Reviewerly/exHarmony huggingface dataset:
Implementation of Obstacle Avoidance Method for Quadcopters Using Path Selection Imitating Tentacles and Backstepping MPC

Path planning is important for fully autonomous flight by a UAV. Since facility inspections using UAVs require flight in narrow spaces, we need to plan the path that can move in all directions to escape from dead end. Path planning in all directions inevitably increases the computational cost. Since UAVs cannot change their speed rapidly, it is desirable to be able to consider the effect of speed when selecting a path. We adopt a method of pre-computing a group of paths using the Lemason’s equation, because the method can take both direction of the UAV and its speed into consideration. We use BS-MPC for path following, which has both computational efficiency and high control performance. We report the investigation that these can be used to fly at what kind of environment.
Fine-grained Access Control in Distributed Cloud Environment using Trust Valuation Model

Cloud computing has been in existence as an adaptable technology that gets integrated with IoT, Big-Data, and WSN to provide reliable, scalable and mesh-free services.However, because of its openness in nature, the privacy of the cloud is an important parameter for today's research.The most important privacy factor in cloud is access control and user trust.Many articles related to access control and trust management were presented, but most of them include highly complex algorithms that result in network overhead.This proposed security framework is for a better and more effective system wherein multiple distributed centers are created with trust-based computing for authentication and validation of requests from users and their resources.The idea of trust here is for efficient decision-making and establishing reliable relationships among users and resources using least computations.Each user has different permissions for each file present in the cloud server.The simulated results shows improvement in the rate of successful transactions, time cost and network overhead.
Pengaruh Fasilitas, Pelayanan dan Koleksi Buku terhadap Minat Baca

The purpose of this study was to determine the effect of library facilities, library services, and book collections on the reading interest of class XI students in the library of SMK Negeri 1 Wonosobo either simultaneously or partially. The population in this study were all students of class XI at SMK Negeri 1 Wonosobo totaling 444 students and a sample of 210 students was taken using proportional random sampling technique. Data were collected by questionnaire. Methods of data analysis using descriptive percentage, multiple regression analysis, hypothesis testing F test and t test. The results showed: 1) there was a simultaneous positive and significant effect between library facilities, library services, and book collections on the reading interest of class XI students in the library of SMK Negeri 1 Wonosobo by 65.2%; 2) There is a positive and partially significant effect between library facilities on reading interest in class XI students in the library of SMK Negeri 1 Wonosobo by 8.41%; 3) There is a positive and partially significant effect between library services on reading interest in class XI students in the library of SMK Negeri 1 Wonosobo by 14.5%; 4) There is a positive and partially significant effect between book collections on reading interest of class XI students in the library of SMK Negeri 1 Wonosobo by 19.36%.
Knowledge Analysis of Charged Particle Motion in Uniform Electromagnetic Field Based on Maxwell Equation

Abstract We study the motion states of charged particles in a homogeneous electromagnetic field based on the Maxwell equations. The authors propose the charged particle properties analysis based on the Maxwell equation and electromagnetic field, first explain the Maxwell equation and electromagnetic field properties analysis, and then analyze the charged particles in the composite field (electric and magnetic field coexistence). List the important knowledge points about the motion of charged particles in an electric field, and determine the center of the circle where the charged particles move in a circular motion, simulate the motion of charged particles in a uniform orthogonal electromagnetic field, if at, the trajectory of the charged particle is a short-amplitude cycloid, if, the trajectory of the charged particle is a long cycloid, if. The realization of simulation is mainly based on theory to obtain phenomena, although it has extensive practical significance for confirmatory experiments, when inspiring and guiding students to carry out inquiry learning, physics teachers should still organically combine simulation experiments with traditional experimental teaching, teacher explanations, and student experiments in teaching design and teaching implementation, in order to cultivate students' independent inquiry ability and experimental innovation ability.
Lexically Constrained Knowledge Distillation for Neural Machine Translation

Knowledge distillation is a representative approach in neural machine translation (NMT) for compressing a large model into a lightweight one. This approach first trains a strong teacher model, and then forces a more compact student model to imitate the teacher. Although the key to successful knowledge distillation is constructing a stronger teacher model, the teacher model using state-of-the-art NMT may remain inadequate owing to translation errors. Accordingly, using an inadequate teacher model severely degrades the student model due to error propagation, especially regarding words important to sentence meaning. To mitigate the degradation problem, we propose a knowledge distillation method using a lexical constraint as privileged information for NMT. The proposed method trains a teacher model with a lexical constraint, a list of words automatically extracted from a target sentence in the training data. We configure the lexical constraint according to the importance of words and the fallibility of NMT. Models trained with our proposed method result in improved translation compared with those trained with a baseline method for English↔German and English↔Japanese translation tasks under the condition without ensemble decoding and beam-search decoding.
Research on the evolution of public opinion and topic recognition based on multi-source data mining

