Reviewerly/exHarmony huggingface dataset:
MU-NET: A MULTISCALE UNSUPERVISED NETWORK FOR REMOTE SENSING IMAGE REGISTRATION

Abstract. Registration for multi-sensor or multi-modal image pairs with a large degree of distortions is a fundamental task for many remote sensing applications. To achieve accurate and low-cost remote sensing image registration, we propose a multiscale unsupervised network (MU-Net). Without costly ground truth labels, MU-Net directly learns the end-to-end mapping from the image pairs to their transformation parameters. MU-Net performs a coarse-to-fine registration pipeline by stacking several deep neural network models on multiple scales, which prevents the backpropagation being falling into a local extremum and resists significant image distortions. In addition, a novel loss function paradigm is designed based on structural similarity, which makes MU-Net suitable for various types of multi-modal images. MU-Net is compared with traditional feature-based and area-based methods, as well as supervised and other unsupervised learning methods on the Optical-Optical, Optical-Infrared, Optical-SAR and Optical-Map datasets. Experimental results show that MU-Net achieves more robust and accurate registration performance between these image pairs with geometric and radiometric distortions.We share the datasets and the code implemented by Pytorch at https://github.com/yeyuanxin110/MU-Net.
Can AI replace Human? A Study on Customer Perception and Attitude towards AI-Based Chatbot in Food Service

Abstract: When interaction comes in digital world means interacting with AI- enabled chatbot, this study focuses on customer perception and attitude to conclude can AI replaced the human? Primary survey was done for collected the customer data, 300 people were targeted out of which 219 responds. The study concludes that customer still prefer human interaction over chatbot even chatbot provides many benefits like quick response, easy to use and convenient to interact at any time. After conclusion there is future scope of this study and some recommendation for food service providers in India. Keywords: Chatbot, Food Service, Artificial Intelligence, Food Industry
Exploring the literary element ‘mood’ in an award-winning Malaysian picturebook: A multimodal analysis

This article examines how an award-winning Malaysian picturebook for young learners entitled ‘The Magic Buffalo’ by Jainal Amambing utilizes visual and textual semiotic resources to develop the literary element ‘mood’. Knowledge of visual and textual meaning-making systems is necessary as it will enable young learners to achieve a deeper understanding of the literary element ‘mood’ in multimodal texts and also be visually literate. The literary element ‘mood’ is chosen because it helps to create the atmosphere and meaning of a story. In addition, this knowledge will also prepare young learners to deal with emotions in real life. The analysis is based on an adaptation of Painter et al.’s multimodal discourse analysis framework. The results of this study revealed that facial expression is the most prominent visual affect utilized in this picturebook, followed by bodily stance and ambiance respectively. The textual analysis reveals that the main character experiences an ongoing mental state, and un/happiness is the most commonly found emotion. The intermodal cohesion analysis clearly highlights how visual choices enhance the meaning provided by the textual choices. The use of visual symbols, facial expressions, and body posture help to corroborate and escalate the textual description of the characters’ emotional states. The study suggests that knowledge of visual and textual meaning systems will help young learners to critically analyse the literary element ‘mood’ and decode the meaning of multimodal texts.
Invisible culture dimension of gender discrimination: Speech cyberbullying against women on Chinese social media

This article examines the root reasons for speech cyberbullying against women in China under the context of the awareness of female independent consciousness and the feminist movement. Analyzing typical cases of speech cyberbullying against women on Chinese social media, we used a combination of historical and critical thinking. In our exploration of the root reasons for speech cyberbullying against women, the male gaze and silenced female, Chinese traditional concepts like guanxi and mianzi, patriarchy, the comparison between individualism and collectivism, and masculinity and feminity are all factors to which we paid close attention. To mitigate the problem of cyberbullying against women, the government should formulate punishments for perpetrators and advocate for women with practical actions on social media.
Verifying angular-position entanglement by Hardy's paradox with multisetting high-dimensional systems

