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Densely Convolutional BU-NET Framework for Breast Multi-Organ Cancer Nuclei Segmentation through Histopathological Slides and Classification Using Optimized Features

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Computer Modeling in Engineering & Sciences 2024年第12期141卷 2375-2397页

作者： Amjad Rehman Muhammad Mujahid robertas damasevicius Faten S.Alamri Tanzila Saba Artificial Intelligence&Data Analytics Lab College of Computer&Information Sciences(CCIS)Prince Sultan UniversityRiyadh11586Saudi Arabia Centre of Real Time Computer Systems Kaunas University of TechnologyKaunasLT-51386Lithuania Department of Mathematical Sciences College of SciencePrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia

This study aims to develop a computational pathology approach that can properly detect and distinguish histology *** is crucial for histopathological image analysis,as it involves segmenting cell ***,challenges exist,such as determining the boundary region of normal and deformed nuclei and identifying small,irregular nuclei *** learning approaches are currently dominant in digital pathology for nucleus recognition and classification,but their complex features limit their practical use in clinical *** existing studies have limited accuracy,significant processing costs,and a lack of resilience and generalizability across diverse *** proposed the densely convolutional Breast U-shaped Network(BU-NET)framework to overcome the mentioned *** study employs BU-NET’s spatial and channel attention methods to enhance segmentation *** inclusion of residual blocks and skip connections in the BU-NEt architecture enhances the process of extracting features and reconstructing the *** enhances the robustness of training and convergence processes by reducing the occurrence of vanishing *** primary objective of BU-NEt is to enhance the model’s capacity to acquire and analyze more intricate features,all the while preserving an efficient working *** BU-NET experiments demonstrate that the framework achieved 88.7%average accuracy,88.8%F1 score for Multi-Organ Nuclei Segmentation Challenge(MoNuSeg),and 91.2%average accuracy,91.8%average F1 for the triple-negative breast cancer(TNBC)*** framework also achieved 93.92 Area under the ROC Curve(AUC)for *** results demonstrated that the technology surpasses existing techniques in terms of accuracy and effectiveness in ***,it showcases the ability to withstand and recover from different tissue types and diseases,indicating possible uses in medical *** research evaluated the efficacy of the proposed method

关键词： Breast cancer histopathology BU-NET deep learning

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Convergence of blockchain and Internet of Things:integration, security, and use cases

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Frontiers of Information Technology & Electronic Engineering 2024年第10期25卷 1295-1321页

作者： robertas damasevicius Sanjay MISRA Rytis MASKELIUNAS Anand NAYYAR Department of Applied Informatics Vytautas Magnus UniversityKaunas 44404Lithuania Department of Applied Data Science Institute for Energy TechnologyHalden 17Norway Department of Multimedia Engineering Kaunas University of TechnologyKaunas 51368Lithuania Graduate School Faculty of Information TechnologyDuy Tan UniversityDa Nang 550000Viet Nam

Internet of Things(IoT) devices are becoming increasingly ubiquitous, and their adoption is growing at an exponential rate. However, they are vulnerable to security breaches, and traditional security mechanisms are not enough to protect them. The massive amounts of data generated by IoT devices can be easily manipulated or stolen, posing significant privacy concerns. This paper is to provide a comprehensive overview of the integration of blockchain and IoT technologies and their potential to enhance the security and privacy of IoT systems. The paper examines various security issues and vulnerabilities in IoT and explores how blockchain-based solutions can be used to address them. It provides insights into the various security issues and vulnerabilities in IoT and explores how blockchain can be used to enhance security and privacy. The paper also discusses the potential applications of blockchain-based IoT(B-IoT) systems in various sectors, such as healthcare, transportation, and supply chain management. The paper reveals that the integration of blockchain and IoT has the potential to enhance the security,privacy, and trustworthiness of IoT systems. The multi-layered architecture of B-IoT, consisting of perception, network, data processing, and application layers, provides a comprehensive framework for the integration of blockchain and IoT *** study identifies various security solutions for B-IoT, including smart contracts, decentralized control, immutable data storage,identity and access management(IAM), and consensus mechanisms. The study also discusses the challenges and future research directions in the field of B-IoT.

