Reviewerly/exHarmony huggingface dataset:
Learning to see the physical world

I am fascinated by how rich and flexible human intelligence is. From a quick glance at the scenes in Figure 1A, we effortlessly recognize the 3D geometry and texture of the objects within, reason about how they support each other, and when they move, track and predict their trajectories. Stacking blocks, picking up fruits---we also plan and interact with scenes and objects in many ways.
MOBILE TECHNOLOGIES AS A TOOL IN EFL TEACHING

Even the groundswell of interest in mobile applications has not so far contributed to their integration into educational programs as an EFL learning tool. The purpose of the present review is to identify the current state and prospects for the use of mobile technologies in EFL teaching. The methodological basis of this research is a theoretical analysis of the literature data on the research topic. The evaluation of contemporary empirical studies conducted in Australia, China, Iran, Turkey, Saudi Arabia, Cyprus, Japan, Malaysia, Spain, Taiwan and other countries, has led to a conclusion that the implementation of mobile technology in EFL teaching gives predominantly positive results due to several merits of mobile devices relative to standard pedagogical tools. It was however underlined that researchers have yet to learn how to conduct methodologically sound, statistically relevant studies that would cover aspects of learning activities beyond the use of mobile technology. The authors conclude that when studying applications, researchers should not try to find a mobile application that can teach students everything they need, but should study the ways in which individual applications help to master a foreign language.
Sketchy With a Chance of Adoption: Can Sketch-Based Telemetry Be Ready for Prime Time?

Sketching algorithms or sketches have emerged as a promising alternative to the traditional packet sampling-based network telemetry solutions. At a high level, they are attractive because of their high resource efficiency and provable accuracy guarantees. While there have been significant recent advances in various aspects of sketching for networking tasks, many fundamental challenges remain unsolved that are likely stumbling blocks for adoption. Our contribution in this paper is in identifying and formulating these research challenges across the ecosystem encompassing network operators, platform vendors/developers, and algorithm designers. We hope that these serve as a necessary fillip for the community to enable the broader adoption of sketch-based telemetry.
The role of visualization of educational material in distance learning

The article discusses the principles that are the foundation of distance learning: completeness, systematicity, availability and openness of materials, interactivity. The main groups of problems that all participants in the educational process faced during the massive transition from full-time education to distance learning were identified — technological, organizational, methodological, as well as the problems of teachers and students being unprepared for this form of education. Examples of the most popular programs for audio and video conferencing are given, which are used by teachers to implement the principle of interactivity in distance learning. The results of a survey of students of the College for the Training of Social Workers of the Department of Labor and Social Protection of the Moscow City, which indicate the implementation of the principle of accessibility and non-compliance with the principle of interactivity in distance learning in a pandemic, are presented. Particular attention is paid to the use of the technology of visualization as a means of increasing the effectiveness of distance learning and the implementation of its principles. The online platform Online Test Pad, which can be used in distance learning, is considered. The use of this platform contributes to the implementation of the principles of completeness, accessibility and openness of distance learning.
Exploring the Blocks World state space

Abstract In this article we study and evaluate combinatorial algorithms for exploring state spaces of prototypical artificial intelligence problems that are represented by very large state space graphs. We are interested in the modeling and analysis of such graphs, including their visualization and quantification. We consider Blocks World as a prototype artificial intelligence problem that is often employed to introduce problem solving strategies using searching, planning, and reasoning algorithms. Our results are mathematical models and combinatorial algorithms supporting the concise definition of the Blocks World state space graph, as well as the exact evaluation of several metrics defined on this graph, including its number of states, its average number of stacks per state, its number of transitions, and its average branching factor. We also present experimental results supporting the effectiveness and efficiency of our proposed algorithms.
Implementation Goals for Multimodal Interfaces in Human-Computer Interaction

A multimodal interface will only be adequate if it is validated by usability criteria, namely, if it promotes: a faster interaction; a selective adaptation to different environments, users or usage behaviours; a shorter learning curve or being more intuitive; the recognition of information in a noisy environment (e.g. at the sound, visual or tactile level); the connection of presented information to a more global contextual knowledge (enabling an easier interpretation); and the translation of information between modalities. Hence, the option for a multimodal interface, over a unimodal, depends on the type of action to be carried out by the user, its potential for increased usability and experience it can provide. The multimodal interface research area constitutes a very active and constantly expanding interdisciplinary territory, and this fact contributes to the numerous implementation goals attributed to these interfaces. This article seeks to identify and enumerate them, supporting itself on a thorough bibliographic analysis.
Differentially Private Outlier Detection in Multivariate Gaussian Signals

