The architecture of ILSTM. by Asmaa Ahmed Awad (16726315)

“…The ILSTM was then used to build an efficient intrusion detection system for binary and multi-class classification cases. The proposed algorithm has two phases: phase one involves training a conventional LSTM network to get initial weights, and phase two involves using the hybrid swarm algorithms, CBOA and PSO, to optimize the weights of LSTM to improve the accuracy. …”

Parameter setting for LSTM. by Asmaa Ahmed Awad (16726315)

“…The ILSTM was then used to build an efficient intrusion detection system for binary and multi-class classification cases. The proposed algorithm has two phases: phase one involves training a conventional LSTM network to get initial weights, and phase two involves using the hybrid swarm algorithms, CBOA and PSO, to optimize the weights of LSTM to improve the accuracy. …”

LITNET-2020 data splitting approach. by Asmaa Ahmed Awad (16726315)

“…The ILSTM was then used to build an efficient intrusion detection system for binary and multi-class classification cases. The proposed algorithm has two phases: phase one involves training a conventional LSTM network to get initial weights, and phase two involves using the hybrid swarm algorithms, CBOA and PSO, to optimize the weights of LSTM to improve the accuracy. …”

Transformation of symbolic features in NSL-KDD. by Asmaa Ahmed Awad (16726315)

“…The ILSTM was then used to build an efficient intrusion detection system for binary and multi-class classification cases. The proposed algorithm has two phases: phase one involves training a conventional LSTM network to get initial weights, and phase two involves using the hybrid swarm algorithms, CBOA and PSO, to optimize the weights of LSTM to improve the accuracy. …”

Fig 9 - by Mouhamad Bodaghie (14838511)

Fig 11 - by Mouhamad Bodaghie (14838511)

Fig 10 - by Mouhamad Bodaghie (14838511)

Fig 12 - by Mouhamad Bodaghie (14838511)

Fig 7 - by Mouhamad Bodaghie (14838511)

Fig 8 - by Mouhamad Bodaghie (14838511)

Fig 3 - by Mouhamad Bodaghie (14838511)

Results for the Pattern Generation task. by Paolo Muratore (8331585)

Severe pediatric brucellosis prediction model in Yunnan Province, China, 2015–2024. by Xin Ma (37268)

“…<b>(b)</b> Variable selection using the BORUTA algorithm to identify key variables associated with the prediction of severe disease, with the selected variables marked by the red dashed lines. …”

Design, development & implementation of a GIS solution for simulating and predicting groundwater conditions & groundwater/surface-water interactions in Abu Dhabi coastal lines. by LALA HOUMMAIDI (8116253)

A secondary structure model of the effects of <i>Cis</i> mutation on splicing efficiency. by Idan Frumkin (3122832)

Characterization of anesthetic effects on network connectivity and their simulated ACh reversal. by Bolaji P. Eniwaye (12915339)

BOFdat Step 3: Identifying species-specific metabolic end goals. by Jean-Christophe Lachance (6619307)

Characterization of anesthetic effects on network dynamics and their simulated ACh reversal for best fit. by Bolaji P. Eniwaye (12915339)

Case-dependent contact reduction. by Md Rafiul Islam (11719003)

Data_Sheet_1_Multiclass Classification Based on Combined Motor Imageries.pdf by Cecilia Lindig-León (7889777)

“…And we propose two new multilabel uses of the Common Spatial Pattern (CSP) algorithm to optimize the signal-to-noise ratio, namely MC2CMI and MC2SMI approaches. …”