Reviewerly/exHarmony huggingface dataset:
Trajectory planning of unmanned aerial vehicle based on the improved biogeography-based optimization algorithm

This paper is concerned with trajectory planning for unmanned aerial vehicle in a three-dimensional complex workspace. Biogeography-based optimization algorithm is widely used in solving practical problems because of its fewer parameters, fast convergence rate, and good global optimization ability. In this paper, some improvements, modifying migration and mutation operations are made on the biogeography-based optimization algorithm to make it suitable for solving the trajectory planning problem. The optimal trajectory obtained by the improved algorithm can be used to generate the reference trajectory. Then, a control scheme of unmanned aerial vehicle based on the Lyapunov theory and radial basis function neural network is formed to track the reference trajectory. The improved trajectory algorithm generates the shortest trajectory and the time consumption is the lowest. Finally, the designed control scheme makes the unmanned aerial vehicle track the different trajectories quite well, the effectiveness of it can be illustrated by algorithm accuracy and electricity consumption.
The Bloch vectors formalism for a finite-dimensional quantum system

Abstract In the present article, we consistently develop the main issues of the Bloch vectors formalism for an arbitrary finite-dimensional quantum system. In the frame of this formalism, qudit states and their evolution in time, qudit observables and their expectations, entanglement and nonlocality, etc are expressed in terms of the Bloch vectors—the vectors in the Euclidean space <?CDATA ${\mathbb{R}}^{{d}^{2}-1}$?> <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" overflow="scroll"> <mml:msup> <mml:mrow> <mml:mi mathvariant="double-struck">R</mml:mi> </mml:mrow> <mml:mrow> <mml:msup> <mml:mrow> <mml:mi>d</mml:mi> </mml:mrow> <mml:mrow> <mml:mn>2</mml:mn> </mml:mrow> </mml:msup> <mml:mo>−</mml:mo> <mml:mn>1</mml:mn> </mml:mrow> </mml:msup> </mml:math> , arising under decompositions of observables and states in different operator bases. Within this formalism, we specify for all d ⩾ 2 the set of Bloch vectors of traceless qudit observables and describe its properties; also, find for the sets of the Bloch vectors of qudit states, pure and mixed, the new compact expressions in terms of the operator norms that explicitly reveal the general properties of these sets and have the unified form for all d ⩾ 2. For the sets of the Bloch vectors of qudit states under the generalized Gell‐Mann representation, these general properties cannot be analytically extracted from the known equivalent specifications of these sets via the system of algebraic equations. We derive the general equations describing the time evolution of the Bloch vector of a qudit state if a qudit system is isolated and if it is open and find for both cases the main properties of the Bloch vector evolution in time. For a pure bipartite state of a dimension d 1 × d 2 , we quantify its entanglement via the characteristics of the Bloch vectors for its reduced states. The introduced general formalism is important both for the theoretical analysis of quantum system properties and for quantum applications, in particular, for optimal quantum control, since, for systems where states are described by vectors in the Euclidean space, the methods of optimal control, analytical and numerical, are well developed.
Social media and democracy : the state of the field, prospects for reform

Over the last five years, widespread concern about the effects of social media on democracy has led to an explosion in research from different disciplines and corners of academia. This book is the first of its kind to take stock of this emerging multi-disciplinary field by synthesizing what we know, identifying what we do not know and obstacles to future research, and charting a course for the future inquiry. Chapters by leading scholars cover major topics – from disinformation to hate speech to political advertising – and situate recent developments in the context of key policy questions. In addition, the book canvasses existing reform proposals in order to address widely perceived threats that social media poses to democracy. This title is also available as Open Access on Cambridge Core.
On Implicit Attribute Localization for Generalized Zero-Shot Learning

Zero-shot learning (ZSL) aims to discriminate images from unseen classes by exploiting relations to seen classes via their attribute-based descriptions. Since attributes are often related to specific parts of objects, many recent works focus on discovering discriminative regions. However, these methods usually require additional complex part detection modules or attention mechanisms. In this paper, 1) we show that common ZSL backbones (without explicit attention nor part detection) can implicitly localize attributes, yet this property is not exploited. 2) Exploiting it, we then propose SELAR, a simple method that further encourages attribute localization, surprisingly achieving very competitive generalized ZSL (GZSL) performance when compared with more complex state-of-the-art methods. Our findings provide useful insight for designing future GZSL methods, and SELAR provides an easy to implement yet strong baseline.
Different environmental conditions in genetic algorithm