High-dimensional entangled states are of crucial importance, as they provide higher channels for quantum information. Angular position, as a continuous variable, provides an infinite Hilbert space theoretically. It is usually represented in discrete bases experimentally because of the convenient modulation of the width of the angular aperture. Thus the combination of the angular apertures will conveniently shape the two photon states. And the entanglement of the two photon states can be naturally demonstrated by Hardy's paradox. Here, by testing Hardy's paradox for two-setting high-dimensional angular subspaces with dimension ranging from 2 to 7 and for multisetting three-dimensional subspaces with setting ranging from 3 to 5, we reveal the high-dimensional entanglement in the angular-position degree of freedom. We show that the high-dimensional angular-position entanglement can yield a much sharper contradiction between the quantum mechanics and classical theories. Our work shows that the angular variable can be considered as an alternative discrete base to provide the high-dimensional entangled states. Thus it may be used as a new platform for quantum information.
MCTK: a Multi-modal Conversational Troubleshooting Kit for supporting users in web applications

Conversational Interfaces for user assistance are becoming persuasive. Today, though, most chatbots are not integrated into the application in which they are placed, but only superimposed, with no communication between the conversational and the graphical interface. We propose Multi-modal Conversational Troubleshooting Kit (MCTK), a Python package to easily integrate a conversational agent for troubleshooting in web applications. MCTK is multi-modal: once the system recognizes the problem the user is encountering, the textual solution in the chat is coupled with visual hints in the GUI. On top of that, MCTK is easy to configure and offers separation of concerns: dialogue designers can work on the conversation without the necessity of modifying the code, and vice versa.
Bayesian Network Approach in Educational Application Development: A Systematic Literature Review and Bibliometric Meta-Analysis

Technological developments have brought about a paradigm shift in the world of education. The education system must be more open and flexible, where students can experience these opportunities according to their skill level. 21st-century education and the application of the elements of Revolution 4.0 Industry in education realize that initiative. The Bayesian Network approach is becoming one of the essential tools in the development of educational applications. Therefore, the persistence of this systematic review is to identify peer-reviewed literature on the Bayesian network approach in education. Scopus and Web of Science, and IEEE citation databases are used in the data-gathering phase. PRISMA approach and keyword search were obtained and analyzed. This bibliographic data of articles published in the journals over ten years were extracted. VOS viewer was used to analyzing the data contained in all journals and articles. This systematic review shows that the development in education can absorb the changes that occur in technology. The findings from 1160 articles extracted show that using the Bayesian approach in the development of educational applications improves the quality of use, especially from the point of students. The level of predictive accuracy generated through the Bayesian network approach improves the quality of educational application development. However, the study's findings indicate that there is scope for research related to the application and use of this approach in the development of educational applications.
Accurate Crowd Counting using Merged Datasets

For city surveillance, intelligent crowd control is crucial. Insufficient samples are huge obstacles in the process of crowd counting and in the learning of deep neural networks. In this work, we have conducted an exploratory study using large and small-scale crowd counting datasets with different scenes and densities. We simply concatenate publicly available datasets to improve the performance of the crowd counting model. We also present a new crowd counting dataset called HaCrowd which has a higher density than the available datasets. We found that merged datasets increase the crowd counting model performance.
A Parallel Turbo Decoder Based on Recurrent Neural Network

A neural network-based decoder, based on a long short-term memory (LSTM) network, is proposed to solve the problem that large decoding delay and performance degradation under non-Gaussian noise due to poor parallelism of existing turbo decoding algorithms. The proposed decoder refers to a unique component coding concept of turbo codes. First, each component decoder is designed based on an LSTM network. Next, each layer of the component decoder is trained, and the trained weights are loaded into the turbo code decoding neural network as initialization parameters. Then, the turbo code decoding network is trained end-to-end. Finally, a complete turbo decoder is realized. The structural advantage of turbo code component coding is fully considered in the design process, and the problem of decoding delay caused by the existence of interleaver is cleverly avoided. The introduction of deep learning technology provides a new idea to solve the traditional communication problems. Simulation results show that the performance of the proposed decoder is improved by 0.5–1.5 dB compared with the traditional serial decoding algorithm in Gaussian white noise and t-distribution noise. When BER performance is close, the LSTM decoder requires half or even less than that of BCJR. Moreover, the results demonstrate that the proposed decoder is adaptive and can be applied to communication systems with various turbo codes. The LSTM decoder shows lower bit error rate, computational complexity and higher decoding efficiency under the same conditions. Therefore, it is necessary to study the turbo code decoding technology based on deep learning combined with the actual channel environment.
Digital Technologies in Environmental Education