The detection of outliers in data, while preserving the privacy of individual agents who contributed to the data set, is an increasingly important task when monitoring and controlling large-scale systems. In this paper, we use an algorithm based on the sparse vector technique to perform differentially private outlier detection in multivariate Gaussian signals. Specifically, we derive analytical expressions to quantify the trade-off between detection accuracy and privacy. We validate our analytical results through numerical simulations.
Multi-criteria methodology for LMS quality assessment within the framework of emergent learning system

In the article, using the case of Learning Management System (LMS), we consider a methodology for assessing the quality of education, taking into account the requests of experts, lecturers, and students. There is a growing relevance of such research due to the digitalization of education, the transition to distance learning as the main or auxiliary form of organizing the educational process. The applied methodology relies on the earlier developed concept of emergent learning and the system for the assessment of the quality of education, using the conception of negentropy. By adapting this methodology to the LMS assessment task, we show the importance of creating a hierarchical scheme of modules and functional elements necessary for an effective organization of the learning process. In order to provide an integral assessment, it is necessary, according to our position, to determine the weighting factor of each module and of each criterion by which this module is assessed and then to determine the values of each criterion for a specific LMS. A proposed flexible assessment system that takes into account the requests of all aspects of the educational process, allows, by modifying the weighting factors, to adapt the equation in accordance with the specificity of the subject area and educational institution within which the LMS is used. As an advantage of this methodology, it makes it possible not only to compare different LMSs in terms of quality but also to identify areas in which it is possible to improve and refine existing LMSs. We analyze the risks associated with the transformation of assessment systems from an auxiliary tool into an end in itself. In this regard, we propose an algorithm for separating qualitative and quantitative factors accounting, which helps to avoid the negative effect of the absolutization of assessment systems. In the conclusion, we outline the ways of developing the design of such a system of the management of educational process in which quality requirements prevail over circumstantial ones.
Research Data Management (RDM) in the Fourth Industrial Revolution (4IR) Era

The emergence of the 4IR has brought new opportunities and possibilities for effective management of research data. Despite the positive impacts and effectiveness of this technological advancement, most academic libraries especially in Africa are not taking advantage of this reality. As a result of this, many libraries in the developing countries are struggling to satisfy the present and future information needs of researchers. Building on the 4IR, sustainable RDM practices in academic libraries become necessary and urgent. The observation led to the decision to address issues related to RDM practices and the 4IR. The authors present the conceptual considerations of RDM, the roles of academic libraries in RDM, and the 4IR technologies as well as strategic actions for academic libraries towards the 4IR. The authors conclude by affirming that the adoption of 4IR will not only connect librarians with machines for “smart” performance, but will expand the scope, visibility, and access to research data, among others.
Gesture Detection using Tensor flow lite Efficient Net Model for Communication and E learning Module for Mute and Deaf

Human communication plays a vital role; without communicating, day-to-day tasks seem difficult to complete. And the world has an almost 5% population that struggles with hearing or speaking disability, which contributes to 430 million people worldwide, and this will grow up to 900million just in the next 25 to 30 years. With the increasing noise pollution, hearing capacity degrades, leading to various hearing problems. The WHO statistics show that 32million kids are acoustically impaired. With disabilities, there are multiple issues these people face, such as lack of learning facilities, job opportunities, communication platforms, etc. These people need a cooperative environment to express, learn at their pace and level of understanding. This paper focuses on developing an application that bridges the gap between these acoustically disabled people and people unknown to their way of communication. The proposed research is an edge device application provides features like a gesture to text, speech to text, e-learning platform, and Alert mechanism. This paper majorly focuses on developing a friendly all in one platform for mute and deaf community for communication, learning and emergency alerts. The research was conducted with two approaches the traditional CNN and Tensorflow lite EfficientNet model to train the ASL (American Sign Language) dataset for the communication platform, where we obtained accuracy of 98.91% and 98.82% respectively. To overcome the computational barriers of traditional CNN approach, Tensorf low lite Efficient Net model was brought into the picture. The proposed methodology would help build a platform for the deaf and mute community to express themselves better and gain wider exposure to the world.
Identifying Clusters of Primary and Secondary School Teachers According to Their Educational Digital Content Perceptions

