Real Computer Research Articles

Инструменты для выполнения и эмуляции квантовых вычислений

Currently, quantum technologies are at the forefront of scientific thought. Large corporations are creating their own quantum supercomputers, developing quantum analogues of classical algorithms, and research is being conducted in the field of quantum cryptography. But since quantum computers have not yet become widespread, the question becomes relevant: how can ordinary users, scientists and researchers keep up with the development of science? One possible solution is to use various kinds of tools to emulate quantum computing on a local non-quantum computer. In addition, there is also the opportunity to have several qubits of IBM's quantum supercomputer available. As a rule, such tools are implemented in the form of libraries for various programming languages. Due to the fact that working with real quantum computers is available only to a narrow circle of researchers, emulators are simply necessary to test hypotheses or algorithms. This article examined the most popular quantum emulators used for quantum computing and allowing emulating the process of a quantum computer. Work was carried out to study quantum emulators, to identify and describe their individual characteristics, to make recommendations for a more convenient start to work with them, as well as to describe their advantages and disadvantages. A review of several libraries for the JavaScript, Python, C / C ++ languages was made, as well as a tool with a web interface (Quantum Programming Studio) and a set of tools from Microsoft (Microsoft Quantum Development Kit), the main language of which is Q #, is examined. At the end of the article, a conclusion is made regarding the considered tools.

A Physics-Informed Neural Network Framework for PDEs on 3D Surfaces: Time Independent Problems

Partial differential equations (PDEs) on surfaces are ubiquitous in all the nature science. Many traditional mathematical methods has been developed to solve surfaces PDEs. However, almost all of these methods have obvious drawbacks and complicate in general problems. As the fast growth of machine learning area, we show an algorithm by using the physics-informed neural networks (PINNs) to solve surface PDEs. To deal with the surfaces, our algorithm only need a set of points and their corresponding normal, while the traditional methods need a partition or a grid on the surface. This is a big advantage for real computation. A variety of numerical experiments have been shown to verify our algorithm.

On Computing the Discrete Hirschman Transform

The Discrete Hirschman Transform (DHT) is a generalization of the entropy-based Hirschman Transform that canonically represents digital signals with sparse basis functions. The DHT is computationally attractive in providing the flexibility in hardware implementations since it has a sparse structure that is similar to that of the Discrete Fourier Transform (DFT) basis. This Hirschman-based algorithm has been widely applied in many digital signal processing algorithms such as denoising, filtering, and linear convolution. In this paper, we have developed two fast algorithms: the radix-2 and radix-4 DHT algorithms. These efficient algorithms significantly reduce the number of nontrivial real computations when compared to the original DHT algorithm and other popular Fast Fourier Transforms (FFTs). We show that it is feasible to realize our new algorithms in hardware through the use of a repetitive application of butterfly computations in a structure that will be familiar to those already working with the similar FFT algorithms. Our proposed algorithms reduce the number of nontrivial real computations while efficiently using available hardware resources.

Quantum bit commitment on IBM QX

Quantum bit commitment (QBC) is a quantum version of the classical bit commitment security primitive. As other quantum security primitives and protocols, QBC improves on cheating detection over its classical counterpart. The implementation of the QBC protocol below relies on the use of common quantum gates: the Hadamard gate used for orthonormal bases and the CNOT gate used to swap qubits. The protocol was run and tested on IBM quantum experience (IBM QX). IBM QX offers two different quantum environments: as a simulator and as a real quantum machine. In our implementation, honest and dishonest participants were considered. Results of both the simulation and the quantum execution were compared against the theoretical expectations. The IBM QX simulator gives results that match the theoretical model. The IBM QX real computer deviates from the expected behavior by a measurable amount. Using the standard deviation and the Hamming distance, the conclusion is that the quantum computer is usable as the difference to the simulator is within an acceptable margin of error. The QBC protocol of choice is fully secure against cheating by Bob. The only way Alice can cheat is using multi-dimensional entanglement. The cost for Alice to cheat is exponential in the number of qubits used, namely $$ O(2^{6n + 3k + 1} ) $$.

