Reviewerly/exHarmony huggingface dataset:
Towards End-User Web Scraping for Customization

Websites are malleable: users can run code in the browser to customize them.However, this malleability is typically only accessible to programmers with knowledge of HTML and Javascript.Previously, we developed a tool called Wildcard which empowers end-users to customize websites through a spreadsheet-like table interface without doing traditional programming.However, there is a limit to end-user agency with Wildcard, because programmers need to first create site-specific adapters mapping website data to the table interface.This means that end-users can only customize a website if a programmer has written an adapter for it, and cannot extend or repair existing adapters.In this paper, we extend Wildcard with a new system for enduser web scraping for customization.It enables end-users to create, extend and repair adapters, by performing concrete demonstrations of how the website user interface maps to a data table.We describe three design principles that guided our system's development and are applicable to other end-user web scraping and customization systems: (a) users should be able to scrape data and use it in a single, unified environment, (b) users should be able to extend and repair the programs that scrape data via demonstration and (c) users should receive live feedback during their demonstrations.We have successfully used our system to create, extend and repair adapters by demonstration on a variety of websites and we provide example usage scenarios that showcase each of our design principles.Our ultimate goal is to empower end-users to customize websites in the course of their daily use in an intuitive and flexible way, and thus making the web more malleable for all of its users.
Parallelism-preserving automatic differentiation for second-order array languages

We develop automatic differentiation (AD) procedures for reductions and scans—parameterized by arbitrary differentiable monoids—in a way that preserves parallelism, by rewriting them as other reductions and scans. This is in contrast with the literature and with existing AD systems, which are either general, but force sequential execution of the derivative program, or only include hand-crafted rules for a select few monoids (usually (0, +), (1, ×), (−∞, max) and (∞, min)) and thus lack the general flexibility of second-order languages.
RETRACTED: Research on the Application Value of Orff Music Education System in College Music Education Based on Computer New Media Technology

Abstract Public music is a part of college education, which can improve students’ music literacy. Through computer multimedia technology, colleges and universities can guide students to study actively, which is the important value of Orff music education system. With the comprehensive reform of China’s higher education, Orff music education system has gradually become an important method in music education, which can improve the quality of students’ learning. Through computer multimedia technology, Orff music education system can lead students to learn more comprehensively, which has become an important way of diversified guidance. Through music, art, sports and other multiple courses, colleges and universities can improve students’ quality, which will better improve students’ participation and creativity. First of all, this paper analyzes the important application value of Orff music education system. Then, this paper puts forward some problems in the application of Orff music education system. Finally, some suggestions are put forward.
Let’s talk about webcams, and a pedagogy of kindness

With the move to online and blended learning, there has been much focus amongst educators on webcam use in online classes. Mandatory webcam policies and privileging use of webcams as the preferred form of engagement disregard the COVID-19 context – in which students have had limited choice about learning in blended or online modes – and significantly undermine trust. This piece argues for the adoption of a pedagogy of kindness, through teaching and learning practices that are sensitive to the material experience of diverse groups of students, and considers some of the complex reasons why insisting on webcam use may exacerbate inequalities.
Protecting the global internet from technology cold wars

Considering the perceived dangers of the global information flow.
Comparative research on the formation of backbone media of wireless self-organizing network by DLA-GF algorithm and ant colony algorithm

A mobile ad hoc network is a complicated distributed system organized by mobile terminals or wireless nodes through wireless connections. The mobile ad hoc network is suitable for those who lack basic communication equipment or do not have technical communication equipment, and the price is relatively high and impractical. It is agreed that the node can move and maintain the connection when connecting or leaving at any time. Wireless ad hoc network routing technology occupies an important position in wireless networks. First, wireless communication depends on wireless routing. At present, it is necessary to select an appropriate route for transmission on wireless communication. Therefore, routing of wireless ad hoc networks is the most important technology in wireless networks. Because the network is a free combination of mobile users, and the bandwidth of the wireless connection network is relatively limited. Network topology Since each node in the network can join or move freely, it is very important to find a link for forwarding data in a dynamic network. This article analyzes the common problems of hop count in MANET networks and compares the backbone of MANET. The wireless ad hoc network composed of DLA-GF algorithm and ant colony algorithm proposes an effective method to detect the routing in the wireless ad hoc network. Combined with route detection, the node sends multiple copies of the hop count packet to increase node communication Degree. The algorithm can effectively overcome the problem of ambiguity in the number of hops in wireless ad hoc networks, and achieve the effect of saving network energy and reducing power consumption.
Ontology Service Center: A Datahub for Ontology Application

