Reviewerly/exHarmony huggingface dataset:
Resolving 100 photons and quantum generation of unbiased random numbers

Macroscopic quantum phenomena, such as observed in superfluids and superconductors, have led to promising technological advancements and some of the most important tests of fundamental physics. At present, quantum detection of light is mostly relegated to the microscale, where avalanche photodiodes are very sensitive to distinguishing single-photon events from vacuum but cannot differentiate between larger photon-number events. Beyond this, the ability to perform measurements to resolve photon numbers is highly desirable for a variety of quantum information applications including computation, sensing, and cryptography. True photon-number resolving detectors do exist, but they are currently limited to the ability to resolve on the order of 10 photons, which is too small for certain proposals. In this work, we extend photon measurement into the mesoscopic regime by implementing a detection scheme based on multiplexing highly quantum-efficient transition-edge sensors to accurately resolve photon numbers between zero and 100. We then demonstrate the use of our system by implementing a quantum random number generator with no inherent bias. This method is based on sampling a coherent state in the photon-number basis and is robust against environmental noise, phase and amplitude fluctuations in the laser, loss and detector inefficiency as well as eavesdropping. Beyond true random number generation, our detection scheme serves as a means to implement quantum measurement and engineering techniques valuable for photonic quantum information processing.
Coordinated Motion Planning Through Randomized <i>k</i> -Opt

This article examines the approach taken by team gitastrophe in the CG:SHOP 2021 challenge. The challenge was to find a sequence of simultaneous moves of square robots between two given configurations that minimized either total distance travelled or makespan (total time). Our winning approach has two main components: an initialization phase that finds a good initial solution and a k -opt local search phase that seeks to optimize this solution. This led to a first-place finish in the distance category and a third-place finish in the makespan category.
Birkhoff-von Neumann Quantum Logic as an Assertion Language for Quantum Programs

A first-order logic with quantum variables is needed as an assertion language for specifying and reasoning about various properties (e.g. correctness) of quantum programs. Surprisingly, such a logic is missing in the literature, and the existing first-order Birkhoff-von Neumann quantum logic deals with only classical variables and quantifications over them. In this paper, we fill in this gap by introducing a first-order extension of Birkhoff-von Neumann quantum logic with universal and existential quantifiers over quantum variables. Examples are presented to show our logic is particularly suitable for specifying some important properties studied in quantum computation and quantum information. We further incorporate this logic into quantum Hoare logic as an assertion logic so that it can play a role similar to that of first-order logic for classical Hoare logic and BI-logic for separation logic. In particular, we show how it can be used to define and derive quantum generalisations of some adaptation rules that have been applied to significantly simplify verification of classical programs. It is expected that the assertion logic defined in this paper - first-order quantum logic with quantum variables - can be combined with various quantum program logics to serve as a solid logical foundation upon which verification tools can be built using proof assistants such as Coq and Isabelle/HOL.
Bounding optimal headings in the Dubins Touring Problem

The Dubins Touring Problem (DTP) stands to find the shortest curvature-constrained multi-goal path connecting a prescribed sequence of locations. The problem is to determine the optimal vehicle heading angle at each location and thus find the shortest sequence of Dubins paths. The heading angles can be determined by iterative refinement of possible heading intervals for which finer resolution yields a shorter path at the cost of increased computational requirements. In this paper, we introduce a novel method to bound the optimal heading angles by eliminating unpromising intervals that cannot contribute to the optimal solution. The method is employed in the branch-and-bound solution of the DTP, where it significantly reduces the search space in finding the optimal solution.
A graph-based sensor recommendation model in semantic sensor network

In the past few years, introducing ontology to describe the concepts and relationships between different entities in semantic sensor network enhances the interoperability between entities. Existing works mostly based on SPARQL retrieval ignore the user’s specific requirements of sensor attributes. Therefore, the recommendation results cannot satisfy the user’s needs. In this article, we propose a graph-based sensor recommendation model. The model mainly includes two parts: (1) Filtering nodes in data graph. In addition to using the traditional graph matching algorithm, we propose a threshold pruning algorithm to narrow the matching scope and improve the matching efficiency. (2) Recommending top- k sensors. We use the improved fast non-dominated sorting algorithm to obtain the local optimal solutions of sensor data set, and we apply the simple additive weight algorithm to characterize and sort local optional solutions. Finally, we recommend the top- k sensors to the user. By comparison, the graph-based sensor recommendation algorithm meets user’s needs more than other algorithms, and experiments show that our model outperforms several baselines in terms of both response time and precision.
Research on the Implementation method of Anthropomorphic Trajectory during Sit to Stand Transfer based on Linkage Mechanism