The e-Schools project strives to increase information and communication technology (ICT) usage in primary and secondary schools in Croatia by providing ICT educational tools and services for teachers, students and schools in general. Among the others, digital educational contents (DEC) for the students were developed, tested and evaluated. In order to investigate teachers' perceptions about the quality and satisfaction with DECs, a survey was conducted. The total of 1 653 teachers participated in the online questionnaire after their students used DEC for a period of time/on their courses. After the data cleaning phase 1 623 teachers were included into data modelling. Data was analysed by means of descriptive data mining technique: latent class cluster analysis (LCCA) was performed with an aim to identify groups of teachers that share similar perceptions on the DEC. Four groups of teachers were identified, differentiating in their level of positive or negative perceptions with certain aspects of DEC: completely satisfied teachers, satisfied teachers, slightly satisfied teachers and slightly unsatisfied. In addition to quantitative analysis, qualitative analysis was performed in order to gain insight into attitudes and experiences that drive teachers' perspectives.
Identify the Presence of Hidden Information Based on Lower Coefficients Value of 2DHWT Sub-bands

This paper introduces an approach which can be discriminated between normal images and images containing hidden information. After applying one scale 2D Haar Wavelet Transform (2DHWT) on the image, a new image sub-band is configured contains the Lower Coefficients Value (LCV) among image detail sub-bands. The differences in three directions between adjacent pixels of approximation and LCV image sub-bands are modeled utilizing 2 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">nd</sup> order Markov chains. Components of sample transition probability matrices (TPMs) are then utilized as feature vector for a proposed approach implemented by linear support vector machine (SVM) and Naive Bayes (NB) classifiers. Proposed approach is evaluated by detection accuracy of three common image embedding methods at three quality factors (QFs) with five different embedding rates. The comparison in using approximation sub-band with the other detail sub-bands reveals that the presented feature vector offers an improvement in detection accuracy.
Distributed Accounting and Blockchain Technology in Financial Accounting

Abstract Blockchain management involves all aspects of blockchain, and its ultimate goal is to improve the efficiency of blockchain operations. This research mainly discusses the application of distributed bookkeeping and blockchain technology in financial accounting. Distributed systems require all nodes within the enterprise to upload inventory data to the system regularly. These data can be uploaded only after most nodes in the system confirm that they are correct. Invalid information is filtered to ensure that the data is true, accurate and reliable. By constructing a blockchain-based supply chain system, the integration and reconstruction capabilities of the supply chain can be improved. The information recording of internal data and external related multi-source data in the block can improve the learning ability of the supply chain. With the passage of time, the cost of holding has gradually decreased from 200,000 yuan before the simulation to 80,000 after the simulation. This research helps to encourage companies to form inventory holding quantities that adapt to their own conditions and reduce inventory holding costs.
Static Video Summarization: A Comparative Study of Clustering-Based Techniques

The spectacular increase of video data, due to the availability of low cost and large storage enabled video capturing devices, has led to problems of indexing and browsing videos. In the past two decades, video summarization has evolved as a solution to cope up with challenges imposed by big video data. Video summarization deals with identification of relevant and important frames or shots for efficient storage, indexing, and browsing of videos. Among various approaches, clustering-based methods have gained popularity in the field of video summarization owing to their unsupervised nature that makes the process independent of the need for the expensive and tedious task of obtaining annotations for videos. This study is an attempt to comprehensively compare various clustering-based unsupervised machine learning techniques along with evaluation of performance of selective local and global features in video summarization. Quantitative evaluations are performed to indicate the effectiveness of global features—color and texture as well as local features—SIFT along with six clustering methods of different nature. The proposed models are empirically evaluated on the Open Video (OV) dataset, a standard video summarization dataset for static video summarization.
Virtual Equipment System: Expansion to Address Alternate Contexts

