Yes / This article presented a novel compact multi-input-multi-output (MIMO) hexagonal monopole antenna with a uniplanar compact frequency-selective-surface (FSS) array for microwave imaging (MWI). The ultra-wideband (UWB) dual-element linear MIMO antenna was designed on the FR4 substrate with 50 Ω coplanar waveguide feed, T-strip isolation, novel numerical calculation, and equivalent circuit analyses. The main issues of realising high-resolution images based on planer UWB antenna for MWI are the low gain, omnidirectional pattern, design size, and mutual coupling of MIMO design. A novel technique was proposed to solve a hybrid issue (mutual coupling) of the MIMO reflected-waves from the FSS array and direct-wave. The uniplanar UWB-FSS unit cell was compacted by combining a square-loop and cross-dipole with a size of 0.095λ×0.095λ. The novel isolated UWB-MIMO antenna and UWB-FSS array (IMAF) were integrated, after investigating the distance between the antenna and FSS. The fabricated IMAF with a stable gain improvement of 4.5 dBi higher than the antenna without FSS, directional radiation pattern, size of 30×73.8×21.6 mm3 observed that a low mutual coupling of -27 dB, and operation bandwidth of 3.0-11.7 GHz. Moreover, a handbag was scanned experimentally via the bi-static approach to detect a small concealed object. The MWI system based on the MIMO antenna with FSS was displayed image resolution of 55% higher than that of MIMO antenna without FSS. The new baggage-scanner approach confirmed that the proposed MIMO antenna with FSS array can lead the humanity for healthy MWI applications.

<p dir="ltr">This thesis involves three topics related to forensic analysis of media data. The first topic is the analysis of images and documents that have been created with a scanner. The goal is to detect and identify scanner model from the scanned images/documents. We propose a deep learning system that can automatically learn the inherent features of the scanned images. This system will produce a scanner model identification and a reliability map for a scanned image. The proposed system has shown promising results in the forensic analysis of scanned images. The second topic is related to forensic integrity of scientific papers. The project is divided into multiple tasks, data collection, image extraction, and manipulation detection. We have constructed a dataset of retracted scientific papers that have been verified to have issues with integrity. We design and maintain a web-based Scientific Integrity System for forensic analysis of the images within scientific publications. The third topic is related to media document analysis. Our goal is to identify the publication style for media document, aiding in the potential document manipulation. We are mainly focusing on image-text consistency check, and synthetic tweets analysis. For image-text inconsistency check, we describe a system that can examine an image in document and the corresponding text caption (or other associated text with the image) to check the image/text consistency. For synthetic tweets analysis, we propose a system to detect and identify the text generation models and paraphrase attack models.</p>