Reviewerly/exHarmony huggingface dataset:
The Application and Research of VR Animation Technology in Intangible Cultural Heritage

With the rapid innovation and widespread use of digital technology, digitization has become an inevitable choice for the inheritance and development of intangible cultural heritage in contemporary times. This paper takes the intangible cultural heritage of Chinese Danzhai Miao batik as an example to study the advantages of VR animation technology applied in the digital transmission and protection of intangible cultural heritage. Combining historical books and documents and physical images, implementing digital restoration of the Danzhai Miao batik in Zbrush, topologizing the material mapping required for the artifacts in Adobe Photoshop, building the VR virtual display education space in 3ds Max, and rendering the final effect. By presenting the final results, the advantages of cooperation between interdisciplinary computer technology and intangible cultural heritage are reflected, and the future research of VR animation technology and 3D digital modeling technology in related fields is summarized. Better build a "panoramic" "experiential" "three-dimensional" digital scenes of intangible cultural heritage. It will provide strong support for the promotion and dissemination of Chinese intangible cultural heritage.
Research on the Display of VR Animation Technology in the Cultural Communication of "Méi School" Art of Peking Opera

This paper takes the image of Mu Guiying in the stone carving Lady General Mu takes Command at the north end of the Wangfeng Terrace of Nanshan Temple in Wutai Mountain as an example to start VR animation display, so as to study the advantages of combining the content of Méi School Art display and VR technology in the dissemination of cultural heritage. Using MAYA and ZBRUSH tools to create 3D models of Mu Guiying's stone sculpture image, combined with virtual reality animation technology, people can immerse themselves in experiencing the charm of the Méi School Art, in order to realize the interactive, active and positive nature of Méi School Art culture dissemination, and promote the positive dissemination and development of intangible cultural heritage. This research uses VR technology to showcase representative characters in Mei Pai Peking Opera, virtualizing and digitally communicating the national culture. Users can easily increase their awareness of Mei Pai Peking Opera culture while effectively communicating the cultural heritage through multimedia and mixed created in digital 3D,including still and moving images for viewing.
A new approach for teaching programming: Model-based Agile Programming (MBAD)

Designing courses for introductory programming courses with a heterogeneous audience (business and IT background as well) is a challenging task. In an internal project of the School of Business at the FHNW University of Applied Sciences and Arts Northwestern Switzerland (FHNW) a group of lecturers developed a concept entitled “Model-based agile development” (MBAD) which supports the learning of elementary programming concepts in an agile environment and builds the basis for advanced courses. MBAD will be used as a basic learning module for various Bachelor programs at the FHNW.
THERE HAVE NOT BEEN UNIVERSAL CATASTROPHES ON EARTH AND THERE WILL NOT BE

Based on new ideas on the deep magma formation, according to which t here is only one primary basalt magma, the article interprets the causes of catastrophic phenomena (volcanism, plutonism, earthquakes, tsunamis, glaciation, warming, etc.) exclusively in connection with mantle processes. External man-made causes practically make no matter. And endogenous processes proceed slowly, with long interruptions, locally, discretely. Therefore, there have not been universal catastrophes and there will not be. There is no reason for the climate globe-spanning panic.
Sustainable Development, Digitalization, and the Green Economy in Post-COVID-19 Africa

The COVID-19 global pandemic has been revealing on several fronts. Although it was a health problem, it has implications for political, economic, and socio-cultural relations. Politically, the state responded with policy measures to address the economic downturn wrought by the global pandemic. The reaction of the state to the global pandemic varied not only from country to country, but also within the context of the global North and global South. This chapter highlights the views of contributing authors on issues of sustainable development in Africa post-COVID-19. Specifically, the chapter focuses on governance and digitalization from the perspective of natural resource management, climate change and the green economy, the service sector, as well as agriculture and education.
The ‘Academic War’: A Case Study

This chapter focuses on the above-mentioned ‘academic war’ and deals with review articles only in English. Here, the modern theory of argumentation schemes is used, where of special interest is Walton et al.’s (Argumentation Schemes. Cambridge University Press, 2008, p. 220–275) “pragmatic theory of refutation” with its differentiation among “attack, opposition, rebuttal, and refutation” (p. 220) that are all basic notions to critical argumentation. The most important observations from this part of the study elicit several most outstanding characteristic features of the ‘academic war’ under investigation. Firstly, the premises criticism is based on are of predominantly content-oriented, theoretical character or are concerned with the validity of the analysis. This focus on content is primarily directed by the aim of the publications, namely, to refute crucial theoretical claims put forward by the opponent(s). Secondly, the language is highly personalized, i.e., the authors resort not only to the first person singular, thus expressing their own opinion, but also constantly try to involve the audience in the process of argumentation through extensive use of the inclusive ‘we’ and, even more untypical of the written mode of presentation—the direct address (‘you’). Thirdly, in terms of the argumentation schemes analyzed in the study, the fact that the refutations dominate overwhelmingly is not surprising at all, considering the goals and nature of the discourse. There is also abundant use of questions/‘questioning the premises and/or the conclusions’—a feature of this discourse that is more typical of the spoken mode of academic communication. Finally, a distinctive feature of the means of argumentation observed in the corpus is the employment of a lot of metaphors and irony, as well as argumentation schemes such as personal attacks, direct interaction with the reader, ‘preaching’ ethics of intellectual enquiry, story-telling elements, etc., all of them being quite far from logical argumentation proper, usually expected in academic publications.
Beyond the Rhetoric: Digitalization Policy for Resilience in Africa Post-COVID-19

