Reviewerly/exHarmony huggingface dataset:
Internet+ Based Ecological Service Mechanisms for Labor Education

With the rapid development of technologies such as the Internet+, cloud computing, big data, artificial intelligence, and virtual reality, labor education has changed from knowledge accumulation and simple labor skills to innovative and creative capacity improvement. At present, the research attentions of labor education are labor education curriculum, labor values, labor skills, whole-person education, five educations simultaneously, model worker spirits. However, labor education should turn to the multi-dimensionality of student development, is gradually integrated with the subject curriculum, and synergistically promotes the spread and penetration of labor ideas through interdisciplinary labor, collaborative labor, learning by doing, and innovative labor. Research on labor education should deeply shift to improve students’ creative work: the development of integration of labor education and creative literacy, the transformation of labor objectives from the pursuit of simple labor knowledge and skills to innovation, the content of labor from school to school-enterprise alliance based on Internet + . In order to achieve the above, Internet + technology and the eco-service mechanism are very important. Therefore, this study introduces Internet + technology to build the eco-service mechanism of labor education. Internet + technology broadens the possibility of resource source of labor education, combination, and creation, eliminates labor fragmentation. Internet + technology also promotes the ecological flow and comprehensive service of labor education resources to enhance the overall quality of labor education. In the service mechanism of labor education, the enterprise's labor tutors and campus labor teachers are introduced into the labor space and the superior resources of labor space to promote students to labor innovation and improve creative wisdom skills in the cooperation and exchange of diverse talents, and committees to cultivating comprehensive talents with innovative labor thinking and innovative capabilities.
Secure Cloud Database based on Verification Procedure

More and more sensitive data represented by financial data connect with cyberspace. Cloud data management contributes to control the data efficiently. This paper shows a cloud database scheme that holds two verification mechanisms. One is verification whether the retrieved data corresponds to the intended data. Second is the retrieved is surely belongs to the data owner by confirming multi-signature on the data. The cloud does not guarantee the correctness of the returned data; therefore, the former feature is necessary. Besides, since multiple entities are related to data creation nowadays, the data user concern about the authenticity of the multi-data owners. Multi-signature on the cloud database solves this issue. We provide performance analysis and it is shown that the proposed scheme assures the verification, being realized with practical computation time.
Exploration and Practice of Open Sharing Management Mode of University Laboratories Based on Internet Informatization

To solve the common management problems in the open operational mode of laboratory, this thesis proposes an Internet and information-based management mechanism of sharing equipment. It offers offline/online support and guarantee of virtual reality, builds a vertical, hierarchical management model, thus making laboratory management more reasonable and efficient. In this management model, laboratory builds an ecological development system based on an Internet information technological data sharing platform.
Performance Analysis of the IBM Cloud Quantum Computing Lab Against MacBook Pro 2019

Quantum Computing is the conjunction of Quantum Physics, Computer Science, Mathematics and Nanotechnology. While this technology is extremely complex and unexplored, this paper addresses and explains the basic functioning of these devices. Additionally, it covers its most tangible applications nowadays, as well as the short-term implementation and development of these ones. Our research reflects the experimental performance of IBM’s Quantum Computer Cloud Lab. This is an environment designed to interact with IBM’s Quantum Computer by using the Jupyter Notebook interface, Conda package and environment manager, and Python. The results of different computations were mirrored on a 2019 MacBook Pro. The outcomes of these experiments were unexpected due to the low performance of this tool.
On Asymptotic Quiescent Position in Time-Delay Systems

The nonlinear time-delay systems are considered and the limiting behavior of their solutions is investigated. The case in which the solutions have the trivial equilibrium that may not be an invariant set of the system is studied. The Lyapunov–Krasovskii functionals approach is applied to obtain sufficient conditions for the existence of an asymptotic quiescent position in the large. In the case when a general system has a trivial solution, new sufficient conditions for its asymptotic stability are obtained. Examples that illustrate the application of the obtained results are given.
A Computer Vision Toolkit for Adapting to a COVID-19 Lifestyle

With the fomenting situation that the COVID-19 pandemic brought with it since 2020, the need to adapt to a cautious lifestyle is still the need of the hour. According to the CDC, washing hands frequently, maintaining social distancing and wearing facial coverings are essential precautions one must follow. But with everything that’s going on, one can easily forget to follow one. This brings an opportunity for utilizing computer vision aid to adapt to a “COVID lifestyle”. Taking this motivation into consideration, we developed a computer vision system/toolkit that supports facial-mask detection, social distance monitoring and setting hand washing reminders. A novel facial feature-based data creation was proposed for training and testing our CNN model. The modules in our toolkit are highly portable, making it easy for users to incorporate them in their programs/utilities. We also ensure privacy and security while transferring the camera data stream in a server-client network.
Intelligent Techniques for Crowd Detection and People Counting—A Systematic Study

