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U-Net Inspired Deep Neural Network-Based Smoke Plume Detection in Satellite Images

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Computers, Materials & Continua 2024年第4期79卷 779-799页

作者： Ananthakrishnan Balasundaram Ayesha Shaik Japmann Kaur Banga Aman Kumar Singh Centre for Cyber Physical Systems Vellore Institute of Technology(VIT)ChennaiTamil Nadu600127India School of Computer Science and Engineering Vellore Institute of Technology(VIT)ChennaiTamil Nadu600127India

Industrial activities, through the human-induced release of Green House Gas (GHG) emissions, have beenidentified as the primary cause of global warming. Accurate and quantitative monitoring of these emissions isessential for a comprehensive understanding of their impact on the Earth’s climate and for effectively enforcingemission regulations at a large scale. This work examines the feasibility of detecting and quantifying industrialsmoke plumes using freely accessible geo-satellite imagery. The existing systemhas so many lagging factors such aslimitations in accuracy, robustness, and efficiency and these factors hinder the effectiveness in supporting timelyresponse to industrial fires. In this work, the utilization of grayscale images is done instead of traditional colorimages for smoke plume detection. The dataset was trained through a ResNet-50 model for classification and aU-Net model for segmentation. The dataset consists of images gathered by European Space Agency’s Sentinel-2 satellite constellation from a selection of industrial sites. The acquired images predominantly capture scenesof industrial locations, some of which exhibit active smoke plume emissions. The performance of the abovementionedtechniques and models is represented by their accuracy and IOU (Intersection-over-Union) metric.The images are first trained on the basic RGB images where their respective classification using the ResNet-50model results in an accuracy of 94.4% and segmentation using the U-Net Model with an IOU metric of 0.5 andaccuracy of 94% which leads to the detection of exact patches where the smoke plume has occurred. This work hastrained the classification model on grayscale images achieving a good increase in accuracy of 96.4%.

关键词： Smoke plume ResNet-50 U-Net geo satellite images early warning global monitoring

Intrusion Detection Model Using Chaotic MAP for Network Coding Enabled Mobile Small Cells

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Computers, Materials & Continua 2024年第3期78卷 3151-3176页

作者： Chanumolu Kiran Kumar Nandhakumar Ramachandran School of Computer Science and Engineering VIT-AP UniversityAmaravatiAndhra Pradesh522241India

Wireless Network security management is difficult because of the ever-increasing number of wireless network malfunctions,vulnerabilities,and assaults.Complex security systems,such as Intrusion Detection Systems(IDS),are essential due to the limitations of simpler security measures,such as cryptography and firewalls.Due to their compact nature and low energy reserves,wireless networks present a significant challenge for security procedures.The features of small cells can cause threats to the network.Network Coding(NC)enabled small cells are vulnerable to various types of attacks.Avoiding attacks and performing secure“peer”to“peer”data transmission is a challenging task in small cells.Due to the low power and memory requirements of the proposed model,it is well suited to use with constrained small cells.An attacker cannot change the contents of data and generate a new Hashed Homomorphic Message Authentication Code(HHMAC)hash between transmissions since the HMAC function is generated using the shared secret.In this research,a chaotic sequence mapping based low overhead 1D Improved Logistic Map is used to secure“peer”to“peer”data transmission model using lightweight H-MAC(1D-LM-P2P-LHHMAC)is proposed with accurate intrusion detection.The proposed model is evaluated with the traditional models by considering various evaluation metrics like Vector Set Generation Accuracy Levels,Key Pair Generation Time Levels,Chaotic Map Accuracy Levels,Intrusion Detection Accuracy Levels,and the results represent that the proposed model performance in chaotic map accuracy level is 98%and intrusion detection is 98.2%.The proposed model is compared with the traditional models and the results represent that the proposed model secure data transmission levels are high.

关键词： Network coding small cells data transmission intrusion detection model hashed message authentication code chaotic sequence mapping secure transmission

MAIPFE:An Efficient Multimodal Approach Integrating Pre-Emptive Analysis,Personalized Feature Selection,and Explainable AI

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Computers, Materials & Continua 2024年第5期79卷 2229-2251页

作者： Moshe Dayan Sirapangi S.Gopikrishnan School of Computer Science and Engineering VIT-AP UniversityAmaravathiAndhra Pradesh522241India