African countries have acknowledged the role of digitalization in the continental development agenda. This chapter focuses on digitalization policy and the institutional regime at the continental level and in selected African countries. The analysis examines digitalization policies and institutions in terms of the structure and organization of the African digital ecosystem, including the regulatory framework with the related implications for the ownership structure, privacy, cost, and consumer protection. The role of digitalization, as a technological enterprise, is never neutral in any society and harnessing it will require both appropriate policies and institutions. The chapter, with an emphasis on the required, necessary, and sufficient conditions for a sustainable digital landscape in Africa, interrogates and offers viable suggestions, drawing on experiences of digitalization from both the global North and global South, to better contextualize the post-COVID-19 world in Africa as part of the broader effort toward the United Nation-sponsored Agenda 2030 and the African Union’s Agenda 2063.
The African State, Sustainable Development, Digitalization, Green Economy in Africa Post-COVID-19

Policymakers and other stakeholders, both within and beyond, have been involved in various discussions and efforts to attain development on the African continent. This concluding chapter therefore synthesizes, against the backdrop of sustainable development, the role of the UN Agenda 2030 and the African Union Agenda 2063, the increasing significance of digitalization and the natural resources infused discourse on the green economy in Africa’s quest for development. While discussions on the role of natural resources and digitalization in Africa’s development have been part of the African reality in recent times, the underlying argument in this chapter is that the potential impact in Africa of these variables cannot be considered inevitable. Thus, not only should the role of development policy and institutions be approached in a nuanced manner, but also, there is the need to demonstrate that global and continental policy frameworks that underpin the notion of Africa Rising do require human agency to attain the stated goals. The changing fortunes of the African economy became evident during the global pandemic, revealing the precarious nature of the African state. Different aspects and processes of natural resource governance and digitalization on the continent stress the fact that the leapfrogging implications of the development processes involve myriad factors. Hence, even though there is a discernible and flourishing digitalization thrust on the continent, there are questions about the regulatory framework, good governance concerns, and digital divide issues that need addressing to ensure the attainment of development goals.
Protection and Empowerment of Women in the Era of Cyberspace: A Strategic Imperative for India

The advent of the internet turned over a new leaf for mankind as it turned the world into a Global Village and enhanced communication across the globe. It also plays an important role in the empowerment of women as they can access knowledge, information, and services, which was a distant dream for them. They now have the ability to learn new skills and engage in multifarious activities that were narrowed down due to the archaic era which defined traditional gender roles for women. It alsoprovides them with a platform to voice their opinions, interact with the outside world and raise their voices on gendered social issues. However, it is crucial to understand that women have been the victims of violent and heinous crimes for ages. They are often considered as scapegoats and targeted for the commission of socio-legal damages, wrongdoings and crimes transpiring in the Indian society. The cyber space has been no dissimilar for women as they are exposed to crimes like cyber defamation,sexual harassment, indecent exposure by men on the internet, email misrepresentation and much more. They are vulnerable to receiving sexual content and inappropriate messages over the internet which amounts to online abuse. As a result, the cyberspace is not able to have the desired positive impact on women. This study undertakes an analysis of the issues faced by women in the cyberspace. It dwells upon the need for cyber security and effective tackling of cybercrimes for protecting women incyberspace. It offers suggestions to ensure women empowerment in the truest sense.
Resampling Based Particle Filter Estimation of a Quadrotor

Quadrotors have dynamic nonlinearities, coupling effects and unstable open-loop characteristics. Control of quadrotors are still an open issue. Flight controllers need the sensor outputs to calculate the attitude angles. However, unmanned aerial vehicles are prone to sensor noises and disturbances. To control a quadrotor, its states must be effectively estimated. So, in this work, resampling based particle filter is presented and effect of particle size is investigated for attitude estimation problem of a quadrotor.
Measuring the Contribution of Batik Education Treatment Due to the Optimal Control of the Dynamic Model of Drug Addicts

