Paired t-test for detecting the difference between DMFDEM errors and other types of DEM errors. by Qinghua Li (398885)

Notations and definitions used in the algorithm. by Nazym Alimbekova (22766158)

Distance correlation values between groups of parameters corresponding to three adjacent counties, the spatial correlation model (SpC), and the parameters of the error model (ErrM)... by Cosmin Safta (11105442)

Assessment of multiple parameters for Cell2Spatial performance and assignment strategy. by Huamei Li (8815955)

Fast Signal Region Detection With Application to Whole Genome Association Studies by Wei Zhang (405)

Distance correlation values between model parameters corresponding to three adjacent counties, the spatial correlation model (SpC), and to the error model (ErrM). The light orange... by Cosmin Safta (11105442)

Simulation parameter [47,48]. by Nguyen Hong Nhu (22127327)

“…Specifically, we analyze the detection error probability (DEP) at Willie to quantify system covertness, in addition to outage probability (OP) and ergodic rate (ER) experienced by legitimate users, along with asymptotic analysis in the high signal-to-noise ratio (SNR) region. …”

List of key symbols. by Nguyen Hong Nhu (22127327)

“…Specifically, we analyze the detection error probability (DEP) at Willie to quantify system covertness, in addition to outage probability (OP) and ergodic rate (ER) experienced by legitimate users, along with asymptotic analysis in the high signal-to-noise ratio (SNR) region. …”

The system model of UAV-enabled RSMA network. by Nguyen Hong Nhu (22127327)

“…Specifically, we analyze the detection error probability (DEP) at Willie to quantify system covertness, in addition to outage probability (OP) and ergodic rate (ER) experienced by legitimate users, along with asymptotic analysis in the high signal-to-noise ratio (SNR) region. …”

Action potential detection with high temporal accuracy using a convolutional neural network (CNN). by Tjitse van der Molen (20391106)

Action potential detection with high temporal accuracy using a convolutional neural network (CNN). by Tjitse van der Molen (20391106)

Solid-State Nanopore Sensors: Analyte Quantification by Event Frequency Analysis at High Voltages by Julia Järlebark (14601273)

Subjects:

Optimized Bayesian regularization-back propagation neural network using data-driven intrusion detection system in Internet of Things by Ashok Kumar K (21441108)

“…In general, BRBPNN does not show any optimization adaption methods to determine the optimal parameter for appropriate detection. Hence, Binary Black Widow Optimization Algorithm (BBWOA) is proposed in this manuscript to improve the BRBPNN classifier that detects intrusion precisely. …”

Qualitative Examples of Corrected Sentences. by Yutong Liu (4027994)

“…This study proposes an enhanced model based on Bidirectional Encoder Representations from Transformers (BERT), combined with a dependency self-attention mechanism, to automatically detect and correct textual errors in the translation process. …”

Ablation Experiment Results. by Yutong Liu (4027994)

“…This study proposes an enhanced model based on Bidirectional Encoder Representations from Transformers (BERT), combined with a dependency self-attention mechanism, to automatically detect and correct textual errors in the translation process. …”

Meaning of Each Model. by Yutong Liu (4027994)

“…This study proposes an enhanced model based on Bidirectional Encoder Representations from Transformers (BERT), combined with a dependency self-attention mechanism, to automatically detect and correct textual errors in the translation process. …”

Overview of Related Work. by Yutong Liu (4027994)

“…This study proposes an enhanced model based on Bidirectional Encoder Representations from Transformers (BERT), combined with a dependency self-attention mechanism, to automatically detect and correct textual errors in the translation process. …”

Parameter Settings. by Yutong Liu (4027994)

“…This study proposes an enhanced model based on Bidirectional Encoder Representations from Transformers (BERT), combined with a dependency self-attention mechanism, to automatically detect and correct textual errors in the translation process. …”

Comparison with Advanced Models. by Yutong Liu (4027994)

“…This study proposes an enhanced model based on Bidirectional Encoder Representations from Transformers (BERT), combined with a dependency self-attention mechanism, to automatically detect and correct textual errors in the translation process. …”

Overall Model Architecture. by Yutong Liu (4027994)

“…This study proposes an enhanced model based on Bidirectional Encoder Representations from Transformers (BERT), combined with a dependency self-attention mechanism, to automatically detect and correct textual errors in the translation process. …”