Reviewerly/exHarmony huggingface dataset:
Activities on Legislation for Autonomous Vehicles Take Off [Connected and Automated Vehicles]

The COVID-19 pandemic is still holding the world in a stranglehold. Large-scale vaccination is in different stages throughout nations globally, and countries that have come far in terms of vaccinating the population are slowly beginning to open up. The commercial vehicle industry sells more vehicles than it can produce for the moment-a sort of rebound effect from when the world was put on hold last spring. At the same time, the automotive industry is experiencing semiconductor shortages, resulting from unfortunate occurrences such as fires in semiconductor factories, but also because semiconductor companies' order intakes from the automotive industry declined substantially last spring, and the companies turned to other customers.
A power fluctuation evaluation method of PV plants based on RankBoost ranking

Abstract Fluctuation evaluation is an important task in promoting the accommodation of photovoltaic (PV) power generation. This paper proposes an evaluation method to quantify the power fluctuation of PV plants. This consists of an index system and a ranking method based on the RankBoost algorithm. Eleven indices are devised and included in the index system to fully cover diverse fluctuation features. By handling missing and invalid data effectively, the ranking method fuses multiple indices automatically and provides a systematic and comprehensive comparison of power fluctuation. Simulation results based on power data from six PV plants indicate that the evaluation list obtained by the RankBoost ranking method is better represented and more comprehensive than that derived by the equal weight method.
Quantum brachistochrone for multiple qubits

Abstract Efficient control of qubits plays a key role in quantum information processing. In the current work, an alternative set of differential equations are derived for an optimal quantum control of single or multiple qubits with or without interaction. The new formulation enables a great reduction of the computation load by eliminating possible redundant complexity involved in previous algorithms. A relaxation technique is designed for numerically detecting optimal paths involving entanglement. Interesting continuous symmetries are identified in the Lagrangian, which indicates the existence of physically equivalent classes of paths and may be utilized to remove neutral directions in the Jacobian of the evolution. In the ‘ground state’ solution among the set of optimal paths, the time-reversal symmetry of the system shows up, which is expected to be universal for the symmetry-related initial and final state.
Artificial intelligence: Explainability, ethical issues and bias

There is no doubt that Artificial Intelligence (AI) is a topic that is attracting increasing attention from different communities, business and academic. AI adoption and implementation is faced by the difficulty of interpreting and trusting the outcomes of AI algorithms.
RETRACTED ARTICLE: Application of heterogeneous execution body scheduling and VR technology for mimic cloud services in urban landscape design

Regarding the current scheduling models of heterogeneous executive bodies, most of the modeling design is based on space or time characteristics, but its comprehensive consideration of space and time is relatively insufficient, leading to frequent problems of dynamic imbalance and heterogeneous characteristics. In order to complete the dynamic balance and heterogeneous complementarity of the mimic cloud service system, this paper starts with priority and time slice and proposes an execution pool scheduling algorithm. It integrates project time slices with similar indicators of execution pools, sorts scheduling priorities, combines scheduling strategies, and proposes a problem based on the different output data of the executive bodies of multiple heterogeneous mimic cloud service systems. A method for judging the consistency of output data is proposed based on template comparison and confidence correction. The operating system inside the heterogeneous executive scheduling usually runs on the core of the common processing, and for relatively large operations, it runs on a dedicated processor. As a means of experience, VR technology is being widely used in various design fields such as architecture, decoration, gardens, and landscapes. VR technology has basically replaced the traditional forms of paper renderings and electronic plane models and other forms of expression, and its experience and operability are relatively stronger. Urban landscape design belongs to a type of diverse scales and complex fields in the design field. To do a good job in urban landscape design, not only the guidance and control between the building and the city but also key issues such as creativity and rigid management must be considered. Taking VR technology as a means to carry out urban landscape design, and combined with urban characteristics, this paper analyzes and discusses the application of VR technology in urban landscape design.
Yeni Bir Paradigma Olarak Gerçek Zamanlı Blok Zinciri Muhasebe Sistemi

The aim of this study is to evaluate the advantages by examining the effect decentralized blockchain applications on accounting information systems. The blockchain as an Distributed Ledger Technology (DLT) offers new possibilities to recording and backing up sensitive and confidential data of accounting information systems. The blockchain is designed in a structure that allows transactions to be monitored and controlled in real-time. By this way, the question of how to operate the real-time accounting system, as a new paradigm with blockchain technology, and how to apply in the field of taxation have emerged simultaneously. To achieve the aim of the study, a descriptive approach was adopted to explore the basics of blockchain technology and the most important accounting practices (such as accounting entries, taxation). For that purpose, the relevant literature on blockchain accounting system were reviewed and the blockchain reports of the big four companies were examined. As a result, the potential advantages of real-time blockchain accounting system were categorized according to four focus points: transparency and trust; disintermediation;smart contracts; continuous audit.
Shaping a Values-Based Attitude toward Human in the Context of Postmodernism via the Structural-Functional Model