Central Sulawesi placed as the 4 th of addicted drugs highest number in Indonesia.This paper proposes batik education treatment as an alternative for BNNK Palu in conducting its controlling program.There are three running programs; that are education (C 1 ), rehabilitation (C 2 ) and interaction monitoring (K).The contribution is measured by finding the optimal value of parameter control rates of the dynamic model of drug spread addicts population that divided into five sub-population namely the Vulnerable sub-population ( S), the Drug addicted sub-population ( P), Educated sub-population ( Sa), Rehabilitated patient sub-population ( Pa), and Post-rehabilitated patient sub-population ( Ra).Using Pontryagin Method, the programs that respectively treated to S and Pa give the optimal values C 1 = 93.33%,C 2 = 85,74% and K = 10.The research result also shows that the contribution of batik education is 49,36%.
Implementation of the Gath-Geva Clustering Algorithm in the Clustering Districts/Cities in Central Sulawesi Based on Public Health Development Indicators

Public health development indicators are a health indicator set that can describe health problems.The health indicators set can, directly and indirectly, increase longevity and healthy life expectancy.Central Sulawesi was listed as the sixth province in Indonesia with the lowest public health development score.In order to develop an equitable and appropriate health development strategy in each region in Central Sulawesi, this can be done by clustering the districts/cities in central Sulawesi on the basis of public health development indicators using the Gath-Geva Clustering method.The algorithm of the Gath-Geva Clustering method uses a distance norm based on Fuzzy Maximum Likelihood Estimation (FMLE) with an exponential aspect, which allows the method to converge faster and thus reduce the number of iterations.Using the validity index Kwon, rank/weight m = 2, threshold ε = 0.0005, and the iterations maximum number is 1000, we obtained that the optimal number of clusters is 3 clusters, and the attributes of each cluster vary according to the development index of public health.Cluster 1 is a low public health development cluster, cluster 2 is a medium public health development cluster, and Cluster3 is a high public health development cluster.
AL4SLEO: An Active Learning Solution for the Semantic Labelling of Earth Observation Satellite Images—Part 2

In the previous chapter (Part 1), a cascaded Active Learning method was proposed as an efficient solution to three problem cases being typical for Earth observation images: (1) Multi-label semantics, (2) Multi-sensor semantic labelling, and (3) Multi-temporal semantic labelling. In this Part 2, the method is demonstrated using the data acquired by different space-borne sensors such as: TerraSAR-X, Sentinel-1, WorldView-2, and Sentinel-2. The accuracy of $$90\%$$ obtained for the proposed cascaded Active Learning method was compared with traditional or deep learning methods (e.g., k-NN, Latent Dirichlet Allocation (LDA), Convolutional Neural Network (CNN)), and the results demonstrate that the proposed method is at least equal to or better than the methods we used for comparison. This active learning method can be used successfully for benchmark generation of large Earth observation (EO) data sets.
Metaheuristics for Feature Selection: A Comprehensive Comparison Using Opytimizer

The exponential growth of data generation was essential to the recent advances in machine learning. However, processing such an amount of data imposes challenges and constraints, such as redundant and irrelevant information, which increases the computational burden and usually decreases the learning efficiency and effectiveness. In this scenario, feature selection approaches are suitable for data preprocessing and optimization, particularly the ones based on metaheuristic optimization techniques. This chapter provides a comprehensive comparison among metaheuristic-based architectures for feature selection, as well as a hands-on tutorial followed by a case study using the Opytimizer( https://github.com/gugarosa/opytimizer ) framework and the Naïve Bayes classifier.
Measurement Simulation System of Fringe Projection Profilometry Based on Ray Tracing

Fringe projection profilometry (FPP) plays an important role in the quality control of complex surface workpieces. Simulation using realistic image synthesis referring to physical sensors provide valid measures for the design and optimization of FPP systems. In the simulation of FPP, ray tracing can simulate the fringe image acquisition process, considering the comprehensive influence of light source, camera and object attributes. Therefore, a measurement simulation system of FPP based on ray tracing is developed in this paper. The simulation model and measurement principle of FPP are introduced. On this basis, the methodology of simulating camera imaging by ray tracing is proposed, including scene construction, ray generation and gray value calculation. Principle experiments are carried to verify the accuracy and efficiency of simulation system, and comparative experiments are conducted for demonstrating its reproducibility to physical system. The proposed system provides a convenient and accurate mean for analyzing measurement errors and optimizing inspection strategy.
Mixed Integer Programming for Time-Optimal Multi-Robot Coverage Path Planning With Efficient Heuristics

