Wideband high aperture efficiency antennas with beam switching for mmWave 5G base stations

A compact metamaterial inspired sub‐wavelength unit cells are integrated into wideband Vivaldi antenna. A high gain Vivaldi antenna with 50% impedance bandwidth is proposed. The dimensions of the antenna are 1.55 λ₀ × 3.2 λ₀ at 28 GHz. Gain enhancement of 3‐dB achieved by placing metamaterial unit cells in the aperture of the antenna. These unit cells aid in phase correction of the antenna. The 1‐dB gain bandwidth of antenna is 42% with a peak gain of 12.5 dBi indicating high pattern integrity. Corrugations of varying length are introduced in the ground plane to improve front‐to‐back ratio without altering the input impedance bandwidth. The aperture efficiency of the metamaterial loaded Vivaldi antenna is 78% at 28 GHz. The proposed element is used in a stacked module to achieve wide angular coverage of 120°.     

HiPoLDS: A Hierarchical Security Policy Language for Distributed Systems

Expressing security policies to govern distributed systems is a complex and error-prone task. Policies are hard to understand, often expressed with unfriendly syntax, making it difficult for security administrators and for business analysts to create intelligible specifications. We introduce the Hierarchical Policy Language for Distributed Systems (HiPoLDS), which has been designed to enable the specification of security policies in distributed systems in a concise, readable, and extensible way. HiPoLDS design focuses on decentralized execution environments under the control of multiple stakeholders. It represents policy enforcement through the use of distributed reference monitors, which control the flow of information between services. HiPoLDS allows the definition of both abstract and concrete policies, expressing respectively high-level properties required and concrete implementation details to be ultimately introduced into the service implementation.     

Mixed convection flow over a stretching sheet of variable thickness: Analytical and numerical solutions of self‐similar equations

In this study, a mixed convection flow over a nonlinearly stretching sheet of variable thickness is examined. Governing equations are modeled and transformed into dimensionless forms by utilizing dimensionless variables. For further investigation, dimensionless, coupled nonlinear differential equations with suitable boundary conditions are numerically solved using the Matlab built‐in function bvp5c tool, and analytical solutions are also computed using the homotopy analysis method. A comparative study is carried out to check the efficiency and accurateness of the proposed solution methodologies. Convergence of the derived series solutions is carefully checked. The impact of wall thickness parameter, velocity index parameter, Prandtl number, and mixed convection parameter on nondimensional velocity, temperature, skin friction coefficient, and local Nusselt number is examined. The novelty of this examination is that the dimensionless equations are self‐similar in the presence of mixed convection. These self‐similar equations are acquired by establishing a relationship between velocity and temperature power index parameters, and similarity solutions exist only for a particular form of variable surface temperature.     

Week Ahead Electricity Power and Price Forecasting Using Improved DenseNet-121 Method

In the Smart Grid (SG) residential environment, consumers change their power consumption routine according to the price and incentives announced by the utility, which causes the prices to deviate from the initial pattern. Thereby, electricity demand and price forecasting play a significant role and can help in terms of reliability and sustainability. Due to the massive amount of data, big data analytics for forecasting becomes a hot topic in the SG domain. In this paper, the changing and non-linearity of consumer consumption pattern complex data is taken as input. To minimize the computational cost and complexity of the data, the average of the feature engineering approaches includes: Recursive Feature Eliminator (RFE), Extreme Gradient Boosting (XGboost), Random Forest (RF), and are upgraded to extract the most relevant and significant features. To this end, we have proposed the DensetNet-121 network and Support Vector Machine (SVM) ensemble with Aquila Optimizer (AO) to ensure adaptability and handle the complexity of data in the classification. Further, the AO method helps to tune the parameters of DensNet (121 layers) and SVM, which achieves less training loss, computational time, minimized overfitting problems and more training/test accuracy. Performance evaluation metrics and statistical analysis validate the proposed model results are better than the benchmark schemes. Our proposed method has achieved a minimal value of the Mean Average Percentage Error (MAPE) rate i.e., 8% by DenseNet-AO and 6% by SVM-AO and the maximum accurateness rate of 92% and 95%, respectively.     

Intelligent Cloud Based Load Balancing System Empowered with Fuzzy Logic

Cloud computing is seeking attention as a new computing paradigm to handle operations more efficiently and cost-effectively. Cloud computing uses dynamic resource provisioning and de-provisioning in a virtualized environment. The load on the cloud data centers is growing day by day due to the rapid growth in cloud computing demand. Elasticity in cloud computing is one of the fundamental properties, and elastic load balancing automatically distributes incoming load to multiple virtual machines. This work is aimed to introduce efficient resource provisioning and de-provisioning for better load balancing. In this article, a model is proposed in which the fuzzy logic approach is used for load balancing to avoid underload and overload of resources. A Simulator in Matlab is used to test the effectiveness and correctness of the proposed model. The simulation results have shown that our proposed intelligent cloud-based load balancing system empowered with fuzzy logic is better than previously published approaches.     

Computing Topological Invariants of Triangular Chandelier Lattice

A numerical parameter mathematically derived from the graph structure is a topological index. The topological index is the first actual choice in QSAR research and these indices are used to build the correlation model between the chemical structures of various chemicals compounds. Here, we investigate some old degree-based topological indices like Randic index, sum connectivity index, ABC index, GA index, 1^st and 2^nd Zagreb indices, modified second Zagreb index, redefined version of 1^st, 2^nd and 3^rd Zagreb indices, hyper and augmented Zagreb indices, forgotten index and symmetric division degree index, and some new degree-based indices like SK index, SK₁ index, SK₂ index, and AG₁ index of triangular chandelier-lattice (TCL). The results are generalized by using edge partition and closed formulas for topological indices of triangular chandelier-lattice are analysed.     

Hemodialysis for treatment of levofloxacin‐induced neurotoxicity

Levofloxacin, a third‐generation fluoroquinolone antibiotic, is rarely associated with neurotoxicity. Patients with advanced kidney disease are particularly vulnerable to this adverse effect. We present two elderly patients with kidney failure who developed levofloxacin‐induced neurotoxicity, which was successfully treated with frequent hemodialysis, resulting in the full resolution of their symptoms. Neurotoxicity is a well‐known side effect of fluoroquinolone antibiotics. Postulated mechanisms include inhibition of the gamma‐aminobutyric acid A receptors and activation of the excitatory N‐methyl‐D‐aspartate receptors. Risk factors include older age, kidney disease, pre‐existing neurological disorders, and drug–drug interactions. While management of levofloxacin‐induced neurotoxicity includes discontinuation of the drug and supportive care, hemodialysis is not recommended, despite available pharmacokinetic data in support of its dialyzability. The successful use of hemodialysis for the treatment of levofloxacin‐induced neurotoxicity observed in our two patients with kidney failure should be further considered for rapid resolution of this rare fluoroquinolone‐related adverse effect in patients with impaired kidney function.     

Tracking in dense crowds using prominence and neighborhood motion concurrence

Methods designed for tracking in dense crowds typically employ prior knowledge to make this difficult problem tractable. In this paper, we show that it is possible to handle this problem, without any priors, by utilizing the visual and contextual information already available in such scenes.