Comparing Diagnostic Yield of Electromagnetic Navigational Bronchoscopy Guided With Real Time Cone Beam Computer Tomography Compared to Standard Fluoroscopy Guidance for Peripheral and Central Lung Lesions

Comparing Diagnostic Yield of Electromagnetic Navigational Bronchoscopy Guided With Real Time Cone Beam Computer Tomography Compared to Standard Fluoroscopy Guidance for Peripheral and Central Lung Lesions

Redundancy with Processor Sharing servers

The main motivation to investigate redundancy models comes from empirical evidence suggesting that redundancy can help improve the performance of real-world applications. Under redundancy, a job that arrives to this system is dispatched to d servers uniformly chosen at random in order to benefit from the variability of the length of these queues. As soon as one of the copies finishes service, the job (and its copies) is removed from the system, and as a consequence, a job's delay is given by the minimum delay among the servers its copies are sent to. Most of the literature on performance evaluation of redundancy systems has been carried out when First Come First Served (FCFS) is implemented in the servers. In particular, for exponential service time distributions, Gardner et al. [4, 5] and Bonald and Comte [2] show that the stability region is not reduced due to adding redundant copies. In this extended abstract, we focus instead on Processor Sharing (PS) service policy and study how redundancy impacts the stability condition. In particular, we aim to study the impact that the correlation structure of the copies has on the performance of the redundancy-d model. In a recent paper, Gardner et al. [3] showed that the assumption of independent and identically distributed (i.i.d.) copies, can be unrealistic, and that it might lead to theoretical results that do not reflect the results of replication schemes in real-life computer systems. We consider the two extreme cases of correlation; (i) the copies are i.i.d. (ii) the copies of a job are exact replicas (identical copies). We observe that the stability condition strongly depends on the correlation structure, as well as on the number of redundant copies.

On Bayesian new edge prediction and anomaly detection in computer networks

Monitoring computer network traffic for anomalous behaviour presents an important security challenge. Arrivals of new edges in a network graph represent connections between a client and server pair not previously observed, and in rare cases these might suggest the presence of intruders or malicious implants. We propose a Bayesian model and anomaly detection method for simultaneously characterising existing network structure and modelling likely new edge formation. The method is demonstrated on real computer network authentication data and successfully identifies some machines which are known to be compromised.

Bayesian Maximum-A-Posteriori Approach with Global and Local Regularization to Image Reconstruction Problem in Medical Emission Tomography

The Bayesian approach Maximum a Posteriori (MAP) provides a common basis for developing statistical methods for solving ill-posed image reconstruction problems. MAP solutions are dependent on a priori model. Approaches developed in literature are based on prior models that describe the properties of the expected image rather than the properties of the studied object. In this paper, such models have been analyzed and it is shown that they lead to global regularization of the solution. Prior models that are based on the properties of the object under study are developed and conditions for local and global regularization are obtained. A new reconstruction algorithm has been developed based on the method of local statistical regularization. Algorithms with global and local regularization were compared in numerical simulations. The simulations were performed close to the real oncologic single photon emission computer tomography (SPECT) study. It is shown that the approach with local regularization produces more accurate images of ‘hot spots’, which is especially important to tumor diagnostics in nuclear oncology.

Research on denoising optimization algorithm of point cloud in 3d reconstruction

3 d reconstruction have become increasingly important in today’s information age, has become a bridge between real world and computer, usually in the access to the image due to factors such as equipment or environment are people hope there are a large number of high frequency signal, the pretreatment of the 3 d reconstruction is the most basic and crucial step in the technology. In this paper, an optimized adaptive filtering de-noising algorithm is proposed. The concept of minimum intra-class dispersion is introduced into the algorithm, and the genetic algorithm is used to find the optimal threshold, so as to eliminate the disadvantages of the algorithm in searching the scattered point cloud data and promote the overall performance of the algorithm. In this paper, the algorithm improves the speed, simplifies the initial point cloud model, and eliminates a large number of invalid points from the subsequent filtering algorithm.

