Zobrazeno 1 - 10
of 13 412
pro vyhledávání: '"IMRAN, MUHAMMAD"'
Autor:
Liu, Xuesong, Sun, Yao, Cheng, Runze, Xia, Le, Abumarshoud, Hanaa, Zhang, Lei, Imran, Muhammad Ali
Semantic communication (SC) offers promising advancements in data transmission efficiency and reliability by focusing on delivering true meaning rather than solely binary bits of messages. However, privacy concerns in SC might become outstanding. Eav
Externí odkaz:
http://arxiv.org/abs/2410.18418
Autor:
Ahmad, Murad, Ali, Liaqat, Imran, Muhammad, Rameez-ul-Islam, Ikram, Manzoor, Din, Rafi Ud, Ahmad, Ashfaq, Ahmad, Iftikhar
Hyperentangled states are highly efficient and resource economical. This is because they enhance the quantum information encoding capabilities due to the correlated engagement of more than one degree of freedom of the same quantum entity while keepin
Externí odkaz:
http://arxiv.org/abs/2408.16397
This paper jointly investigates user association (UA), mode selection (MS), and bandwidth allocation (BA) problems in a novel and practical next-generation cellular network where two modes of semantic communication (SemCom) and conventional bit commu
Externí odkaz:
http://arxiv.org/abs/2408.07820
The advent of Ultra-Reliable Low Latency Communication (URLLC) alongside the emergence of Open RAN (ORAN) architectures presents unprecedented challenges and opportunities in Radio Resource Management (RRM) for next-generation communication systems.
Externí odkaz:
http://arxiv.org/abs/2407.17598
Autor:
Jabbar, Abdul, Kazim, Jalil Ur-Rehman, Shawky, Mahmoud A., Imran, Muhammad Ali, Abbasi, Qammer, Ur-Rehman, Masood
This paper presents the design and comprehensive measurements of a compact high-gain 32 element planar antenna array covering the n257 (26.5-29.5 GHz) millimeter wave (mmWave) band. First an 8-element quasi-uniform linear array is designed using a se
Externí odkaz:
http://arxiv.org/abs/2407.09944
Sentiment analysis is a key technology for companies and institutions to gauge public opinion on products, services or events. However, for large-scale sentiment analysis to be accessible to entities with modest computational resources, it needs to b
Externí odkaz:
http://arxiv.org/abs/2406.16071
Sentiment Analysis (SA) is a crucial aspect of Natural Language Processing (NLP), addressing subjective assessments in textual content. Syntactic parsing is useful in SA because explicit syntactic information can improve accuracy while providing expl
Externí odkaz:
http://arxiv.org/abs/2406.15163
Autor:
Ali, Aamir, Imran, Muhammad, Kuznetsov, Valentin, Trigazis, Spyridon, Pervaiz, Aroosha, Pfeiffer, Andreas, Mascheroni, Marco
The CMSWEB cluster is pivotal to the activities of the Compact Muon Solenoid (CMS) experiment, as it hosts critical services required for the operational needs of the CMS experiment. The security of these services and the corresponding data is crucia
Externí odkaz:
http://arxiv.org/abs/2405.15342
Autor:
Jiang, Hongxu, Imran, Muhammad, Ma, Linhai, Zhang, Teng, Zhou, Yuyin, Liang, Muxuan, Gong, Kuang, Shao, Wei
Denoising diffusion probabilistic models (DDPMs) have achieved unprecedented success in computer vision. However, they remain underutilized in medical imaging, a field crucial for disease diagnosis and treatment planning. This is primarily due to the
Externí odkaz:
http://arxiv.org/abs/2405.14802
During times of crisis, social media platforms play a crucial role in facilitating communication and coordinating resources. In the midst of chaos and uncertainty, communities often rely on these platforms to share urgent pleas for help, extend suppo
Externí odkaz:
http://arxiv.org/abs/2405.11897