IM- LTS: An Integrated Model for Lung Tumor Segmentation using Neural Networks and IoMT by Jayapradha J, Su-Cheng Haw, Naveen Palanichamy, Kok-Why Ng, Senthil Kumar Thillaigovindhan

Get full text

Prediction and optimization of Rhodamine B removal from water using metal-organic frameworks: RSM-CCD, ANN, non-linear kinetics, and isotherm studies by Simon Bbumba, John Ssekatawa, Ibrahim Karume, Emmanuel Tebandeke, Moses Kigozi, Solomon Yiga, Robert Setekera, Joseph Ssebuliba, Steven Sekitto, Ruth Mbabazi, Ivan Kiganda, Maximillian Kato, Patrick Taremwa, Moses Murungi, Chinaecherem Tochukwu Arum, Collins Yiiki Letibo, Geofrey Kaddu, Margret Namugwanya, John Kusasira, Peace Mwesigwa, Muhammad Ntale

Get full text

Using machine learning techniques for DSP software performance prediction at source code level by Weihua Liu, Erh-Wen Hu, Bogong Su, Jian Wang

“…To validate the new model, we measure experimentally the execution time of a set of functions selected from PHY DSP Benchmark and run them on TIC64 DSP processor. It is observed that the average absolute relative prediction error is less than 10% between the computed performance from the new model and the actual measured execution time.…”
Get full text

Explainable AI-based suicidal and non-suicidal ideations detection from social media text with enhanced ensemble technique by Daniyal Alghazzawi, Hayat Ullah, Naila Tabassum, Sahar K. Badri, Muhammad Zubair Asghar

Get full text

Dynamic thermalization on noisy quantum hardware by Hugo Perrin, Thibault Scoquart, Andrei I. Pavlov, Nikolay V. Gnezdilov

“…Thermal observables occur upon classically averaging quantum mechanical observables over randomized variants of their time evolution that run independently on a digital quantum processor. Using an IBM quantum computer, we experimentally find thermal occupation probabilities with finite positive and negative temperatures defined by the initial state’s energy. …”
Get full text

Optically levitated nanoparticles as receiving antennas for low frequency wireless communication by Zhenhai Fu, Jinsheng Xu, Shaochong Zhu, Chaoxiong He, Xunming Zhu, Xiaowen Gao, Han Cai, Peitong He, Zhiming Chen, Yizhou Zhang, Nan Li, Xingfan Chen, Ying Dong, Shiyao Zhu, Cheng Liu, Huizhu Hu

Get full text

Review of iris segmentation and recognition using deep learning to improve biometric application by Rasheed Hind Hameed, Shamini Sara Swathy, Mahmoud Moamin A., Alomari Mohammad Ahmed

Get full text

Support Vector Machine (SVM) for Tomato Leaf Disease Detection by Shafaf Ibrahim, Nur Afiqah Mohd Fuad, Nor Azura Md Ghani, Raihah Aminuddin, Budi Sunarko

Get full text

ZK-STARK: Mathematical Foundations and Applications in Blockchain Supply Chain Privacy by Arade Madhuri S., Pise Nitin N.

Get full text

Downscaling NOx emission into 1 km resolution over a typical mega-city based on POI with machine learning method by Zining Yang, Hengheng Ge, Chun Zhao, Xuchao Yang, Qiuyan Du, Zihan Xia, Gudongze Li

Get full text

Tunable wideband microwave photonic phase shifter and true time delay using a waveguide bragg grating by Zahra Nasehi, S. Esmail Hosseini

Get full text

An acoustic microscope for microflaw inspection and subsurface imaging by J. Litniewski

“…The microscope works in the frequency range of 20-70 MHz where images are created on the computer monitor screen or printed out using a video copy processor. …”
Get full text

Digital technologies in education by Natalya Shumafovna Kozlova

“…It’s been shown that digital technologies are necessary for the educational process but not sufficient for increasing the effectiveness of academic work. …”
Get full text

Monolithically integrated asynchronous optical recurrent accelerator by Bo Wu, Haojun Zhou, Junwei Cheng, Wenkai Zhang, Shiji Zhang, Chaoran Huang, Dongmei Huang, Hailong Zhou, Jianji Dong, Xinliang Zhang

“…This innovation enables the efficient processing of large-scale parallel signals and positions optical processors as a pivotal technology for applications such as autonomous driving and intelligent robotics.…”
Get full text

Analysis of GPR Wave Propagation Using CUDA-Implemented Conformal Symplectic Partitioned Runge-Kutta Method by Hongyuan Fang, Jianwei Lei, Man Yang, Ziwei Li

“…For forward modeling of large sizes and fine structures, numerical accuracy and computational efficiency are not high, due to the stability conditions and the dense grid number. …”
Get full text

Tensor-powered insights into neural dynamics by Boyang Zang, Tao Sun, Yang Lu, Yuhang Zhang, Guihuai Wang, Sen Wan

“…Furthermore, LS-STM demonstrates better performance in decoding neural signals with limited samples and the tensor weights of the LS-STM decoder enable the retrospective identification of key neurons during the neural encoding process. This study introduces a novel tensor computing approach and perspective for decoding high-dimensional neural information in the field.…”
Get full text

Creating Tail Dependence by Rough Stochastic Correlation Satisfying a Fractional SDE; An Application in Finance by László Márkus, Ashish Kumar, Amina Darougi

“…We model this rough stochastic correlation by a suitably transformed fractional Ornstein–Uhlenbeck process and simulate artificial stock prices, which allows computing tail dependence and the Herding Behavior Index (HIX) as functions in time. …”
Get full text

Expansion of Impervious Surface Area in Pekanbaru (1990–2018) and Predictions for 2038 Using Big Data by Wirawan Bayu Andrianto, Siregar Yusni Ikhwan, Sukendi Sukendi, Mulyadi Mulyadi

“…This situation can result in environmental degradation and unpreparedness of government officials so that the growth process leads to unsustainability. The development of spatial big data technology and high-performance cloud computing, the phenomenon of built-up land growth that occurs in Pekanbaru City can be studied further. …”
Get full text

Transformer-Guided Serial Knowledge Distillation for High-Precision Anomaly Detection by Danyang Wang, Bingyan Wang

“…Unsupervised anomaly detection (AD) remains a notable challenge in computer vision research, due to the inherent absence of annotated anomalous data and the unpredictable nature of anomaly manifestations. …”
Get full text

Regularized Fractional Power Parameters for Image Denoising Based on Convex Solution of Fractional Heat Equation by Hamid A. Jalab

“…Denoising is one of the most fundamental image restoration problems in computer vision and image processing. This paper proposes an image denoising algorithm based on convex solution of fractional heat equation with regularized fractional power parameters. …”
Get full text