Abstract Position and attitude change during sit to stand transfer is the most important change in daily life. On the basis of fully studying the existing equipment, position and attitude during sit to stand transfer is analysed, and the mathematical model of this process is established, the motion trajectory of hip joint during sit to stand transfer is normalized, then the feature points are extracted from motion trajectory. Based on the feature points, and using the linkage mechanism, the dimension synthesis of linkage mechanism is completed by graphic method, the method of realizing anthropomorphic motion trajectory during sit to stand transfer is given systematically based on linkage mechanism. The simulation results show that the designed mechanism can realize the anthropomorphic motion trajectory accurately during sit to stand transfer, and it lays a good foundation for the subsequent design of sit to stand assistance equipment.
Probing fundamental aspects of quantum mechanics with quantum computers

IBM quantum computers are used to perform a recently-proposed experiment testing the necessity of complex numbers in the standard formulation of quantum mechanics. While the noisier devices are incapable of delivering definitive results, it is shown that certain devices possess sufficiently small error rates to yield convincing evidence that a faithful description of quantum phenomena must involve complex numbers. The results are consistent with previous experiments and robust against daily calibration of these devices. This work demonstrates the feasibility of using freely-available, noisy, intermediate-scale quantum devices to test foundational features of quantum mechanics.
Accelerated Convergence of Contracted Quantum Eigensolvers through a Quasi-Second-Order, Locally Parameterized Optimization

A contracted quantum eigensolver (CQE) finds a solution to the many-electron Schr\"odinger equation by solving its integration (or contraction) to the 2-electron space -- a contracted Schr\"odinger equation (CSE) -- on a quantum computer. When applied to the anti-Hermitian part of the CSE (ACSE), the CQE iterations optimize the wave function with respect to a general product ansatz of two-body exponential unitary transformations that can exactly solve the Schr\"odinger equation. In this work, we accelerate the convergence of the CQE and its wavefunction ansatz via tools from classical optimization theory. By treating the CQE algorithm as an optimization in a local parameter space, we can apply quasi-second-order optimization techniques, such as quasi-Newton approaches or non-linear conjugate gradient approaches. Practically these algorithms result in superlinear convergence of the wavefunction to a solution of the ACSE. Convergence acceleration is important because it can both minimize the accumulation of noise on near-term intermediate-scale quantum (NISQ) computers and achieve highly accurate solutions on future fault-tolerant quantum devices. We demonstrate the algorithm, as well as some heuristic implementations relevant for cost-reduction considerations, comparisons with other common methods such as variational quantum eigensolvers, and a fermionic-encoding-free form of the CQE.
An architecture for data integrity in untrustworthy social networks

Social media platforms have the power to massively influence public opinion, and as such, are under increased pressure to submit to state regulation. They operate under a centralised model, in which users should trust the service provider that the information being presented has not been altered. This paper presents an architecture for enabling independent verification of content integrity in social networks. Our solution assumes a scenario of an untrustworthy social network provider, utilising public key cryptography for signing user content, and distributed hash tables for storing detached signatures. We have developed a proof of concept system that has been used to demonstrate the feasibility of the proposed solution.
Case StudiesSports

This chapter provides an in-depth look at how to produce immersive and interactive sound for more than 60 different sports. These case studies include immersive sound design philosophy, microphone selection, placement and mixing options for immersive sound plus the multiple derivative mixes that are required.
A Survey on Sign Language Recognition with Efficient Hand Gesture Representation

Abstract: Image classification is one amongst classical issue of concern in image processing. There are various techniques for solving this issue. Sign languages are natural language that want to communicate with deaf and mute people. There's much different sign language within the world. But the most focused of system is on Sign language (SL) which is on the way of standardization there in the system will focused on hand gestures only. Hand gesture is extremely important a part of the body for exchange ideas, messages, and thoughts among deaf and dumb people. The proposed system will recognize the number 0 to 9 and alphabets from American language. It'll divide into three parts i.e., pre-processing, feature extraction, classification. It'll initially identify the gestures from American Sign language. Finally, the system processes that gesture to recognize number with the assistance of classification using CNN. Additionally, we'll play the speech of that identified alphabets. Keywords: Hybrid Approach, American Sign Language, Number Gesture Recognition. Feature Extraction.
Mist Removal Using Fast Algorithm Based on Linear Operator

