Reviewerly/exHarmony huggingface dataset:
Taskrunner: A Flexible Framework Optimized for Low Latency Quantum Computing Experiments

Superconducting circuits, as used for quantum computing experiments, are commonly interfaced by microwave pulse sequences with gigahertz frequencies. To generate and analyze these pulses, we developed a versatile FPGA-based electronics platform. The modular FPGA firmware guarantees highest accuracy on the nanosecond timescale. More complex data acquisition and control schemes utilize the real-time co-processor of the heterogeneous Multiprocessor System-on-Chip (MPSoC) through an application-specific framework called Taskrunner. The framework complements the FPGA logic with versatile and low-latent control, data aggregation and evaluation capabilities. Within the framework, user tasks are specified conveniently using standard C language and compiled on the fly directly on the MPSoC platform.In this paper, we present the architecture of our Taskrunner software framework. We also provide timing benchmarks and compare execution times of common quantum computing characterization experiments with an FPGA-only approach.
Research on Artificial Intelligence Network Based on Deep Learning

Deep learning is part of the latest trends in machine learning and artificial intelligence research. This is part of the most popular trends in scientific research today. However, as deep learning develops rapidly, its progress is hard to keep up. Adaptive optimization methods, such as Adam, Adagrad, or RMSprop, have poor generalization performance compared to stochastic gradient descent (SGD). These methods tend to perform well in the initial stages of training, but SGD performs better in the latter stages of training. This article explains what problems artificial neural networks can be used for and the basic structure of these problems shows the development of deep learning and proposes solutions and related optimization methods for different problems.
The Algorithm of Document Classification of Research and Education Institution Using Machine Learning Methods

Currently, there are many classification technologies based on machine learning and artificial intelligence. However, a sufficient theoretical basis for the integration of existing classification methods for the analysis of documents of scientific and educational institutions is not developed. Within the framework of the research provided in the article, an algorithm of classification of documents is formed, taking into account the specifics of the documents of the subject area of scientific and educational institution. The system of characteristics, by which the documents can be grouped to solve the problem of combined classification, is also presented. The article considers the approach of preprocessing text allowing the use of well-known methods of machine learning to improve the accuracy and speed of documents classification. Thus, the conducted research can be used to solve the problem of classification of documents in electronic document management systems of scientific and educational institutions.
Research on Integrated Communication and Positioning Technology of Ship Formation in Weak Navigation Environment

Nowadays, communication device and positioning device are generally equipped on sophisticated shipborne combat platforms. If they are installed separately, they will occupy more platform space and be overcrowded; moreover, they will also reduce stealth performance and electromagnetic compatibility of ships. To solve this problem, we propose an integrated communication and localization method based on digital phased array antenna, employ its simultaneous multiple beams ability to reduce the time of signal search and communication link establishment, and meanwhile we apply super resolution Direction of Arrival (DOA) estimation algorithm and two-way propagation delay to carry out direction finding and ranging precisely. This method we present in this paper can realize the integration of communication and localization, furthermore, it does not rely on satellite system, especially suitable for the situation of ships formation self-organizing communication network and mutual positioning under weak navigation even satellite rejection environment.
Adaptive Visual Control of Robotic Manipulator With Uncertainties in Kinematics and Dynamics

In this paper, we develop a novel adaptive scheme for uncalibrated visual feedback systems of robotic manipulators to address the uncertainties in the kinematics and dynamics, which resulted from unknown parameters in the camera and the robotic manipulator’s physical model. A mixed estimated method is adopted to parameterize and estimate those unknown parameters in a practical model. To ensure the capability of the introduced controller, we claim novel adaptive algorithms to make the estimated errors of those unknown parameters converge to a small range. Numerical simulations confirm the validity of the presented scheme, whose image tracking error converges asymptotically towards zero via the Lyapunov method.
User Interface Design

This chapter provides the framework for understanding the influence of culture on the development of user interfaces. After the presentation of the influence of culture on the HMI, HMI-relevant cultural dimensions for the development of intercultural user interfaces are presented. Finally, the most important approaches, concepts and methods for intercultural user interface design (IUID) are presented.
Gaussian pseudospectral optimization method with smoothing penalty function path constraint handling for UAV obstacle avoidance planning

