This paper shows that as the dimensionality of a noninteger dimensional falls below 2, the potential becomes constant irrespective of separation between objects and the force between them disappears, which represents a new paradigm of asymptotic freedom. Since asymptotic freedom is at the basis of many applications such as those of strange metals, unconventional superconductors, and fractional quantum Hall states, the new paradigm presented here can potentially have new and unexpected applications. It also is of relevance to the study of anomalous mechanical effects that are important in metamaterials.

In this paper, the problem of computing the number of degrees of freedom (NDF) of the field radiated by a strip current along all the possible lines orthogonal to the source is addressed. As well known, the NDF is equal to the number of singular values of the radiation operator that are before a critical index at which they abrupt decay. Unfortunately, in the considered case, the solution of the associate eigenvalue problem is not known in closed-form, and this prevents us from directly evaluating the singular values of the radiation operator. To overcome this drawback, a weighted adjoint operator is exploited. The latter allows obtaining an eigenvalue problem whose solution is known in closed-form but, at the same time, it modifies the singular values behavior. However, since the change affects only the dynamics of the singular values but not the critical index at which they abrupt decay, the NDF of the radiated field can be analytically estimated by resorting to the weighted adjoint operator.

An analysis of the transient behavior of DC networks consisting of voltage sources, capacitors, and series loss-free resistors (SLFRs) is presented. The realization of an SLFR was achieved by means of a topological variation of the positive output-voltage buck-boost converter operated in discontinuous-conduction mode (DCM). It is demonstrated that even simple RC circuits containing SLFRs exhibit behavior that is described by Abel nonlinear differential equations, which do not have an exact analytical solution. Some possible applications of the SLFRs in power electronics, DC microgrids and renewable energy power systems, include loss-free charge and discharge of capacitor banks, voltage equalization of capacitors, and loss-free voltage clamping circuits. The concept of the SLFR can also be applied for voltage control in DC microgrids, employing the droop voltage technique, equalization of power and current in voltage sources associated in parallel (including batteries and DC-DC converters), and also input and output voltage natural balance in input-series output-series (ISOS) association of DC converters. The theoretical analysis results are validated via numerical examples and computer simulation.

This article proposes a cognitive radio enabled radio frequency (RF)/free-space optical (FSO) communication model for an aerial relay network, which is consisting of UAV relay nodes and high altitude platform systems.

We propose a novel technique for finding representatives from a large, unsupervised dataset. The approach is based on the concept of self-rank, defined as the minimum number of samples needed to reconstruct all samples with an accuracy proportional to the rank-$K$ approximation. Our proposed algorithm enjoys linear complexity w.r.t. the size of original dataset and simultaneously it provides an adaptive upper bound for approximation ratio. These favorable characteristics result in filling a historical gap between practical and theoretical methods in finding representatives.

The new so-called COVID-19 virus is unfortunately founded to be highly transmissible across the globe. In this study, we propose a novel approach for estimating the spread level of the virus for each country for three different dates between April and May 2020. Unlike previous studies, this investigation does not process any historical data of spread but rather relies on the socio-economic indicators of each country. Actually, more than 1000 socio-economic indicators and more than 190 countries were processed in this study. Concretely, data preprocessing techniques and feature selection approaches were applied to extract relevant indicators for the classification process. Countries around the globe were assigned to 4 classes of spread. To find the class level of each country, many classifiers were proposed based especially on Support Vectors Machines (SVM), Multi-Layer Perceptrons (MLP) and Random Forests (RF). Obtained results show the relevance of our approach since many classifiers succeeded in capturing the spread level, especially the RF classifier, with an F-measure equal to 93.85% for April 15th, 2020. Moreover, a feature importance study is conducted to deduce the best indicators to build robust spread level classifiers. However, as pointed out in the discussion, classifiers may face some difficulties for future dates since the huge increase of cases and the lack of other relevant factors affecting this widespread.

