Application of Grey Wolf Optimizer Algorithm for Optimal Power Flow of Two-Terminal HVDC Transmission System

This paper applies a relatively new optimization method, the Grey Wolf Optimizer (GWO) algorithm for Optimal Power Flow (OPF) of twoterminal High Voltage Direct Current (HVDC) electrical power system. The OPF problem of pure AC power systems considers the minimization of total costs under equality and inequality constraints. Hence, the OPF problem of integrated AC-DC power systems is extended to incorporate HVDC links, while taking into consideration the power transfer control characteristics using a GWO algorithm. This algorithm is inspired by the hunting behavior and social leadership of grey wolves in nature. The proposed algorithm is applied to two different case-studies: the modified 5-bus and WSCC 9-bus test systems. The validity of the proposed algorithm is demonstrated by comparing the obtained results with those reported in literature using other optimization techniques. Analysis of the obtained results show that the proposed GWO algorithm is able to achieve shorter CPU time, as well as minimized total cost when compared with already existing optimization techniques. This conclusion proves the efficiency of the GWO algorithm

Inflation Dynamics: The Case of Egypt

Inflation as a phenomenon has witnessed remarkable changes starting from mid-eighties of the last century. Inflation rates have become less persistent, less responsive to supply side shocks. In addition, the relative importance of demand pull inflation as one of the major determinants of inflation has decreased due to efficient monetary policies that have been adopted by central banks all over the world to reduce inflation based on anchoring inflation expectations. Moreover, the slope of Phillips curve has flattened as many factors have appeared to be more influential on inflation rather than output gap, namely inflation expectations. These changes constitute in the new economic literature what so called “Inflation Dynamics”. In this context, this study focuses on analyzing inflation dynamics in Egypt in (1980-2009) in order to identify to what extent “Inflation Dynamics” in Egypt is different from or similar to those witnessed globally. The study applied a Vector Auto Regressive model (VAR) and other econometrics models to analyze “Inflation Dynamics” in Egypt in three sub periods: the 1980s, the 1990s and the first decade of the new millennium. The study concluded that Inflation Dynamics in Egypt is completely different from those observed globally. Inflation rates in Egypt have become more persistent especially starting from 2000; Inflation shocks are now lasting longer and have a long-term impact on the future inflation paths. On the other hand, demand bull inflation still considers one of the most important inflation determinants, as it is solely responsible for explaining 30% of the changes in inflation rates. In addition, the study confirmed that inflation rates in Egypt have become more responsive to supply side shocks starting from 2006. As for the slope of Phillips curve, the study confirmed that similar to the changes observed globally, the slope of Phillips Curve for the Egypt economy has flattened reflecting the increasing importance of other inflation determinants rather than output gap.Inflation, Inflation dynamics, Inflation persistence, The Egyptian economy, Demand-pull inflation, Cost-push inflation, Inflation expectations, markets and prices rigidities, Phillips curve, Government debt, Monetary policies, Vector Auto Regression (VAR)

Self-Interference Cancellation Using Time-Domain Phase Noise Estimation in OFDM Full-Duplex Systems

In full-duplex systems, oscillator phase noise (PN) problem is considered the bottleneck challenge that may face the self-interference cancellation (SIC) stage especially when orthogonal frequency division multiplexing (OFDM) transmission scheme is deployed. Phase noise degrades the SIC performance significantly, if not mitigated before or during the SIC technique. The presence of the oscillator phase noise has different impacts on the transmitted data symbol like common phase error (CPE) and inter-carrier interference (ICI). However, phase noise can be estimated and mitigated digitally in either time or frequency domain. Through this work, we propose a novel and simple time domain self-interference (SI) phase noise estimation and mitigation technique. The proposed algorithm is inspired from Wiener filtering in time domain. Simulation results show that the proposed algorithm has a superior performance than the already-existing time-domain or frequency domain PN mitigation solutions with a noticeable reduction in the computational complexity

Evolutionary Centrality and Maximal Cliques in Mobile Social Networks

This paper introduces an evolutionary approach to enhance the process of finding central nodes in mobile networks. This can provide essential information and important applications in mobile and social networks. This evolutionary approach considers the dynamics of the network and takes into consideration the central nodes from previous time slots. We also study the applicability of maximal cliques algorithms in mobile social networks and how it can be used to find the central nodes based on the discovered maximal cliques. The experimental results are promising and show a significant enhancement in finding the central nodes

Sphingosine kinase 1 in breast cancer: A new molecular marker and a therapy target

It is now well-established that sphingosine kinase 1 (SK1) plays a significant role in breast cancer development, progression, and spread, whereas SK1 knockdown can reverse these processes. In breast cancer cells and tumors, SK1 was shown to interact with various pathways involved in cell survival and chemoresistance, such as nuclear factor-kappa B (NFκB), Notch, Ras/MAPK, PKC, and PI3K. SK1 is upregulated by estrogen signaling, which, in turn, confers cancer cells with resistance to tamoxifen. Sphingosine-1-phosphate (S1P) produced by SK1 has been linked to tumor invasion and metastasis. Both SK1 and S1P are closely linked to inflammation and adipokine signaling in breast cancer. In human tumors, high SK1 expression has been linked with poorer survival and prognosis. SK1 is upregulated in triple negative tumors and basal-like subtypes. It is often associated with high phosphorylation levels of ERK1/2, SFK, LYN, AKT, and NFκB. Higher tumor SK1 mRNA levels were correlated with poor response to chemotherapy. This review summarizes the up-to-date evidence and discusses the therapeutic potential for the SK1 inhibition in breast cancer, with emphasis on the mechanisms of chemoresistance and combination with other therapies such as gefitinib or docetaxel. We have outlined four key areas for future development, including tumor microenvironment, combination therapies, and nanomedicine. We conclude that SK1 may have a potential as a target for precision medicine, its high expression being a negative prognostic marker in ER-negative breast cancer, as well as a target for chemosensitization therapy

Map++: A Crowd-sensing System for Automatic Map Semantics Identification

Digital maps have become a part of our daily life with a number of commercial and free map services. These services have still a huge potential for enhancement with rich semantic information to support a large class of mapping applications. In this paper, we present Map++, a system that leverages standard cell-phone sensors in a crowdsensing approach to automatically enrich digital maps with different road semantics like tunnels, bumps, bridges, footbridges, crosswalks, road capacity, among others. Our analysis shows that cell-phones sensors with humans in vehicles or walking get affected by the different road features, which can be mined to extend the features of both free and commercial mapping services. We present the design and implementation of Map++ and evaluate it in a large city. Our evaluation shows that we can detect the different semantics accurately with at most 3% false positive rate and 6% false negative rate for both vehicle and pedestrian-based features. Moreover, we show that Map++ has a small energy footprint on the cell-phones, highlighting its promise as a ubiquitous digital maps enriching service.Comment: Published in the Eleventh Annual IEEE International Conference on Sensing, Communication, and Networking (IEEE SECON 2014