In recent years, cognitive radio (CR) has been introduced as a new paradigm for enabling much higher spectrum utilization by dynamically accessing and sharing the spectrum with incumbent radio devices. This paper proposes an innovative and practical spectrum-sharing approach and evaluates its performance. The goal is to minimize CR's harmful interference to incumbent primary users and to maximize the utility of spectrum-sharing networks by exploiting the proposed radio environment map (REM). REM-enabled CR adaptation algorithms are developed for various operational environments, namely, the open area and the dense urban area. This paper also compares the performance gain when using the Global REM and the Local REM, respectively. The impact of imperfect REM information due to node mobility and REM dissemination delay is simulated. By exploiting the REM information, CR can make situation-aware adaptations in transmit power, transmit timing, routing protocol, and topology, thereby reducing interference to primary users. More importantly, the painful hidden node or hidden receiver problem can be mitigated with the help of the Global REM. REM-enabled CR could be a cost-efficient and reliable approach to "waterfilling" underutilized spectrum in both space and time domains.
The potential for wide-spread use of wireless sensor networks (WSN) in military monitoring, homeland security, and other areas continues to expand. There are, however, security concerns that must be addressed before this potential is realized. One threat to WSNs is the denial-ofsleep attack, a particular type of denial-of-service attack that rapidly drains sensor node batteries by keeping radios active when they should be sleeping to conserve energy. Simple denial-of-sleep attacks involving unauthenticated or replayed packets are difficult to distinguish from bursty data and can force network devices to incorrectly remain in receive mode. This research introduces Clustered Adaptive Rate Limiting, or CARL, a rate limiting approach based on current host-based intrusion detection techniques that is designed to defeat denial-of-sleep attacks. We use simulation to examine tradeoffs and to demonstrate the potential benefits of the CARL mechanism. Providing support for adaptive rate-limiting at the MAC layer, especially in networks that might encounter bursty data, is essential if WSN are to achieve their full potential for mission-critical applications.
The impact of fingers on numerical cognition has received a great deal of attention recently. One sub-set of these studies focus on the relation between finger gnosis (also called finger sense or finger gnosia), the ability to identify and individuate fingers, and mathematical development. Studies in this subdomain have reported mixed findings so far. While some studies reported that finger gnosis correlates with or predicts mathematics abilities in younger children, others failed to replicate these results. The current study explores the relationship between finger gnosis and two arithmetic operations—addition and subtraction. Twenty-four second to third graders participated in this fMRI study. Finger sense scores were negatively correlated with brain activation measured during both addition and subtraction. Three clusters, in the left fusiform, and left and right precuneus were found to negatively correlate with finger gnosis both during addition and subtraction. Activation in a cluster in the left inferior parietal lobule (IPL) was found to negatively correlate with finger gnosis only for addition, even though this cluster was active both during addition and subtraction. These results suggest that the arithmetic fact retrieval may be linked to finger gnosis at the neural level, both for addition and subtraction, even when behavioral correlations are not observed. However, the nature of this link may be different for addition compared to subtraction, given that left IPL activation correlated with finger gnosis only for addition. Together the results reported appear to support the hypothesis that fingers provide a scaffold for arithmetic competency for both arithmetic operations.
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