Trajectory planning is an important basis for autonomous flight of unmanned aerial vehicle (UAV). A Gaussian pseudospectral trajectory planning algorithm based on smoothing penalty function is proposed. Firstly, the boundary conditions and dynamic constraints of UAV are considered, and the path constraints are studied to establish the trajectory planning dynamic optimization model. Then, smoothing function is introduced to tackle the path constraints and this method is employed to transform the converted constraints. Combined with Gauss-Legendre collocation, the proposed method is given in detail. Finally, simulation experiment is carried out on UAV model. After the simulation experiment, the proposed method has better path constraints satisfaction and performance index than those of traditional Gaussian pseudospectral method.
The Promises and Perils of Robo-Advisers: Challenges and Regulatory Approaches

Artificial intelligence is changing the operation and business model of many intermediaries in financial markets. Investing through online automated platforms, known as robo-advisers, is becoming very popular around the globe. In fact, some studies estimate that robo-advisers worldwide will be managing USD 2.85 trillion by 2025. This chapter analyses the promises and perils of robo-advice, as well as the challenges and regulatory responses adopted in various countries and regions around the world, including the United States, the United Kingdom, the European Union, Australia, Hong Kong, Mainland China, and Singapore. It will conclude by showing that, despite the existence of various legal and regulatory challenges that need to be addressed, robo-advisers are expected to play a significant role in the future of the financial sector by reducing the costs of investment and wealth management services, and democratizing access to capital markets.
Legaltech and the Future of Startup Lawyering

How are the practice and business of law likely to be impacted by the rise of “legaltech”—the wide array of emerging technologies and innovative processes that are aimed at improving the delivery of legal services? This chapter focuses on one particular type of legal practice, the representation of venture-backed technology startup companies, as a useful case study for how legaltech is already making significant inroads in this arena and, further, how these technologies have the potential to change corporate and transactional lawyering more broadly in the future. The chapter explores why startup lawyering makes for a revealing and instructive case study of legaltech’s future impact on the legal industry; assesses the current state of startup lawyering practices, including how and to what degree the status quo is already in flux due to emergent legaltech innovations; and considers the import for startup lawyers of several technological innovations that are on the horizon, including artificial intelligence, distributed ledger technologies and legal workflow solutions. The chapter concludes with predictions of how the emerging technologies discussed may alter the business models and practices of startup law firms.
Distributed Trust Using Blockchain for Efficient Pharmaceutical Supply Chain

With traditional ERP systems, there is a lack of networking among suppliers, partners, and logistics providers. So, there is a need to have a holistic view of production and movement of goods from production to last mile delivery. The physical and digital supply chains need to be integrated to ensure secure supply chains that promote business excellence, collaboration among stakeholders, and reduce costs. The high-level view over their supply chains allows them to function better in a multi-channel world. It also helps them identify where to reduce stock without compromising customer service. Otherwise, it leads to a delay in delivery, counterfeit products, thefts, fraud, and cyberpiracy, which may lead to lawsuits and losing of brand image. The tacit function of supply chain management is to provide tracking of specific goods in the supply chain. So, it is imperative to leverage the blockchain technology stack to map multi-enterprise value networks and enable connected multi-modal networks.
Communicating Through Subliminal-Free Signatures

By exploiting the inherent randomness used by certain digital signature protocols, subliminal channels can subvert these protocols without degrading their security. Due to their nature, these channels cannot be easily detected by an outside observer. Therefore, they pose a severe challenge for protocol designers. More precisely, designers consider certain assumptions implicitly, but in reality these assumptions turn out to be false or cannot be enforced or verified. In this paper we exemplify exactly such a situation by presenting several subliminal channels with a small capacity in Zhang et al. and Dong et al.’s subliminal-free signature protocols.
Mathematic

Abstract This paper provides a classical interpretation of mathematics from terms to categories such as arithmetic, geometry, algebra, and trigonometry. The background of interpretation is based on mathematics itself as reasoning, which contains systematic and structure. However, the mathematical term is recognized by them, but it comes with a variety of symbols and ways of interpretation. That interpretation is accumulated into universe of discourse which is a means of mathematics itself, and it states the mathematic.
Recommender System for Multiple Databases Based on Web Log Mining