We investigate time-optimal Multi-Robot Coverage Path Planning (MCPP) for both unweighted and weighted terrains, which aims to minimize the coverage time, defined as the maximum travel time of all robots. Specifically, we focus on a reduction from MCPP to Min-Max Rooted Tree Cover (MMRTC). For the first time, we propose a Mixed Integer Programming (MIP) model to optimally solve MMRTC, resulting in an MCPP solution with a coverage time that is provably at most four times the optimal. Moreover, we propose two suboptimal yet effective heuristics that reduce the number of variables in the MIP model, thus improving its efficiency for large-scale MCPP instances. We show that both heuristics result in reduced-size MIP models that remain complete (i.e., guaranteed to find a solution if one exists) for all MMRTC instances. Additionally, we explore the use of model optimization warm-startup to further improve the efficiency of both the original MIP model and the reduced-size MIP models. We validate the effectiveness of our MIP-based MCPP planner through experiments that compare it with two state-of-the-art MCPP planners on various instances, demonstrating a reduction in the coverage time by an average of 27.65% and 23.24% over them, respectively.
AL4SLEO: An Active Learning Solution for the Semantic Labelling of Earth Observation Satellite Images—Part 1

Active Learning is when a machine is interactively interrogating a user (information source) to label selected data samples with appropriate annotations. Our approach is based on Active Learning, a sub-category of supervised machine learning, where–based on user-selected representative data points and their interactive classification—the support by expert image analysts provides highly reliable image classification results for all unlabeled data points. The basic idea behind Active Learning is that a machine learning algorithm (e.g., a Support Vector Machine approach) selects some promising data from which it learns, thus achieving greater classification accuracy with fewer training points. Active Learning can also include Relevance Feedback that supports users to search for other images of interest (e.g., patches of large satellite images) in a large repository. In addition, any newly discovered classes that do not exist yet can then be defined by these expert users exploiting their specific domain knowledge; however, different experts with individual class-specific expertise might assign different labels to the new classes. We assumed that there is already a list of predefined semantic labels for the already known classes, but when using this method, new classes can be discovered, or some anomalies within the data can be detected and annotated. The idea behind this Active Learning method is that it is designed to obtain higher classification accuracies (depending on the given class) with very few training examples. The method can be applied to a single image, to multiple images (from different locations), to multi-temporal images (same location over a period of time), and even to multi-sensor images (same location acquired by different sensors). In this Part 1, a cascaded Active Learning method is proposed as an efficient solution to three problem cases being typical for Earth observation images: (1) Multi-label semantics, (2) Multi-sensor semantic labelling, and 3) Multi-temporal semantic labelling. In the following, the data used for demonstration was acquired by the space-borne sensors TerraSAR-X, Sentinel-1, WorldView-2, and Sentinel-2. The results obtained for the proposed cascaded Active Learning method will be given in Part 2.
Recursive Cross-View: Use Only 2D Detectors to Achieve 3D Object Detection Without 3D Annotations

Heavily relying on 3D annotations limits the real-world application of 3D object detection. In this letter, we propose a method that does not demand any 3D annotation, while being able to predict fully oriented 3D bounding boxes. Our method, called Recursive Cross-View (RCV), utilizes the three-view principle to convert 3D detection into multiple 2D detection tasks, requiring only a subset of 2D labels. We propose a recursive paradigm, in which instance segmentation and 3D bounding box generation by Cross-View are implemented recursively until convergence. Specifically, our proposed method involves the use of a frustum for each 2D bounding box, which is then followed by the recursive paradigm that ultimately generates a fully oriented 3D box, along with its corresponding class and score. Note that, class and score are given by the 2D detector. Estimated on the SUN RGB-D and KITTI datasets, our method outperforms existing image-based approaches. To justify that our method can be quickly used to new tasks, we implement it on two real-world scenarios, namely 3D human detection and 3D hand detection. As a result, two new 3D annotated datasets are obtained, which means that RCV can be viewed as a (semi-) automatic 3D annotator. Furthermore, we deploy RCV on a depth sensor, which achieves detection at 7 fps on a live RGB-D stream. RCV is the first 3D detection method that yields fully oriented 3D boxes without consuming 3D labels.
Safely: Safe Stochastic Motion Planning Under Constrained Sensing via Duality

Consider a robot operating in an uncertain environment with stochastic, dynamic obstacles. Despite the clear benefits for trajectory optimization, it is often hard to keep track of each obstacle at every time step due to sensing and hardware limitations. We introduce the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\mathtt {Safely}{}$</tex-math></inline-formula> motion planner, a receding-horizon control framework, that simultaneously synthesizes both a trajectory for the robot to follow as well as a sensor selection strategy that prescribes trajectory-relevant obstacles to measure at each time step while respecting the sensing constraints of the robot. We perform the motion planning using sequential quadratic programming, and prescribe obstacles to sense based on a novel connection between the duality information associated with the convex subproblems and the effect of uncertainty reduction through Kalman filter updates. We guarantee safety by ensuring that the probability of the robot colliding with any of the obstacles is below a prescribed threshold at every time step of the planned robot trajectory. We demonstrate the efficacy of the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\mathtt {Safely}{}$</tex-math></inline-formula> motion planner through software and hardware experiments.