关键词： Blockchain Internet of Things(loT) Blockchain-based IoT(B-IoT) Security Scalability Privacy

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Performance of Deep Learning Techniques in Leaf Disease Detection

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Computer Systems Science & Engineering 2024年第5期48卷 1349-1366页

作者： robertas damasevicius Faheem Mahmood Yaseen Zaman Sobia Dastgeer Sajid Khan Centre of Real Time Computer Systems Kaunas University of TechnologyKaunas51386Lithuania Department of Computer Science Air UniversityIslamabad44000Pakistan Department of Computer Science City UniversityPeshawar25000Pakistan

Plant diseases must be identified as soon as possible since they have an impact on the growth of the corresponding ***,the identification of leaf diseases is essential in this field of *** brought on by bacteria,viruses,and fungi are a significant factor in reduced crop *** machine learning models have been applied in the identification of plant diseases,however,with the recent developments in deep learning,this field of study seems to hold huge potential for improved *** study presents an effective method that uses image processing and deep learning approaches to distinguish between healthy and infected *** effectively identify leaf diseases,we employed pre-trained models based on Convolutional Neural Networks(CNNs).There are four deepneural networks approaches used in this study:ConvolutionalNeuralNetwork(CNN),Inception-V3,Dense Net-121,and *** focus was on optimizing the hyper-parameters of these deep learningmodels with prior *** the evaluation of these deep neural networks,standard evaluation measures are used,such as F1-score,recall,precision,accuracy,and AreaUnderCurve(AUC).The overall outcomes showthe better performance of Inception-V3 with an achieved accuracy of 95.5%,as well as the performance of DenseNet-121 with an accuracy of 94.4%.VGG-16 performed well as well,with an accuracy of 93.3%,and CNN achieved an accuracy of 91.9%.

关键词： Smart agriculture deep learning plant disease recognition

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Mitochondria-localized β-actin is essential for priming innate antiviral immune signaling by regulating IRF3 protein stability

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Cellular & Molecular Immunology 2019年第10期16卷 837-840页

作者： Xin Xie Martin Endara-Coll Raza Mahmood robertas Jankauskas Tamara Gjorgjieva Piergiorgio Percipalle Science Division Biology ProgramNew York University Abu Dhabi(NYUAD)P.O.Box 129188 Abu DhabiUnited Arab Emirates Department of Molecular Biosciences The Wenner-Gren InstituteStockholm UniversitySE-10691StockholmSweden New York University Center for Genomics and Systems Biology NYUNew YorkNYUSA

Antiviral innate immunity acts as a defensive barrier to viral infection in both immune and nonimmune *** viral nucleic acids present in the cytoplasm after viral replication can activate sensors such as the RIG-I-lik... 详细信息

关键词： immunity immune stability

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Multiple conical odd harmonics from filament-inscribed nanogratings

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Photonics Research 2023年第11期11卷 1814-1819页

作者： robertas GRIGUTIS VYTAUTAS JUKNA GINTARAS TAMOŠAUSKAS AUDRIUS DUBIETIS Laser Research Center Vilnius UniversityLT-10223 VilniusLithuania

We report on the observation of conical third,fifth,seventh,and ninth harmonics that gradually emerge during the supercontinuum generation by filamentation of femtosecond midinfrared pulses in lithium strontium hexafluoroaluminate *** show that the generation of conical odd harmonics is an optical signature of lightdriven material reorganization in the form of volume nanogratings at the site irradiated by repetitive femtosecond *** angle-resolved spectral measurements demonstrate remarkably broad spectra of individual odd harmonics,benefiting from a spectrally broadened pump pulse(supercontinuum),and reveal that filamentinscribed nanogratings represent photonic structures that are able to provide ultrabroad phase-matching bandwidths covering the wavelength range from the ultraviolet to the near *** propose a scenario that interprets the generation of conical fifth,seventh,and ninth harmonics as nanograting phase-matched cascaded noncollinear four-wave mixing processes.