With the growth of data-oriented research in humanities, a large number of research datasets have been created and published through web services. However, how to discover, integrate and reuse these distributed heterogeneous research datasets is a challenging task. Ontology is the soul between series digital humanities resources, which provides a good way for people to discover and understand these datasets. With the release of more and more linked open data and knowledge bases, a large number of ontologies have been produced at the same time. These ontologies have different publishing formats, consumption patterns, and interactions ways, which are not conductive to the user’s understanding of the datasets and the reuse of the ontologies. The Ontology Service Center platform consists of Ontology Query Center and Ontology Validation Center, mainly using linked data and ontology-based technologies. The Ontology Query Center realizes the functions of ontology publishing, querying, data interaction and online browsing, while the Ontology Validation Center can verify the status of using certain ontologies in the linked datasets. The empirical part of the paper uses the Confucius portrait as an example of how OSC can be used in the semantic annotation of images. In a word, the purpose of this paper is to construct the applied ecology of ontology to promote the development of knowledge graphs and the spread of ontology.
RETRACTED: The Practice of Multidimensional Interactive Teaching Mode Based on Big Data Analysis in College English Teaching

Abstract English is one of the world’s universal language. With the frequent exchange of our country with the world, the society has a higher demand for English talents. According to the analysis of big data, the reform of the traditional teaching method and the cultivation of the comprehensive English talent are the goal of the English education in our country, including the multi-dimensional interactive teaching mode, the limitation of the traditional mode, the practice teaching activity and the training of the students’ language expression ability. To provide students with a good language learning environment is the function of the interactive teaching mode which should be promoted in our education [1].
Regulation of Cryptocurrency in Various Jurisdiction across the World

Various national and regional authorities have been forced to grapple with their regulation given the expansive growth of the cryptocurrency over the years While the terminology used to describe cryptocurrency varies from one jurisdiction to another, one of the most common actions identified across jurisdictions is the Government issued notices about the pitfalls of investing in cryptocurrency markets mostly issued by the Central Banks As earlier stated, the warnings issued by various countries majorly centres around the fact that cryptocurrencies may create an avenue for illegal activities such as money laundering, terrorism, and other organized crimes.
Application of quantum optimization techniques (QUBO method) to cargo logistics on ships and airplanes

The video (https://youtu.be/qB07ueMVw0w) presents our ongoing work on the optimization of cargo logistics processes with containers using quantum computing, mainly in airplanes and barges, of great international relevance. Combinatorial optimization problems are computationally complex in conventional computing. The origins of Quantum Computing date back to the early 90's. This discipline allows solving problems that in conventional computing are complex [1]. We present a Quantum Computing tool, the QUBO method (Quadratic Unconstrained Binary Optimization) [2], which is suitable for formulating combinatorial optimization problems. QUBO is a recently developed tool, based on Quantum Annealing and is implemented in some current quantum computers. It consists of minimizing outputs of the type x <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">T</sup> Qx with x being a binary decision vector and Q a square or triangular matrix with constant parameters provided by the model. Restrictions can be added to the treated system. These problems have to do with making good decisions in environments where a large number of binary decisions (Yes/No) must be made and each set of decisions produces a corresponding objective function value, such as a cost or benefit value. In the video we also present the example of the Number Partitioning Problem.
How Strong Is a Counterfactual?

The literature on counterfactuals is dominated by strict accounts (SA) and variably strict accounts (VSA). Counterexamples to the principle of Antecedent Strengthening were thought to be fatal to SA; but it has been shown that by adding dynamic resources to the view, such examples can be accounted for. We broaden the debate between VSA and SA by focusing on a new strengthening principle, Strengthening with a Possibility. We show dynamic SA classically validates this principle. We give a counterexample to it and show that extra dynamic resources cannot help SA. We then show VSA accounts for the counterexample if it allows for orderings on worlds that are not almost-connected, and that such an ordering naturally falls out of a Kratzerian ordering source semantics. We conclude that the failure of Strengthening with a Possibility tells strongly against Dynamic SA and in favor of an ordering source-based version of VSA.
The Creation Method of a Head-up Display for Cars Using an iPhone

The aim of this work is to present some aspects on creating a HUD (head-up display) for ears using a mobile phone. A head-up display is a premium feature in a ear, which can enhance driving safety, because the driver does not have to look down on the gages, he can look at the road, but still be able to see some useful data like, the speed of the vehicle or the current time. This data is projected to the windscreen of the vehicle, so the driver can look the road thought the windscreen, but still be able the be noticed if he did not respect the speed limit. The projection is small and transparent, so the driver will not be bothered, by the projection and it won’t influence his field of view during driving.
Application of quantum approximate optimization algorithm to mission planning of command and control organization