We propose an extended genetic algorithm (GA) with different local environmental conditions. Genetic entities, or configurations, are put on nodes in a ring structure, and location-dependent environmental conditions are applied for each entity. Our GA is motivated by the geographic aspect of natural evolution: Geographic isolation reduces the diversity in a local group, but at the same time, can enhance intergroup diversity. Mating the genetic entities across different environments can make it possible to search for a broad area of the fitness landscape. We validate our extended GA for finding the ground state of the three-dimensional spin-glass system and find that the use of different environmental conditions makes it possible to find the lower-energy spin configurations at relatively shorter computation time. Our extension of GA belongs to a meta-optimization method and thus can be applied for a broad research area in which finding the optimal state in a shorter computation time is the key problem.
Correctness of Sequential Monte Carlo Inference for Probabilistic Programming Languages

Probabilistic programming is an approach to reasoning under uncertainty by encoding inference problems as programs. In order to solve these inference problems, probabilistic programming languages (PPLs) employ different inference algorithms, such as sequential Monte Carlo (SMC), Markov chain Monte Carlo (MCMC), or variational methods. Existing research on such algorithms mainly concerns their implementation and efficiency, rather than the correctness of the algorithms themselves when applied in the context of expressive PPLs. To remedy this, we give a correctness proof for SMC methods in the context of an expressive PPL calculus, representative of popular PPLs such as WebPPL, Anglican, and Birch. Previous work have studied correctness of MCMC using an operational semantics, and correctness of SMC and MCMC in a denotational setting without term recursion. However, for SMC inference -- one of the most commonly used algorithms in PPLs as of today -- no formal correctness proof exists in an operational setting. In particular, an open question is if the resample locations in a probabilistic program affects the correctness of SMC. We solve this fundamental problem, and make four novel contributions: (i) we extend an untyped PPL lambda calculus and operational semantics to include explicit resample terms, expressing synchronization points in SMC inference; (ii) we prove, for the first time, that subject to mild restrictions, any placement of the explicit resample terms is valid for a generic form of SMC inference; (iii) as a result of (ii), our calculus benefits from classic results from the SMC literature: a law of large numbers and an unbiased estimate of the model evidence; and (iv) we formalize the bootstrap particle filter for the calculus and discuss how our results can be further extended to other SMC algorithms.
Underwater salient object detection based on red channel correction

Under the environment of ocean development, underwater object detection technology has been widely used. Underwater salient object detection technology plays an important role in this process. The characteristics of light transmission under water determine the attenuation of color information in underwater images. In this paper, a method of underwater salient object detection based on red channel correction is designed based on the characteristics of the fastest attenuation of red channel in underwater images. First, the red channel component of the underwater image is weighted and corrected, and then the corrected three RGB components are used to construct the quaternion. The salient target detection calculation is carried out by PQFT method, and finally the salient object image is obtained. Experimental results show that, compared with the traditional SR and PQFT methods, the proposed method has higher accuracy and lower error rate in detecting the boundary of visually significant underwater object.
SpartanGold: A Blockchain for Education, Experimentation, and Rapid Prototyping

Since the introduction of Bitcoin and the blockchain, the cryptocurrency space has seen rapid innovation in both academic research and in cutting edge designs from industry. Student interest has likewise increased rapidly. All of these areas would benefit from the ability to rapidly prototype ideas without becoming bogged down in complex code bases: academic researchers need a way to highlight key concepts of their designs; industry engineers could vet their early designs and identify potential challenges; and students would be able to play with key concepts of the blockchain in a simple, easy to understand codebase. This paper introduces SpartanGold, a blockchain implementation written in JavaScript patterned after Bitcoin. Several features of Bitcoin’s design are simplified or eliminated, though those features may be added in easily. SpartanGold supports a single-threaded mode where miners communicate via JavaScript events, and a multi-process mode where miners and clients send messages over TCP/IP. While the former mode simplifies testing and can provide cleaner demonstrations, the latter mode provides a more realistic experience. We show the utility of SpartanGold by implementing different designs of mining pools and by showing how Bitcoin’s UTXO model could be added to SpartanGold.
covid19.analytics: An R Package to Obtain, Analyze and Visualize Data from the 2019 Coronavirus Disease Pandemic

With the emergence of a new pandemic worldwide, novel strategies attempting to understand its evolution and dynamics, empowered by computational techniques such as data analysis and computational modelling, have also emerged.Several initiatives under the umbrella of open science are contributing to tackle this unprecedented situation.In particular, the R Language (Ihaka & Gentleman, 1996; R Core Team, 2016) could be an excellent tool and ecosystem for approaches focusing on open science and reproducible research.Hence it is not surprising that with the onset of the pandemic, a large number of R packages and resources were made available for researchers working in the pandemic.In this paper, we present the covid19.analyticsR package, which allows users to access and analyze worldwide data from publicly available resources.The covid19.analyticsR package allows users to obtain live 1 worldwide data of reported cases from the novel Coronavirus Disease (COVID-19), as well as related datasets, such as genomics data, testing and vaccinations records, and historical pandemics records.It does this by accessing and retrieving data publicly available and published by several sources, such as: * corresponding author 1 The data usually is accessible from the repositories with a 24 hours delay.
An empirical characterization of event sourced systems and their schema evolution — Lessons from industry