The problem of shaping a values-based attitude toward humans requires complex, universal, and multilevel solutions (natural-scientific, cosmological-anthropological, sociological, cultural, moral, and ethical aspects). Another side of the problem lies in the postmodern devaluation of classical values that has caused a crisis in the education of the younger generations. The article presents the author’s conceptual, scientific-methodical, structural-functional model and technology for shaping a values-based attitude toward humans by stages in the humanities-oriented educational environment. Given postmodern trends in the post-Soviet countries with “young democracies”, the structural components of this model are as follows: the consideration of human nature in mastering disciplines, as well as out-of-classroom and out-of-school work, that seek to shape humanistic consciousness, feelings, and behavior based on basic values. In this regard, it is essential to help students learn to respect themselves, understand their personality (reflexivity), and resist external negative factors (emotional stability). Besides, it is important to consider the axiological component in a study of human nature, teach students to realize the value of others and develop their empathy skills.
Image Classification and Detection of Insulators using Bag of Visual Words and Speeded up Robust Features

Electrical substation online monitoring in computer vision technology is based on image processing algorithm to perform visual analysis. This paper presents classification of ceramicand glass insulators through Bag of Visual Words and detection of these insulators by Point Feature Matching. The training image datasets are used for categorization by forming a visual vocabulary while a new unlabeled image from testing image dataset is classify using nearest neighbor classification method for features descriptor. For detection we use Speeded up Robust Features for detecting position of insulator present in cluttered scene image. Matching process is done between test and reference image and decision is made based on similar features. We conducted experiment on insulators to verify the superiority of our proposed method. The proposed method can be used in security, surveillance and inspection system
Enhancing Security Using Quantum Computing (ESUQC)

In a classical computer, the computation is based on transistors which encode the information in bits and usually vulnerable to attack by professional attackers. In quantum computing, the computation is based on qubits. Using single-qubit the information is encoded in the combination of two bits. Quantum computing is a completely new technology that holds all the characteristic of quantum mechanics to solve a particular problem faster than a classical computer. For solving these problems, a scientist uses a “logical qubit” since classical computer bits consist of mechanical relays or vacuum tubes which is possible to flip unexpectedly. It is possible to create quantum algorithms using qubit that run faster than classical algorithms and these algorithms reduce the time complexity and also it is impossible for the attackers to attack. There are some most popular algorithms which are possible in the quantum world, and they are Grover’s algorithm and Shor’s algorithm.
Asymptotically Optimal Circuit Depth for Quantum State Preparation and General Unitary Synthesis

The Quantum State Preparation problem aims to prepare an $n$-qubit quantum state $|\psi_v\rangle =\sum_{k=0}^{2^n-1}v_k|k\rangle$ from the initial state $|0\rangle^{\otimes n}$, for a given unit vector $v=(v_0,v_1,v_2,\ldots,v_{2^n-1})^T\in \mathbb{C}^{2^n}$ with $\|v\|_2 = 1$. The problem is of fundamental importance in quantum algorithm design, Hamiltonian simulation and quantum machine learning, yet its circuit depth and size complexity remain open when ancillary qubits are available. In this paper, we study efficient constructions of quantum circuits with $m$ ancillary qubits that can prepare $|\psi_v\rangle$ in depth $\tilde O\left(\frac{2^n}{m+n}+n\right)$and size $O(2^n)$, achieving the optimal value for both measures simultaneously. These results also imply a depth complexity of $\Theta(4^n/(m+n))$ for quantum circuits implementing a general $n$-qubit unitary using $m = O(2^n/n)$ ancillary qubits. This resolves the depth complexity for circuits without ancillary qubits, and for circuits with exponentially many ancillary qubits, this gives a quadratic saving from $O(4^n)$ to $\tilde \Theta(2^n)$. Our circuits are deterministic, prepare the state and carry out the unitary precisely, utilize the ancillary qubits tightly and the depths are optimal in a wide range of parameter regime. The results can be viewed as (optimal) time-space tradeoff bounds, which is not only theoretically interesting, but also practically relevant in the current trend that the number of qubits starts to take off, by showing a way to use a large number of qubits to compensate the short qubit lifetime.
Image Collation: Matching Illustrations in Manuscripts