In the era of rapid network development, the internet has become the main medium for the spread of online public opinion. Users can express their views on hot issues through text, pictures, and videos anytime and anywhere, analyse the evolving trend of netizens' emotions in emergencies to discover the law of public opinion evolution and potential risks, and provide decision support for public opinion guidance and control. In this paper, Python is used to pre-process the collected text data, and proposes a method based on spectral clustering algorithm, using the Latent Dirichlet Allocation to extract text topics. From the perspective of multi-language and multi-source data, it mines high-value public opinion topics in online public opinion, and uses data visualisation methods to study the emotional tendencies of netizens. The research results can clearly reveal the content of discussion and the emotional attitude of netizens in the period of public opinion transmission.
Readability Indexes of E-commerce Reviews with Laplacian Score Algorithm

Online customer reviews are valuable user-generated content to help in purchasing decision process. There are many customer reviews available in today's online marketplaces, allowing customers to evaluate them for a better knowledge of the product or service they will be purchasing. In addition to the recommendation system, expert opinions, and product descriptions, online customer reviews play a significant supporting role. However, due to the abundance of reviews, it is unclear whether these reviews are of high quality and useful to other customers. New online customer reviews may be of high quality, but because they are not widely known, other customers may overlook them. As a result, it is necessary to assess the quality of customer reviews that able the reviews to help a customer in their decision-making process. Existing studies tend to ignore quality indicators such as length and readability that provide a way to evaluate the important characteristic by employing a simple statistical analysis method. Hence, we propose the implementation of the Laplacian Score Algorithm to measure the readability index importance in the selection of the top-5 readability measure, to be used with other quality features in measuring the review quality. To validate the proposed framework, we use six review datasets from Amazon. The result shows that the basic structural information of a review text such as word, character, sentence and syllable counts give more influence to the quality of the reviews. Whereas advanced structural information such as difficult words and polysyllable count has less significance to the determination of the quality of a review text when it involves only the readability index measurement.
Analysis on Digital Watermarking Technology and Its Applications

Digital watermarking technology is a technology that embeds specific information into digital products to protect the copyright, integrity, and anti-copying, and to track the digital products. Digital watermarks play a very important role in ensuring the safety of digital works. This paper mainly analyzes several main algorithms for digital image watermarking and four other algorithms, including digital watermarking technology based on machine learning methods, digital watermarking technology based on image segmentation technology, digital watermarking technology based on adversarial attacks, and digital watermarking technology based on wavelet transformation. This paper also discusses three existing applications of digital watermarks, covering the application of digital watermark in vector maps, the application of digital watermark in digital file protection, and the application of digital watermarking in multimedia copyright protection. Moreover, this paper discusses image digital watermarking algorithm through mathematical formulas. This paper provides a comprehensive analysis on digital watermarking technology and its applications to the related researchers.
Capitalizing Entrepreneurship: The Rise of Growth Equity

Growth equity (GE) funds have emerged as the third major private equity asset class for investors, alongside venture capital (VC) and buyout (B/O) funds, and as an important new source of external equity capital for private companies and entrepreneurs wishing to fund growth without surrendering control. GE funds have the same organizational and operational structure as VC and B/O funds, and their private-firm investments generally fall on the corporate finance spectrum between late-stage VC and buyout financing. Virtually unknown before 2000, GE funds now raise over $100 billion annually, have assets under management of more than $1.2 trillion, and dry powder totaling almost $400 billion. Their emergence as a key corporate finance tool has allowed entrepreneurial firms to remain private much longer than in the past and, in many ways, GE financing has replaced going public as a source of growth capital. We define growth equity funding and trace the development of GE fund-raising and investment as described in the professional and academic literatures. We also analyze a large sample of VC, GE, and B/O funds and deals drawn from the Preqin database and show that GE shares characteristics with both VC and B/O funding but should be considered a distinct new asset class and corporate finance vehicle. We conclude by briefly describing a suggested GE research agenda.
Lower Bounds for the Number of Decryption Updates in Registration-Based Encryption

