A Novel Approach for Detecting Anomalous Energy Consumption Based on Micro-Moments and Deep Neural Networks حسب Yassine Himeur (14158821)

"…Experimental results on simulated and real datasets collected at two regions, which have extremely different climate conditions, confirm that the proposed deep micro-moment architecture outperforms other machine learning algorithms and can effectively detect anomalous patterns. …"

Exploring new horizons in neuroscience disease detection through innovative visual signal analysis حسب Nisreen Said Amer (17984077)

"…To address this, our study focuses on visualizing complex EEG signals in a format easily understandable by medical professionals and deep learning algorithms. We propose a novel time–frequency (TF) transform called the Forward–Backward Fourier transform (FBFT) and utilize convolutional neural networks (CNNs) to extract meaningful features from TF images and classify brain disorders. …"

From Collatz Conjecture to chaos and hash function حسب Masrat Rasool (17807813)

"…The effectiveness and dependability of the proposed hash function are evaluated by comparing it with two well-known hash algorithms, namely SHA-3 and SHA-2, as well as several other Chaos-based hash algorithms. …"

Integration of nonparametric fuzzy classification with an evolutionary-developmental framework to perform music sentiment-based analysis and composition حسب Abboud, Ralph

"…Unlike existing solutions, MUSEC is: (i) a hybrid crossover between supervised learning (SL, to learn sentiments from music) and evolutionary computation (for music composition, MC), where SL serves at the fitness function of MC to compose music that expresses target sentiments, (ii) extensible in the panel of emotions it can convey, producing pieces that reflect a target crisp sentiment (e.g., love) or a collection of fuzzy sentiments (e.g., 65% happy, 20% sad, and 15% angry), compared with crisp-only or two-dimensional (valence/arousal) sentiment models used in existing solutions, (iii) adopts the evolutionary-developmental model, using an extensive set of specially designed music-theoretic mutation operators (trille, staccato, repeat, compress, etc.), stochastically orchestrated to add atomic (individual chord-level) and thematic (chord pattern-level) variability to the composed polyphonic pieces, compared with traditional evolutionary solutions producing monophonic and non-thematic music. …"
احصل على النص الكامل
احصل على النص الكامل
احصل على النص الكامل
احصل على النص الكامل

ML-Based Handover Prediction and AP Selection in Cognitive Wi-Fi Networks حسب Muhammad Asif Khan (7367468)

"…Due to the complex nature of the radio environment, analytical models may not characterize the wireless channel, which makes the solution of these problems very difficult. …"

Diagnostic performance of artificial intelligence in detecting and subtyping pediatric medulloblastoma from histopathological images: A systematic review حسب Hiba Alzoubi (18001609)

"…</p><h3>Conclusion</h3><p dir="ltr">AI algorithms show promise in detecting and subtyping medulloblastomas, but the findings are limited by overreliance on one dataset, small sample sizes, limited study numbers, and lack of meta-analysis Future research should develop larger, more diverse datasets and explore advanced approaches like deep learning and foundation models. …"

Artificial intelligence-enhanced electrocardiography for accurate diagnosis and management of cardiovascular diseases حسب Muhammad Ali Muzammil (17910611)

"…Using AI, especially deep learning convolutional neural networks (CNNs), to look at single, continuous, and intermittent ECG leads that has led to fully automated AI models that can interpret the ECG like a human, possibly more accurately and consistently. …"

Secure and Anonymous Communications Over Delay Tolerant Networks حسب Spiridon Bakiras (16896408)

"…Instead, our work introduces a novel message forwarding algorithm that delivers messages, from source to destination, via a random walk process. …"

From low-cost sensors to high-quality data: A summary of challenges and best practices for effectively calibrating low-cost particulate matter mass sensors حسب Michael R. Giordano (9976173)

"…The methods for correcting and calibrating these biases and dependencies that have been used in the literature likewise range from simple linear and quadratic models to complex machine learning algorithms. Here we review the needs and challenges when trying to get high-quality data from low-cost sensors. …"

Capillary trapping in mixed-wet porous media: Implications for subsurface carbon dioxide sequestration حسب Saideep Pavuluri (21792941)

"…Insights from this study can be used for improving pore network models and training machine learning algorithms.</p><h2>Other Information</h2><p dir="ltr">Published in: International Journal of Multiphase Flow<br>License: <a href="http://creativecommons.org/licenses/by/4.0/" target="_blank">http://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1016/j.ijmultiphaseflow.2025.105307" target="_blank">https://dx.doi.org/10.1016/j.ijmultiphaseflow.2025.105307</a></p>…"

The use of semantic-based predicates implication to improve horizontal multimedia database fragmentation حسب Getahun, Fekade

"…We particularly discuss multimedia primary horizontal fragmentation and focus on semantic-based textual predicates implication required as a pre-process in current fragmentation algorithms in order to partition multimedia data efficiently. …"
احصل على النص الكامل
احصل على النص الكامل
احصل على النص الكامل
احصل على النص الكامل

Enhancement of SAR Speckle Denoising Using the Improved Iterative Filter حسب Yahia, Mohamed

"…The recent advancement in synthetic aperture radar (SAR) technology has enabled high-resolution imaging capability that calls for efficient speckle filtering algorithms to preprocess radar imagery. …"
احصل على النص الكامل