Gate-induced drain leakage in FD-SOI devices: What the TFET teaches us about the MOSFET

This paper compares the gate-induced drain leakage (GIDL) in fully-depleted (FD) silicon-on-insulator (SOI) tunneling field effect transistor (TFET) and in standard metal-oxide-semiconductor FET (MOSFET) fabricated in the same process. The measurements show that the MOSFET GIDL current is lower than the GIDL in a TFET with the same junction doping, especially for devices with thick gate oxide and under low drain bias. A model describing lateral band-to-band tunneling (BTBT) is developed for GIDL in the FD-SOI TFET. By combining the model of gate-controllable tunneling diode in series with a field effect diode, we achieve an accurate picture of GIDL in FD-SOI MOSFETs.     

GIFMarking: The robust watermarking for animated GIF based deep learning

Animated GIF has become a key communication tool in contemporary social platforms thanks to highly compatible with affective performance, and it is gradually adopted in commercial applications. Therefore, the copyright protection of the animated GIF requires more attention. Digital watermarking is an effective method to embed invisible data into a digital medium that can identify the creator or authorized users. However, few works have been devoted to robust watermarking for the animated GIF. One of the main challenges is that the animated image also contains time frame dimension information compare with still images. This paper proposes a robust blind watermarking framework based 3D convolutional neural networks for the animated GIF image, which achieves watermark image embedding and extraction for the animated GIF. Also, noise simulation is developed in frame-level to ensure robustness for the attack of the temporal dimension in this framework. Furthermore, the invisibility of the watermarked animated image is optimized by adversarial learning. Experimental results provide the effectiveness of the proposed framework and show advantages over existing works.     

Single-Cell Microgels for Diagnostics and Therapeutics

Cell encapsulation within hydrogel droplets is transforming what is feasible in multiple fields of biomedical science such as tissue engineering and regenerative medicine, in vitro modeling, and cell-based therapies. Recent advances have allowed researchers to miniaturize material encapsulation complexes down to single-cell scales, where each complex, termed a single-cell microgel, contains only one cell surrounded by a hydrogel matrix while remaining <100 μm in size. With this achievement, studies requiring single-cell resolution are now possible, similar to those done using liquid droplet encapsulation. Of particular note, applications involving long-term in vitro cultures, modular bioinks, high-throughput screenings, and formation of 3D cellular microenvironments can be tuned independently to suit the needs of individual cells and experimental goals. In this progress report, an overview of established materials and techniques used to fabricate single-cell microgels, as well as insight into potential alternatives is provided. This focused review is concluded by discussing applications that have already benefited from single-cell microgel technologies, as well as prospective applications on the cusp of achieving important new capabilities.     

The reconstruction and application of virtual Chinese human female

The virtual human is an interactive computer model integrating anatomical, biophysical, physiological and biomechanical characteristics of human being. The virtual Chinese human female number 1 (VCH-F1) is a high-resolution dataset of a standard Chinese female.This paper covers our 5-year work with VCH-F1 dataset. We will introduce the reconstruction of VCH-F1 three-dimensional (3D) model and our efforts to put this dataset into practical task such as the construction of the health sciences educational facilities, the research about the mechanism of acupuncture and the realization of virtual image-guided neurosurgery.Our experience with this work demonstrates a broad scope and variety of applications of VCH-F1 dataset in medicine and biology. Further works still need to be done to make this dataset a routine clinical tool.     

Artistic collaboration in designing VR visualizations

This article describes one of the recent major collaborative efforts, a class on designing VR scientific visualizations that was co-taught with professors and students from Brown University's computer science department and the Rhode Island School of Design's (RISD's) illustration department. We discuss here the experiences that led us to this conclusion; along with some of the tools we have developed to facilitate working with artists. Many of the experiences and conclusions relayed here are the results of this class. We then discuss three important themes that we derived from our experiences, which are all motivated by a desire to better facilitate artistic collaborations.     

A hierarchical digital watermarking method for image tamper detection and recovery

In this paper, we present an efficient and effective digital watermarking method for image tamper detection and recovery. Our method is efficient as it only uses simple operations such as parity check and comparison between average intensities. It is effective because the detection is based on a hierarchical structure so that the accuracy of tamper localization can be ensured. That is, if a tampered block is not detected in level-1 inspection, it will be detected in level-2 or level-3 inspection with a probability of nearly 1. Our method is also very storage effective, as it only requires a secret key and a public chaotic mixing algorithm to recover a tampered image. The experimental results demonstrate that the precision of tamper detection and localization is 99.6% and 100% after level-2 and level-3 inspection, respectively. The tamper recovery rate is better than 93% for a less than half tampered image. As compared with the method in Celik et al. [IEEE Trans. Image Process. 11(6) (2002) 585], our method is not only as simple and as effective in tamper detection and localization, it also provides with the capability of tamper recovery by trading off the quality of the watermarked images about 5 dB.     

An Enhanced Parallel Loop Self-Scheduling Scheme for Cluster Environments

Approaches for dealing with scheduling and load-balancing in PC-based cluster systems are famous and well known. In such environments, Self-Scheduling Schemes are suitable for parallel loops with independent iterations. However, while schemes such as FSS, GSS, and TSS fit most computer systems, they cannot provide good load-balancing. Chao-Tung Yang and Shun-Chi Chang proposed a parallel loop scheduling scheme for heterogeneous PC cluster systems in Yang and Chang [13]. Though the proposed scheme allows users to choose parameters before execution initialization, weaknesses in it motivated us to develop further improvements. For instance, using fixed and monotonous parameters can easily lead to invalid scheduling due to use of previously input information. Thus, in this paper we propose a new scheme that fits most widely available computer systems and allows the scheduling parameter to be adjusted dynamically in order to provide higher overall performance.     

Image segmentation and edge enhancement with stabilized inversediffusion equations

We introduce a family of first-order multidimensional ordinary differential equations (ODEs) with discontinuous right-hand sides and demonstrate their applicability in image processing. An equation belonging to this family is an inverse diffusion everywhere except at local extrema, where some stabilization is introduced. For this reason, we call these equations "stabilized inverse diffusion equations" (SIDEs). Existence and uniqueness of solutions, as well as stability, are proven for SIDEs. A SIDE in one spatial dimension may be interpreted as a limiting case of a semi-discretized Perona-Malik equation (1990, 19994). In an experiment, SIDE's are shown to suppress noise while sharpening edges present in the input signal. Their application to image segmentation is also demonstrated.     

Solving A\underline x =\underline b Using a Modified Conjugate Gradient Method Based on Roots of A

We consider the modified conjugate gradient procedure for solving A = in which the approximation space is based upon the Krylov space associated with A ^1/p and , for any integer p. For the square-root MCG (p=2) we establish a sharpened bound for the error at each iteration via Chebyshev polynomials in . We discuss the implications of the quickly accumulating effect of an error in in the initial stage, and find an error bound even in the presence of such accumulating errors. Although this accumulation of errors may limit the usefulness of this method when is unknown, it may still be successfully applied to a variety of small, almost-SPD problems, and can be used to jump-start the conjugate gradient method. Finally, we verify these theoretical results with numerical tests.