Differential Game for Distributed Power Control in Device-to-Device Communications Underlaying Cellular Networks

Wireless Personal Communications - In the formulating of power control for wireless networks, the radio channel is commonly formulated using static models of optimization or game theory. In these...     

Method to Stop Geopolymer Reaction

The objective of this study was to develop a method to stop geopolymer reaction at early ages so that the molecular structure can be determined and its link to setting behavior probed. Solvent extraction, using a mixture of alcohol and acetone to remove water, was seen to suspend reaction up to at least 53 h, allowing enough time for nuclear magnetic resonance (NMR) tests to determine structure. However, this method caused precipitation of soluble species present at early ages, confounding interpretation of the spectra and thus making it suitable only for mature geopolymers. A combination of water treatment to extract soluble species and solvent treatment to extract water was seen to stop the geopolymer reaction long enough (> 1 week) for NMR tests in specimens with and without calcium.     

Pistacia lentiscus extract as a green inhibitor for copper corrosion in 0.5 M of H2SO4: electrochemical characterization and theoretical investigations

Journal of Applied Electrochemistry - The current work aims to study the effect of Pistacia lentiscus (Pil) essential oil originating from Chefchaouen city, which is located in northeastern Morocco...     

On the coexistence of a primary user with an energy harvesting secondary user: a case of cognitive cooperation

In this paper, we consider a cognitive scenario where an energy harvesting secondary user shares the spectrum with a primary user. The secondary source helps the primary source in delivering its undelivered packets during periods of silence of the primary source. The primary source has a queue for storing its data packets, whereas the secondary source has two data queues: a queue for storing its own packets and the other for storing the fraction of the undelivered primary packets accepted for relaying. The secondary source is assumed to be a battery‐based node, which harvests energy packets from the environment. In addition to its data queues, the secondary user has an energy queue to store the harvested energy packets. The secondary energy packets are used for primary packets decoding and data packets transmission. More specifically, if the secondary energy queue is empty, the secondary source can neither help the primary source nor transmit a packet from the data queues. The energy queue is modeled as a discrete‐time queue with Markov arrival and service processes. Because of the interaction of the queues, we provide inner and outer bounds on the stability region of the proposed system. We investigate the impact of the energy arrival rate on the stability region. Numerical results show the significant gain of cooperation.Copyright © 2014 John Wiley & Sons, Ltd.     

An iterative learning approach for network contraction: Path finding problem in stochastic time‐varying networks

Path finding problem has a broad application in different fields of engineering. Travel time uncertainty is a critical factor affecting this problem and the route choice of transportation users. The major downside of the existing algorithms for the reliable path finding problem is their inefficiency in computational time. This study aims to develop a network contraction approach to reduce the network size of each specific origin and destination (OD) pair in stochastic time‐dependent networks. The network contraction is based on the comparison of optimistic and pessimistic solutions resulting from minimum and maximum travel time realizations of a Monte‐Carlo simulation (MCS)‐based approach. In this respect, the researchers propose a learning approach to utilize the information of the realizations in the initial iterations of the MCS approach. Implementation of this approach is in place for several OD pairs of two real‐world large‐scale applications. First, it is calibrated for the Chicago downtown network; the performance and accuracy of the proposed approach are investigated by comparing the results against that of the approach without any network contraction. In addition, the Salt Lake City network illustrates the transferability of the approach to other networks. The results demonstrate significant computational improvements, with an acceptable accuracy level relative to the approach without network contraction.     

On the hierarchy of distribution-sensitive properties for data structures

In this paper new dependencies are added to the hierarchy of the distribution-sensitive properties for data structures. Most remarkably, we prove that the working-set property is equivalent to the unified-bound property; a fact that had gone unnoticed since the introduction of such bounds in the Eighties by Sleator and Tarjan.     

Wave Passage and Ground Motion Incoherency Effects on Seismic Response of an Extended Bridge

This paper investigates the implications of ground motion spatial variability on the seismic response of an extended highway bridge. An existing 59-span, 2,164-meter bridge with several bearing types and irregularity features was selected as a reference structure. The bridge is located in the New Madrid Seismic Zone and supported on thick layers of soil deposits. Site-specific bedrock input ground motions were selected based on a refined probabilistic seismic hazard analysis of the bridge site. Wave passage and ground motion incoherency effects were accounted for after propagating the bedrock records to the ground surface. The results obtained from inelastic response-history analyses confirm the significant impact of wave passage and ground motion incoherency on the seismic behavior of the bridge. The amplification in seismic demands exceeds 150%, whereas the maximum suppression of these demands is less than 50%. The irregular and unpredictable changes in structural response owing to asynchronous earthquake records necessitate in-depth seismic assessment of major highway bridges with advanced modeling techniques to realistically capture their complex seismic response.     

Cooperative Q‐learning techniques for distributed online power allocation in femtocell networks

In this paper, we address the problem of distributed interference management of femtocells that share the same frequency band with macrocells using distributed multi‐agent Q‐learning. We formulate and solve two problems representing two different Q‐learning algorithms, namely, femto‐based distributed and sub‐carrier‐based distributed power controls using Q‐learning (FBDPC‐Q and SBDPC‐Q). FBDPC‐Q is a multi‐agent algorithm that works on a global basis, for example, deals with the aggregate macrocell and femtocell capacities. Its complexity increases exponentially with the number of sub‐carriers in the system. Also, it does not take into consideration the sub‐carrier macrocell capacity as a constraint. To overcome these problems, SBDPC‐Q is proposed, which is a multi‐agent algorithm that works on a sub‐carrier basis, for example, sub‐carrier macrocell and femtocell capacities. Each of FBDPC‐Q and SBDPC‐Q works in three different learning paradigms: independent (IL), cooperative (CL), and weighted cooperative (WCL). IL is considered the simplest form for applying Q‐learning in multi‐agent scenarios, where all the femtocells learn independently. CL and WCL are the proposed schemes in which femtocells share partial information during the learning process in order to strike a balance between practical relevance and performance. We prove the convergence of the CL paradigm when used in the FBDPC‐Q algorithm. We show via simulations that the CL paradigm outperforms the IL paradigm in terms of the aggregate femtocell capacity, especially in networks with large number of femtocells and large number of power levels. In addition, we propose WCL to address the CL limitations. Finally, we evaluate the robustness and scalability of both FBDPC‐Q and SBDPC‐Q, against several typical dynamics of plausible wireless scenarios (fading, path loss, random activity of femtocells, etc.). We show that the CL paradigm is the most scalable to large number of femtocells and robust to the network dynamics compared with the IL and WCL paradigms. Copyright © 2014 John Wiley & Sons, Ltd.