Employing Remote Sensing, Data Communication Networks, AI, and Optimization Methodologies in Seismology

Abdalzaher, Mohamed S.; El-Sayed, Hesham; Fouda, Mostafa M.

doi:10.1109/jstars.2022.3216998

Cited by 26 publications

(6 citation statements)

References 197 publications

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“…Geophysics and Seismology: Filtering plays a critical role in the analysis of seismic data. Filters help identify earthquake events, locate underground structures, and study ground motion characteristics in geophysics and seismology [63].…”

Section: Other Application Fields Of Filtering Methodsmentioning

confidence: 99%

Filtering Methods for Biomedical Image Denoising

Zhao

2023

Preprint

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In this paper, the filtering method of biomedical image denoising is described comprehensively. Firstly, it introduces the biomedical image denoising, describes the relationship between biomedical image denoising and medical care, introduces the filtering methods, the filtering methods of biomedical image denoising, the challenges encountered by the current filtering methods, and other application fields of filtering methods. Firstly, the background of biomedical image denoising is introduced. Biomedical image denoising is a challenge. Different imaging modes have different noise characteristics, and noise levels can vary greatly depending on the specific application. Secondly, it describes that biomedical image denoising plays an important role in medical care, and the biomedical image directly affects the patient's diagnosis, treatment plan and the overall quality of medical care service. Then the filtering method is introduced in detail, describing the core concepts and related features of linear filtering, nonlinear filtering and frequency domain filtering, and then focusing on the adaptive filtering method, describing the characteristics, conditions of use, common algorithms and advantages of adaptive filtering method. Then the filter methods of biomedical image denoising are introduced, and the core concepts of Gaussian filter, median filter, total variation denoising and Wiener filter are introduced respectively. Then, the challenges encountered by filtering methods are described, such as the accurate selection of filters, the balance between noise reduction and image detail preservation are introduced. Finally, the application of filtering method in other fields is mentioned, such as audio processing, speech recognition and so on. In summary, this paper comprehensively expounds the denoising and filtering methods of biomedical images, the filtering methods of medical image denoising, the relationship between medical image denoising and medical care, and the challenges encountered by filtering methods.

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Section: Other Application Fields Of Filtering Methodsmentioning

confidence: 99%

Filtering Methods for Biomedical Image Denoising

Zhao

2023

Preprint

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“…To address the scalability issues associated with model checking, partial, order reduction (POR) techniques have been developed. POR is a state space, reduction technique that, aims to minimize the number of states needed to be, examined during the, verification process without losing the ability to detect errors (Abdalzaher et al, 2022;Abdalzaher et al, 2019;Krichen et al, 2022). It works on the principle that many, different interleaving's of independent, actions do, not need to be considered separately, as they produce equivalent outcomes, with respect to the properties being verified.…”

Section: Literature Reviewmentioning

confidence: 99%

Enhancing Computer Security through Formal Verification of Cryptographic Protocols Using Model Checking and Partial Order Techniques

Saeed,

Ibrar,

Mahmood

et al. 2024

ABBDM

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This study explores the integration of partial, order reduction techniques with model checking to enhance the verification of cryptographic protocols. Cryptographic, protocols are essential for securing digital communications, and data; however, ensuring their robustness and reliability through traditional verification methods can be challenging due to, their complexity and the vast number of potential executions, paths. This research utilizes the SPIN, model checker and PROMELA language to model and verify three types of, cryptographic protocols: a basic authentication handshake, an encrypted data transfer, protocol, and a complex, multi-factor authentication process. Each protocol was, verified with and, without the application of partial order reduction techniques. The findings demonstrate that partial order, reduction, not only significantly reduces the computational resources, required—by approximately 40%—but also maintains the thoroughness needed to identify critical, security flaws such as replay, attacks, data integrity breaches, and authentication failures. This study, underscores the, efficacy of combining partial order reduction with model, checking, proposing that this, approach significantly improves the scalability and efficiency, of cryptographic protocol, verification. The results advocate, for the continued development and application of these, techniques to ensure the secure and reliable deployment of cryptographic protocols in various digital environments

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“…According to [40] and [48], an indicative definition of the IoT comprises IP-enabled devices, which may communicate with one another to aid data gathering and analysis as well as system monitoring and control. Additionally, smart monitoring and control may be accomplished if the system is intelligent.…”

Section: Smartness and Iotmentioning

confidence: 99%

Toward Secured IoT-Based Smart Systems Using Machine Learning

et al. 2023

Self Cite

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Machine learning (ML) and the internet of things (IoT) are among the most booming research directions. Smart cities, smart campuses (SCs), smart homes, smart cars, early warning systems (EWSs), etc.; or it could be called ''Smart x'' systems are implemented using ML and IoT. Those systems will alter how various world entities communicate with one another. This paper spots light on the significant roles of the IoT in SS. Also, it focuses on the importance of ML in IoT-based SS. Besides, an overview of smartness and IoT is presented. Then, this paper offers ML benchmarking along with a taxonomy that categorizes the ML models into linear and non-linear ones depending on the problem type (classification or regression). Afterward, the commonly utilized evaluation metrics are provided. In addition, this paper considers the trust techniques used for mitigating different security aspects in IoT networks, which play a crucial part in regulating the new era of communication. Moreover, two case studies devoting ML for IoT-based SS, namely IoT-based SC and IoT-based EWS, are considered for data collection and manipulation with guided research directions. Finally, the paper presents effective recommendations of ML's significant roles in SC and earthquake EWS for interested scholars.INDEX TERMS Machine learning, Internet of Things, smart systems, security.

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Employing Remote Sensing, Data Communication Networks, AI, and Optimization Methodologies in Seismology

Cited by 26 publications

References 197 publications

Filtering Methods for Biomedical Image Denoising

Filtering Methods for Biomedical Image Denoising

Enhancing Computer Security through Formal Verification of Cryptographic Protocols Using Model Checking and Partial Order Techniques

Toward Secured IoT-Based Smart Systems Using Machine Learning

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