Scrambled Prime Key Encryption by Haraty, Ramzi A.

“…To enhance data security different cryptographic algorithms are used. …”
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Unsupervised Deep Learning for Classification Of Bats Calls Using Acoustic Data by Arshad, Muhammad Arbab

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Simulations of the penetration of 6061-T6511 aluminum targets by spherical-nosed VAR 4340 steel projectiles by Warren, Thomas

“…In the context of an analysis code, this approximation eliminates the need for discretizing the target as well as the need for a contact algorithm. Thus, this method substantially reduces the computer time and memory requirements. …”
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Integrative toxicogenomics: Advancing precision medicine and toxicology through artificial intelligence and OMICs technology by Ajay Vikram Singh (204056)

“…As personalized medicine and toxicogenomics involve huge data processing, AI can expedite this process by providing powerful data processing, analysis, and interpretation algorithms. …”

DeepRaman: Implementing surface-enhanced Raman scattering together with cutting-edge machine learning for the differentiation and classification of bacterial endotoxins by Samir Brahim, Belhaouari

“…This method offers precise endotoxin classification and holds significant potential for expedited medical diagnoses and therapeutic decision-making in cases of pathogenic infections. ConclusionWe present the effectiveness of DeepRaman, an innovative architecture inspired by the Progressive Fourier Transform and integrated with the scalogram transformation method, in classifying raw SERS Raman spectral data from biological specimens with unparalleled accuracy relative to conventional machine learning algorithms. …”
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Overview of Artificial Intelligence–Driven Wearable Devices for Diabetes: Scoping Review by Arfan Ahmed (17541309)

“…WDs coupled with artificial intelligence (AI) algorithms show promise to help understand and conclude meaningful information from the gathered data and provide advanced and clinically meaningful analytics.…”

Efficient utilization of scalable multipliers in parallel to compute GF(p) elliptic curve cryptographic operations by Gutub, Adnan

“…This paper presents the design and implementation of an elliptic curve cryptographic core to realize point scalar multiplication operations used for the GF(p) elliptic curve encryption/decryption and the elliptic curve digital signature algorithm (ECDSA). The design makes use of projective coordinates together with scalable Montgomery multipliers for data size of up to 256-bits. …”
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A Framework for Predictive Modeling in Sustainable Projects by Labban, Tarek

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Vibration suppression in a cantilever beam using a string-type vibration absorber by Issa, Jimmy S.

“…The string is rigidly connected to the fixed end of the beam and through a spring and damper to a second point on the beam. The finite element method is used to model the system and a reduced order model is obtained through modal reduction performed on both the string and the beam. …”
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Applications of fast fourier transform in the integrity evaluation of deep foundations by Abi Shdid, Caesar

“…The method is developed and validated using experimental data, and is based on applying the fast Fourier transform mapping algorithm on data obtained from cross-hole sonic logging. …”
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Higher-order statistics (HOS)-based deconvolution for ultrasonic nondestructive evaluation (NDE) of materials by Ghouti, Lahouari

“…Performance evaluation of the proposed methods and comparisons with existing methods are made by means of Monte-Carlo simulations, experimental data and analysis. The first scheme makes use of the complex cepstrum of the third-order cumulants (complex bicepstrum) of the ultrasonic signals. …”
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Privacy-preserving energy optimization via multi-stage federated learning for micro-moment recommendations by Md Mosarrof Hossen (21399056)

“…<p>Human behavior significantly impacts domestic energy consumption, making it essential to monitor and improve these consumption patterns. …”

A comprehensive review of deep reinforcement learning applications from centralized power generation to modern energy internet frameworks by Sakib Mahmud (15302404)

“…Deep reinforcement learning (DRL) offers a data-driven alternative that couples perception with sequential decision-making. …”

A novel few shot learning derived architecture for long-term HbA1c prediction by Marwa Qaraqe (10135172)

“…For the first time in the literature, this work proposes a novel FSL-derived algorithm for the long-term prediction of clinical HbA1c measures. …”

A multi-pretraining U-Net architecture for semantic segmentation by Cagla Copurkaya (22502042)

“…The proposed approach makes advantage of data augmentation to generate newly synthesized images, which are subsequently processed using a watershed mask. …”

Using machine learning to support students’ academic decisions by ALLAH, AISHA QASIM GHAZAL FATEH

“…This approach uses other students’ grades to make a prediction. This research tests and compares the performance of Decision Trees, Random Forests, Gradient-Boosted trees, and Deep Learning machine learning regression algorithms to predict student GPA. …”
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Identity and Aggregate Signature-Based Authentication Protocol for IoD Deployment Military Drone by Saeed Ullah Jan (9079260)

“…Both GPS and UAVN/FANET use open network channels for data broadcasting, which are exposed to several threats, thus making security risky and challenging. …”

Artificial intelligence based anomaly detection of energy consumption in buildings: A review, current trends and new perspectives by Yassine Himeur (14158821)

“…<p dir="ltr">Enormous amounts of data are being produced everyday by sub-meters and smart sensors installed in residential buildings. …”

Legal and Ethical Considerations of Artificial Intelligence for Residents in Post-Acute and Long-Term Care by Barry Solaiman (19160614)

“…Second, how discrimination and bias in algorithmic decision-making can undermine Medicare coverage for PA-LTC, causing doctors' recommendations to be ignored and denying residents the care they are entitled to. …”

Artificial intelligence models for predicting the mode of delivery in maternal care by Rawan AlSaad (14159019)

“…</p><h3>Objectives</h3><p dir="ltr">This study aims to evaluate and compare the predictive accuracy of AI algorithms in predicting the mode of delivery (vaginal or cesarean) using routinely collected antepartum data from electronic health records (EHRs). …”