Energy-efficient coverage with wireless sensors

Many sensor networks are deployed for the purpose of covering and monitoring a particular region, and detecting the object of interest in the region. In these applications, coverage is one of the centric problems in sensor networks. Such problem is centered around a basic question: ``How well can the sensors observe the physical world?\u27\u27 The concept of coverage can be interpreted as a measure of quality of service provided by the sensing function in various ways depending on sensor devices and applications. On the other hand, sensor nodes are usually battery-powered and subject to limitations based on the available battery energy. It is, therefore, critical to design, deploy and operate a wireless sensor network in an energy-efficient manner, while satisfying the coverage requirement. In order to prolong the lifetime of a sensor network, we explore the notion of connected-k-coverage in sensor networks. It requires the monitored region to be k-covered by a connected component of active sensors, which is less demanding than requiring k-coverage and connectivity among all active sensors simultaneously. We investigate the theoretical foundations about connected-k-coverage and, by using the percolation theorem, we derive the critical conditions for connected-k-coverage for various relations between sensors\u27 sensing radius and communication range. In addition, we derive an effective lower bound on the probability of connected-k-coverage, and propose a simple randomized scheduling algorithm and select proper operational parameters to prolong the lifetime of a large-scale sensor network. It has been shown that sensors\u27 collaboration (information fusion) can improve object detection performance and area coverage in sensor networks. The sensor coverage problem in this situation is regarded as information coverage. Based on a probabilistic sensing model, we study the object detection problem and develop a novel on-demand framework (decision fusion-based) for collaborative object detection in wireless sensor networks, where inactive sensors can be triggered by nearby active sensors to collaboratively sense and detect the object. By using this framework, we can significantly improve the coverage performance of the sensor networks, while the network power consumption can be reduced. Then, we proceed to study the barrier information coverage problem under the similar assumption that neighboring sensors may collaborate with each other to form a virtual sensor which makes the detection decision based on combined sensed readings. We propose both centralized and distributed schemes to operate a sensor network to information-cover a barrier efficiently. At last, we propose and study a multi-round sensor deployment strategy based on line-based sensor deployment model, which can use the fewest sensors to cover a barrier. We have an interesting discovery that the optimal two-round sensor deployment strategy yields the same barrier coverage performance as other optimal strategies with more than two rounds. This result is particularly encouraging as it implies that the best barrier coverage performance can be achieved with low extra deployment cost by deploying sensors in two rounds. In addition, two practical solutions are presented to deal with realistic situations when the distribution of a sensor\u27s residence point is not fully known

Barrier information coverage with wireless sensors

Abstract—Sensor networks have been deployed for many barrier coverage applications such as intrusion detection and border surveillance. In these applications, it is critical to operate a sensor network in an energy-efficient manner so the barrier can be covered with as few active sensors as possible. In this paper, we study barrier information coverage which exploits collaborations and information fusion between neighboring sensors to reduce the number of active sensors needed to cover a barrier and hence to prolong the network lifetime. Moreover, we propose a practical solution to identify the barrier information coverage set which can information-cover the barrier with a small number of active sensors. The effectiveness of the proposed solution is demonstrated by numerical and simulation results. I

Interfacing Nickel Nitride and Nickel Boosts Both Electrocatalytic Hydrogen Evolution and Oxidation Reactions

Electrocatalysts of the hydrogen evolution and oxidation reactions (HER and HOR) are of critical importance for the realization of future hydrogen economy. In order to make electrocatalysts economically competitive for large-scale applications, increasing attention has been devoted to developing noble metal-free HER and HOR electrocatalysts especially for alkaline electrolytes due to the promise of emerging hydroxide exchange membrane fuel cells. Herein, we report that interface engineering of Ni3N and Ni results in a unique Ni3N/Ni electrocatalyst which exhibits exceptional HER/HOR activities in aqueous electrolytes. A systematic electrochemical study was carried out to investigate the superior hydrogen electrochemistry catalyzed by Ni3N/Ni, including nearly zero overpotential of catalytic onset, robust long-term durability, unity Faradaic efficiency, and excellent CO tolerance. Density functional theory computations were performed to aid the understanding of the electrochemical results and suggested that the real active sites are located at the interface between Ni3N and Ni