关键词： pump harmonics conical

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Multi-Layered Deep Learning Features Fusion for Human Action Recognition

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Computers, Materials & Continua 2021年第12期69卷 4061-4075页

作者： Sadia Kiran Muhammad Attique Khan Muhammad Younus Javed Majed Alhaisoni Usman Tariq Yunyoung Nam robertas Damaševicius Muhammad Sharif Department of Computer Science HITEC University TaxilaTaxilaPakistan College of Computer Science and Engineering University of Ha’ilHa’ilSaudi Arabia College of Computer Engineering and Sciences Prince Sattam Bin Abdulaziz UniversityAl-KhrajSaudi Arabia Department of Computer Science and Engineering Soonchunhyang UniversityAsanKorea Faculty of Applied Mathematics Silesian University of TechnologyGliwicePoland Department of Computer Science COMSATS University IslamabadWah CampusPakistan

Human Action Recognition(HAR)is an active research topic in machine learning for the last few *** surveillance,robotics,and pedestrian detection are the main applications for action *** vision researchers have introduced many HAR techniques,but they still face challenges such as redundant features and the cost of *** this article,we proposed a new method for the use of deep learning for *** the proposed method,video frames are initially pre-processed using a global contrast approach and later used to train a deep learning model using domain transfer *** Resnet-50 Pre-Trained Model is used as a deep learning model in this *** are extracted from two layers:Global Average Pool(GAP)and Fully Connected(FC).The features of both layers are fused by the Canonical Correlation Analysis(CCA).Then features are selected using the Shanon Entropy-based threshold *** selected features are finally passed to multiple classifiers for final *** are conducted on five publicly available datasets as IXMAS,UCF Sports,YouTube,UT-Interaction,and *** accuracy of these data sets was 89.6%,99.7%,100%,96.7%and 96.6%,*** with existing techniques has shown that the proposed method provides improved accuracy for ***,the proposed method is computationally fast based on the time of execution.

关键词： Action recognition transfer learning features fusion features selection classification

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企鹅享受“难以置信的泡泡”体验（英文）

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英语画刊(高中版) 2020年第33期 10-11页

作者： robertas Lisickis

为了让动物园里的企鹅在疫情期间保持活力和好心情,英国纽基动物园决定为企鹅们安装一个泡泡机。Considering how fun bubbles can actually be,the Newquay Zoo recently decided to install a bubble machine in their penguin enclosure in hopes of keeping the very social birds entertained during the lockdown when visitor counts sank to ***,oh boy,did the penguins have some fun.

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区块链和物联网的融合：集成、安全性和用例（英文）

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Frontiers of Information Technology & Electronic Engineering 2024年第10期 1295-1322页

作者： robertas DAMA?EVI?IUS Sanjay MISRA Rytis MASKELIūNAS Anand NAYYAR 维陶塔斯·马格努斯大学应用信息学系能源技术研究所应用数据科学系考纳斯理工大学多媒体工程系维新大学信息技术学院研究生院

物联网（Io T）设备变得越来越普遍，其采用率呈指数级增长。然而，它们很容易受到安全漏洞的影响，传统的安全机制不足以保护它们。物联网设备生成的大量数据很容易被操纵或窃取，从而带来严重的隐私问题。本文旨在全面概述区块链和物... 详细信息

物联网（Io T）设备变得越来越普遍，其采用率呈指数级增长。然而，它们很容易受到安全漏洞的影响，传统的安全机制不足以保护它们。物联网设备生成的大量数据很容易被操纵或窃取，从而带来严重的隐私问题。本文旨在全面概述区块链和物联网技术的集成及其增强物联网系统安全性和隐私性的潜力。研究了物联网中的各种安全问题和漏洞，探讨如何使用基于区块链的方案来解决这些问题。提供了对物联网中各种安全问题和漏洞的见解，并探讨如何使用区块链来增强安全性和隐私性。还讨论了基于区块链的物联网（BIo T）系统在医疗保健、运输和供应等各个领域的潜在应用。揭示了区块链和物联网的集成可增强物联网系统的安全性、隐私性和可信度。B-Io T的多层架构包括感知层、网络层、数据处理层和应用层，为区块链和物联网技术的集成提供了全面的框架。该研究确定了B-Io T的各种安全解决方案，包括智能合约、去中心化控制、不可变数据存储、身份和访问管理（IAM）以及共识机制。该研究还讨论了B-Io T领域的挑战和未来研究方向。

关键词：区块链物联网(Io T) 基于区块链的物联网(B-Io T) 安全性可扩展性隐私

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