Medical Internet of Things(IoT)devices are becoming more and more common in healthcare.This has created a huge need for advanced predictive health modeling strategies that can make good use of the growing amount of multimodal data to find potential health risks early and help individuals in a personalized way.Existing methods,while useful,have limitations in predictive accuracy,delay,personalization,and user interpretability,requiring a more comprehensive and efficient approach to harness modern medical IoT devices.MAIPFE is a multimodal approach integrating pre-emptive analysis,personalized feature selection,and explainable AI for real-time health monitoring and disease detection.By using AI for early disease detection,personalized health recommendations,and transparency,healthcare will be transformed.The Multimodal Approach Integrating Pre-emptive Analysis,Personalized Feature Selection,and Explainable AI(MAIPFE)framework,which combines Firefly Optimizer,Recurrent Neural Network(RNN),Fuzzy C Means(FCM),and Explainable AI,improves disease detection precision over existing methods.Comprehensive metrics show the model’s superiority in real-time health analysis.The proposed framework outperformed existing models by 8.3%in disease detection classification precision,8.5%in accuracy,5.5%in recall,2.9%in specificity,4.5%in AUC(Area Under the Curve),and 4.9%in delay reduction.Disease prediction precision increased by 4.5%,accuracy by 3.9%,recall by 2.5%,specificity by 3.5%,AUC by 1.9%,and delay levels decreased by 9.4%.MAIPFE can revolutionize healthcare with preemptive analysis,personalized health insights,and actionable recommendations.The research shows that this innovative approach improves patient outcomes and healthcare efficiency in the real world.

关键词： Predictive health modeling Medical Internet of Things explainable artificial intelligence personalized feature selection preemptive analysis

Correlation Composition Awareness Model with Pair Collaborative Localization for IoT Authentication and Localization

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Computers, Materials & Continua 2024年第4期79卷 943-961页

作者： Kranthi Alluri S.Gopikrishnan School of Computer Science and Engineering VIT-AP UniversityAmaravathiAndhra Pradesh522241India

Secure authentication and accurate localization among Internet of Things(IoT)sensors are pivotal for the functionality and integrity of IoT networks.IoT authentication and localization are intricate and symbiotic,impacting both the security and operational functionality of IoT systems.Hence,accurate localization and lightweight authentication on resource-constrained IoT devices pose several challenges.To overcome these challenges,recent approaches have used encryption techniques with well-known key infrastructures.However,these methods are inefficient due to the increasing number of data breaches in their localization approaches.This proposed research efficiently integrates authentication and localization processes in such a way that they complement each other without compromising on security or accuracy.The proposed framework aims to detect active attacks within IoT networks,precisely localize malicious IoT devices participating in these attacks,and establish dynamic implicit authentication mechanisms.This integrated framework proposes a Correlation Composition Awareness(CCA)model,which explores innovative approaches to device correlations,enhancing the accuracy of attack detection and localization.Additionally,this framework introduces the Pair Collaborative Localization(PCL)technique,facilitating precise identification of the exact locations of malicious IoT devices.To address device authentication,a Behavior and Performance Measurement(BPM)scheme is developed,ensuring that only trusted devices gain access to the network.This work has been evaluated across various environments and compared against existing models.The results prove that the proposed methodology attains 96%attack detection accuracy,84%localization accuracy,and 98%device authentication accuracy.

关键词： Sensor localization IoT authentication network security data accuracy precise location access control security framework

Trusted Certified Auditor Using Cryptography for Secure Data Outsourcing and Privacy Preservation in Fog-Enabled VANETs

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Computers, Materials & Continua 2024年第5期79卷 3089-3110页

作者： Nagaraju Pacharla K.Srinivasa Reddy School of Computer Science and Engineering VIT-AP UniversityAmaravatiAndhra Pradesh522237India

With the recent technological developments,massive vehicular ad hoc networks(VANETs)have been established,enabling numerous vehicles and their respective Road Side Unit(RSU)components to communicate with oneanother.The best way to enhance traffic flow for vehicles and traffic management departments is to share thedata they receive.There needs to be more protection for the VANET systems.An effective and safe methodof outsourcing is suggested,which reduces computation costs by achieving data security using a homomorphicmapping based on the conjugate operation of matrices.This research proposes a VANET-based data outsourcingsystem to fix the issues.To keep data outsourcing secure,the suggested model takes cryptography models intoaccount.Fog will keep the generated keys for the purpose of vehicle authentication.For controlling and overseeingthe outsourced data while preserving privacy,the suggested approach considers the Trusted Certified Auditor(TCA).Using the secret key,TCA can identify the genuine identity of VANETs when harmful messages aredetected.The proposed model develops a TCA-based unique static vehicle labeling system using cryptography(TCA-USVLC)for secure data outsourcing and privacy preservation in VANETs.The proposed model calculatesthe trust of vehicles in 16 ms for an average of 180 vehicles and achieves 98.6%accuracy for data encryption toprovide security.The proposedmodel achieved 98.5%accuracy in data outsourcing and 98.6%accuracy in privacypreservation in fog-enabled VANETs.Elliptical curve cryptography models can be applied in the future for betterencryption and decryption rates with lightweight cryptography operations.