Finding information from a large collection of resources is a tedious and time-consuming process. Due to information overload, searchers often need help and assistance to search and find the information. Recommender system is one of the innovative solutions to the problem related to information searching and retrieval. It helps and assist searchers by recommending the possible solution based on the previous search activities. These activities can be obtained from the web log, which requires a web log mining approach to extract all the keywords. In this study, keywords obtained from the library web log were analysed and the search keyword patterns were obtained. These keyword patterns were from several databases or resources that were subscribed by the library. The finding revealed some of the popular keywords and the most searchable databases among the searchers. This information was used to design and develop the recommender system that can be used to assist other searchers. The usability test of the recommender system showed that it is beneficial and useful to the searchers. These findings will also benefit the management in planning and managing the subscription of online databases at the university’s library.
An Improved CornerNet-Lite Method for Pedestrian Detection of Unmanned Aerial Vehicle Images

Pedestrian detection is a key component to analyze the outdoor scene, which has an important part in object detection of unmanned aerial vehicle (UAV) images. The original ComerNet-Lite is sensitive to shooting angle and environments, making it difficult to detect pedestrians in case of distortion, blur and small scale. To address this issue, this paper proposes an improved ComerNet-Lite framework, which can effectively detect pedestrians in unknown angles and complex environments. First, CornerNet-Lite is improved by introducing the stacked hourglass module into the backbone to raise the ability to capture features and extracting information at every scale of UAV images. Second, we employ soft non maximum suppression (Soft-NMS) to improve pedestrian detection accuracy by modifying the confidence and detection box of the adjacent pedestrian. Finally, we evaluate improved CornerNet-Lite on the VisDrone2019 dataset achieves satisfactory results.
Graph Classification Model Based on Graph Neural Networks and Graph Distance

In recent years, multiple Graph Neural Network models have been proposed and applied to processing graph data and classification of graphs. However, when the graph data is limited, the model classification results are not satisfactory. In this paper, we propose a Graph Neural Network based model, which calculates the graph distance and Wasserstein's center of gravity on the base class tag, uses the K-Means method and Lloyd's algorithm, and gets the superclass by aggregation, which is called graph neural graph attention model (GNN-GAT). GIN is used as the feature extractor, and GNN network is used for classification. Secondly, we used MusicNtWrk to make two sets of graph datasets representing music mono-chord, downloaded the Triangles and Letter_high datasets, and imported these four kinds of datasets into the model for classification test and analysis.
The Model of Informational Space for Innovation and Design Activities in the University

The University loses the role of the only source of knowledge in the context of widespread use of network technology for access to information.Simple interfaces for obtaining knowledge on demand provide an opportunity for rapid self-education in the process of realization industrial or domestic tasks.Rethinking the role and place of the univer sity in training engineers and scientists, modernizing of models of information technology achievements' use by universities in their information systems becomes critically important. Problem Statement. Students are poorly involved in research and innovation activity, the model of organization of the work of universities separates the educational process from other activities.Purpose.To develop a model of scientific and educational information space for innovative and project activity of the community of teaching stuff and university students.Materials and Methods.The methods of logical and comparative analysis have been used. Results. The model of the integrated scientific and educational information space of a technical university with the organization of work on the basis of reliable sources is proposed. Taking into account the possibility of various ways of developing scientific research and the need for the formation of appropriate project teams, the information system for the project activity based on the concept of adaptive case management is proposed. The subsystem of the knowledge base of the training system for drilling equipment designing has been developed.Conclusions.The described models of scientific and educational work provide a project approach to the management of joint work of teaching stuff and students.The introduction of such management model necessitates the use of methods of project-based learning.Further research will aim at developing ways of implementation of project-oriented learning in the educational process of the higher education institution within the existing legislative and regulatory framework.
Protecting Locations with Differential Privacy against Location-Dependent Attacks in Continuous LBS Queries

With the development of location-based services (LBS), concerns on location privacy frequently arise. Location data often contains users' sensitive information, and direct release it may pose a threat to users' privacy. Differential privacy (DP), as a privacy preserving method with solid mathematical foundation, has been widely used in location data release. However, most if not all of the existing location DP mechanisms only consider static scenarios or perturb the location at single timestamp, which are vulnerable to the so-called location-dependent attacks (LDA) in continuous LBS queries. In this paper, an optimal location DP mechanism against LDA is proposed. Firstly, the necessary conditions for LDA defense are derived by combining the perturbation mechanism of location DP. Then the algorithm of safe perturbance region generation is established to dynamically calculate the perturbation range at each timestamp. Finally, we set up the optimization problem with the real-time quality loss as the optimization objective and the location DP and safe perturbance region as the optimization conditions, and realize the optimal DP mechanism for LDA by solving the optimization problem. Experiment results on real-world datasets show that our mechanism can effectively resist LDA, which also balance privacy protection and data utility well.
Blockchain Introduced