Event sourced systems are increasing in popularity because they are reliable, flexible, and scalable. In this article, we point a microscope at a software architecture pattern that is rapidly gaining popularity in industry, but has not received as much attention from the scientific community. We do so through constructivist grounded theory, which proves a suitable qualitative method for extracting architectural knowledge from practitioners. Based on the discussion of 19 event sourced systems we explore the rationale for and the context of the event sourcing pattern. A description of the pattern itself and its relation to other patterns as discussed with practitioners is given. The description itself is grounded in the experience of 25 engineers, making it a reliable source for both new practitioners and scientists. We identify five challenges that practitioners experience: event system evolution, the steep learning curve, lack of available technology, rebuilding projections, and data privacy. For the first challenge of event system evolution, we uncover five tactics and solutions that support practitioners in their design choices when developing evolving event sourced systems: versioned events, weak schema, upcasting, in-place transformation, and copy-and-transform.
Entanglement-free witnessing of quantum incompatibility in a high-dimensional system

Quantum incompatibility, as an important quantum resource, is believed to play a key role in quantum information processing tasks. In order to detect this property, an entanglement-free incompatibility witness is proposed via constructing a combined quantum state discrimination task with prior-measurement and post-measurement information strategies. Here we experimentally implement the witness of the incompatibility of mutually unbiased measurements under different noise levels in a qutrit system. Moreover, we estimate the robustness of incompatibility using collected data. Our work paves the path for understanding quantum incompatibility and exploring the features of the quantum resource.Received 13 June 2020Revised 12 February 2021Accepted 13 February 2021DOI:https://doi.org/10.1103/PhysRevResearch.3.023017Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article's title, journal citation, and DOI.Published by the American Physical SocietyPhysics Subject Headings (PhySH)Research AreasQuantum correlations in quantum informationQuantum information processingQuantum measurementsQuantum opticsQuantum protocolsResource theoriesGeneral PhysicsQuantum InformationAtomic, Molecular & Optical
An Intelligent Framework for Online Product Recommendation Using Collaborative Filtering

Recommendation systems have become a vital area of research in recent times. These recommendation systems are very much needed for e-commerce applications to identify the products liked by a customer which helps the companies to promote product sales and improve their product quality. It also helps the users to arrive at the purchasing decision without reading the online reviews about the product. The key idea behind the proposed work is to analyze the user preference for the products from the online data by employing the collaborative filtering-based recommendation framework. The concept of collaborative filtering is best suited for recommendation systems involving a large set of product users. It generates a user-item matrix and finds the list of products liked by the individual users. It gives prediction regarding the product that a user could buy in the future and also recommends the products which are liked by the customers who have similar interests. It gives a comparative analysis in terms of performance metrics and accuracy of different collaborative filtering techniques.
Excited State Search Using Quantum Annealing

Quantum annealing (QA) is one of the ways of finding ground states of problem Hamiltonians. We initially apply transverse fields corresponding to a driver Hamiltonian and adiabatically change the Hamiltonian to the problem Hamiltonian to obtain the target ground state. However, for some purposes such as quantum chemistry, both ground and excited states are needed to understand the properties of the molecules. Here, we describe a scheme based on QA to search arbitrary excited states of problem Hamiltonians. By splitting the degeneracy of the driver Hamiltonian with inhomogeneous transverse fields, we can prepare a nondegenerate excited state as the initial state, and an adiabatic change of the Hamiltonian provides a target excited state as long as the adiabatic condition holds. We also show that our scheme enables us to find a desired excited state by designing the driver Hamiltonian suitably even in the presence of weak decoherence. These results are important for quantum chemistry and post-quantum cryptography.
Digital Forensic Analysis Of Michat Application On Android As Digital Proof In Handling Online Prostitution Cases

Smartphone technology and the Internet are very popular lately, especially with various features, one of which is instant messaging. But behind it all, instant messaging like MiChat is very vulnerable to becoming a crime, one of which is Online Prostitution. To follow up on Online Prostitution activities, it is necessary to carry out mobile forensics to find evidence which is then given to be given to the authorities. This study uses the MiChat application as an online prostitution media, and uses the National Institute of Justice (NIJ) method which has five basic stages is, preparation, collection, examination, analysis, and reporting. This research uses MOBILedit Forensic Express, and SysTools SQLite Viewer.
Utilization of distance education during COVID_19 crisis

