Improving Circulating Tumor Cell Detection Using Image Synthesis and Transformer Models in Cancer Diagnostics by Shuang Liang, Xue Bai, Yu Gu

“…This study proposes a data generation method using the Segment Anything Model (SAM) combined with a copy–paste strategy. …”
Get full text

CCTNet: CNN and Cross-Shaped Transformer Hybrid Network for Remote Sensing Image Semantic Segmentation by Honglin Wu, Zhaobin Zeng, Peng Huang, Xinyu Yu, Min Zhang

“…Furthermore, a simplified and efficient feature aggregation module is leveraged to gradually aggregate local and global information at different stages. Extensive comparison experiments on the ISPRS Vaihingen and Potsdam datasets reveal that our method obtains superior performance compared with state-of-the-art lightweight methods.…”
Get full text

Transformational leadership, co-worker support, engagement and motivation at institutions of higher learning in Windhoek, Namibia by Utjiua Ndjoonduezu, Annelisa Murangi

“…Main findings: The results showed that there is a positive relatedness between transformational leadership and employee engagement as well as transformational leadership and work motivation, even though not statistically significant. …”
Get full text

TRANSFORMATION OF VALUES OF THE HIGH TECHNOLOGY PROJECTS FROM A VUCA TO A BANI ENVIRONMENT MODEL by Sergiy Bushuyev, Kateryna Piliuhina, Elams Chetin

“…Tasks to be solved: to analyze the transformation from the VUCA model to the BANI model, to present values and their differentiation as the basis for survival in the new world order, to develop a method for assessing project risks in the BANI environment. …”
Get full text

Investigation of a transformer-based hybrid artificial neural networks for climate data prediction and analysis by Shangke Liu, Ke Liu, Zheng Wang, Yuanyuan Liu, Bin Bai, Rui Zhao

“…Lastly, LSTM is adept at handling long-term dependencies, ensuring the model can remember and utilize information over extended time spans.Results and DiscussionExperiments conducted on temperature data from Guangdong Province in China validate the performance of the proposed model. Compared to four different climate prediction decomposition methods, the proposed hybrid model with the Transformer method performs the best. …”
Get full text

EHR-protect: A steganographic framework based on data-transformation to protect electronic health records by Adifa Widyadhani Chanda D'Layla, Ntivuguruzwa Jean De La Croix, Tohari Ahmad, Fengling Han

“…EHR-Protect uses logarithmic pixel transformation and adaptive techniques such as difference expansion and EHR magnitude reduction to minimize distortions in carrier medical images. …”
Get full text

Implementation of Fuzzy Logic Scheme for Assessment of Power Transformer Oil Deterioration Using Imprecise Information by Zuhaib Nishter, Fangzong Wang

“…In this case, a fuzzy logic-based scheme is developed based upon the membership function, a rule-based and defuzzification method that works with imprecision and the implementation of uncertainty in assessing the condition of transformer oils. …”
Get full text

Transforming Fe-Cu alloys with unprecedented BCC Cu precipitates toward dual mechanical functionalities by Jeong Rae Kim, Hyun-Su Kang, Tae-Wan Ko, Young Jae Hwang, Gun Hee Kim, Seon-Jin Choi, Kwangchoon Lee, Hyuk-Su Han, Hyung Giun Kim, Taeg Woo Lee

Get full text

Expression analysis of transforming growth factor beta (TGF-β) in oral squamous cell carcinoma by Arun Ganesh, P.P. Ashikha Shirin Usman, Ameya K.P., Priya Thomas, Dhanraj M. Ganapathy, Durairaj Sekar

“…Although much progress has been made to control OSCC in recent years, therapies for OSCC remain challenging. Interestingly, transforming growth factor β (TGF-β) plays an important role in the extracellular microenvironment and different cellular processes like migration, proliferation, etc. …”
Get full text

Development and validation of an artificial intelligence-based pipeline for predicting oral epithelial dysplasia malignant transformation by Adam J. Shephard, Hanya Mahmood, Shan E. Ahmed Raza, Anna Luíza Damaceno Araújo, Alan Roger Santos-Silva, Marcio Ajudarte Lopes, Pablo Agustin Vargas, Kris D. McCombe, Stephanie G. Craig, Jacqueline James, Jill Brooks, Paul Nankivell, Hisham Mehanna, Syed Ali Khurram, Nasir M. Rajpoot

“…Manual grading of OED is subject to substantial variability and does not reliably predict prognosis, potentially resulting in sub-optimal treatment decisions. Method We developed a Transformer-based artificial intelligence (AI) pipeline for the prediction of malignant transformation from whole-slide images (WSIs) of Haematoxylin and Eosin (H&E) stained OED tissue slides, named ODYN (Oral Dysplasia Network). …”
Get full text