The mission planning problem in command and control organization can be mapped into a combinatorial optimization problem with many variables and is difficult to solve. The traditional heuristic list planning method faces the problems of high time complexity and poor real-time response. For the mission planning problem in command and control organization, a quantum circuit solution scheme is proposed based on quantum approximate optimization algorithm in this work. Firstly, the mission planning problem is transformed into a typical combinatorial optimization problem, the exact coverage problem. Then, by constructing the corresponding mathematical model, the final state Hamiltonian expression of the quantum approximate optimization algorithm for the exact coverage problem is derived. The quantum circuit based on the quantum approximate optimization algorithm is designed. Finally the parameters in the quantum logic gate are optimized by the momentum gradient descent algorithm, and the simulation experiment is carried out by using the quantum software development environment of the Origin Quantum Computing Company. The simulation results show that the quantum circuit scheme can be used to solve the mission planning problem, reduce the time complexity of the algorithm, and improve the resource utilization to a certain extent. This work lays the foundation for further application of quantum algorithm to solving the mission planning problem in command and control organization.
Instagram Hashtag Prediction Using Deep Neural Networks

Instagram is one of the most popular photos sharing services. For more convenient content search people use hashtags (#nature, #love, etc.) in posts with photos. The author’s aim is to make hashtag prediction possible and convenient for users. The paper provides a reader with a detailed theoretical overview of Multi-Label Image Classification, Knowledge Distillation, and an overview of ResNet architecture. Next, the author proposes improvements on ResNet architecture allowing the model to boost quality and converge faster. Finally, the model type Self-Improving-Modified-Resnet (SIMR) is presented. Their main feature is the additional bottleneck block used as the tool incorporating benefits from a combination of self-training and knowledge distillation.
RETRACTED ARTICLE: Big data-based twin network target tracking and local regional economic development

When presenting and analyzing big data, this article believes that big data can provide people with the convenience hidden behind massive data, so people can make better decisions based on the objective laws of the development of things. Big data can derive the laws hidden in the data by analyzing a large amount of data. Through careful analysis and data mining, the possibility of personal privacy being exposed will also increase. Target tracking is still a challenging task in image processing, and it has always attracted the attention of experts and scholars at home and abroad. Target tracking algorithms based on twin networks are becoming more and more extensive and have achieved good results, but they have also led to various competitions, the most representative of which is based on fully folded dual network tracking algorithms. Today, China applies big data technology in economic development, but it still faces many challenges, including lack of application awareness, limited technology, and sharing barriers. This article explains the special meaning of big data, discusses its importance to the regional economic development of a certain province, and proposes important measures to make full use of the role of big data in local regional economic development. With the development of local regional economy and the improvement of people’s living standards, the role of the government has changed from promoting the local regional economy to providing public services. Therefore, local governments must change their functions, consider the role of the market in regulating resources, strengthen the subjective initiative of enterprises, and coordinate the allocation of resources between the state and the market in order to promote regional economic development.
RETRACTED: Analysis of University Students Entrepreneurial Opportunities and Risks Based on the Big Data

Abstract In the era of big data, how to use big data for innovation and entrepreneurship has become a hot topic for colleges and society. In the era of big data, college students are faced with many opportunities and new challenges [1-3]. This paper analyzes the current situation of college students’ entrepreneurship in the era of big data, discusses the opportunities and risks that big data brings to college students’ entrepreneurship, and finally discusses how college students in the era of big data control the entrepreneurial opportunities and better prevent entrepreneurial risks.
Quantitative Equational Reasoning

Equational logic has been a central theme in mathematical reasoning and in reasoning about programs. We introduce a quantitative analogue of equational reasoning that allows one to reason about approximate equality. The equality symbol is annotated with a real number that describes how far apart two terms can be. We develop the counterparts of standard results of equational logic, in particular, a completeness theorem. We define quantitative algebras and free quantitative algebras which yield monads on categories of metric spaces. We show that key examples of probability metrics, in particular, the Kantorovich metric and the Wasserstein p-metrics, arise from simple quantitative theories. Finally we develop a quantitative version of the theory of effects in programming languages.
Application of Online Courses and Teaching Model of "Blended + Flipped"