This chapter provides an introductory explanation of Blockchain technology and how it works, concentrating on its potential for social impact. It describes the history of the development of Blockchain, which is a form of distributed ledger technology.
Notions from Linear Algebra and Bra-Ket Notation

The Schrödinger equation ( 1.63 ) is linear in the wave function ψ(x, t). This implies that for any set of solutions ψ 1(x, t), ψ 2(x, t), …, any linear combination ψ(x, t) = C 1ψ 1(x, t) + C 2ψ 2(x, t) + … with complex coefficients C n is also a solution. The set of solutions of Eq. ( 1.63 ) for fixed potential V will therefore have the structure of a complex vector space, and we can think of the wave function ψ(x, t) as a particular vector in this vector space. Furthermore, we can map this vector bijectively into different, but equivalent representations where the wave function depends on different variables.
Weld Point Cloud Segmentation Algorithm Fused Contour Feature

In the scene of industrial quality inspection, the traditional point cloud segmentation algorithm applied to weld point cloud segmentation has the disadvantage of slow segmentation speed and low segmentation accuracy. To solve these problems, this paper proposes a weld point cloud segmentation algorithm which fuses contour features, the algorithm separates the contour and searches for key points of contour features, partitions the weld contour, then uses the RANSAC algorithm to remove the straight point cloud in each area, and finally retains the remaining point cloud and maps it back to the three-dimensional space. The experiment compared the RANSAC plane segmentation algorithm, the region growing segmentation algorithm and the improved segmentation algorithm. The experimental results show that the improved segmentation algorithm has the advantages of faster segmentation speed, higher segmentation accuracy and good robustness, and solves the problems of over-segmentation and under-segmentation in the traditional point cloud segmentation.
Shapley-value-based Quality Degradation Analysis Method for Adaptive Bitrate Streaming Services

In video-streaming services, adaptive bitrate (ABR) streaming is widely used, and service providers should monitor the quality of their services so that they can detect the quality degradation. Although many quality-estimation models have been developed for monitoring ABR streaming services, these models are insufficient for service providers. This is because, to improve their services after quality degrades, service providers need to know which quality-influencing features, such as audio bitrate, video representation (i.e., video bitrate, framerate, and resolution), and stalling, cause the degradation. In this paper, we propose a Shapley-value-based quality degradation analysis method to provide contribution values, which indicate the degree of quality degradation due to each quality-influencing feature for improving their services. The proposed method adapts the Shapley value concept to our problem and calculates the contribution values by comparing the estimated quality with the maximum quality, i.e., the quality of viewing history with the highest audio bitrates, highest quality level of video representation, and no stalling. In the evaluation, a viewing experiment dataset on ABR streaming is used, and results show that our proposed method can extract the quality-influencing feature that decreases quality the most by calculating contribution values.
A New Denosing Method Based on Local Similarity for Removing Impulse Noise

Due to the randomness and complexity of impulse noise, it is a difficult task to remove impulse noise from damaged natural images. This paper proposes a two-stage denoising method in order to effectively remove low-to-medium-density impulse noise. In the noise detection stage, the LCI impulse noise detector was studied and analyzed, and then the clean edge pixels were screened out from the candidate noise by introducing the edge pixel detector, so as to achieve the purpose of reducing the false detection rate of noise. In the second stage of noise removal, a filter based on LCI weight is designed. The filter takes all pixels in the neighborhood of the center pixel as the reference object, but the weight of each pixel in filtering is related to its own local similarity, which can reduce the interference of pixels suspected of noise to the filtered pixels. By testing on common test images, it can be found that the improved noise detector can accurately and quickly detect the impulse noise. In terms of image quality restoration performance, the filtering effect of the proposed filter is better than or comparable to other noteworthy methods in objective indicators. In addition, the denoising method has great advantages in terms of running time and model complexity.