Smart cities intend to form people’s lives more enjoyable and safer using advanced technologies. The crowded communities like schools, colleges, stadiums, or holy spots impact human convenience and also the threat of human security. Counting of people is a difficult task in crowded situations as it faces different problems like the intensity of light, moving of objects, and occlusion problem with the increase in human population, and there is a need to monitor crowd. Human monitoring can be quite an expensive and tedious task, making the way for the upcoming automated crowd monitoring systems. The importance for video-based monitoring systems is on the rise leading to the growth of interest in the field of crowd analysis comprises of detection, tracking, behavioral analysis, etc. Recent trends show that deep learning algorithms can detect and estimate the crowd density with high accuracy rate. This research work presents the recent advancement in the area of crowd detection and people counting using intelligent techniques.
Requirement Analysis of Complex System Based on DSL

In recent years, MBSE (model-based system engineering) is finding wider and wider application in the practical engineering, however, in model-driven engineering, requirements analysis has no suitable model to support. Thus, this paper proposes to use domain-specific languages (DSL) to support requirements analysis and to build a language for requirements analysis. Based on the needs of practical engineering and analysis methodology to determine the syntax and the semantics of the DSL. Using the DSL built, analyzed the functional requirements and the non-functional requirements of the manned/unmanned aircraft collaborative air warfare systems. Meanwhile, this method is compared with the method of using SysML, which proves the effectiveness of the method presented in this paper.
Introduction to Data Visualization

We learned the basics of NumPy in the previous chapter. This chapter is fully focused on learning more functions of NumPy library. We will also learn the basics of Matplotlib library for data visualizations. Just like the previous chapter, we will have a lot of hands-on programming in this chapter too. The chapter covers the following topics:
Embracing security transformation with MDR

Digital transformation has become a major area of focus for nearly every business in every sector. With 65% of GDP around the world expected to be digitalised by 2023, it is clear that digital transformation is more than just another passing buzz phrase. 1 The advantages of joining the wave of digitalisation include increased agility, better customer experience, better employee productivity and improved operational efficiency. But in an age of increasing threats, security needs to be considered a priority when it comes to transformation – yet many digital transformation strategies overlook security completely or see it as an afterthought.
FAULT DIAGNOSIS OF TURNOUT SWITCH MACHINE BASED ON BRAIN-INSPIRED INTELLIGENCE

As the core equipment to control the running direction of railway vehicle, the turnout switch machine, its failure will lead to a series of problems. At present, more and more researchers conduct intelligent re-search on its fault diagnosis. In this paper, aiming at different types of faults during the operation of turnout switch machines, a spiking neural networks model based on apoptosis mechanism (BASNNs) is established as a classifier for fault diagnosis. The model uses neuron competition rules and intelligent unsupervised learning algorithms to update the network. The system uses the non-contact measurement of the sound signal as the input, and uses the combination of empirical mode decomposition (EMD) and wavelet packet decomposition energy entropy (WPDE) to extract features of the sound data. Experimental results show that the proposed method has better data recognition ability than traditional ANNs with the same number of layers.
Reinforcement Learning With Dual-Observation for General Video Game Playing

Reinforcement learning algorithms have performed well in playing challenging board and video games. More and more studies focus on improving the generalisation ability of reinforcement learning algorithms. The GVGAI Learning Competition aims to develop agents capable of learning to play different game levels that were unseen during training. This paper summarises the five years' GVGAI Learning Competition editions. At each edition, three new games were designed. The training and test levels were designed separately in the first three editions. Since 2020, three test levels of each game were generated by perturbing or combining two training levels. Then, we present a novel reinforcement learning technique with dual-observation for general video game playing, assuming that it is more likely to observe similar local information in different levels rather than global information. Instead of directly inputting a single, raw pixel-based screenshot of the current game screen, our proposed general technique takes the encoded, transformed global and local observations of the game screen as two simultaneous inputs, aiming at learning local information for playing new levels. Our proposed technique is implemented with three state-of-the-art reinforcement learning algorithms and tested on the game set of the 2020 GVGAI Learning Competition. Ablation studies show the outstanding performance of using encoded, transformed dual observations as input.
Development of an Online Programming Environment That Enables Real-Time Monitoring of Learning Status