In hazy or foggy weather conditions image quality gets degraded which affects the performance of outdoor computer vision system. In this project a fast algorithm is proposed based on linear transformation by assuming that a linear relationship exists in the minimum channel between the hazy image and the haze-free image for dehazing single image. Firstly, the principle of linear transformation is analyzed and then the method of estimating a medium transmission map is elaborated &amp; the weakening strategies are introduced to solve the problem of brightest areas of distortion. To accurately estimate the atmospheric light, an additional channel method is proposed based on quad-tree subdivision. In this method, average grays and gradients in the region are employed as assessment criteria. Finally, the haze-free image is obtained using the atmospheric scattering model.
KNOWLEDGE TYPE AND NEW PRODUCT LAUNCH SUCCESS: THE MODERATING EFFECT OF KNOWLEDGE MANAGEMENT SYSTEM

The process of new product launch success is crucial for the corporate success of a firm. The purpose of this research is to explore the critical role of knowledge management system in leveraging knowledge type to improve new product launch success within the context of leather gloves industry in Pakistan. Data were collected from 429 leather gloves firms in Sialkot Pakistan using quantitative survey questionnaire. The participants were 211 product managers of leather gloves firms in Sialkot Pakistan. This study adopts the partial Least Square Structural Equation Modeling (PLS-SEM) for the purpose of data analysis. As such, the results of the analysis revealed that knowledge management system, knowledge tacitness, and knowledge complexity, all have direct significant positive impact on new product launch success. Interestingly, knowledge management system was not found to moderate the relationship between knowledge type and new product launch success. This study is one of the few that investigated the moderating effect of knowledge management system on the relationship between knowledge type and new product launch success among product managers in the leather gloves industry. The results contribute extensive inputs beneficial for policymakers, the government of Pakistan, firm owners, product managers, as well as other stakeholders to formulate successful policies and practices.
EKF-based fusion algorithm for magnetic nail navigation technology

Limited by the difficulty of vehicle speed control when registering QR codes and the high maintenance cost of QR codes, the development of automated guided vehicle (AGV) navigation technology based on QR codes has encountered bottlenecks in the development of industrial logistics. The information fusion of the magnetic positioning method and the odometer can overcome the shortcomings of the AGV navigation technology based on the two-dimensional code. By laying magnetic nails on the ground, the magnetic positioning method provides the attitude of the closest magnetic nail relative to the automated guided vehicle. The experimental results show that the average path accuracy of the magnetic nail navigation based on the EKF algorithm proposed in this paper is 83&plusmn;15 mm, and the average magnetic positioning accuracy is 11.7&plusmn;0.59 mm.
A Survey on Automatic Essay Evaluation System using Machine Learning

Manually assessment of descriptive answers in exam and assessment of an Essay requires more time and effort. In this era of E-Learning the Automated System for essay assessment is need of the time. There are many researches has been performed for this domain. In this paper we have reviewed some of the work related to this. Most of research uses Semantic Similarity Score and Sentimental Analysis for this purpose. Mostly NLTK and POS (Part of the Speech) is used. Various traditional algorithm of Machine Learning like SVM, Naïve Bayes, Random Forest etc. are used for performance classification. They have used measurement parameters in terms of KAPPA Statistics (QWK). We have also summarized methods related to Essay Evaluations with pros and cons in this paper. Feature selection methods and NLP attributes are also discussed.
Sound Pedagogies

Sound Pedagogies C. Kubasta (bio) Click for larger view View full resolution [End Page 40] In junior high, Mrs. R was a strict grammarian who made us diagram sentences, and even then I thought I'd prefer Mr. D (but he had a reputation for throttling students in the hallway), so in high school I tried to avoid both Mr. M, whose attentions to girl-athletes seemed inappropriate, and Mrs. C, who was a prescriptivist who taught the college-prep classes (although when she was dying we all went caroling at her house, and her already-grieving husband gave each singer an orange), and gravitated toward Mr. X who I've thought of for years as a friend and mentor—until last winter when he sent me a Facebook message apologizing for not sleeping with me, worried I'd think myself "unloveable," and everything he taught me seemed ruined: poetry, discovery of my voice, and a love of Joni Mitchell, John Prine, and Leonard Cohen, although I should have known then, because the lyrics to "Chelsea Hotel #2" have no place in a sophomore curriculum. Within the Reed-Kellogg systema base line containsthe simple sentence and a vertical linethat extends through the base separatessubject from predicate. In teachinggrammar, a proper sentencemust have both, and the predicateis a verb and its object (at least implied). Where it becomes difficult—to parse or diagram—is whether the object is director indirect. Should the linebe straight or a backslash, signalingthe earlier subject? Other modifiershang below the base lineplaced according to whatthey alter. What seemssimple takes on layers,hangers-on, additional weight. They are everywhere: Mr. X — Dr. Why — just call me Zeee Cf: the choice of texts. Sunlight fights its way through the window's grime. Whatever you've done to survive is the least dirty thing in the room. [End Page 41] C. Kubasta C. Kubasta writes poetry, fiction, and hybrid forms. Her most recent book is the short story collection Abjectification (Apprentice House, 2020). She wants to thank the artist Mollie Oblinger for layout help with "Sound Pedagogies." Find her at ckubasta.com and follow her @CKubastathePoet on Instagram and Twitter. Copyright © 2022 Pleiades and Pleiades Press
Domestic Research Trend Analysis of Resource Circulation Using Topic Modeling Analysis

