A System for Extracting Sentiment from Large-Scale Arabic Social Data

Autor: Wang, Hao, Bommireddipalli, Vijay R., Hanafy, Ayman, Bahgat, Mohamed, Noeman, Sara, Emam, Ossama S.

Social media data in Arabic language is becoming more and more abundant. It is a consensus that valuable information lies in social media data. Mining this data and making the process easier are gaining momentum in the industries. This paper describe

Externí odkaz: http://arxiv.org/abs/1511.04661

Upcycled cosmetic ingredients: extraction process optimization via green solvents by the means of I-optimal and Box–Behnken designs

Autor: Nariman Ali Abdelrahim, Marina Noshy Saad, Martina Ashraf Zaghloul, Ossama Samueal Neaz

Publikováno v: Discover Applied Sciences, Vol 6, Iss 12, Pp 1-16 (2024)

Abstract Current trends are shifting attention to the sustainable valorization of food bio-waste management and by-product utilization, as they are rich in nutrients and bioactive compounds, such as dietary fiber, polyphenols, and peptides. Upcycled

Externí odkaz: https://doaj.org/article/f4ec053fc2714b229a899d9685a6824a

Practical Experiences with the First Relative Gravimeter of Type Scintrex CG-6 Autograv in Dubai, The United Arab of Emirates

Autor: Ossama S. Aly, Eman A. Al Khatibi, Basem Elsaka

Publikováno v: World Journal of Engineering and Technology. :237-247

In September 2019, the Dubai Municipality of Dubai Emirate, the United Arab of Emirates, has received its first Scintrex CG-6 Autograv gravity meter. This paper describes the installation and initial gravity signals with the new CG-6 Autograv gravime

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::2102d6c0f80c0d68181be2434cf78fbf
https://doi.org/10.4236/wjet.2020.82019

Efficient Noisy Sound-Event Mixture Classification Using Adaptive-Sparse Complex-Valued Matrix Factorization and OvsO SVM

Autor: Phetcharat Parathai, Gholamreza Rafiee, Wai Lok Woo, Mohammed A. M. Abdullah, Naruephorn Tengtrairat, Ossama S. Alshabrawy

Publikováno v: Parathai, P, Tengtrairat, N, Woo, W L, Abdullah, M A M, Rafiee, G & Alshabrawy, O 2020, ' Efficient Noisy Sound-Event Mixture Classification Using Adaptive-Sparse Complex-Valued Matrix Factorization and OvsO SVM ', Sensors (Basel, Switzerland), vol. 20, no. 16 . https://doi.org/10.3390/s20164368
Sensors (Basel, Switzerland)
Sensors, Vol 20, Iss 4368, p 4368 (2020)
Sensors
Volume 20
Issue 16

This paper proposes a solution for events classification from a sole noisy mixture that consist of two major steps: a sound-event separation and a sound-event classification. The traditional complex nonnegative matrix factorization (CMF) is extended

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7ee486d078bc001955530050e5c598a9
https://nrl.northumbria.ac.uk/id/eprint/44001/1/sensors-20-04368.pdf

Deep learning-based automated speech detection as a marker of social functioning in late-life depression

Autor: Peter Gallagher, I. Nicol Ferrier, Roisin McNaney, Patrick Olivier, Karim Ladha, Bethany Little, John T. O'Brien, Daniel Stow, Cassim Ladha, Thomas Ploetz, Ossama S. Alshabrawy, Jaume Bacardit, Dan Jackson

Publikováno v: Psychological Medicine

BackgroundLate-life depression (LLD) is associated with poor social functioning. However, previous research uses bias-prone self-report scales to measure social functioning and a more objective measure is lacking. We tested a novel wearable device to

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7c4f27d2050ac8301dda0e33988856b5