As of 2021, the demand for online lectures has increased, and it has become difficult to understand students′ learning status in programming practice classes. Therefore, to effectively enhance learners′ motivation and ability even in online lectures, we developed an online programming environment that allows teachers to monitor how learners are programming in real-time. Our environment is flexible enough to support practical application development exercises, and the operation logs are recorded in detail. We introduced our environment to a hybrid lecture, including online and face-to-face lectures, and the analysis results showed some tendencies, such as the higher the grade, the more often the program was executed. The questionnaire survey results showed that about 90% of the students gave a positive opinion, but some improvements were found to be necessary. In the future, we will work on implementing features that were deemed necessary to improve the quality of the lecture.
Examples of Flow Control

This chapter gives some examples of flow control as well as ways to do the examples using indexing. The first example uses nested for loops and if/else statements. The second example uses the while statement. The third example is of nested for loops. The fourth example uses a for loop, an if statement, and a next statement. The fifth example is of a for loop, a repeat loop, an if statement, and a break statement.
THE EFFECTIVENESS OF USING MIND MAPPING STRATEGY TOWARD WRITING ABILITY FOR THE TENTH-GRADE STUDENTS AT SMA NEGERI 3 MOJOKERTO

Especially for students, writing become more important to be mastered in delivering their ideas during writing activity. To developing their ideas, students need strategy. It must be given high attention by teachers during teaching. One of the strategies to develop the ideas in writing is Mind Mapping strategy. Mind mapping have important role for students in writing recount text. Students will be easier to connect one event to other events. Same as the other strategy in learning process, mind mapping have some steps to do that. In this research, the researcher wants to measure The Effectiveness of Using Mind Mapping Strategy toward Writing Ability for The Tenth-Grade Students at SMA Negeri 3 Mojokerto in academic year 2016/2017. The result of t-test was 7,153. After got the t- test score, the reseracher compared it with t-table (df = n1 + n2 – 2 = 72; significance 5% = 0.05). The value of t-table was 1.666. It means that too is highest than table (7.153 &gt; 1.666).
Design of cross-system identity authentication system suitable for new-type electric power system

In order to solve the flexibility boundary security access problem of new-type electric power system, this paper has designed a cross-system identity authentication system which can help power grid and systems both on the generation side and demand side to build a foundation of trust for further data sharing. This system can realize a variety of cryptograph-based unified identity authentication such as PKI-based, IBC-based, blockchain-based identity authentication, etc. This system is also designed to meet high concurrency requirements of identity authentication. In order to verify the fucntion of the CSIA system, this paper has also make the system workflow simulated. The test results showed that the system can provide a cross-system identity authentication service effectively for systems and devices based on different identity authentication technology.
Multilingual Sentiment Analysis for User Discussions on Social Networks: An Approach Based on a Modified SVM Algorithm

Sentiment analysis of users’ messages on social networks is a compelling task in terms of both academic research and application of the research results to real-world business analytics. One of the key problems of sentiment detection in real-world discussions on social media is their mixed languages and, thus, the demand for multilingual instruments. In this paper, we, first, shortly describe the existing research on multilingual sentiment analysis. We suggest our own approach of data processing for classification and an enhanced sentiment detection method based on the SVM algorithm. To evaluate these methods, we apply them to marked-up noisy data from ad hoc discussions on social networks (in English, Russian, French, and German language) and clean data from Twitter US Airline Sentiment collection and assess the quality of sentiment detection by standard metrics. We show that our method reaches highest values of F1-score (0.78 and 0.94) for noisy and clean datasets.
Towards Advanced Evaluation of Collaborative XR Spaces

Extended Reality (XR) technologies such as head-mounted displays are deemed beneficial for the collaboration of co-located as well as distributed people. As such, XR technologies appear particularly promising for supporting distant and hybrid teaching which became highly relevant during the Covid-19 pandemic. Despite the potential awarded to such technologies, practical applications are still very rare. In order to investigate the impediments to the practical adoption of XR technologies, the respective systems should be evaluated in real-world settings. Existing evaluation tools are, however, not suited for this purpose. In this paper, we explain why today’s evaluation tools such as questionnaires, observation, and performance measurements are not sufficient for evaluating long-time, exploratory, and collaborative tasks that are typical in educational settings. To address this gap, we follow a top-down approach: Based on an existing model of user acceptance, we specify the variables that are to be optimized by HCI research and outline the potential of wearable-based measuring instruments to quantitatively assess these parameters. Eventually, we point out related research gaps that should be addressed by future research.
Multi-user Steerable Virtual Reality Cycling System with 3D Virtual Explorable Environment