The recent corona crisis situation caused a sudden turnover in the delivery of lessons at all levels of education in the Czech Republic.The well-established face-to-face instruction was unexpectedly replaced by the distance format, generally linked to higher education courses, which are well planned, specially designed, and supported by smart technologies.The main objective of this study is to illustrate this situation from secondary and tertiary school teachers´ perspectives.It focuses on the tools of distance education that teachers were able to use after the lockdown from their homes providing only limited technical resources.The study was conducted at Secondary and Tertiary School for medical Staff in Olomouc involving 64 teachers of both general and technical (medical) subjects, who were asked to answer questions regarding technologies and tools used within the distance education.Data obtained from this study revealed that most respondents used predominantly email communication and free online sources.
A Dynamic Memory Allocation Optimization Mechanism Based on Spark

Spark is a distributed data processing framework based on memory. Memory allocation is a focus question of Spark research. A good memory allocation scheme can effectively improve the efficiency of task execution and memory re... | Find, read and cite all the research you need on Tech Science Press
Mapping hydrothermal alteration zones using ASTER images in the Arabian–Nubian Shield: A case study of the northwestern Allaqi District, South Eastern Desert, Egypt

In order to map and differentiate ore-bearing hydrothermal alteration zones at the northwestern part of Allaqi-Heiani, we use a combined method of the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) image processing, field relationship, mineralogical features, and rock chemical compositions. Hydrothermal alteration zones are identified on the basis of Advanced Spaceborne Thermal Emission and Reflection Radiometer data. Propylitic, phyllic, argillic, and silicification zones are recorded in different types of igneous and metamorphic rocks typically with chromite, goethite, ilmenite, galena and gold. Crosta and CEN techniques using ASTER are successfully applied to highlight the hydrothermal alteration zones and the structural elements represented by lithologic contacts and faults/fracture zones. Combining data of lineaments, alteration zones and ore mineralogy studied after obtaining a consequence of each map allowed predicting and mapping areas of probable high mineral resources. According to petrographic and remote sensing studies, types of alteration include sericitization, chloritization, epidotization, kaolinitization, carbonatization and silicification. The results of remote sensing in the study area are confirmed by X-ray diffraction (XRD), petrography, and SEM. In the studied district, there are ophiolitic ultramafic rocks, island-arc assemblage of metasediments, volcaniclastics and metagabbro-diorite, syntectonic granite and dykes. Accordingly, to the present study can identify the most potential areas of mineralization taking us into consideration the overlapping of high lineament density areas with abundant alterations.
Design, Development and Characterization of Graphene Sand Nano-Composite for Water Filtration

&#x0D; Water purification and filtration is a global issue and many researchers are engaged to resolve this problem by adopting the scientific approach, graphene sand composite was prepared through bio- synthesized technique. River sand was used in this context to remove the impurities already present in the sand 0.1M nitric acid treated the sand and the product was powder black in colour, referred as GSC, graphene sand composite. SEM, XRD and FTIR characterization was used to analyze the results. SEM images showed nano sized layers or sheets of graphene extending outwards.The XRD peak represents the multi lagered graphene structure which is formed by the treatment of the composite with acid and application of the high temperature during experiment UV-visible spectroscopy results successfully reveals the filtration difference between mud water and filtered water.&#x0D;
ProFormer: Towards On-Device LSH Projection Based Transformers

At the heart of text based neural models lay word representations, which are powerful but occupy a lot of memory making it challenging to deploy to devices with memory constraints such as mobile phones, watches and IoT.To surmount these challenges, we introduce ProFormer -a projection based transformer architecture that is faster and lighter making it suitable to deploy to memory constraint devices and preserve user privacy.We use LSH projection layer to dynamically generate word representations on-the-fly without embedding lookup tables leading to significant memory footprint reduction from O(V.d) to O(T ), where V is the vocabulary size, d is the embedding dimension size and T is the dimension of the LSH projection representation.We also propose a local projection attention (LPA) layer, which uses self-attention to transform the input sequence of N LSH word projections into a sequence of N/K representations reducing the computations quadratically by O(K 2 ).We evaluate ProFormer on multiple text classification tasks and observed improvements over prior state-of-the-art on-device approaches for short text classification and comparable performance for long text classification tasks.Pro-Former is also competitive with other popular but highly resource-intensive approaches like BERT and even outperforms small-sized BERT variants with significant resource savings -reduces the embedding memory footprint from 92.16 MB to 1.7 KB and requires 16× less computation overhead, which is very impressive making it the fastest and smallest on-device model.