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The atomic structures and the electronic states of active and inactive dopant sites in semiconductor are elucidated successfully by using X-ray absorption near-edge structure (XANES), Auger electro...

Defects in solids are typically recognized as unfavorable, leading to degradation of the structure and properties of the material. However, defects occasionally provide extraordinary benefits as the active sites of catalysts and chemical reactions, and can result in the creation of new electronic states. In particular, a low-dimensional material can become a defect-rich material due to the unique ratio of surface area to volume, giving many dangling bonds. Herein, we report the rapid (20 min) synthesis of MoS2 quantum dots (QDs) with a diameter of 4 nm at room temperature using nanosecond pulsed laser ablation in a binary solvent. The MoS2 QDs are crystalline particles composed of 3–5 layers and contain sulfur vacancies at an atomic concentration of 1% acting as a functional defect. The MoS2 QDs exhibit excellent electrocatalytic performance (Tafel slope = 49 mV dec−1) for the hydrogen evolution reaction and high quantum yield blue photoluminescence with a large Stokes shift.

This paper verifies the method of multi-sensor data fusion in the field of smart home. A multi-source sensor data fusion model based on fire detection is proposed, and the methods of fusion calculation and decision analysis are mainly studied. Nowadays, the traditional single sensor is replaced by a multi-source sensor especially in fire detection (Wang in Comp Intell Syst 1(1–4):1–22 [1]), and three main detector (CO, smoke, and temperature) are significantly changed when the fire occurs, and the data fusion algorithm is used to calculate the result, thereby improving the system accuracy and reducing the false alarm rate by using the self-learning and self-adaptive ability of BP neural network on the feature layer. Then, the result is transmitted into the decision-making layer, and the fuzzy logic inference algorithm is used to make the final decision and judgment. Simulation experiments show that the fusion system can meet the data collection, processing, fusion, and analysis of fire detection scenarios in smart home security, can effectively identify the accurate fire situation, and can respond quickly.

Defects in solids are typically recognized as unfavorable, leading to degradation of the structure and properties of the material. However, defects occasionally provide extraordinary benefits as the active sites of catalysts and chemical reactions, and can result in the creation of new electronic states. In particular, a low-dimensional material can become a defect-rich material due to the unique ratio of surface area to volume, giving many dangling bonds. Herein, we report the rapid (20 min) synthesis of MoS

This paper investigates minimum mean square error (MMSE) with asynchronous interference mitigation in cooperative base station systems. We consider the asynchronous transmission because of the different propagation times between the base station (BS) and mobile stations (BSs). Meanwhile, the channel quantization errors duo to channel quantization is taken into account in our analysis. The proposed scheme is robust to asynchronous interference and channel quantization errors in BSs cooperation systems. Simulations results show that proposed MMSE scheme achieve an improved performance compared with the conventional MMSE in BSs cooperative systems.

Cooperation spectrum sensing as a key technology of effectively mitigating the effects of multipath fading and shadowing on the performance of cognitive system, is widely studied in recent years. However, little research on the joint optimization scheme considering p-th power detector and optimal fusion rule has been found. In this paper, the method have been proposed in which joint optimize p-th power of p-th power detector, optimal sensing threshold and minimal determining number of users c to minimize the total error probability of detecting the presence or absence of primary users. Simulation results show that cooperative sensing system has the best p-th power and perception threshold , and the optimal fusion rule to make the total error probability minimal can be found.

Cognitive radio is a promising technology. The spectrum scarcity problem can be overcome by enabling unlicensed users to access the licensed spectrum bands. In this paper, we focus on power efficiency maximization of cognitive system by jointly considering the parameters of spectrum sensing time and transmit power. In addition, we propose to investigate power efficiency of cognitive relay transmission scheme based on that of non-relay transmission. Finally, we provide the simulation results to show that the throughput and power efficiency of the proposed approach can be significantly improved compared to that of the non-relay transmission scheme in cognitive radio networks. Furthermore, numerical results demonstrate that there exist the optimal parameters to maximize power efficiency.

A relay selection algorithm is proposed to improve the system performance based on statistical channel state information(CSI) in amplify-and-forward(AF) cooperative networks. An exact and upper bound ergodic capacity formulation were derived for AF relay selection network. Theoretical analysis and simulation results validate the Tightness and feasibility of upper bound ergodic capacity.

An approximate outage probability formulation were derived for decode-and-forward (DF) cooperative relay networks on the premise of guarantee primary user quality of service (QoS) and limit of maximal power in cognitive user. The full space diversity is achieved on optimal relay selection strategy. By Monte Carlo simulation, the rationality of the approximate outage probability formulation is validated. Theoretical analysis and simulation results show that, in cognitive system, number of relay are sources of diversity gain.

Scarcity of the spectrum is becoming a major issue based on traditional frequency planning scheme, cognitive radio (CR) has been proposed for better spectrum utilization efficiency by intelligently sensing and opportunistic access. In this paper, a novel method is proposed to determine signal to noise ratio threshold (SNRT) based on transmission power and complexity of cognitive detector under lognormal shadowing conditions. Since there is tradeoff between detection probability and false alarm probability, we can maximize spectrum utilization efficiency with pre-determined detection performance,meanwhile SNRT is adjusted to void unacceptable interference to primary receiver (PR) and minimize complexity of cognitive detector according to transmission power. Numerical results will show that cognitive radio can adjust SNRT adaptively in order to guarantee the PR decoding signal from primary transmitter (PT) without unacceptable interference.