The design and implementation of a multi-user virtual reality cycling system are presented in this paper. This system is designed to incorporate full steering, speed synchronization, online/local multiplayer, and a 3D virtual explorable environment. To achieve those functions and achieve technical feasibility, multiple sensors, and specially designed 3D printed hardware components were integrated. An ultrasonic sensor was introduced into the system for speed detection and synchronization. A novel turn mechanism component was invented and 3D printed for the bike's turning and steering function. An open world virtual town was built utilizing the Unity 3D engine for visual immersion and interaction. It used the Google cardboard mobile virtual reality (VR) system as the head-mounted display (HDM), for information display and versatility. Lastly, the Unity network framework was incorporated to achieve simultaneous co-existence of up to 20 players. Previous, similar products lacked natural steering control, and a multiplayer and explorable virtual environment. Overall, this prototype system successfully achieved all design objectives and made indoor VR cycling a more intuitive and interactive activity.
A Linear Pathfinding Algorithm for Planning Laser Treatment

Neurosurgeons non-invasively use Magnetic Resonance Imaging (MRI) as guidance to plan for laser treatment. Such a technique is mainly used for treating brain cancer cells, i.e., a brain tumor. In this paper, a novel approach is being implemented that may provide computational guidance for laser treatment planning. The approach applies a linear pathfinding algorithm on a MRI-Slice. A linear path’s cost is calculated based on certain reasonable assumption and best of these path are suggested to the treatment planner. The preliminary results display that our approach can locate those voxels that are assigned tumor designation based on simple thresholding technique on voxel values of the MRI-Slice data. These lines are calculated and drawn over the MRI image to indicate the best spot. We evaluate the preliminary results using MRI software tools such as 3D Slicer and ImageJ/Fiji. The evaluation shows that our approach could provide a cost based linear path guidance mimicking the cost of applying laser treatment along the same path. Our algorithm therefore could provide computational guidance for a laser treatment planner.
Input and Output

The first step to solving many computational problems is reading data from the command line, interactive input, text or binary files, a network, a serial port, or a combination of these. The final step often involves writing data to text or binary files. In this chapter, we’ll cover input and output methods in detail, including reading and writing file formats important to scientific and numerical analyses—plain text files; binary files; the ubiquitous Excel formats .csv, .xls, and .xlsx; HDF5; netcdf4; XML; JSON; YAML; .ini; SQLite; and HTML.
Graphics and Animation in PyQt

As you design GUIs, you will find out that you can also explore your creative and artistic side through drawing and animating widgets. Since graphics are such an immense part of graphical applications, this chapter is only able to introduce topics related to 2D graphics, including lines, shapes, animations, and painting. If you are interested in creating GUIs that work with 3D visuals, Qt also has support for various graphics APIs, including OpenGL and Vulkan. If you are really interested in graphics in Qt 6, have a look at .
Intellectual Property and Artificial Intelligence: Emerging Prospects and Challenges

The 20th century is remarkably characterized by an increase in inventiveness due to more breakthroughs in science and technology and the emergence of Artificial Intelligence (AI) systems. Recent records show that AI systems, in addition to being an aid in the inventive process, are now capable of making independent inventions using data and instructions inputted by their programmers. Meanwhile, Intellectual property law (IP) ensures that one’s intellectual outputs (labour) is not exploited or annexed by another without one’s consent and approval. However, because AI is not a person and is in fact man’s brainchild, a growing debate in the field of IP and AI has been whether AI can, under IP law, obtain or be granted authorship/inventorship rights over its works and inventions. It is against this backdrop that this paper, while highlighting the milestone achieved by AI, its importance and prospects, evaluates what this challenge means for AI under extant IP laws. The paper concludes by making certain recommendations that would allow for the accommodation of AI within the law.
The Theory of Epistemic Spaces for the Diversity and the Unity of Knowing and Science

In this chapter, the concept of epistemic space is advanced, defined and explicated for the understanding of fuzzy spaces in the development of the theory of knowing as the theory of intellectual investment flows and the theory of information-knowledge system as the theory of intellectual capital stocks. In this framework, the theory of intellectual investment-capital process is seen as the theory of intellectual stock-flow dynamics, where the intellectual information-capital stocks provide capital-service input flows into the general neuro-decision-choice space and the intellectual investment flows provide continual updating of intellectual stocks in the space of quality-quantity dualities. The relevant spaces and sub-spaces are introduced leading to the definition and explication of the epistemic space and the development of theory of epistemic space for the understanding of both the theories of knowing and knowledge seen in terms of neuro-decision-choice activities over the space of problem–solution dualities.