NOTICE OF RETRACTION: While investigating potential publication-related misconduct in connection with the ICIMTech 2021 Conference Proceedings, serious concerns were raised that cast doubt on the integrity of the peer-review process and all papers published in the Proceedings of this Conference. The integrity of the entire Conference has been called into question. As a result, of its investigation, ACM has decided to retract the Entire Conference Proceedings and all related papers from the ACM Digital Library.
A Novel Architectural Model for Dynamic Updating and Verification of Data Storage in Cloud Environment

Cloud computing is a quickly emerging computing model in the IT industry. Due to the rapid increase in technology, many clients want to store multiple copies of the same data in multiple data centers. Clients are outsourcing the data to cloud service providers and enjoying the high quality of service. Cloud service providers (CSP) are going to charge extra amounts for storing multiple copies; CSP must provide the firm guarantee for storing multiple copies. This paper proposes a new system model for storing and verifying multiple copies; this model deals with identifying tarnished copies which are transparent for the clients. Also, it deals with dynamic data control in the cloud with optimal results.
Recognition of Emotion in Indian Classical Dance Using EMG Signal

Indian classical dance forms like Kathak are an enrichment of Indian culture and tradition. These dance forms glorify its beauty by expressing nine emotions (Navras) such as Adbhut (amazed), Bhayanaka (fearful), Hasya (humorous), Karuna (tragic), Raudra (fierce), Shringar (loving smile), Veer (heroic), Bibhatsa (disgusted), and Shant (peaceful). Identifying correct emotions is an important task. The objective of this research work is to recognize Navras in the Kathak dance. Proposed research work can assist dance teachers in an accurate and unbiased evaluation process of dance examination. This research work analyzed the Electromyogram (EMG) signals acquired from eleven subjects. The EMG signals collected from the various locations on the face and neck represent the emotions and head movement. The EMG signals are processed to extract integrated EMG (IEMG) features. This research introduced a new feature named 'difference in IEMG feature' for improving the accuracy of emotion recognition. For the classification of nine emotions, the Least Square Support Vector Machine (LSSVM), Nonlinear Autoregressive Exogenous Network (NARX), and Long- and Short-Term Memory (LSTM) classifiers were used. The classifiers' performance is judged with head motion and without head motion. The classification accuracies are calculated using a maximum, variance, and mean of the feature. LSSVM, NARX, and LSTM classifiers achieved 60.80%, 81.67%, and 92.28% classification accuracies, respectively, using the IEMG feature and head motion. Using the new feature, LSSVM, NARX, and LSTM classifiers achieved 64.29%, 81.27%, and 93.63% classification accuracies, respectively. The overall classification accuracy improved by 1.46% by using the new feature.
Mining detailed information from the description for App functions comparison

The rapid development of Apps not only brings huge economic benefit but also causes increasingly fierce competition. In such a situation, developers are required to develop and update innovative functions to attract and retain users. Afterwards, analysing the functions of similar products can help developers formulate a well-designed plan at the beginning of development as well as make updated strategies during the version update process. However, although there have been some methods that can be applied to extract the features from App descriptions to achieve this purpose to some extent, the features they obtained do not cover the details of App functions. Therefore, to conduct an in-depth research on App functions, a novel method is proposed to extract App features with detailed information and an approach to integrate the gained results for further helping developers obtain the valuable knowledge better is provided. Subsequently, a series of experiments is carried out to evaluate our method. The results reveal that the proposed method can mine the features with detailed information from descriptions and integrate them effectively and also can assist developers to compare with other competitors and develop a better competitive analysis scheme.
An improved Kohonen self-organizing map clustering algorithm for high-dimensional data sets

&lt;p&gt;Manipulating high-dimensional data is a major research challenge in the ﬁeld of computer science in recent years. To classify this data, a lot of clustering algorithms have already been proposed. Kohonen self-organizing map (KSOM) is one of them. However, this algorithm has some drawbacks like overlapping clusters and non-linear separability problems. Therefore, in this paper, we propose an improved KSOM (I-KSOM) to reduce the problems that measures distances among objects using EISEN Cosine correlation formula. So far as we know, no previous work has used EISEN Cosine correlation distance measurements to classify high-dimensional data sets. To the robustness of the proposed KSOM, we carry out the experiments on several popular datasets like Iris, Seeds, Glass, Vertebral column, and Wisconsin breast cancer data sets. Our proposed algorithm shows better result compared to the existing original KSOM and another modiﬁed KSOM in terms of predictive performance with topographic and quantization error.&lt;/p&gt;