The study responds to the current goal of environmental education in Slovakia, which is to create a functioning integrated system of environmental education, instruction and awareness, using innovative tools while maintaining the principles of sustainable development. Many schools already have innovative didactic tools or technology, but the lack of interactive software on environmental education remains a problem. There is also a need for uniform methodological materials for teachers, using teaching strategies based on the effective development of pupils` environmental competences through digital technologies. This case study aims to present an analysis of the current state of environmental education and a digital support model for pupils` environmental education. The authors refer to the proposed and practically tested teaching material created in the Smart Notebook software.
Direct measurement of density-matrix elements with a phase-shifting technique on a quantum photonic chip

A direct measurement protocol allows reconstructing specific elements of the density matrix of a quantum state without using quantum state tomography. Until now, most direct measurement protocols have relied on ancillary pointers, which add complexity and are not always easy to implement experimentally. In this paper, we experimentally validate a direct measurement protocol requiring no ancillary pointers that calculates the value of a specific element of a quantum state's density matrix using only six projection measurements. We prepare path-encoded arbitrary four-dimensional quantum states on a silicon-based quantum photonic chip and measure the density-matrix elements of the four-dimensional quantum states using this protocol, with experimental results deviating from ideal values by an average of only $0.010\ifmmode\pm\else\textpm\fi{}0.004$. This approach has the potential to be applied to quantum information applications where only partial information about the quantum state needs to be extracted, for example, problems such as entanglement witnessing, fidelity estimation of quantum systems, and quantum coherence estimation.
Life skills education capacity structure of teacher in the context of current education innovation

The current general education innovation has clearly defined the quality and capacity goals that students need to achieve, in which shows the integration of life skills in the requirements of each quality and capacity at each educational level. With this innovation, the requirement on life skills education capacity of high school teachers is set. Thus, training in pedagogical schools should pay attention to developing this capacity for students. The article studies the structure of life skill education capacity of pedagogical students, creating a premise for pedagogical schools to develop this capacity for students, meeting the requirements of reforming the general education program in 2018.
Does Size Matter? Exploring how Standard and Large-Scale Displays affect Off-site Experts during AR-Remote Collaboration

Most efforts on Augmented Reality (AR) remote collaboration have been devoted to on-site individuals in need of assistance. Yet, since remote experts do not have access to the local environment, it is also important to explore how different methods affect the situation understanding and interaction. This work describes a user study with 16 participants aimed at comparing how remote individuals interact with standard (C1) and large-scale displays (C2) while providing assistance during a remote maintenance scenario. Results suggest condition C2 was preferred by the majority of participants, being considered more useful to analyze important details of the task context, as well as more easily create content.
Implementation Details for Controlling Contactless 3D Virtual Endoscopy

In the medical world, with the innovative application of medical informatics, it is possible to enable many aspects of surgeries that were not able to be addressed before. One of these is contactless surgery planning and controlling the visualization of medical data. In our approach to contactless surgery, we adopted a new framework for hand and motion detection based on augmented reality. We developed a contactless interface for a surgeon to control the visualization options in our DICOM (Digital Imaging and Communications in Medicine) viewer platform that uses a stereo camera as a sensor device input that controls hand/finger motions, in contactless mode, and applied it to 3D virtual endoscopy. In this paper, we will present our proposal for defining motion parameters in contactless, incisionless surgeries. We enabled better surgeon’s experience, more precise surgery, real-time feedback, depth motion tracking, and contactless control of visualization, which gives freedom to the surgeon during the surgery. We implemented motion tracking using stereo cameras with depth resolution and precise shutter sensors for depth streaming. Our solution provides contactless control with a range up to 2–3 m that enables the application in the operating room.
Future kindergarten teachers’ pedagogical support in the process of distance learning

The authors reveal the features of a pedagogical support organization for students of higher educational institutions (on the experience of future kindergarten teacher training) in the process of distance learning. The organization of pedagogical support of the distance learning process is carried out in several scopes, namely: analytical and diagnostic (monitoring of distance learning courses; students’ characteristics studying; identifying their cognitive and professional interests; determining the individual style of cognitive activity; monitoring educational subjects’ interaction); educational (conducting activities that increase distance learning participants’ psychological competence); advisory (advising on the development of learning material, advising distance learning participants on development, learning, professional and personal self-determination, on specific issues that arise during learning) and methodological (creating recommendations for teachers to increase student’s motivation and pedagogical support organization). The authors show that pedagogical support is not only pedagogical activity, aimed at student’s personality self-realization, but also the lecturer’s value attitude to each student’s personality; respect for their individual identities; perception of the student as an equal one, as a subject of the educational process and their lives, who have a unique inner world and ‘Me-concept’; care for future kindergarten teachers’ psychological comfort. Providing students with pedagogical support, the lecturer’s task is to select the types and means of support that would allow the student to unleash their inner potential without imposing a particular way of solving problems
Informatics Research on Mental Health Functioning: Decision Support for the Social Security Administration Disability Program