Registration-based encryption (Garg, Hajiabadi, Mahmoody, Rahimi, TCC’18) aims to offer what identity-based encryption offers without the key-escrow problem, which refers to the ability of the private-key generator to obtain parties’ decryption keys at wish. In RBE, parties generate their own secret and public keys and register their public keys to the key curator (KC) who updates a compact public parameter after each registration. The updated public parameter can then be used to securely encrypt messages to registered identities. A major drawback of RBE, compared with IBE, is that in order to decrypt, parties might need to periodically request so-called decryption updates from the KC. Current RBE schemes require $$\varOmega (\log n)$$ number of updates after n registrations, while the public parameter is of length $${\text {poly}}(\log n)$$ . Clearly, it would be highly desirable to have RBEs with only, say, a constant number of updates. This leads to the following natural question: are so many (logarithmic) updates necessary for RBE schemes, or can we decrease the frequency of updates significantly? In this paper, we prove an almost tight lower bound for the number of updates in RBE schemes, as long as the times that parties receive updates only depend on the registration time of the parties, which is a natural property that holds for all known RBE constructions. More generally, we prove a trade-off between the number of updates in RBEs and the length of the public parameter for any scheme with fixed update times. Indeed, we prove that for any such RBE scheme, if there are $$n \ge \left( {\begin{array}{c}k+d\\ d+1\end{array}}\right) $$ identities that receive at most d updates, the public parameter needs to be of length $$\varOmega (k)$$ . As a corollary, we find that RBE systems with fixed update times and public parameters of length $${\text {poly}}(\log n)$$ , require $$\varOmega (\log n/{\text {loglog}}n)$$ decryption updates, which is optimal up to a $$O({\text {loglog}}n)$$ factor.
Measuring Decubitus Wounds Using Augmented Reality Glasses - A User Interface Study

We present a study on the usability of three different user interfaces for an augmented reality glasses system. The application is intended for use in hospitals by nursing professionals. During wound care, images can be taken with the Microsoft HoloLens 2 and measured directly. The photos must always be taken at the same distance from the wound to follow the healing process. We present and juxtapose three aim assistants to take a picture of the wound and acquire wound data. To gain a first impression about the goodness of usability and the preferred targeting assistant, we conducted a small usability study. Participants were asked to perform wound measuring tasks using our application’s varying user interfaces. In this study, we identified strengths and weaknesses for each user interface based on the conducted research and identified approaches for further improvements.
Turbulence, Periodic Orbits and Koopman Analysis

Periodic orbits are known to be very important in describing chaotic attractors and the hope has been that they may also help our understanding of fluid turbulence. I'll discuss work trying to find periodic orbits buried in turbulent flows which, most recently, has utilised Dynamic Mode Decomposition/Koopman analysis.
The model of a parallel life cycle of configurable information systems based on a methodological framework

The paradigm of developing information systems that has developed today is characterized by an insoluble contradiction between the problem of compliance of the developed system with the user›s expectations and the means of solving it. The latter are aimed at making it easier for the developer to make changes to the system or to speed up the prototyping and development process and do not solve the problems of extracting and delivering information about what the user expects from the system. To solve this problem, it is necessary to reconsider the fundamental principles of the organization of the development process. To do this, the article proposes a methodological framework for designing configurable information systems, consisting of the structure of a configurable information system, which allows describing its single model consistent at different levels of detail, as well as the process of creation inextricably linked with it, which is filling and, if necessary, detailing the structure with subsequent filling with content reflecting the specifics of technologies and implementation features.
Tuning ForestDisc Hyperparameters: A Sensitivity Analysis

This paper presents and analyzes ForestDisc, a discretization method based on tree ensemble and moment matching optimization. ForestDisc is a supervised and multivariate discretizer that transforms continuous attributes into categorical ones following two steps. At first, ForestDisc extracts for each continuous attribute the ensemble of split points learned while constructing a Random Forest model. It then constructs a reduced set of split points based on moment matching optimization. Previous works showed that ForestDisc enables an excellent performance compared to 22 popular discretizers. This work analyzes ForestDisc performance sensitivity to its tunning parameters and provides some guidelines for users when using the ForestDisc package.
Can a Machine Reading Comprehension Model Improve Ad-hoc Document Retrieval?