关键词： Vehicular ad-hoc networks data outsourcing privacy preservation cryptography keys trusted certified auditors data security

New avenues for the treatment of immunotherapy-resistant pancreatic cancer

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World Journal of Gastrointestinal Oncology 2024年第4期16卷 1134-1153页

作者： Luis Guilherme de Oliveira Silva Fabian Fellipe Bueno Lemos Marcel Silva Luz Samuel Luca Rocha Pinheiro Mariana dos Santos Calmon Gabriel Lima Correa Santos Gabriel Reis Rocha Fabrício Freire de Melo Instituto Multidisciplinar em Saúde Universidade Federal da BahiaVitória da Conquista 45029-094BahiaBrazil

Pancreatic cancer(PC)is characterized by its extremely aggressive nature and ranks 14th in the number of new cancer cases worldwide.However,due to its complexity,it ranks 7th in the list of the most lethal cancers worldwide.The pathogenesis of PC involves several complex processes,including familial genetic factors associated with risk factors such as obesity,diabetes mellitus,chronic pancreatitis,and smoking.Mutations in genes such as KRAS,TP53,and SMAD4 are linked to the appearance of malignant cells that generate pancreatic lesions and,consequently,cancer.In this context,some therapies are used for PC,one of which is immunotherapy,which is extremely promising in various other types of cancer but has shown little response in the treatment of PC due to various resistance mechanisms that contribute to a drop in immunotherapy efficiency.It is therefore clear that the tumor microenvironment(TME)has a huge impact on the resistance process,since cellular and non-cellular elements create an immunosuppressive environment,characterized by a dense desmoplastic stroma with cancerassociated fibroblasts,pancreatic stellate cells,extracellular matrix,and immunosuppressive cells.Linked to this are genetic mutations in TP53 and immunosuppressive factors that act on T cells,resulting in a shortage of CD8+T cells and limited expression of activation markers such as interferon-gamma.In this way,finding new strategies that make it possible to manipulate resistance mechanisms is necessary.Thus,techniques such as the use of TME modulators that block receptors and stromal molecules that generate resistance,the use of genetic manipulation in specific regions,such as microRNAs,the modulation of extrinsic and intrinsic factors associated with T cells,and,above all,therapeutic models that combine these modulation techniques constitute the promising future of PC therapy.Thus,this study aims to elucidate the main mechanisms of resistance to immunotherapy in PC and new ways of manipulating this process,resulting in a more efficient therapy

关键词： Pancreatic cancer Immunotherapy Resistance Tumor microenvironment manipulation Combined immunotherapy

Immune pathway through endometriosis to ovarian cancer

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World Journal of Clinical Oncology 2024年第4期15卷 496-522页

作者： Mariana Santos Calmon Fabian Fellipe Bueno Lemos Marcel Silva Luz Samuel Luca Rocha Pinheiro Luis Guilherme de Oliveira Silva Gabriel Lima Correa Santos Gabriel Reis Rocha Fabrício Freire de Melo Instituto Multidisciplinar em Saúde Universidade Federal da BahiaVitória da Conquista 45029-094BahiaBrazil

Endometriosis is an estrogen-dependent inflammatory disease,defined by the presence of functional endometrial tissue outside of the uterine cavity.This disease is one of the main gynecological diseases,affecting around 10%-15%women and girls of reproductive age,being a common gynecologic disorder.Although endometriosis is a benign disease,it shares several characteristics with invasive cancer.Studies support that it has been linked with an increased chance of developing endometrial ovarian cancer,representing an earlier stage of neoplastic processes.This is particularly true for women with clear cell carcinoma,low-grade serous carcinoma and endometrioid.However,the carcinogenic pathways between both pathologies remain poorly understood.Current studies suggest a connection between endometriosis and endometriosis-associated ovarian cancers(EAOCs)via pathways associated with oxidative stress,inflammation,and hyperestrogenism.This article aims to review current data on the molecular events linked to the development of EAOCs from endometriosis,specifically focusing on the complex relationship between the immune response to endometriosis and cancer,including the molecular mechanisms and their ramifications.Examining recent developments in immunotherapy and their potential to boost the effectiveness of future treatments.

