Cluster based effective prediction approach for improving the curable rate of lymphatic filariasis affected patients

Rajagopal, Renuka Devi; Murugan, Saravanan; Kottursamy, Kottilingam; Raju, V.

doi:10.1007/s10586-018-2282-0

Cited by 14 publications

(2 citation statements)

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…It is common for IoT tools and sensors to be installed without considering the availability of potential vulnerabilities, making them vulnerable to eavesdropping and jamming, among other things (Baskar et al, 2020). If there is a state of security for any item, tangible or not, it is impossible to be in a state of security and yet be useful (Rajagopal et al, 2019). Objects are considered safe if they can retain their maximal inherent value under a variety of circumstances (Zhang et al, 2021).…”

Section: General Discussion About the Internet Of Things (Iot) In Sma...mentioning

confidence: 99%

Challenges and vulnerability evaluation of smart cities in IoT device based on cybersecurity mechanism

Almagrabi

2022

Expert Systems

View full text Add to dashboard Cite

In recent times, Cyber thieves discover new software vulnerabilities and attack vectors to take advantage of them. Cyber Security (CS) specialists are having a constant battle to stay on top of the latest threats. Knowledge sharing, sometimes called intelligence sharing, can enhance collective resilience and responsiveness in the face of dangers if peers are willing to share information proactively. Internet of Things (IoT) is the buzz word which integrates almost all the technology concerning computation and communication. Before the IoT goal can be fully realized, some barriers must be addressed, with security and privacy being two of the most essential. When IoT devices connect to an IoT gateway or other edge device, the sensor data they gather is either transmitted to the cloud for analysis or processed locally. Based on the received information, they act and it can expose a device as well as its data. Insufficient or no device authentication and authorization are common problems, as is poor or no encryption. Due to restricted energy supplies and low processing power, IoT security and privacy are complex, especially for resource‐constrained devices. In this article, IoT‐CS security problems and associated threats are discussed. The overarching goals were identifying assets and exploring possible threats, assaults, and vulnerabilities encountered by the IoT in the sectors like healthcare, transportation, utilities, safety, and environmental health that might be significantly improved with IoT‐CS deployment in smart cities. The predominant challenges in the deployment of the IoT related technologies had been studied in the aspects of cyber security and mitigation strategies had been discussed.

show abstract

Section: General Discussion About the Internet Of Things (Iot) In Sma...mentioning

confidence: 99%

Challenges and vulnerability evaluation of smart cities in IoT device based on cybersecurity mechanism

Almagrabi

2022

Expert Systems

View full text Add to dashboard Cite

show abstract

“…Synthetic underwater images were utilized for training a Convolutional Neural Network (CNN) model with CycleGAN. ANN has been in trend in recent years and finds its applications in a variety of domains including medicine [9,10]. A model to uplift the resolution and quality of SONAR images taken underwater using Generative Adversarial Network (GAN) was introduced by Sung et al [11].…”

Section: Introductionmentioning

confidence: 99%

A Novel AlphaSRGAN for Underwater Image Super Resolution

Cherian¹,

Poovammal²

2021

Computers, Materials &Amp; Continua

View full text Add to dashboard Cite

Obtaining clear images of underwater scenes with descriptive details is an arduous task. Conventional imaging techniques fail to provide clear cut features and attributes that ultimately result in object recognition errors. Consequently, a need for a system that produces clear images for underwater image study has been necessitated. To overcome problems in resolution and to make better use of the Super-Resolution (SR) method, this paper introduces a novel method that has been derived from the Alpha Generative Adversarial Network (AlphaGAN) model, named Alpha Super Resolution Generative Adversarial Network (AlphaSRGAN). The model put forth in this paper helps in enhancing the quality of underwater imagery and yields images with greater resolution and more concise details. Images undergo pre-processing before they are fed into a generator network that optimizes and reforms the structure of the network while enhancing the stability of the network that acts as the generator. After the images are processed by the generator network, they are passed through an adversarial method for training models. The dataset used in this paper to learn Single Image Super Resolution (SISR) is the USR 248 dataset. Training supervision is performed by an unprejudiced function that simultaneously scrutinizes and improves the image quality. Appraisal of images is done with reference to factors like local style information, global content and color. The dataset USR 248 which has a huge collection of images has been used for the study is composed of three collections of images-high (640 × 480) and low (80 × 60, 160 × 120, and 320 × 240). Paired instances of different sizes-2×, 4× and 8×-are also present in the dataset. Parameters like Mean Opinion Score (MOS), Peak Signal-to-Noise Ratio (PSNR), Structural Similarity (SSIM) and Underwater Image Quality Measure (UIQM) scores have been compared to validate the improved efficiency of our model when compared to existing works.

show abstract

Qualitative Study on Data Mining Algorithms for Classification of Mammogram Images

Arivazhagan

Govindarajan

2020

New Trends in Computational Vision and Bio-Inspired Computing

View full text Add to dashboard Cite

Cluster based effective prediction approach for improving the curable rate of lymphatic filariasis affected patients

Cited by 14 publications

References 7 publications

Challenges and vulnerability evaluation of smart cities in IoT device based on cybersecurity mechanism

Challenges and vulnerability evaluation of smart cities in IoT device based on cybersecurity mechanism

A Novel AlphaSRGAN for Underwater Image Super Resolution

Qualitative Study on Data Mining Algorithms for Classification of Mammogram Images

Contact Info

Product

Resources

About