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Bilevel Feature Extraction-Based Text Mining for Fault Diagnosis of Rail...

An Optimization Framework for Mobile Data Collection in Energy-Harvestin...

bh1750 digital light intensity sensor

bh1750 digital light intensity sensor working code #include <Wire.h> #include <BH1750.h> BH1750 lightMeter; void setup(){   Serial.begin(9600);   lightMeter.begin();   Serial.println("Running..."); } void loop() {   uint16_t lux = lightMeter.readLightLevel();   Serial.print("Light: ");   Serial.print(lux);   Serial.println(" lx");   delay(1000); }

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An Adaptive Subcarrier Sharing Scheme for OFDM-Based Cooperative Cognitive Radios

An Adaptive Subcarrier Sharing Scheme for OFDM-Based Cooperative Cognitive Radios ABSTRACT: •                   Incorporation of orthogonal frequency division multiplexing (OFDM) in cooperative cognitive radio network facilitates subcarrier sharing to achieve spatial diversity with opportunistic spectrum access. •       In addition, adaptive modulation has been adopted widely in wireless communication to improve spectral efficiency. Use of adaptive modulation for cooperative cognitive relaying transmission to maximize throughput under bit error rate (BER) constraint is an open issue. •       In this paper, we propose an adaptive subcarrier sharing scheme for OFDM-based cooperative cognitive radio system, wherein cognitive (secondary) system helps the primary system to achieve its target rate of communication in exchange for opportunistic spectrum...

Cooperative Spectrum Sensing with Data Mining of Multiple Users’ Historical Sensing Data

Cooperative Spectrum Sensing with Data Mining of Multiple Users’ Historical Sensing Data ABSTRACT: •                            The current cooperative spectrum sensing still can not effectively exploit the temporal correlations among sensing data, especially the correlations between the current sensing data and the historical data. •       This paper uses sticky hierarchical Dirichlet process-hidden Markov model to exploit the historical sensing data of multiple users, and classifies the historical sensing data into groups according to their latent spectrum states. •        The proposed spectrum sensing algorithm can fuse the historical sensing data into prior knowledge, which can be used to improve the accuracy in spectrum decision. •        Furthermore, a rejection...