods for natural language processing of Serbian, ranging from developing a corpus of free text from books and the internet, annotated corpora for classification and named entity recognition tasks to various methods and models performing these tasks. In this paper, we review the initiatives, resources, methods, and their availability.
SOA for Dynamically Integrated Virtual Learning Environment Systems with Cloud Based Services

SOA is structural approach for creating services to be reused and shared, so it provides agility and cost saving in software development by dividing the application into multiple software components to be reused in other systems. Cloud computing is truly scalable and provide virtualized resources which users can subscribe. Using a cloud and SOA in virtual learning systems provide a great chance for learners to enhance gained learning outcomes. The adoption of cloud services also assists in reducing the cost of software, hardware, human resources and infrastructure. This paper will use SOA and cloud computing to transfer virtual learning systems in the cloud to be more integrated and interoperable through showing a conceptual model of distributed virtual learning system and using cloud computing combined with services oriented architecture, to contribute in interoperability and integration of e-learning systems in general
Data Association Between Perception and V2V Communication Sensors

The connectivity between vehicles, infrastructure, and other traffic participants brings a new dimension to automotive safety applications. Soon all the newly produced cars will have Vehicle to Everything (V2X) communication modems alongside the existing Advanced Driver Assistant Systems (ADAS). It is essential to identify the different sensor measurements for the same targets (Data Association) to use connectivity reliably as a safety feature alongside the standard ADAS functionality. Considering the camera is the most common sensor available for ADAS systems, in this paper, we present an experimental implementation of a Mahalanobis distance-based data association algorithm between the camera and the Vehicle to Vehicle (V2V) communication sensors. The implemented algorithm has low computational complexity and the capability of running in real-time. One can use the presented algorithm for sensor fusion algorithms or higher-level decision-making applications in ADAS modules.