Arduino Based Economic and Real Time Consumption Rate Computing

Arduino based design of economic and real-time fuel consumption rate computing by digital mileage meter is intended to develop effective and economic mileage meter that can promptly exhibit fuel mileage of a vehicle and show it. This device can be added to augment the existing running automotive system also, which works on carburetor or for that matter fuel injection technology. The cumbersome task of computing and manually checking the mileage can be automated using this device. Infra-red and position sensors have been assembled with Atmega328P microcontroller and installed on the motorbike. The efficacy of the designed mileage meter is revealed by comparing results with literature and real condition.

P3695Predicting adverse outcomes after TAVI procedure - a comparison of two CoreValve generations using real-life outcomes and patient-specific computer simulations

Abstract Background and aim Post-procedure conduction abnormalities (CA) and paravalvular aortic regurgitation (PAR) continue to strain TAVI outcomes. Computer simulations, based on patient-specific anatomy, valve properties, and implantation position, have been validated for prediction of these complications. The new-generation CoreValve Evolut PRO has been shown to have lower levels of PAR and CA than previous generations. The aim was to compare clinical outcomes after Evolut Pro implantation in real-life with outcomes of virtual deployment of the same size, implantation depth adjusted CoreValve Evolut R. Methods Patients undergoing Evolut Pro implantation at a single centre were included into the study. Postoperative Doppler echocardiography was assessed to define PAR, the pre- and postoperative 12-lead ECGs for CA, and the postoperative angiograms to measure implantation depth based on annular plane distance from the non-coronary and left coronary aortic valve cusps. Preoperative multislice computed tomography was used to generate patient-specific models of the native aortic root. Implantation of the Evolut R valve and corresponding aortic root deformation was simulated using computational mechanics, whereas blood flow and level of PAR were predicted using computational fluid dynamics. Prediction of CA – new onset left bundle branch block or atrioventricular block type II or III -was based on calculations of contact pressure in a patient-specific region of the aortic root containing the AV conduction system (ROI). Outcomes were predicted in three implantation depth positions - high, medium, low – where the position closest to the real-life implantation depth was chosen for outcome comparisons. Results Study diagram is shown in Figure 1. Thirty-three patients (57% female, mean age 82±6 years old) underwent a TAVI intervention with an Evolut PRO valve. Evolut PRO implantation depths were, in general, closest to the lowest modeled Evolut R depth. Comparison demonstrated similar overall incidence of moderate-to-severe PAR. The Evolut R simulation predicted 18 patients without PAR and 2 with PAR. With the Evolute PRO, 1 of the 18 not predicted developed significant PAR, and 1 of the 2 predicted did not develop PAR. CA were notably higher with the Evolut R simulation, where CA were present in 9 out of 12 patients, as compared to the observed 5 out of 12 with the Evolut PRO. Figure 1 Conclusion Single-centre outcomes after Evolut Pro implantation in real-life showed a similar overall incidence of moderate-to-severe PAR and a lower incidence of conduction abnormalities as compared to the same size, implantation depth adjusted, patient-specific Evolut R modeled outcomes. As inferred from the results, computer simulations may have high clinical utility in supporting clinical decisions regarding valve choice in TAVI procedures. Acknowledgement/Funding Horizon 2020 European Commission Project H2020-MSCA-ITN-2016 (764738)

Anonymous certificateless multi-receiver encryption scheme for smart community management systems

In community management services, it is a common requirement for management centers to send the same encrypted message to some units and individuals in the community, while avoiding the leakage of personal information of the user. In order to achieve this goal safely and efficiently, the multi-receiver encryption is a good option. In the setting, a sender generates the ciphertext for a designed group of receivers. Any receiver in the group can obtain the plaintext by decrypting the ciphertext using his own private key, and the true identity of the receiver is kept secret to anyone including other receivers. Recently, several certificateless multi-receiver encryption (CLMRE) schemes have been introduced, and all of them are proved to be secure in the random oracles model (ROM). ROM is a simulation of the hash function and can not replace the real hash function computation. In this paper, a new CLMRE scheme is constructed and it is proved to be secure based on decision bilinear Diffie–Hellman problem in the standard model (SM). It achieves the anonymity of the receivers and is suitable for smart community management systems.