We propose a method to solve ad-hoc document retrieval tasks using a reading comprehension model. To solve the ad-hoc retrieval task, the proposed method generates a question for the given query, and a reading comprehension model is employed to determine whether the target document contains a corresponding answer to the generated question, thereby estimating the relevance of the document. Experimental results show that a simple application did not improve the performance in ad-hoc retrieval tasks. Through extensive analysis of the experimental results, however, we found that the proposed method was effective for improving the performance when it was applied to queries containing proper nouns.
بوابة التعلم الإلكتروني لطلاب أقسام المكتبات والمعلومات والأرشيف : دراسة حالة طلاب قسم الوثائق والمكتبات والمعلومات جامعة دمياط = E-Learning Portal for Students of the Library, Information and Archives Departments : Case Study for Students of the Library and Information Department, Damietta University

التعلم الإلكتروني | طلاب أقسام المكتبات والمعلومات | بوابات التعلم الذاتي | التعليم عن بعد | E-Learning | Students of Libraries and Information Departments | Selflearning Portals | Distance Education | Online Education
GENERIC COMPLEXITY OF ALGORITHMIC PROBLEMS

Generic approach is one of the approaches to the study of algorithmic problems for almost all inputs, born at the intersection of computational algebra and computer science. Within the framework of this approach, algorithms are studied that solve a problem for almost all inputs, and for the remaining rare inputs give an undefined answer. This review reflects two areas of research of generic complexity of algorithmic problems in algebra, mathematical logic, number theory, and theoretical computer science. The first direction is devoted to the construction of generic algorithms for problems that are unsolvable and hard in the classical sense. In the second direction, algorithmic problems are sought that remain unsolvable or hard even in the generic sense. Such problems are important in cryptography.
Study of the dynamics of the maturity level of the educational organization of secondary vocational education

The article is devoted to assessing the level of maturity of an institution of secondary vocational education. It considers both a methodology for assessing maturity for one period (year) and tracking the history of changes in maturity levels. The object of the research was the Krasnoyarsk College of Radio Electronics and Information Technologies. Self-assessment is based on surveys of college teachers and staff, including former ones, for different periods. The structure of the study is based on the Voyager Plant Optimization method; the questionnaires were developed following the McKinsey model and adapted to the system of secondary vocational education in Russia. The obtained results reflect the continued tendency towards the degradation of the educational organization in question, unfortunately.
AuCM: Course Map Data Analytics for Australian IT Programs in Higher Education

Concept maps have emerged as an essential tool for illustrating the mutual relationships between knowledge in the domain. It provides guidance and suggestions in many educational applications such as optimal study order generating, curriculum design and course evaluation. However, there are no consistent datasets for concept map research. In this work, we aim to build a comprehensive dataset for learning concept maps. Specifically, we collect 1292 undergraduate courses in Information Technology (IT) and Computer Science (CS) from 14 Australian universities including course ID, category and prerequisite requirements. Besides, we analyze the semantic properties based on the concepts retrieved from the course description and visualize them to illustrate how our dataset could be used. To the best of our knowledge, this is the first dataset containing course information from Australian universities.
Contributors

Other| November 01 2022 Contributors 19th-Century Music (2022) 46 (2): 194. https://doi.org/10.1525/ncm.2022.46.2.194 Views Icon Views Article contents Figures & tables Video Audio Supplementary Data Peer Review Share Icon Share Facebook Twitter LinkedIn MailTo Tools Icon Tools Get Permissions Cite Icon Cite Search Site Citation Contributors. 19th-Century Music 1 November 2022; 46 (2): 194. doi: https://doi.org/10.1525/ncm.2022.46.2.194 Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All Content19th-Century Music Search This content is only available via PDF. © 2022 by The Regents of the University of California. All rights reserved. Please direct all requests for permission to photocopy or reproduce article content through the University of California Press's Reprints and Permissions web page, https://www.ucpress.edu/journals/reprints-permissions.2022The Regents of the University of California Article PDF first page preview Close Modal You do not currently have access to this content.
Fringe pattern defect identification using Kalman filter and machine learning

The article introduces a Kalman filter and naive Bayes classifier based machine learning model for defect identification in the noisy fringe pattern. The simulation results corroborate the performance of the proposed method.
Bayesian Network Representation of Joint Normal Distributions - Cascading Regressions Model

This article is the first of a series discussing the Bayesian Network representation of multivariate normal distributions. A joint normal distribution being fully specified by its mean vector and its covariance matrix is not simple to interact with as its Bayesian network equivalent. Representing a joint normal distribution as a Bayesian network enables visualizing and interacting with the distribution through the lens of probabilistic graphical models with TKRISK®. We demonstrate in this article a simple yet powerful approach using a cascading regressions approach.