Improvement of Kernel Principal Component Analysis-Based Approach for Nonlinear Process Monitoring by Data Set Size Reduction Using Class Interval by Mohammed Tahar Habib Kaib (21633176)

Digital circuit design through simulated evolution (SimE) by Sait, Sadiq M.

“…In this paper, the use of simulated evolution (SimE) algorithm in the design of digital logic circuits is proposed. …”
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A quantum algorithm for evolving open quantum dynamics on quantum computing devices by Zixuan Hu (13719685)

“…<p dir="ltr">Designing quantum algorithms for simulating quantum systems has seen enormous progress, yet few studies have been done to develop quantum algorithms for open quantum dynamics despite its importance in modeling the system-environment interaction found in most realistic physical models. …”

Learning-Based Space-Time Adaptive Processing by El Khatib, Alaa

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Design of a TE-pass reflection mode optical polarizer by Khan, M.A.

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Design of a vibration absorber for harmonically forced damped systems by Issa, Jimmy

“…Two different numerical approaches are used in solving the problem; the first is based on the genetic algorithm technique and the second on the downhill simplex method. …”
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Power system output feedback stabilizer design via geneticalgorithms by Abdel-Magid, Y.L.

“…The paper demonstrates the use of genetic algorithms to design output feedback power system stabilizers. …”
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Self-Checking Hardware Design for Montgomery Exponentiation-Based Cryptography by Muhammad Ali Akbar (16875915)

“…<p dir="ltr">Montgomery exponentiation is widely used for public-key-based cryptography systems. The current state-of-the-art designs for this algorithm are well-analyzed in terms of hardware overhead but are not investigated for faults caused by physical attacks. …”

Defining quantitative rules for identifying influential researchers: Insights from mathematics domain by Ghulam Mustafa (458105)

A Hybrid Fault Detection and Diagnosis of Grid-Tied PV Systems: Enhanced Random Forest Classifier Using Data Reduction and Interval-Valued Representation by Khaled Dhibi (16891524)

Design and Analysis of Lightweight Authentication Protocol for Securing IoD by Saeed Ullah Jan (9079260)

“…Its security has been verified formally using Random Oracle Model (ROM), ProVerif2.02 and informally using assumptions and pragmatic illustration. …”

Humanizing AI in medical training: ethical framework for responsible design by Mohammed Tahri Sqalli (18420840)

“…Humanizing AI in medical training is crucial to ensure that the design and deployment of its algorithms align with ethical principles and promote equitable healthcare outcomes for both medical practitioners trainees and patients. …”

Brain Source Localization in the Presence of Leadfield Perturbations by Momin, Rabiya Nakhat

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Wearable Real-Time Heart Attack Detection and Warning System to Reduce Road Accidents by Muhammad E. H. Chowdhury (14150526)

Recursive least-squares backpropagation algorithm for stop-and-go decision-directed blind equalization by Abrar, Shafayat

“…To overcome this problem, in this work, a fast converging recursive least squares (RLS)-based complex-valued backpropagation learning algorithm is derived for S&G-DD blind equalization. …”
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Deep Reinforcement Learning for Resource Constrained HLS Scheduling by Makhoul, Rim

“…The two main steps in HLS are: operations scheduling and data-path allocation. In this work, we present a resource constrained scheduling approach that minimizes latency and subject to resource constraints using a deep Q learning algorithm. …”
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Using machine learning for disease detection. (c2013) by Jreij, Georges Antoun

“…Classification consists of predicting group membership for new data instances by learning from pre-classified data instances. …”
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Methods for system-on-chip test design, scheduling and optimization. (c2006) by Farah, Rana

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A flexible genetic algorithm-fuzzy regression approach for forecasting: The case of bitumen consumption by Azadeh, Ali

“…Design/methodology/approach In the proposed approach, the parameter tuning process is performed on all parameters of genetic algorithm (GA), and the finest coefficients with minimum errors are identified. …”
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Selection of the learning gain matrix of an iterative learning control algorithm in presence of measurement noise by Saab, Samer S.

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