Zobrazeno 1 - 10
of 11 333
pro vyhledávání: '"Abdulla, P."'
Publikováno v:
Journal of Artificial Intelligence and Systems, 2024, 6, 34-58 https://iecscience.org/journals/AIS ISSN Online: 2642-2859
In recent years, ML algorithms have been shown to be useful for predicting diseases based on health data and posed a potential application area for these algorithms such as modeling of diseases. The majority of these applications employ supervised ra
Externí odkaz:
http://arxiv.org/abs/2412.16768
Publikováno v:
INTERNATIONAL JOURNAL of RENEWABLE ENERGY RESEARCH, Vol.13, No.3, September, 2023
With industrial and technological development and the increasing demand for electric power, wind energy has gradually become the fastest-growing and most environmentally friendly new energy source. Nevertheless, wind power generation is always accomp
Externí odkaz:
http://arxiv.org/abs/2412.13356
Autor:
Abdullah, Abdulhady Abas, Abdulla, Srwa Hasan, Toufiq, Dalia Mohammad, Maghdid, Halgurd S., Rashid, Tarik A., Farho, Pakshan F., Sabr, Shadan Sh., Taher, Akar H., Hamad, Darya S., Veisi, Hadi, Asaad, Aras T.
Nowadays, Natural Language Processing (NLP) is an important tool for most people's daily life routines, ranging from understanding speech, translation, named entity recognition (NER), and text categorization, to generative text models such as ChatGPT
Externí odkaz:
http://arxiv.org/abs/2412.15252
Publikováno v:
Journal of Environmental Science and Economics, 2024
Given the fact that climate change has become one of the most pressing problems in many countries in recent years, specialized research on how to mitigate climate change has been adopted by many countries. Within this discussion, the influence of adv
Externí odkaz:
http://arxiv.org/abs/2412.16166
Measurement of numerical values of the anomalous density, $\sigma$, which plays important role in Bose -- Einstein condensation, and, especially, determination of its sign, has been a long standing problem. We develop Hartree -- Fock -- Bogoliubov th
Externí odkaz:
http://arxiv.org/abs/2411.15816
Autor:
Abdulla, Parosh Aziz, Atig, Mohamed Faouzi, Cailler, Julie, Liang, Chencheng, Rümmer, Philipp
This paper proposes a Graph Neural Network-guided algorithm for solving word equations, based on the well-known Nielsen transformation for splitting equations. The algorithm iteratively rewrites the first terms of each side of an equation, giving ris
Externí odkaz:
http://arxiv.org/abs/2411.15194
Autor:
Morshed, Abrar, Shihab, Abdulla Al, Jahin, Md Abrar, Nahian, Md Jaber Al, Sarker, Md Murad Hossain, Wadud, Md Sharjis Ibne, Uddin, Mohammad Istiaq, Siraji, Muntequa Imtiaz, Anjum, Nafisa, Shristy, Sumiya Rajjab, Rahman, Tanvin, Khatun, Mahmuda, Dewan, Md Rubel, Hossain, Mosaddeq, Sultana, Razia, Chakma, Ripel, Emon, Sonet Barua, Islam, Towhidul, Hussain, Mohammad Arafat
The COVID-19 pandemic has affected millions of people globally, with respiratory organs being strongly affected in individuals with comorbidities. Medical imaging-based diagnosis and prognosis have become increasingly popular in clinical settings for
Externí odkaz:
http://arxiv.org/abs/2411.05029
Autor:
Hirani, Gaurav, Abdulla, Waleed
The deep convolutional neural network (DCNN) in computer vision has given promising results. It is widely applied in many areas, from medicine, agriculture, self-driving car, biometric system, and almost all computer vision-based applications. Filter
Externí odkaz:
http://arxiv.org/abs/2410.21644
Autor:
Abdulla, Parosh Aziz, Chen, Yo-Ga, Chen, Yu-Fang, Holík, Lukáš, Lengál, Ondřej, Lin, Jyun-Ao, Lo, Fang-Yi, Tsai, Wei-Lun
We present a new method for the verification of quantum circuits based on a novel symbolic representation of sets of quantum states using level-synchronized tree automata (LSTAs). LSTAs extend classical tree automata by labeling each transition with
Externí odkaz:
http://arxiv.org/abs/2410.18540
Autor:
Awais, Muhammad, Alharthi, Ali Husain Salem Abdulla, Kumar, Amandeep, Cholakkal, Hisham, Anwer, Rao Muhammad
Significant progress has been made in advancing large multimodal conversational models (LMMs), capitalizing on vast repositories of image-text data available online. Despite this progress, these models often encounter substantial domain gaps, hinderi
Externí odkaz:
http://arxiv.org/abs/2410.08405