Web applications (WAs) are constantly evolving and deployed at broad scale. However, they are exposed to a variety of attacks. The biggest challenge facing organizations is how to develop a WA that fulfills their requirements with respect to sensitive data exchange, E-commerce, and secure workflows. This paper identifies the most critical web vulnerabilities according to OWASP Top Ten, their corresponding attacks, and their countermeasures. The application of these countermeasures will guarantee the protection of the WAs against the most severe attacks and prevent several unknown exploits.

A document by Hala Neji . Click on the document to view its contents.

We propose the approaches that using the neighbour relation of nodes in the graph to solve the minimum vertex cover problem.

This paper presents a linear complexity iterative rake detector for the recently proposed orthogonal time frequency space (OTFS) modulation scheme. The basic idea is to extract and coherently combine the received multipath components of the transmitted symbols in the delay-Doppler grid using maximal ratio combining (MRC) to improve the SNR of the combined signal. We reformulate the OTFS input-output relation in simple vector form by placing guard null symbols or zero padding (ZP) in the delay-Doppler grid and exploiting the resulting circulant property of the blocks of the channel matrix. Using this vector input-output relation we propose a low complexity iterative decision feedback equalizer (DFE) based on MRC. The performance and complexity of the proposed detector favorably compares with the state of the art message passing detector. An alternative time domain MRC based detector is also proposed for even faster detection. We further propose a Gauss-Seidel based over-relaxation parameter in the rake detector to improve the performance and the convergence speed of the iterative detection. We also show how the MRC detector can be combined with outer error-correcting codes to operate as a turbo DFE scheme to further improve the error performance. All results are compared with a baseline orthogonal frequency division multiplexing (OFDM) scheme employing a single tap minimum mean square error (MMSE) equalizer.

Lung cancer causes the most cancer deaths worldwide and has one of the lowest five-year survival rates of all cancer types. It is reported that more than half of patients with lung cancer die within one year of being diagnosed. Because mediastinal lymph node status is the most important factor for the treatment and prognosis of lung cancer, the aim of this study is to improve the predictive value in assessing the computed tomography (CT) of mediastinal lymph-node malignancy in patients with primary lung cancer. This paper introduces a new method for creating pseudo-labeled images of CT regions of mediastinal lymph nodes by using the concept of recurrence analysis in nonlinear dynamics for the transfer learning. Pseudo-labeled images of original CT images are used as input into deep-learning models. Three popular pretrained convolutional neural networks (AlexNet, SqueezeNet, and DenseNet-201) were used for the implementation of the proposed concept for the classification of benign and malignant mediastinal lymph nodes using a public CT database. In comparison with the use of the original CT data, the results show the high performance of the transformed images for the task of classification. The proposed method has the potential for differentiating benign from malignant mediastinal lymph nodes on CT, and may provide a new way for studying lung cancer using radiology imaging.

To economically dispatch distributed energy resources (DERs) while addressing operational concerns of the electric grid, distribution locational marginal price (DLMP)-based market frameworks have been formulated for the electric distribution grid. This paper proposes to extend this methodology to thermal grids, i.e. district heating or cooling systems, and presents a market-clearing mechanism based on the alternating direction method of multipliers (ADMM) for coordinating between thermal grid, electric grid and DER operation. The ability of the proposed mechanism to achieve the market equilibrium for a combined thermal and electric grid is demonstrated for a test case with 22 flexible loads (FLs).

Virtual absorption concept has been recently introduced as a new phenomenon observed in electromagnetics and optics consisting of an undefined energy accumulation within a finite volume of material without dissipation. The anomalous behaviour is achieved by engaging the complex zero scattering eigenmodes of the virtual absorbing system by illuminating it with a proper complex frequency, whose value is strictly determined by the system characteristics. In this paper, we investigate on the position of the zero-pole scattering pairs in the complex frequency plane as a function of the input impedance of the metasurface-based lossless virtual absorber. We analytically derive the conditions under which a properly modulated monochromatic plane wave can be virtually absorbed by the system and stored within its volume. The analysis is developed by modelling the propagation of a normally impinging plane wave though its equivalent transmission line model terminated on an arbitrary reactive load, which in turn models the input impedance of the metasurface-based system under consideration. The study allows to determine a priori whether the metasurface-based system can support the virtual absorption or not by evaluating the time-constant from its equivalent circuit.