Illustrations are an essential transmission instrument. For an historian, the first step in studying their evolution in a corpus of similar manuscripts is to identify which ones correspond to each other. This image collation task is daunting for manuscripts separated by many lost copies, spreading over centuries, which might have been completely re-organized and greatly modified to adapt to novel knowledge or belief and include hundreds of illustrations. Our contributions in this paper are threefold. First, we introduce the task of illustration collation and a large annotated public dataset to evaluate solutions, including 6 manuscripts of 2 different texts with more than 2 000 illustrations and 1 200 annotated correspondences. Second, we analyze state of the art similarity measures for this task and show that they succeed in simple cases but struggle for large manuscripts when the illustrations have undergone very significant changes and are discriminated only by fine details. Finally, we show clear evidence that significant performance boosts can be expected by exploiting cycle-consistent correspondences. Our code and data are available on http://imagine.enpc.fr/~shenx/ImageCollation.
PREDICTION OF WEATHER FORECASTING BY USING MACHINE LEARNING

Weather forecasting has become important now a day because of varying climatic conditions around the world.Many technologies have been introduced to predict the weather whose accuracy is around 70%.Weather forecasting is used in machine learning.It is a powerful technique to predict the weather with more accuracy.Weather dataset is collected and analysed and algorithms on it to predict the weather.Using a Back Propagation Neural Network the error rate becomes less and many factors that are involved to predicting the weather gives the accurate results.To compare and evaluate the performance of above model and the programming was carried out using Visual Studio as a tool.
Borromean states in discrete-time quantum walks

In the right conditions, removing one particle from a multipartite bound state can make it fall apart. This feature, known as the "Borromean property", has been recently demonstrated experimentally in Efimov states. One could expect that such peculiar behavior should be linked with the presence of strong inter-particle correlations. However, any exploration of this connection is hindered by the complexity of the physical systems exhibiting the Borromean property. To overcome this problem, we introduce a simple dynamical toy model based on a discrete-time quantum walk of many interacting particles. We show that the particles described by it need to exhibit the Greenberger-Horne-Zeillinger (GHZ) entanglement to form Borromean bound states. As this type of entanglement is very prone to particle losses, our work demonstrates an intuitive link between correlations and Borromean properties of the system. Moreover, we discuss our findings in the context of the formation of composite particles.
Retrieval of Photometric Parameters of Minerals Using a Self-Made Multi-Angle Spectrometer Based on the Hapke Radiative Transfer Model

In this paper, a self-made, mineral, multi-angle, spectrum measurement device is employed to measure the multi-angle spectra of olivine and plagioclase; the multi-angle spectra of ilmenite in the Reflectance Experiment Laboratory (RELAB) Spectral Library are collected; and the optimized retrieval of the photometric parameters of the Hapke model is realized. Importantly, the derived result of the single-scattering albedo (SSA) is stable and has both mathematical meaning and physical meaning. The derived Legendre polynomial coefficients of the phase function can better simulate the variation in the mineral spectra with angle. This paper compares the effects of multi-angle and single-angle spectral data on the photometric parameter derived results. The setting of the Legendre polynomial coefficient of the scattering phase function mainly affects the simulation accuracy of the mineral spectra as a function of angle. Using this coefficient to optimize the retrieval, the simulation accuracy is moderately improved compared with the single-angle simulation. The estimation of photometric parameters based on multi-angle spectral data can provide a basis for setting the empirical values of the phase function parameters from single-angle spectral calculations, which can more truly reflect the law of reflectance spectra changing with angle than Lucey’s traditional empirical value of the phase function (b = −0.4 and c = 0.25). The results of multi-angle spectra retrieval in this paper show that the Legendre polynomial coefficients of the phase function vary with wavelength rather than being constant and that different minerals differ greatly.
The Role of Digital Technologies in the New Present and Future of Higher Education

Abstract Over the last two decades, digitization has transformed the world as we know it. It has changed our economies, industries, leisure, social practices, job markets, politics, and—of course—how we learn. Access to information has continuously been getting faster and more universal.
Implementation of Harris Hawks Optimization (HHO) algorithm to solve engineering problems

