Protocol misbehavior detection framework using machine learning classification in vehicular Ad Hoc networks

Wireless Networks - A novel approach is proposed to detect protocol misbehavior using state-of-the-art machine learning frameworks and entropy. Nodes in Vehicular Ad Hoc Networks (VANETs) use...     

Unknown input observer design and analysis for networked control systems

The insertion of communication networks in the feedback loops of control systems is a defining feature of modern control systems. These systems are often subject to unknown inputs in a form of disturbances, perturbations, or attacks. The objective of this paper is to design and analyse an observer for networked dynamical systems with unknown inputs. The network effect can be viewed as either a perturbation or time-delay to the exchanged signals. In this paper, we (1) review an unknown input observer (UIO) design for a non-networked system, (2) derive the networked unknown input observer (N_etUIO) dynamics, (3) design a N_etUIO such that the effect of higher delay order terms are nullified and (4) establish stability-guaranteeing bounds on the networked-induced time-delay and perturbation. The formulation and results derived in this paper can be generalised to scenarios and applications where the signals are perturbed due to a different source of perturbation or delay.     

GIS and Multi-Criteria Evaluation: Robust Tools for Integrated Water Resources Management

Abstract

Integrated water resources planning and management are considered very complex issues. These issues are usually addressed through the multi-sectoral, interdisciplinary and hierarchal decomposition approaches. In general, integrated resource management indicates the consideration of water, social, socio-economic, economic and environmental issues. The current study aims at merging the GIS and Multi-Criteria Evaluation (MCE) techniques for the integrated water resource management of a cropped area. An area of about 120,000 Hectares located in the Northern Nile River Delta area with a coastal zone on the Mediterranean was selected and GIS was applied to represent the area's different environment, social, economic, and water factors. Different randomization cropping pattern distribution scenarios were proposed. Through the merging of GIS and MCE approaches, three scenarios were run and evaluated at three different levels: farm, canal catchment area and whole area. This merging resulted in a very powerful tool for the evaluation of different plans. The merging of GIS and MCE really facilitated the decision making process for these types of integrated water management problems.     

Novel transmit antenna selection strategy for massive MIMO downlink channel

In this paper, we deal with the problem of acquiring the channel state information (CSI) at the transmitter in large-scale multiple input multiple output (MIMO) systems, so-called massive MIMO systems. Clearly, obtaining CSI plays a central role to provide high system performance. Even though, in frequency-division duplexed systems, acquiring this information requires a prohibitive amount of feedback, since it increases with the number of transmit antenna. In this work, we design an efficient transmit antenna selection strategy aware of the amount of required CSI for a point-to-multipoint transmission in massive MIMO systems. The proposed strategy provides high sum-rate with limited CSI feedback and limited computational complexity. Innovatively, the antenna selection in our strategy is performed in a decentralized fashion successively at the receiving users. Two schemes are proposed in this work to perform the antenna selection at each user. Next, taking into consideration that the large-scale MIMO transmitter suffers from imperfect knowledge of CSI, we design a new performance criterion. Computer simulations validate that, when the CSI is perfectly known, the proposed strategy is able to achieve high performance in terms of system sum-rate while a significant reduction in both CSI feedback overhead and computational complexity is observed. Moreover, assuming imperfect CSI, the new proposed criterion achieves higher performance when the estimation accuracy is low and at high SNR regime.     

High Salinity Relaying to Reduce Vibrio parahaemolyticus and Vibrio vulnificus in Chesapeake Bay Oysters (Crassostrea virginica)

Cases of Vibrio infections in the United States have tripled from 1996 to 2009 and these infections are most often associated with the consumption of seafood, particularly oysters (Crassostrea virginica). Information is needed on how to reduce numbers of Vibrio parahaemolyticus and Vibrio vulnificus in bi‐valve molluscan shellfish (for example, oysters). The purpose of this study was to evaluate the effectiveness of high salinity relaying or treatment in recirculating aquaculture systems (RASs) as methods to reduce the abundance of V. parahaemolyticus and V. vulnificus in oysters. For relaying field trials, oysters were collected from approved harvest waters, temperature abused outside under a tarp for 4 h, and then transferred to high (29 to 33 ppt.) and moderate (12 to 19 ppt.) salinities. For RAS treatment trial, oysters were transferred to 32 to 34 ppt. salinity at 15 °C. After 7, 14, 21, and in some instances 28 d, oysters were collected and analyzed for V. parahaemolyticus and V. vulnificus levels using multiplex real‐time PCR. Initial levels of V. parahaemolyticus and V. vulnificus ranged from 3.70 to 5.64 log₁₀ MPN/g, and were reduced by 2 to 5 logs after 21 to 28 d in high salinity water (29 to 34 ppt.). Oyster mortalities averaged 4% or less, and did not exceed 7%. Relaying of oysters to high salinity field sites or transfer to high salinity RAS tanks was more effective in reducing V. vulnificus compared with V. parahaemolyticus. These results suggest that high salinity relaying of oysters is more effective in reducing V. vulnificus than V. parahaemolyticus in the oyster species used in this study.     

Measurement and Explanation of DC/RF Power Loci of an Active Patch Antenna

A case study of an active transmitting patch antenna revealed a characteristic loop locus of DC power versus RF output power as drive frequency was varied, with an operational bandwidth substantially smaller than the impedance bandwidth of the radiator. An approximate simulation technique, based on separation of the output capacitance of the power transistor, yielded easily visualized plots of power dependence on internal load impedance, and a simple interpretation of the experimental results in terms of a near‐resonance condition between the output capacitance and output packaging inductance.     

Power control and clustering in heterogeneous cellular networks

Recently, it is widely believed that significant coverage and performance improvement can be achieved through the deployment of small cells in conjunction with the well-established macro cells. However, it is expected that the high density of base stations in such heterogeneous cellular networks will give rise to multiple design problems related to both co-tier (small-to-small) and cross-tier (between small and macro cells) interference. Fortunately, cooperation between base stations will play a major role to cope with these problems and hence to enhance the users’ data rates. In this paper, we consider a two-tier cellular network comprised of a macro cell underlaid with multiple small cells where both co-tier and cross-tier interference are taken into account. We study the scenario where the small cell base stations seek to maximize a common objective by forming multiple clusters through cooperation. These base stations have also to allocate power to their associated users and, at the same time, control the total aggregate interference caused to the macro cell user which has to be kept below a threshold prefixed by the macro cell base station. We consider two utility functions: the overall sum rate of the small cell network and the minimum data rate of the small cell users. We formulate the studied problems as mixed integer nonlinear optimization problems and we discuss their NP hardness. Therefore, due to the complexity of finding the optimal solution, we design heuristic algorithms which resolves efficiently the tradeoff between computational complexity and performance. We show through simulations that the designed heuristics approach the optimal solution (obtained using the complex exhaustive search algorithm) with highly reduced computational complexity.