Special Issue on “Optics for AI and AI for Optics”

Wei, Jinlong; Yi, Lilin; Cheng, Qixiang; Lau, Alan Pak Tao

doi:10.3390/app10093262

Cited by 7 publications

(3 citation statements)

References 21 publications

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“…The KNN classifier seems to be a basic, easy-to-implement supervised ML technique that could potentially be used to tackle classification and regression issues. This method is used to find people who have made fraudulent credit card purchases or filed fraudulent vehicle insurance claims [32]. The test data is represented by the green dot in Figure 5, while category A of the training set is represented by the blue squares and category B by the red triangles.…”

Section: • Support Vector Machine (Svm)mentioning

confidence: 99%

Identification of Security Issues and Finding their Solution in Cloud Computing

Himanshu Kalra

2024

IJRITCC

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The advent of Cloud Computing has simplified on-demand access to IT services including data storage and administration. In addition, it seeks to secure systems and make them functional. With these benefits, there are significant security constraints for cloud providers. When it comes to cloud computing, one of the biggest obstacles is ensuring the safety of data and services. Considering this, several solutions have been put into place to boost cloud security by keeping an eye on everything from resources to services to networks to identify and stop intrusions as soon as they occur. The term "Intrusion Detection System" (IDS) refers to an improved technique used to regulate network traffic and identify abnormal activity. This paper presents the identification of Security Issues and Finding their Solution in Cloud Computing using machine learning techniques including Support Vector Machine (SVM), Random Forest (RF), K-Nearest Neighbor (KNN), Multi-Layer Protocol (MLP). This model is trained and evaluated using NSL-KDD dataset. The experimental findings show the highest accuracy of 93.5% with the use of SVM model. As a result, the achieved results demonstrate strong performance concerning Accuracy, Precision, Recall, and F1-Score when compared to recent studies.

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Section: • Support Vector Machine (Svm)mentioning

confidence: 99%

Identification of Security Issues and Finding their Solution in Cloud Computing

Himanshu Kalra

2024

IJRITCC

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“…Support Vector Machine (SVM) is an asymmetrical identification of structure-based minimization [43] of possibility and a classification of linear and non-linear statistics datasets. The intention is to discern an agitated hydroplane within an N-dimensional space (Where N is the number of attributes) that predominantly classifies the statistics data points.…”

Section: F Artificial Intelligence Algorithm Helps To Detect Tumorsmentioning

confidence: 99%

Use of AI Techniques on Photonic Crystal Sensing for the Detection of Tumor

Sharma

Tharani

2022

j.electron.electromedical.eng.med.inform

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Tumors can cause severe problem to human beings. Sometime it can be a cause of death. Earlier there were lack of treatment and technological deficiency, due to which it was unable to detect tumor cells and even unable to offer proper treatment for these diseases. This study aims to use Photonic crystal (PhC) due to their ample choice of structures and litheness to endure with every sphere of influence has been utilized them twenty decade back to now a day and have extremely huge prospects in imminent future also. They have revealed their incidence in the field of imaging, sensing, fabricating industries, automation, medical, mechatronics, computronics, mechanochromic, underwater acoustic detection, pharma industries and nanoimprinting etc. If we are discussing about current and impending applications of PhC then it comprises smart sensing and detection of disunite diseases, anonymous viruses and a range of tumors. Artificial intelligence (AI) is also playing incredibly essential role in analyzing and creating entities equivalent to the change in human behavior. AI tools and techniques are utilizing to create intelligent entities through which it is accomplishing countless feats. The PhC along with the artificial intelligence are utilizing as Optical Neural Network (ONN), Artificial Neural Network (ANN), Cellular Computing, Plasma Technology, Parallel Processing, Image Processing etc. Here in this study designated photonic crystal has been used for the detection of infected cell in human body. Sometimes these infected cells are unable to trace by normal pathological investigations and slowly they take a shape of Tumors. But thanks to Photonics crystal sensors that they have made it true not only for detection but we can say for early detection of such tumors in human body. These early detection and proper investigation is possible only because of AI impacts on photonics crystal. This study focuses on detection and observation of bio molecules for selectivity, sensitivity, reflectivity and concentration. By change in wavelength i.e. from 1.5 μm to 4 μm the refractive index (RI) of tumor cell can be measured which is observed by measuring sensitivity between 11258 nm/RIU to 32358 nm/RIU. Tumors have refractive indices varies between 1.3342 to 1.4251. It is observed that sarcoma level is directly proportional to the RI of tumor. Various AI algorithms like support vector machine (SVM) obtained accuracy as 96%, K- nearest neighbor (KNN) shows as 70%, logistic regression (LR) shows as 88%, random forest (RF) show it as 90%, fuzzy logic (FL) and artificial neural network (ANN) observed accuracy as 93% and 95% respectively.

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“…The contributing field of photonics towards AI includes Neuro-morphic electronic system, Optical Neural Network (ONN), Nano Photonics, meta-materials, optical sensing, optical imaging [8], optical computing, Information Processing Machines etc. These above mentioned optics emerging domains can be integrated with AI tools [9] to enhance the efficiency and performance of these systems.…”

Section: Introductionmentioning

confidence: 99%

Photonics for AI and AI for Photonics: Material and Characteristics Integration

Sharma¹,

Tharani²

2021

Fiber Optics - Technology and Applications

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We are living in the technological era, where everything is integrated with each other. If we are discussing regarding communication, it is integrated with one or two technologies. If we are discussing regarding automation, discussing regarding Image processing, discussing regarding embedded system, they all are integrated with a combination of technologies. Correspondingly Artificial Intelligence (AI) and Photonics are also integrated with each other. Now a day as AI is utilizing with photonics in abundant fields as well photonics is also serving AI to facilitate ultrafast AI networks to offer a novel class of Information Processing Machines (IPM). This chapter is based on identification and implementation of photonics for AI utility and AI for photonics. In this category a Dual core Photonics crystal fiber (PCF) is proposed which serve to identify infected cells of human being along with the integration of AI. This proposed design of PCF is providing relative sensitivity and confinement loss in an optimized manner with the impact of AI. Here potency of AI as well as of Photonics is explained to serve their applications related to each other.

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Special Issue on “Optics for AI and AI for Optics”

Abstract: We live in an era of information explosion and digital revolution that has resulted in rapid technological developments in different aspects of life [...]

Cited by 7 publications

References 21 publications

Identification of Security Issues and Finding their Solution in Cloud Computing

Identification of Security Issues and Finding their Solution in Cloud Computing

Use of AI Techniques on Photonic Crystal Sensing for the Detection of Tumor

Photonics for AI and AI for Photonics: Material and Characteristics Integration

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