Learn to Cluster Faces with Better Subgraphs

Face clustering can provide pseudo-labels to the massive unlabeled face data and improve the performance of different face recognition models. The existing clustering methods generally aggregate the features within subgraphs that are often implemented based on a uniform threshold or a learned cutoff position. This may reduce the recall of subgraphs and hence degrade the clustering performance. This work proposed an efficient neighborhood-aware subgraph adjustment method that can significantly reduce the noise and improve the recall of the subgraphs, and hence can drive the distant nodes to converge towards the same centers. More specifically, the proposed method consists of two components, i.e. face embeddings enhancement using the embeddings from neighbors, and enclosed subgraph construction of node pairs for structural information extraction. The embeddings are combined to predict the linkage probabilities for all node pairs to replace the cosine similarities to produce new subgraphs that can be further used for aggregation of GCNs or other clustering methods. The proposed method is validated through extensive experiments against a range of clustering solutions using three benchmark datasets and numerical results confirm that it outperforms the SOTA solutions in terms of generalization capability

Interfacing Nickel Nitride and Nickel Boosts Both Electrocatalytic Hydrogen Evolution and Oxidation Reactions

Electrocatalysts of the hydrogen evolution and oxidation reactions (HER and HOR) are of critical importance for the realization of future hydrogen economy. In order to make electrocatalysts economically competitive for large-scale applications, increasing attention has been devoted to developing noble metal-free HER and HOR electrocatalysts especially for alkaline electrolytes due to the promise of emerging hydroxide exchange membrane fuel cells. Herein, we report that interface engineering of Ni3N and Ni results in a unique Ni3N/Ni electrocatalyst which exhibits exceptional HER/HOR activities in aqueous electrolytes. A systematic electrochemical study was carried out to investigate the superior hydrogen electrochemistry catalyzed by Ni3N/Ni, including nearly zero overpotential of catalytic onset, robust long-term durability, unity Faradaic efficiency, and excellent CO tolerance. Density functional theory computations were performed to aid the understanding of the electrochemical results and suggested that the real active sites are located at the interface between Ni3N and Ni

Spontaneous rotational symmetry breaking in KTaO3_3 interface superconductors

Strongly correlated electrons could display intriguing spontaneous broken symmetries in the ground state. Understanding these symmetry breaking states is fundamental to elucidate the various exotic quantum phases in condensed matter physics. Here, we report an experimental observation of spontaneous rotational symmetry breaking of the superconductivity at the interface of YAlO$_3$/KTaO$_3$ (111) with a superconducting transition temperature of 1.86 K. Both the magnetoresistance and upper critical field in an in-plane field manifest striking twofold symmetric oscillations deep inside the superconducting state, whereas the anisotropy vanishes in the normal state, demonstrating that it is an intrinsic property of the superconducting phase. We attribute this behavior to the mixed-parity superconducting state, which is an admixture of $s$-wave and $p$-wave pairing components induced by strong spin-orbit coupling. Our work demonstrates an unconventional nature of the pairing interaction in the KTaO$_3$ interface superconductor, and provides a new platform to clarify a delicate interplay of electron correlation and spin-orbit coupling.Comment: 7 pages, 4 figure

Structure determination of DNA methylation lesions N1-meA and N3-meC in duplex DNA using a cross-linked protein–DNA system

N1-meA and N3-meC are cytotoxic DNA base methylation lesions that can accumulate in the genomes of various organisms in the presence of SN2 type methylating agents. We report here the structural characterization of these base lesions in duplex DNA using a cross-linked protein–DNA crystallization system. The crystal structure of N1-meA:T pair shows an unambiguous Hoogsteen base pair with a syn conformation adopted by N1-meA, which exhibits significant changes in the opening, roll and twist angles as compared to the normal A:T base pair. Unlike N1-meA, N3-meC does not establish any interaction with the opposite G, but remains partially intrahelical. Also, structurally characterized is the N6-meA base modification that forms a normal base pair with the opposite T in duplex DNA. Structural characterization of these base methylation modifications provides molecular level information on how they affect the overall structure of duplex DNA. In addition, the base pairs containing N1-meA or N3-meC do not share any specific characteristic properties except that both lesions create thermodynamically unstable regions in a duplex DNA, a property that may be explored by the repair proteins to locate these lesions