The disability determination process of the Social Security Administration’s (SSA’s) disability program requires assessing work-related functioning for individual claimants alleging disability due to mental impairment. This task is particularly challenging because the determination process involves the review of a large file of information, including objective medical evidence and self-reports from claimants, families, and former employers. To improve this decision-making process, SSA entered an interagency agreement with the Rehabilitation Medicine Department, Epidemiology and Biostatistics Section, in the Clinical Center of the National Institutes of Health, intending to use data science and informatics to develop decision support tools. This collaborative effort over the past decade has led to the development of the Work Disability–Functional Assessment Battery and has initiated an approach to applying natural language processing to the review of claimants’ files for information on mental health functioning. This informatics research collaboration holds promise for improving the process of disability determination for individuals with mental impairments who make claims at the SSA.
"Education and labour market performance in Romania. An empirical analysis of the urban-rural gap "

As education is the foundation of a prosperous and sustainable society and given the increasingly visible gap between urban and rural, the aim of the research undertaken in this paper is to present the level of education and labour market integration in Romania, in a comparative urban-rural approach. The dataset compiled for Romania is organized in two sub-panels, urban and rural, including indicators of the education system, but also fundamental credentials of the labour market, for the period 2000-2020. The research methodology is based on the application of two advanced econometric models, namely spatial models (lag and error) and Gaussian graphical models (GGMs). The results highlight the coordinates of the Romanian education system in the two areas of residence, urban-rural, but also the link between education and the labour market outcomes. Based on our findings, we propose adequate strategies to mitigate the gap between rural and urban and enhance the labour market performance.
Using quizlet to teach vocabulary

This study concerns with the major objective of foreign language teaching: vocabulary acquisition. The modern trends of teaching and the vast advance of technology enable teachers to use online and mobile applications in a very wide range. The real effect of using such a method need to be measured. Accordingly, this experimental-design study investigated the effect of Quizlet, a rapidly growing application with an online and mobile phone version, on vocabulary acquisition. Two groups of low-level EFL learners at Prince Sattam Bin Abdulaziz University in Saudi Arabia (N = 42) participated in the study. Each group underwent a pretest and a posttest to assess their acquisition of the assigned vocabulary lessons that were extracted from their syllabus. After using Quizlet for vocabulary learning for a month, the experimental group participants show a significant improvement in vocabulary posttest. Accordingly, the study acknowledges and recommends using the application at university level.
Information Competency Of University Students In Media Education Projects

The article deals with the research in the development of information competency of university students and project-based learning.The research methods are a review of current research on students' projectbased learning and development of their information competency, modeling and extrapolation.It is noted that the educational results of project-based learning of students are media-education projects as research and innovative projects to solve educational problems and learning objectives, affecting the quantitative and qualitative changes in the development of students' professional competency, including information competency, and self-development.The authors of the study emphasize that media education projects promote personal development with the help and through the content of social media and digital technologies, to develop information literacy in dealing with appropriate digital resources, project literacy, teaching various means of self-expression through digital tools.The teaching conditions of developing students' information competency as a transprofessional competency within the promotion of project-based learning in higher education and mastering academic skills by students in the form of media-education projects are also outlined.The paper describes the pedagogical experience of promoting the project-based learning system in a higher education institution and implementing pedagogical conditions of students' information competency development through the preparation of media education projects.
FuseME: Distributed Matrix Computation Engine based on Cuboid-based Fused Operator and Plan Generation

Operator fusion is essentially and widely used in a large number of matrix computation systems in science and industry. The existing distributed operator fusion methods focus on only either low communication cost with the risk of out of memory or large-scale processing with high communication cost. We propose a distributed elastic fused operator called Cuboid-based Fused Operator (CFO) that achieves both low communication cost and large-scale processing. We also propose a novel fusion plan generator called Cuboid-based Fusion plan Generator (CFG) that finds a fusion plan to fuse more operators including large-scale matrix multiplication. We implement a fast distributed matrix computation engine called FuseME by integrating both CFO and CFG seamlessly. FuseME outperforms the state-of-the-art systems including SystemDS by orders of magnitude.