Research on pairing-free certificateless batch anonymous authentication scheme for VANET by Cheng SONG, Ming-yue ZHANG, Wei-ping PENG, Zong-pu JIA, Zhi-zhong LIU, Xi-xi YAN

“…To solve the problem of security and efficiency of anonymous authentication in vehicular ad hoc network,a pairing-free certificateless batch anonymous authentication scheme was proposed.The public and private keys and pseudonyms were jointly generated by the trusted third party and vehicle,so the system security didn't depend on the tamper device.The scheme can realize authentication,anonymity,traceability,unforgeability,forward or backward security,and so on.Furthermore,under the random oracle model,the scheme can resist Type I and Type II attacks.Because there is no need to use certificates during authentication,the system storage load is effectively reduced.At the same time,the scheme realizes the batch message authentication on the basis of pairing-free operation,so the authentication efficiency is improved.Therefore,the scheme has important theoretical significance and application value in the resource-limited internet of things or embedded environment.…”
Get full text

Deep feature batch correction using ComBat for machine learning applications in computational pathology by Pierre Murchan, Pilib Ó Broin, Anne-Marie Baird, Orla Sheils, Stephen P Finn

“…ComBat harmonization significantly reduced the AUROC for TSS prediction, with mean AUROCs dropping to approximately 0.5 for most models, indicating successful mitigation of batch effects (e.g., CCL-ResNet50 in TCGA-COAD: Pre-ComBat AUROC = 0.960, Post-ComBat AUROC = 0.506, p < 0.001). …”
Get full text

VIOLET: Vectorized Invariance Optimization for Language Embeddings Using Twins by Mikhail E. Ram, G. Manju

“…We present VIOLET, a novel positive pair-based information maximisation strategy for fine-tuning BERT to generate robust, invariant, and semantically meaningful sentence embeddings. VIOLET extends the Barlow Twins framework by addressing both redundancy reduction and invariance preservation within the embedding space. …”
Get full text

Embedded Hardware-Efficient FPGA Architecture for SVM Learning and Inference by B. B. Shabarinath, Muralidhar Pullakandam

“…In this paper, we propose Parallel SMO, a new algorithm that selects multiple violating pairs in each iteration, allowing batch-wise updates that enhance convergence speed and optimize parallel computation. …”
Get full text

stDyer enables spatial domain clustering with dynamic graph embedding by Ke Xu, Yu Xu, Zirui Wang, Xin Maizie Zhou, Lu Zhang

“…We introduce stDyer, an end-to-end deep learning framework for spatial domain clustering in SRT data. stDyer combines Gaussian Mixture Variational AutoEncoder with graph attention networks to learn embeddings and perform clustering. Its dynamic graphs adaptively link units based on Gaussian Mixture assignments, improving clustering and producing smoother domain boundaries. stDyer’s mini-batch strategy and multi-GPU support facilitate scalability to large datasets. …”
Get full text

Accelerating EdDSA Signature Verification with Faster Scalar Size Halving by Muhammad ElSheikh, İrem Keskinkurt Paksoy, Murat Cenk, M. Anwar Hasan

Get full text

Simulation and Prediction of Springback in Sheet Metal Bending Process Based on Embedded Control System by Jinhan Xu, Jun Yan, Yan Huang, Dawei Ding

“…Amidst the accelerating pace of automation in sheet metal bending, the need for small-batch, multi-varietal, efficient, and adaptable production modalities has become increasingly pronounced. …”
Get full text

Investigation of BSA adsorption performances of metal ion attached mineral particles embedded cryogel discs by Ömür Acet

“…The experiments were studied in a batch system. The highest amount of adsorbed BSA (356,8 mg/g particles) onto discs was obtained at pH 7.0 (phosphate buffer), 4 mg/mL concentration of BSA. …”
Get full text

Adsorption potential of CuO-embedded chitosan bead for the removal of acid blue 25 dye by Ismaila Olalekan Saheed, Nuraliah Irdina Zairuddin, Syaza Atikah Nizar, Megat Ahmad Kamal Megat Hanafiah, Ahmad Faiz Abdul Latip, Faiz Bukhari Mohd Suah