Virtual Equipment System (VES) is a body-centric 3D User Interface design framework built to advance the development of interfaces that capitalize on user’s proprioception in immersive environments. In a previous poster paper submitted to HCII last year, we focused on the application of this framework in developing a series of virtually embodied interfaces for adjusting auditory and visual user settings. We outfitted the user with Virtual Equipment that correspond to the user’s sensory organs. For example, by interacting with Virtual Headphones and performing gestures, the user can adjust the audio volume of the system. Similarly, the user can interact with Virtual Goggles to adjust brightness settings. Since then, we have expanded the development of the VES and its functionalities. In particular, to support additional contexts in the form of a set of Virtual Equipment known as Equipment Set or simply as Set. A user can simultaneously be “wearing” several Equipment Sets, each designed for a specific context. That is to say, multiple Equipment Sets affect the user at the same time, though the user can only interact with a Set at a time. With simple actions, however, the user can switch between different Sets and access the functionalities of the Set within the context of its use. So far, we have built three demos to showcase VES in different contexts: Auditory and Visual user settings, privacy settings using VES in combination with the Voodoo Doll technique, and telematic sensory settings through the use of Alternate Avatars.
Container ID Detection and Recognition

Deep learning-based text detection from images is a stimulating research area. Here, we propose a deep learning framework for detecting container ID and ISO. The steps involve container detection, text detection, character detection, and character classification. The RetinaNet model is utilized for container detection and character detection. For text detection, semantic segmentation is used. Semantic segmentation is the task of classifying each and every pixels in the image to a predefined class. For character classification, a custom CNN model is utilized. The system overcomes the disadvantages of the manual system. The proposed frameworks outperform the existing techniques for container ID detection and recognition with good accuracy.
Stepwise Evaluation Methodology for Smart Watch Sensor Function and Usability

Physiological and behavioral sensors on consumer-grade wearable devices have great potential to inform augmented cognition applications in everyday living. However, lack of understanding of usability and function of new devices when embedded within larger technical systems is a barrier to their implementation in translational research. Practical evaluation methods are needed to overcome this fundamental barrier in a rapidly changing consumer-grade device landscape. We describe a stepwise evaluation methodology developed in our lab that is designed to rapidly evaluate and position consumer-grade sensors for use in larger studies.
A graph-based path planning algorithm for the control of tower cranes

This paper presents a new path planning procedure for transportation tasks of three degrees of freedom tower cranes assuming a known, regularly updated and quadratic obstacle map derived by imaging sensors. Key objectives are the identification of either short, energy-efficient or low exciting load sway paths and the capability to be combined with an anti-sway controller and its trajectory generation module. An exact cell decomposition is carried out for the workspace of the tower crane introducing cells in the shape of circle parts. The height of each cell is determined considering the payload dimensions to ensure collision free paths. Moreover, a graph is derived by assigning a node to each cell and connecting the neighbors with circle arcs in tangential direction and lines in radial direction. The path finding is carried out utilizing an extended version of the novel graph searching algorithm L*. The extension follows from the fact that the height costs depend on the investigated path and thus need to be considered during the search. A simulation example of a realistic scenario is provided in order to discuss the generated paths.
To the question about selecting software to support the Learning process in informatics at secondary school realized online

The article analyzes the experience of teaching informatics in a comprehensive Moscow school in a distance form in 2020 during the coronavirus pandemic. Of all the variety of problems and issues generated by the pandemic, the issue of choosing the optimal system and application software to support the learning process stands out. The possibility of using various types of domestic free operating systems for these purposes is analyzed, and their brief comparative characteristics are given. It's considered what kind of application software, which is included in the distribution of the Alt Education 9 operating system, can be used to support the teaching of all topics of the informatics course in primary, secondary and high school. The advantages of the Alt Education 9 operating system over similar domestic operating systems are listed, and the conclusion is drawn about the need to select this type of operating system as the optimal option for implementing the educational process in a remote form.
Research on Immersive Virtual Reality Display Design Mode of Cantonese Porcelain Based on Embodied Interaction

In recent years, the development of Immersive Virtual Reality (IVR) provides new opportunities for the protection and inheritance of traditional handicrafts. Cantonese porcelain (CP) is one of the most important intangible cultural heritages in China based on its special cultural content and unique form of expression. However, according to the survey, we found that it is difficult for people to acquire the knowledge of CP because cultural connotation of CP is metaphorical, and it is difficult for people to have a profound cognition and understanding of it. To address the problems, this paper proposes an IVR display design mode of CP based on embodied interaction, and proves the availability of the mode with design practice. According to this mode, the knowledge of CP in IVR can be delivered to people through virtual roaming and interaction from three levels: physical embodiment, imaginary embodiment and knowledge construction. Through tests for participants, this method has been proved to be helpful for people to quickly establish the knowledge framework of CP. Furthermore, it provides a method reference for other development of traditional handicrafts.