Since the Wastes Control Act of 1987, Korea has laid the groundwork for proper waste management. The Framework Act on Resource Circulation was enacted in 2016 to manage and use waste throughout the entire lifecycle efficiently. Furthermore, “resource circulation” has recently become mainstream in domestic policies, such as establishing a digital-based resource circulation industrial complex as a part of the Korean New Deal 2.0. This study collected domestic studies on resource circulation, which has recently emerged as a major environmental issue, and analyzed research trends using topic modeling analysis. Relevant articles were collected from the Korea Citation Index using the keywords “resource circulation” and “circular economy,” and topic modeling analysis was performed on 207 papers and 712 keywords. Seven topics were drawn from the analysis: (1) energy-climate change policy, (2) eco-friendly design and systems, (3) waste electronics and plastic management, (4) revitalization of circular economy and local community, (5) environmental laws related to resource circulation, (6) concrete using recycled resources, and (7) matter flow analysis and management systems. In sum, it was found that many resource circulation studies have been conducted to address energy and climate change issues. In addition, resource circulation studies are not limited to policies and laws. Various studies are carried out across disciplines, such as engineering research on the management and utilization of specific resources and analytical research using tools, such as life cycle analysis (LCA). The findings of this study contributed to organizing major issues in recent resource circulation-related research and guiding future resource circulation-related studies.
POSSIBILITY OF TEACHING LEVELS IN COURSES OF MATHEMATICS WITH USE OF INFORMATION TECHNOLOGIES

Currently, the main goal of general education is to be intellectually and physically developed, have a wide range of spiritual needs, have a scientific worldview, be ready to take an active part in the life of society, be able to act independently and evaluate events, adapt to changes in society. This is the formation of personality. The article developed exercises for creating equations and transmitting them to students using the LearningApps.org application. The course of mathematics shows the organization of online learning using information technology. The teacher creates an algorithm for the equations in the application, solves linear equations and shares exercises with students to restore them. The app assesses student performance and allows students to use the assessment results and provide feedback.
Framework for Video Summarization Using CNN-LSTM Approach in IoT Surveillance Networks

The surveillance industry is rapidly changing and growing. Processing of surveillance videos to maintain useful information is a challenging and time-consuming task. This work proposes a framework for the effective summarization of surveillance videos by combining the advantages of deep learning to the internet of things (IoT). A convolutional neural network (CNN) is used for the selection of significant video features from the selected video frames and a long short term memory network (LSTM) is used for the generation of video summary in the compact from preserving the salient information. Summarization of the videos can be sent to the receiver over a network providing benefits of reduced bandwidth utilization and transmission cost. The proposed framework has the benefits of autonomous operations without the need for human intervention. Since the time consumed to analyze the summarized text is comparatively less than for the video, quick decision making and faster action in case of emergency is possible increasing the efficiency at crucial situations.
Literature Analysis Related to Online Physical Education Classes for Adolescents Due to COVID-19

The purpose of this study is to analyze the research contents related to online physical education classes conducted in Korea due to COVID-19, and to explore the future-oriented development direction, particulary, physical education classes in preparation for the another potential pandemic. In order to achieve the purpose of this study, 22 studies related to online physical education classes were collected from 2020 to the present after the outbreak of COVID-19. Categorization was conducted centering on the subject of the collected literature. Through categorization, the classification of previous studies by subject was organized into three categories: class status, class management difficulties, and class type or class effect. The research results are as follows.<BR> First, it was possible to grasp the starting process of online physical education classes. As for the teaching method, interactive real-time classes, content utilization-oriented classes, and task performance-oriented classes were used to construct online classes fit for physical education classes. Second, in the preparation for online physical education classes, instructors struggled to adapt their existing curriculum to an online format on short notice, but overcame it by collaborating with colleagues and communicating with students to better improve the quality of classes. Third, due to early struggles of suddenly adjusting to the pandemic, instructors have gradually made efforts to increase the efficiency of the operation of online classes and develop physical education classes fit for circumstances under a pandemic.