SURGE - Spatial User Recommendations using Geographical metrics and sEmantics حسب Ramon Hermoso (20135370)

"…The query and every element in the set of data consists of physical coordinates and a set of keywords. …"

Video 1_TDE-3: an improved prior for optical flow computation in spiking neural networks.mp4 حسب Matthew Yedutenko (5142461)

"…Proposed in the literature bioinspired neuromorphic Time-Difference Encoder (TDE-2) combines event-based sensors and processors with spiking neural networks to provide real-time and energy-efficient motion detection through extracting temporal correlations between two points in space. However, on the algorithmic level, this design leads to a loss of direction-selectivity of individual TDEs in textured environments. …"

Data Sheet 1_TDE-3: an improved prior for optical flow computation in spiking neural networks.pdf حسب Matthew Yedutenko (5142461)

"…Proposed in the literature bioinspired neuromorphic Time-Difference Encoder (TDE-2) combines event-based sensors and processors with spiking neural networks to provide real-time and energy-efficient motion detection through extracting temporal correlations between two points in space. However, on the algorithmic level, this design leads to a loss of direction-selectivity of individual TDEs in textured environments. …"

supporting data for PHD thesis entitled " Arousal Regulation and Neurofeedback Treatment for ADHD Children" حسب Yuliang Wang (9151616)

"…Analyses use standardized mean differences (Hedges g) under random-effects models, stratified by comparator type (medicine, active, sham, passive) and, where applicable, contrasted across protocol families (customised algorithm, SCP, SMR, TBR).</p><p dir="ltr">The supporting dataset contains the <b>raw arm-level descriptive statistics</b> required to compute effect sizes: per study, outcome, and timepoint it lists group means, standard deviations, and sample sizes for neurofeedback and control arms, along with rater, comparator category, protocol type, and outcome direction coding (so higher values consistently reflect the intended construct). …"

Data_Sheet_1_Curriculum guide for teaching house officers and faculty: applying procedure codes effectively using chemical denervation as a model.PDF حسب Maryam Berri (17330017)

"…The methodology of the algorithmic approach proved to be innovative for avoiding billing write-offs and loopbacks that were beneficial for the training process. …"

Data_Sheet_2_Curriculum guide for teaching house officers and faculty: applying procedure codes effectively using chemical denervation as a model.PDF حسب Maryam Berri (17330017)

"…The methodology of the algorithmic approach proved to be innovative for avoiding billing write-offs and loopbacks that were beneficial for the training process. …"

Supporting files for thesis "Deep-learning-based Morphological Modelling: Case Study in Soft Robot Control, Shape Sensing and Deformation" حسب Yingqi Li (9151304)

"…Considering 2D images are more accessible and common compared to 3D topology data, this thesis also investigates soft tissue modelling via medical images. …"

Echo Peak حسب Rocco De Marco (14146593)

"…</p><p dir="ltr">For classification, the algorithm iteratively processes the audio in overlapping time windows. …"

Table 1_Genome-wide identification and expression analysis of phytochrome gene family in Aikang58 wheat (Triticum aestivum L.).xlsx حسب Zhu Yang (756364)

"…Additionally, the least absolute shrinkage and selection operator (LASSO) regression algorithm in machine learning was used to screen transcription factors such as bHLH, WRKY, and MYB that influenced the expression of TaAkPHY genes. …"

Table 12_Genome-wide identification and expression analysis of phytochrome gene family in Aikang58 wheat (Triticum aestivum L.).xlsx حسب Zhu Yang (756364)

"…Additionally, the least absolute shrinkage and selection operator (LASSO) regression algorithm in machine learning was used to screen transcription factors such as bHLH, WRKY, and MYB that influenced the expression of TaAkPHY genes. …"

Table 8_Genome-wide identification and expression analysis of phytochrome gene family in Aikang58 wheat (Triticum aestivum L.).xlsx حسب Zhu Yang (756364)

"…Additionally, the least absolute shrinkage and selection operator (LASSO) regression algorithm in machine learning was used to screen transcription factors such as bHLH, WRKY, and MYB that influenced the expression of TaAkPHY genes. …"

Table 7_Genome-wide identification and expression analysis of phytochrome gene family in Aikang58 wheat (Triticum aestivum L.).xlsx حسب Zhu Yang (756364)

"…Additionally, the least absolute shrinkage and selection operator (LASSO) regression algorithm in machine learning was used to screen transcription factors such as bHLH, WRKY, and MYB that influenced the expression of TaAkPHY genes. …"

Image 4_Genome-wide identification and expression analysis of phytochrome gene family in Aikang58 wheat (Triticum aestivum L.).tif حسب Zhu Yang (756364)

"…Additionally, the least absolute shrinkage and selection operator (LASSO) regression algorithm in machine learning was used to screen transcription factors such as bHLH, WRKY, and MYB that influenced the expression of TaAkPHY genes. …"

An optional formula for calculating crustal thickness using Sr/Y ratio and its application to the southeastern margin of the Central Asian Orogenic Belt حسب Xu Ma (45624)

"…Global lower crust-derived magmatic rock (younger than 23 Ma) data from diverse geological settings were selected and filtered using key geochemical criteria, alternating and iteratively using K-means clustering algorithm and improved Thompson tau method to exclude outliers. …"

Table 5_Genome-wide identification and expression analysis of phytochrome gene family in Aikang58 wheat (Triticum aestivum L.).xlsx حسب Zhu Yang (756364)

"…Additionally, the least absolute shrinkage and selection operator (LASSO) regression algorithm in machine learning was used to screen transcription factors such as bHLH, WRKY, and MYB that influenced the expression of TaAkPHY genes. …"

Table 2_Genome-wide identification and expression analysis of phytochrome gene family in Aikang58 wheat (Triticum aestivum L.).xlsx حسب Zhu Yang (756364)

"…Additionally, the least absolute shrinkage and selection operator (LASSO) regression algorithm in machine learning was used to screen transcription factors such as bHLH, WRKY, and MYB that influenced the expression of TaAkPHY genes. …"

Image 1_Genome-wide identification and expression analysis of phytochrome gene family in Aikang58 wheat (Triticum aestivum L.).tif حسب Zhu Yang (756364)

"…Additionally, the least absolute shrinkage and selection operator (LASSO) regression algorithm in machine learning was used to screen transcription factors such as bHLH, WRKY, and MYB that influenced the expression of TaAkPHY genes. …"

Image 7_Genome-wide identification and expression analysis of phytochrome gene family in Aikang58 wheat (Triticum aestivum L.).tif حسب Zhu Yang (756364)

"…Additionally, the least absolute shrinkage and selection operator (LASSO) regression algorithm in machine learning was used to screen transcription factors such as bHLH, WRKY, and MYB that influenced the expression of TaAkPHY genes. …"

Table 3_Genome-wide identification and expression analysis of phytochrome gene family in Aikang58 wheat (Triticum aestivum L.).xlsx حسب Zhu Yang (756364)

"…Additionally, the least absolute shrinkage and selection operator (LASSO) regression algorithm in machine learning was used to screen transcription factors such as bHLH, WRKY, and MYB that influenced the expression of TaAkPHY genes. …"

Image 6_Genome-wide identification and expression analysis of phytochrome gene family in Aikang58 wheat (Triticum aestivum L.).tif حسب Zhu Yang (756364)

"…Additionally, the least absolute shrinkage and selection operator (LASSO) regression algorithm in machine learning was used to screen transcription factors such as bHLH, WRKY, and MYB that influenced the expression of TaAkPHY genes. …"