Effect of unitary transformation on Bayesian information criterion for source numbering in array processing

An approach based on unitary transformation for the problem of estimating the number of signals is proposed in this study. Among the information theoretic criteria, the authors focus on the conventional Bayesian information criterion (BIC) in the presence of a uniform linear array. The sample covariance matrix of this array is transformed into the real symmetric one by using a unitary transformation. This real symmetric matrix has real eigenvalues and eigenvectors. Therefore its eigenvalue decomposition needs only real computations. Since the eigenvalues of this real symmetric matrix are equal to the eigenvalues of the sample covariance matrix, by replacing them in BIC formula, the term log-likelihood of BIC does not change but it is obtained by fewer computations. Also by considering the resulting real eigenvectors instead of the complex eigenvectors as a part of free parameters in the parameter vector of the model, they have a reduction in the number of degrees of freedom in the penalty term of BIC. This reduction makes their proposed method outperform BIC. They refer to this approach as unitary BIC. A series of simulations are included to demonstrate the usefulness of this approach.

Quantum-Inspired Acromyrmex Evolutionary Algorithm

Obtaining efficient optimisation algorithms has become the focus of much research interest since current developing trends in machine learning, traffic management, and other cutting-edge applications require complex optimised models containing a huge number of parameters. At present, computers based on the classical Turing-machine are inefficient when intent to solve optimisation tasks in complex and wicked problems. As a solution, quantum computers that should satisfy the Deutsch-Church-Turing principle have been proposed but this technology is still at an early stage. quantum-inspired algorithms (QIA) have emerged trying to fill-up an existing gap between the theoretical advances in quantum computation and real quantum computers. QIA use classical computers to simulate some physical phenomena such as superposition and entanglement to perform quantum computations. This paper proposes the quantum-inspired Acromyrmex evolutionary algorithm (QIAEA) as a highly efficient global optimisation method for complex systems. We present comparative statistical analyses that demonstrate how this nature-inspired proposal outperforms existing outstanding quantum-inspired evolutionary algorithms when testing benchmark functions.

Joint estimation of time delays and directions of arrival using proper set of antenna elements of a high-order antenna array

In this work, we investigate the accuracy and complexity deviation between using all or selected antenna elements of a massive MIMO array for source localization. In addition, we address the problem of highly resolving the propagation time delay, and the angles of arrival (azimuth and elevation) associated with signals in multipath communication channels for many location-based services and three-dimensional (3D) beamforming. The 3D unitary matrix pencil (3D UMP) algorithm is enhanced and applied in a new way to evaluate these parameters simultaneously from the estimated space channel frequency response (S-CFR) using wideband orthogonal multicarrier signals and uniform rectangular array (URA). Furthermore, the 2D UMP is enhanced to estimate the unknown parameters of wideband signals impinging on 8 different array configurations that are structured as combinations of uniform linear arrays (ULAs). It is not necessary to use all antenna elements of a high-order antenna array for source localization. Due to the dependency on mobile unit location, the phase uncertainties and the deviation of received signal strength between array elements, using the proper set of antenna elements can provide a comparable accuracy and a considerable reduction in the computational complexity of the localization algorithm. The computational complexity is further reduced by exploiting real computation and similar eigen-structure property, and using a priori information of wireless positioning. The IEEE 802.11ac system parameters are used in our experiments.

Gaze direction affects walking speed when using a self-paced treadmill with a virtual reality environment