关键词： Ovarian neoplasms Endometriosis Endometriosis-associated ovarian cancers Immune response Immunotherapy

不均匀海底地形影响下柔性板与斜向来浪的相互作用

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哈尔滨工程大学学报（英文版） 2024年第2期23卷 261-275页

作者： Saista Tabssum Balaji Ramakrishnan School of Advanced Science-Mathematics VIT-APAmravati744101India Department of Civil Engineering Indian Institute of TechnologyBombay 400076India

The present work analyzes the interaction of oblique waves by a porous flexible breakwater in the presence of a step-type bottom.The physical models for both scattering and trapping cases are considered and developed within the framework of small amplitude water-wave theory.Darcy’s law is used to model the wave interaction with the porous medium.It is assumed that the varying bottom extends over a finite interval,connected by a finite length of uniform bottom near an impermeable wall,and a semi-infinite length of bottom in the open water region.The boundary value problem is solved using the eigenfunction expansion method in the uniform bottom regions,while a modified mild-slope equation(MMSE)is used for the region with the varying bottom.Additionally,a mass-conserving jump condition is employed to handle the solution at slope discontinuities in the bottom.A system of equations is derived by matching the solutions at interfaces.The reflection coefficient and force on the breakwater and impermeable wall are plotted and analyzed for various parameters,such as the length of the varying bottom,depth ratio,angle of incidence,and flexural rigidity.It is observed that moderate values of flexural rigidity and depth ratio significantly contribute to an optimum reflection coefficient and reduce the wave force on the wall and breakwater.Remarkably,the outcomes of this study are assumed to be applicable in the construction of this type of breakwater in coastal regions.

关键词： Porous flexible breakwater Varying bottom Mild-slope equation Reflection coefficient Wave force

Usher syndrome:Genetic diagnosis and current therapeutic approaches

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World Journal of Otorhinolaryngology 2024年第1期11卷 1-17页

作者： Beatriz Rocha Cuzzuol Jonathan Santos Apolonio Ronaldo Teixeira da Silva Júnior Lorena Sousa de Carvalho Luana Kauany de SáSantos Luciano Hasimoto Malheiro Marcel Silva Luz Mariana Santos Calmon Henrique de Lima Crivellaro Fabian Fellipe Bueno Lemos Fabrício Freire de Melo Instituto Multidisciplinar em Saúde Universidade Federal da BahiaVitória da Conquista 45029-094BahiaBrazil

Usher Syndrome(USH)is the most common deaf-blind syndrome,affecting approximately 1 in 6000 people in the deaf population.This genetic condition is characterized by a combination of hearing loss(HL),retinitis pigmentosa,and,in some cases,vestibular areflexia.Among the subtypes of USH,USH type 1 is considered the most severe form,presenting profound bilateral congenital deafness,vestibular areflexia,and early onset RP.USH type 2 is the most common form,exhibiting congenital moderate to severe HL for low frequencies and severe to profound HL for high frequencies.Conversely,type 3 is the rarest,initially manifesting mild symptoms during childhood that become more prominent in the first decades of life.The dual impact of USH on both visual and auditory senses significantly impairs patients'quality of life,restricting their daily activities and interactions with society.To date,9 genes have been confirmed so far for USH:MYO7A,USH1C,CDH23,PCDH15,USH1G,USH2A,ADGRV1,WHRN and CLRN1.These genes are inherited in an autosomal recessive manner and encode proteins expressed in the inner ear and retina,leading to functional loss.Although non-genetic methods can assist in patient triage and disease extension evaluation,genetic and molecular tests play a pivotal role in providing genetic counseling,enabling appropriate gene therapy,and facilitating timely cochlear implantation(CI).The CRISPR/Cas9 system and viral-based gene replacement therapy have recently emerged as highly promising techniques for treating USH.Regarding drug therapy,PTC-124 and Nb54 have been identified as promising drug interventions for genetic HL in USH.Simultaneously,CI has proven to be critical in the restoration of hearing.This review aims to summarize the genetic and molecular diagnosis of USH and highlight the importance of early diagnosis in Cuzzuol BR et al.Diagnosis and current treatments of USH WJO https://*** 2 January 19,2024 Volume 11 Issue 1 guiding appropriate treatment strategies and improving patient prognosis.

关键词： Usher syndromes Hearing loss Retinitis pigmentosa Diagnosis Genetic therapies Cochlear implantation Quality of life