Preparation of bainite phase microstructure by laser-electromagnetic induction hybrid solid-state phase transformation by Qunli Zhang, Lian You, Yi Yu, Zhijun Chen, Wenjian Wang, Mykola Anyakin, Jianhua Yao

“…In this paper, the surface heat treatment of 42CrMo steel is carried out by using a laser heat source to achieve complete austenitization, then with electromagnetic induction heating for several times to implement insulation, and eventually to promote bainite phase transformation. In conjunction with the temperature history curves, OM, SEM, and EBSD are used to characterize the bainite morphology and percentage of bainite via different parameters of the hybrid process. …”
Get full text

MSTNet: a multi-stage progressive network with local–global transformer fusion for image restoration by Ruyu Liu, Lin Wang, Jie He, Jiajia Wang, Jianhua Zhang, Xiufeng Liu, Chaochao Wang, Haoyu Zhang, Sheng Dai

“…In the medical field, image restoration techniques can significantly improve the quality of endoscopic images, helping doctors make more accurate diagnoses and providing higher-quality data support for computer vision-assisted detection. Existing methods for image restoration mainly use convolutional neural networks (CNNs) or Transformer models, which have different advantages and limitations in capturing spatial and channel information of the image. …”
Get full text

LMVT: A hybrid vision transformer with attention mechanisms for efficient and explainable lung cancer diagnosis by Jesika Debnath, Al Shahriar Uddin Khondakar Pranta, Amira Hossain, Anamul Sakib, Hamdadur Rahman, Rezaul Haque, Md.Redwan Ahmed, Ahmed Wasif Reza, S M Masfequier.Rahman Swapno, Abhishek Appaji

“…Furthermore, we integrate attention mechanisms based on the Convolutional Block Attention Module (CBAM) and feature selection techniques derived from the Simple Gray Level Difference Method (SGLDM) to improve discriminative focus and minimize redundancy. …”
Get full text

High‐frequency content within the QRS complex can predict ventricular tachyarrhythmias in hypertrophic cardiomyopathy by Takeshi Tsutsumi, Jun Yokomachi, Takafumi Nakajima, Kentaro Minami, Nami Takano, Kuniaki Iwasawa, Gaku Oguri, Shigeru Toyoda, Toshiaki Nakajima

“…We measured bipolar X, Y, and Z leads and calculated the frequency power using continuous wavelet transform (CWT). We compared frequency powers, ranging from 15 to 250 Hz, between patients with HCM with and without L‐VAs. …”
Get full text

General Solution of Linear Fractional Neutral Differential Difference Equations by Hai Zhang, Jinde Cao, Wei Jiang

“…This paper is concerned with the general solution of linear fractional neutral differential difference equations. The exponential estimates of the solution and the variation of constant formula for linear fractional neutral differential difference equations are derived by using the Gronwall integral inequality and the Laplace transform method, respectively. …”
Get full text

A Transformer-Based Approach for Efficient Geometric Feature Extraction from Vector Shape Data by Longfei Cui, Xinyu Niu, Haizhong Qian, Xiao Wang, Junkui Xu

“…The extraction of shape features from vector elements is essential in cartography and geographic information science, supporting a range of intelligent processing tasks. Traditional methods rely on different machine learning algorithms tailored to specific types of line and polygon elements, limiting their general applicability. …”
Get full text

Assessing the Generalization Capacity of Convolutional Neural Networks and Vision Transformers for Deforestation Detection in Tropical Biomes by P. J. Soto Vega, D. Lobo Torres, G. X. Andrade-Miranda, G. A. O. P. da Costa, R. Q. Feitosa

“…Deep Learning (DL) models, such as Convolutional Neural Networks (CNNs) and Vision Transformers (ViTs), have become popular for change detection tasks, including the deforestation mapping application. …”
Get full text

Fate-tox: fragment attention transformer for E(3)-equivariant multi-organ toxicity prediction by Sumin Ha, Dongmin Bang, Sun Kim

“…For variability of substructures, we used three fragmentation methods such as BRICS, Bemis-Murcko scaffolds, and RDKit Functional Groups to formulate fragment-level graphs so that diverse substructures can be used to identify toxicity for different organs. …”
Get full text

Multiscale feature fusion and enhancement in a transformer for the fine-grained visual classification of tree species by Yanqi Dong, Zhibin Ma, Jiali Zi, Fu Xu, Feixiang Chen

“…To address these challenges, we propose multiscale feature fusion (MFF) and enhancement in transformers to improve recognition performance. The method consists of a Swin transformer backbone, an MFF module, a discriminative feature enhancement (DFE) module, and a texture feature enhancement (TFE) module. …”
Get full text

A case study on entropy-aware block-based linear transforms for lossless image compression by Borut Žalik, David Podgorelec, Ivana Kolingerová, Damjan Strnad, Štefan Kohek

“…Many popular lossless compression methods incorporate predictions and various types of pixel transformations, in order to reduce the information entropy of an image. …”
Get full text