Recently, optimization techniques have become very important and popular in different engineering applications. In this paper we demonstrate how Harris Hawks Optimization (HHO) algorithm can be used to solve certain optimization problems in engineering. In the second part, biological fundamentals, as well as method explanation are given. Afterwards, the HHO algorithm and its' applicability is explained in detail. The pseudo code for this algorithm was written using MATLAB R2019a software suite. Harris Hawks Optimization (HHO) algorithm was used for optimization of engineering problems, such as: speed reducer optimization, pressure vessel optimization, cantilever beam optimization and tension/compression spring optimization. The statistical results and comparisons show that the HHO algorithm provides very promising and competitive results compared to others metaheuristic algorithms.
Character Design Generation System Using Multiple Users' Gaze Information

We investigate an interactive evolutionary computation (IEC) using multiple users' gaze information when users partially participate in each design evaluation. Many previous IEC systems have a problem that user evaluation loads are too large. Hence, we proposed to employ user gaze information for evaluating designs generated by IEC systems in order to solve this problem. In this proposed system, users just view the presented designs, not assess, then the system automatically creates users' favorite designs. With the user's gaze information, the proposed system generates coordination that can satisfy many users. In our previous study, we verified the effectiveness of the proposed system from a real system operation viewpoint. However, we did not consider the fluctuation of the users during a solution candidate evaluation. In the actual operation of the proposed system, users may change during the process due to the user interchange. Therefore, in this study, we verify the effectiveness of the proposed system when varying the users participating in each evaluation for each generation. In the experiment, we employ two types of situations as assumed in real environments. The first situation changes the number of users evaluating the designs for each generation. The second situation employs various users from the predefined population to evaluate the designs for each generation. From the experimental results in the first situation, we confirm that, despite the change in the number of users during the solution candidate evaluation, the proposed system can generate coordination to satisfy many users. Also, from the results in the second situation, we verify that the proposed system can also generate coordination which both users who participate in the coordination evaluation can more satisfy.
A New General Maximum Intensity Projection Technology via the Hybrid of U-Net and Radial Basis Function Neural Network

Maximum intensity projection (MIP) technology is a computer visualization method that projects three-dimensional spatial data on a visualization plane. According to the specific purposes, the specific lab thickness and direction can be selected. This technology can better show organs, such as blood vessels, arteries, veins, and bronchi and so forth, from different directions, which could bring more intuitive and comprehensive results for doctors in the diagnosis of related diseases. However, in this traditional projection technology, the details of the small projected target are not clearly visualized when the projected target is not much different from the surrounding environment, which could lead to missed diagnosis or misdiagnosis. Therefore, it is urgent to develop a new technology that can better and clearly display the angiogram. However, to the best of our knowledge, research in this area is scarce. To fill this gap in the literature, in the present study, we propose a new method based on the hybrid of convolutional neural network (CNN) and radial basis function neural network (RBFNN) to synthesize the projection image. We first adopted the U-net to obtain feature or enhanced images to be projected; subsequently, the RBF neural network performed further synthesis processing for these data; finally, the projection images were obtained. For experimental data, in order to increase the robustness of the proposed algorithm, the following three different types of datasets were adopted: the vascular projection of the brain, the bronchial projection of the lung parenchyma, and the vascular projection of the liver. In addition, radiologist evaluation and five classic metrics of image definition were implemented for effective analysis. Finally, compared to the traditional MIP technology and other structures, the use of a large number of different types of data and superior experimental results proved the versatility and robustness of the proposed method.
Automatic Pre Processing of Marathi Text for Summarization

The text summarization is a technique where the original large text is condensed into smaller version without changing its abstract meaning. The text summarization is done on the common foreign and regional languages typically, but infrequent work has been observed for the Marathi language. As the amount of e-contents on web is increasing drastically, the users are facing difficulty to read the newspaper articles with extraction of its different perspectives with sorting. We are focussing on educational, Political and sports news for summarization, which will be helpful for students who are appearing for competitive exams. This paper explores the preprocessing techniques for Marathi e-news articles.
Incorporating Widget Positioning in Interaction Models of Search Behaviour

Models developed to simulate user interactions with search interfaces typically do not consider the visual layout and presentation of a Search Engine Results Page (SERP). In particular, the position and size of interfacewidgets ---such as entity cards and query suggestions---are usually considered a negligible constant. In contrast, in this work, we investigate the impact of widget positioning on user behaviour. To this end, we focus on one specific widget: the Query History Widget (QHW). It allows users to see (and thus reflect) on their recently issued queries. We build a novel simulation model based on Search Economic Theory (SET) that considers how users behave when faced with such a widget by incorporating its positioning on the SERP. We derive five hypotheses from our model and experimentally validate them based on user interaction data gathered for an ad-hoc search task, run across five different placements of the \qhw on the SERP. We find partial support for three of the five hypotheses, and indeed observe that a widget's location has a significant impact on search behaviour.