BackgroundIn a previous study it was observed that participants increase their walking speed during a dual task while walking on a self-paced treadmill in a virtual reality (VR) environment (Gait Real time Analysis Interactive Lab (GRAIL)). This observation is in contrast with the limited resources hypothesis, which suggests walking speed of healthy persons to decrease when performing a cognitive dual task. AimThe aim of the present study was therefore to determine whether the cognitive demand of the task, an aroused feeling, discrepancy in optic flow or a change in gaze direction caused participants to walk faster in this computer assisted rehabilitation environment. MaterialsThe GRAIL included a self-paced treadmill, a motion-capture system and synchronized VR environments. MethodsThirteen healthy young adults (mean age 21.6 ± 2.5) were included in this study. Participants walked on the self-paced treadmill while seven different intervention conditions (IC) were offered. Prior to each IC, a control condition (CC) was used to determine the natural self-selected walking speed. Walking speed during the last 30 s of each IC was compared with the walking speed during the last 30 s of the preceding CC. ResultsResults show that the height on which a visual task was presented in the VR environment, influenced walking speed. Participants walked faster when gaze was directed above the focus of expansion. SignificanceThese findings contribute to a further understanding of the differences between walking in a real life environment or computer assisted rehabilitation environment. When analyzing gait on a self-paced treadmill in the future, one must be attentive where to place a visual stimulus in the VR environment.

Effect of age on spatial memory performance in real museum vs. computer simulation

BackgroundHealthy older adults frequently complain on difficulty in recalling the locations of objects of everyday use. Cognitive abilities decline with normal aging; inefficiencies of information processing, as well as deterioration of neuronal structures, may impede the performance of complex cognitive skills such as spatial memory. Extraneous, task-irrelevant cognitive load in real environments is usually high and might interfere with spatial memory abilities of older adults. The purpose of this study was to determine (1) the extent to which older adults maintain their cognitive capacity during a spatial memory task as compared to young adults and (2) whether this capacity is affected by performance of the task in a real environment setting where the cognitive demands are similar to a simulation, but the physical demands (navigating via walking versus via a mouse) vary.MethodsIn the museum, participants physically moved between display stations to locate hidden tokens performing a task in which an ongoing representation of previous searches had to be remembered. A comparable task was implemented via mouse actions on a computer simulation. Seventeen healthy older (60–80 years) and twenty younger (20–45 years) adults performed both tasks in a counterbalanced order.ResultsThe younger group was superior to the older group in terms of success rate and completion time for both conditions. All participants performed better during the simulated task. The delta between the total performance score in the two settings of the older group was significantly larger as compared to the younger group, suggesting a differential impact of setting on the groups.ConclusionsOur results highlight the importance and feasibility of experimentation in ecologically relevant settings: differences were found in the way the cognitive performance of older and younger adults was affected by setting. Older adults appear to preserve basic cognitive abilities required for successful performance of object–location memory tasks. However, real museum setting appeared to impose higher demands on the older adults.

Fast HUB Floating-Point Adder for FPGA

Several previous publications have shown the area and delay reduction when implementing real number computation using half-unit biased (HUB) formats for both floating-point and fixed-point. In this brief, we present an HUB floating-point adder for field-programmable gate array (FPGA) which greatly improves the speed of previous proposed HUB designs for these devices. Our architecture is based on the double path technique which reduces the execution time since each path works in parallel. We also deal with the implementation of unbiased rounding in the proposed adder. Experimental results are presented showing the goodness of the new HUB adder for FPGA.

A Theory of NP-completeness and Ill-conditioning for Approximate Real Computations

We develop a complexity theory for approximate real computations. We first produce a theory for exact computations but with condition numbers. The input size depends on a condition number, which is not assumed known by the machine. The theory admits deterministic and nondeterministic polynomial time recognizable problems. We prove that P is not NP in this theory if and only if P is not NP in the BSS theory over the reals. Then we develop a theory with weak and strong approximate computations. This theory is intended to model actual numerical computations that are usually performed in floating point arithmetic. It admits classes P and NP and also an NP-complete problem. We relate the P vs. NP question in this new theory to the classical P vs. NP problem.

A Proposed Web Based Real Time Brain Computer Interface (BCI) System for Usability Testing

Hallway testing, Remote Usability testing, Expert review, Automated expert review and A/B testing are the methods commonly used for Usability testing. However, there is no reliable system that integrates Brain Computer Interface (BCI) into the testing process with focus given towards user emotion analysis using electroencephalography (EEG) signals. This paper proposes a system that would be able to identify user emotions while they are conducting usability tests and the results would be able to increase the accuracy of the usability test. In the proposed system the results of the usability test would be displayed in real time on a dashboard and a summary report can be generated for distribution.