Get full text

Enhanced expression of full-length human cytomegalovirus fusion protein in non-swelling baculovirus-infected cells with a minimal fed-batch strategy. by Marco Patrone, Nuno Carinhas, Marcos Q Sousa, Cristina Peixoto, Claudio Ciferri, Andrea Carfì, Paula M Alves

Get full text

scCobra allows contrastive cell embedding learning with domain adaptation for single cell data integration and harmonization by Bowen Zhao, Kailu Song, Dong-Qing Wei, Yi Xiong, Jun Ding

Get full text

A novel strategy for controllable electrofabrication of molecularly imprinted polymer biosensors utilizing embedded Prussian blue nanoparticles by Bahareh Babamiri, Mohammadreza Farrokhnia, Mehdi Mohammadi, Amir Sanati Nezhad

“…Abstract The reproducibility of ultrasensitive biosensors is vital for clinical research, scalable manufacturing, commercialization, and reliable clinical decision-making, as batch-to-batch variations introduce significant uncertainty. …”
Get full text

Laccase Enzyme Embedded on Zinc Oxide/silver Doped Zinc Oxide Nanoparticle-chitosan-PVPP Composite Beads by Hilda Dinah Kyomuhimbo, Usisipho Feleni, Hendrik G. Brink

Get full text

Embedded machine learning for fault detection in conveyor systems using multi-sensor data and discrete wavelet transform by Hoang Duc Do, Quang Minh Vien, Khang Hoang Vinh Nguyen, Can Duy Le

“…The model is developed using the TensorFlow Lite framework, incorporating batch normalization to stabilize and accelerate the learning process. …”
Get full text

A Near-Real-Time Imaging Algorithm for Focusing Spaceborne SAR Data in Multiple Modes Based on an Embedded GPU by Yunju Zhang, Mingyang Shang, Yini Lv, Xiaolan Qiu

Get full text

A novel dual embedding few-shot learning approach for classifying bone loss using orthopantomogram radiographic notes by Pradeep Kumar Yadalam, Amit Rajabhau Pawar, Prabhu Manickam Natarajan, Carlos M. Ardila

“…Key techniques such as batch normalization and dropout layers were implemented to improve learning stability and reduce overfitting. …”
Get full text

stGuide advances label transfer in spatial transcriptomics through attention-based supervised graph representation learning by Yupeng Xu, Hao Dai, Jinwang Feng, Keren Xu, Qiu Wang, Pingting Gao, Chunman Zuo, Chunman Zuo

“…The growing availability of spatial transcriptomics data offers key resources for annotating query datasets using reference datasets. However, batch effects, unbalanced reference annotations, and tissue heterogeneity pose significant challenges to alignment analysis. …”
Get full text

Novel MOF-Derived carbon-embedded acicular mullite for efficient removal of bisphenol A and 17α-ethinylestradiol: adsorption mechanisms and thermodynamic studies by Liu Deyong, Xiong Guangcheng, Xiong Guangcheng, Xu Xingcan, Xu Qi, Xu Qi, Liu Lisheng, Wang Chu, Wang Chu, Zhou Qiuhong, Zhou Qiuhong

“…The adsorption performance of MOF-M-C for BPA and EE2 in aqueous solutions was systematically evaluated through batch experiments, investigating parameters such as contact time, temperature, pH, ionic strength, and coexisting anions. …”
Get full text

Silver nanoparticles (Ag-NPs) embedded in zeolite framework: A comprehensive study on bromide removal from water, including characterization, antibacterial properties, and adsorpti... by Aiman Eid Al-Rawajfeh, Albara Ibrahim Alrawashdeh, Mohammad Taha Etiwi, Ali Alnawaiseh, Muhammad Kashif Shahid, Mohanad H.M. Masad, Sumaia Omar Oran, Solhe F. Alshahateet

Get full text

Optimizing binary neural network quantization for fixed pattern noise robustness by Francisco Javier Andreo-Oliver, Gines Domenech-Asensi, Jose Angel Diaz-Madrid, Ramon Ruiz-Merino, Juan Zapata-Perez

“…Binary neural networks (BNN) are particularly attractive for resource-constrained embedded systems due to their reduced memory footprint and computational requirements. …”
Get full text