Mutual coupling, or equivalently, the isolation between antennas, is a key parameter in antenna system design. In this work, the previously defined impedance density is generalized, and it is demonstrated how it can be used to obtain spatial information about the mutual coupling. The generalized impedance density is a real-valued scalar and it can be visualized as a three-dimensional density in space. It is shown that there is a strong connection between regions with a positive (negative) generalized impedance density and a decrease (increase) of the coupling when an absorber is placed in that region. This predictive ability is a useful feature, which is tested for three numerical cases. The results are robust to the shape of the platform, and it can be compared across frequencies. By placing absorbers based on the generalized impedance density, it is possible to reduce the required amount of absorbers needed to obtain a certain reduction in mutual coupling. The visualization results and predictions of absorber positions are compared with a Poynting vector based method. Placing absorbers based on the generalized impedance density had a larger impact on the mutual coupling, compared to the predictions with the Poynting vector based method in the investigated cases.

The world of technology is changing. It used to be one where users could post on social media, order clothes online, and play mobile games without a care in the world. As time progressed, companies eventually realized that they could collect small pieces of information from a user’s technological habits, and use that to form a profile of the user of some sort. Such a profile could be used for marketing, grouping, or even just to sell-off. I conducted a study of mobile device application developers, specifically relating to iOS third-party applications. This is more of a hidden loophole in the “security” of Apple’s iOS. This is important to the field of data privacy because many users use third-party applications without the knowledge of what data is being taken and when it is being taken. I used a packet-monitoring service to listen in on third-party applications and wrote a script to filter out relevant pieces of data that were being sent back to an application’s server. The findings of this study concluded that third-party iOS applications have unmonitored power to access pieces of information like contacts, location, and emails.

Non-orthogonal multiple access (NOMA) is a promising candidate for future mobile networks as it enables improved spectral-efficiency, massive connectivity and low latency. This paper derives exact and asymptotic bit error rate (BER) expressions under Rayleigh fading channels for NOMA systems with arbitrary number of users and arbitrary number of receiving antennas and modulation orders, including binary phase-shift keying and rectangular/square quadrature amplitude modulation. Furthermore, the power coefficients’ bounds, which ensure users’ fairness, and solve the constellation ambiguity problem, are derived for N=2 and 3 users cases with any modulation orders. In addition, this paper determines the optimal power assignment that minimizes the system’s average BER. These results provide valuable insight into the system’s BER performance and power assignment granularity. For instance, it is shown that the feasible power coefficients range becomes significantly small as the modulation order, or N, increases, where the BER performance degrades due to the increased inter-user interference. Hence, the derived expressions can be crucial for the system scheduler in allowing it to make accurate decisions of selecting appropriate N, modulation orders, and power coefficients to satisfy the users’ requirements. The presented expressions are corroborated via Monte Carlo simulations.

This pre-print reports on a significant further development of our previously published work on Linear TDA-MAC: N. Morozs, P. Mitchell, and Y. Zakharov, “Linear TDA-MAC: Unsynchronized scheduling in linear underwater acoustic sensor networks,” IEEE Netw. Lett., vol. 1, no. 3, pp. 120–123, 2019.

Deep convolutional neural networks (Deep CNN) have achieved hopeful performancefor single image super-resolution. In particular, the Deep CNN skip Connection andNetwork in Network (DCSCN) architecture has been successfully applied to naturalimages super-resolution. In this work we propose an approach called SDT-DCSCN thatjointly performs super-resolution and deblurring of low-resolution blurry text imagesbased on DCSCN. Our approach uses subsampled blurry images in the input and origi-nal sharp images as ground truth. The used architecture is consists of a higher numberof filters in the input CNN layer to a better analysis of the text details. The quantitativeand qualitative evaluation on different datasets prove the high performance of our modelto reconstruct high-resolution and sharp text images. In addition, in terms of computa-tional time, our proposed method gives competitive performance compared to state ofthe art methods.