Semi-Supervised Deep Learning for Multi-Tissue Segmentation from Multi-Contrast MRI

Journal of Signal Processing Systems - Segmentation of thigh tissues (muscle, fat, inter-muscular adipose tissue (IMAT), bone, and bone marrow) from magnetic resonance imaging (MRI) scans is useful...     

Long Duration Persistent Photocurrent in 3 nm Thin Doped Indium Oxide for Integrated Light Sensing and In-Sensor Neuromorphic Computation

Miniaturization and energy consumption by computational systems remain major challenges to address. Optoelectronics based synaptic and light sensing provide an exciting platform for neuromorphic processing and vision applications offering several advantages. It is highly desirable to achieve single-element image sensors that allow reception of information and execution of in-memory computing processes while maintaining memory for much longer durations without the need for frequent electrical or optical rehearsals. In this work, ultra-thin (<3 nm) doped indium oxide (In₂O₃) layers are engineered to demonstrate a monolithic two-terminal ultraviolet (UV) sensing and processing system with long optical state retention operating at 50 mV. This endows features of several conductance states within the persistent photocurrent window that are harnessed to show learning capabilities and significantly reduce the number of rehearsals. The atomically thin sheets are implemented as a focal plane array (FPA) for UV spectrum based proof-of-concept vision system capable of pattern recognition and memorization required for imaging and detection applications. This integrated light sensing and memory system is deployed to illustrate capabilities for real-time, in-sensor memorization, and recognition tasks. This study provides an important template to engineer miniaturized and low operating voltage neuromorphic platforms across the light spectrum based on application demand.     

Epitaxial lift-off GaAs HEMT's

An extensive study of epitaxial lift-off (ELO) Al_0.3Ga _0.7As/GaAs modulation doped heterostructure high electron mobility field-effect transistors (HEMT's) is presented. Effects of ELO on electron transport properties of two-dimensional electron gas at AlGaAs/GaAs interface are investigated. An ELO HEMT with 1.5 μm gate length had a maximum extrinsic transconductance g_m-max=125 mS/mm, a unity current gain cut-off frequency f_t=10.5 GHz, and a maximum frequency of oscillation f_max=12 GHz. Statistical distributions of maximum intrinsic transconductance of ELO HEMT's are presented and compared with their on-wafer counterparts. Stability of the ELO HEMT's has also been evaluated by continuous operation at room temperature under dc bias     

Algebraic properties of cryptosystem PGM

In the late 1970s Magliveras invented a private-key cryptographic system calledPermutation Group Mappings (PGM). PGM is based on the prolific existence of certain kinds of factorization sets, calledlogarithmic signatures, for finite permutation groups. PGM is an endomorphic system with message space ℤ_|G| for a given finite permutation groupG. In this paper we prove several algebraic properties of PGM. We show that the set of PGM transformations ℐ _G is not closed under functional composition and hence not a group. This set is 2-transitive on ℤ_|G| if the underlying groupG is not hamiltonian and not abelian. Moreover, if the order ofG is not a power of 2, then the set of transformations contains an odd permutation. An important consequence of these results is that the group generated by the set of transformations is nearly always the symmetric group ℒ_|G|. Thus, allowing multiple encryption, any permutation of the message space is attainable. This property is one of the strongest security conditions that can be offered by a private-key encryption system. S. S. Magliveras was supported in part by NSF/NSA Grant Number MDA904-82-H0001, by U.S. West Communications, and by the Center for Communication and Information Science of the University of Nebraska.     

Wireless Brain Computer Interface for Smart Home and Medical System

Wireless Personal Communications - The number of aged and disabled people has been increasing worldwide. To look after these people is a big challenge in this era. However, scientists overcome the...     

Efficient dissemination of personalized information using content-based multicast

There has been a surge of interest in the delivery of personalized information to users (e.g., personalized stocks or travel information), particularly as mobile users with limited terminal device capabilities increasingly desire updated and targeted information in real time. When the number of information recipients is large and there is sufficient commonality in their interests, as is often the case, IP multicast is an efficient way of delivering the information. However, IP multicast services do not consider the structure and semantics of the information in the multicast process. We propose the use of Content-Based Multicast (CBM) where extra content filtering is performed at the interior nodes of the IP multicast tree; this will reduce network bandwidth usage and delivery delay, as well as the computation required at the sources and sinks. We evaluate the situations in which CBM is advantageous. The benefits of CBM depend critically upon how well filters are placed at interior nodes of the IP multicast tree and the costs depend upon those introduced by filters themselves. Further, we consider the benefits of allowing the filters to be mobile so as to respond to user mobility or changes in user interests and the corresponding costs of filter mobility. The criterion that we consider is the total network bandwidth utilization. For this criterion, we develop an optimal filter placement algorithm, as well as a heuristic that executes faster than the optimal algorithm. We evaluate the algorithms by means of simulation experiments. Our results indicate that filters can be effective in substantially reducing bandwidth. We also find filter mobility is worthwhile if there is marked large-scale user mobility. We conclude with suggestions for further work.     

Proposal for st-Routing Protocol

A routing protocol chooses one of the several paths (routes) from a source node to a destination node in the computer network, to send a packet of information. In this paper, we propose a new routing protocol, which we call st-routing protocol, based on st-numbering of a graph. The protocol fits well in noisy environments where robustness of routing using alternative paths is a major issue. The proposed routing protocol provides a systematic way to retry alternative paths without generating any duplicate packets. The protocol works for only those networks that can be represented by biconnected graphs.     

A study of printed spiral coils for neuroprosthetic transcranialtelemetry applications

We have explored the use of printed spiral coils (PSC's) for neuroprosthetic transcranial telemetry applications. We fabricated two-dimensional PSC's on a thin (25 μm) polyimide substrate using copper (35 μm) as a conducting material. All the coils had a fixed inner diameter of 1.0 cm. We fabricated two sets of coils. One set of coils consisted of 2- to 5-turn circular and square spiral coils and had different trace widths (W), different spacings (S) between adjacent traces, and different outer diameters. The other set of coils consisted of 5-turn circular spiral coils and had fixed inner and outer diameters but different W to S ratios. We measured loss resistances (R_s and R_p) and quality factors (Q) of these coils at different resonating frequencies in the range of 5-40 MHz. Over this frequency range, we observed that for fixed inner and outer diameters, the coil with the largest W achieved the lowest R_s and the highest R, and Q. These electrical properties and the fact that these coils can conform to the complex convoluted cortical surface suggest that a PSC can provide a viable alternative to a conventional wire-wound coil for neuroprosthetic transcranial telemetry applications     

Statistical coding method for facial features

Model-based techniques have been shown to give high compression rates for coding head and shoulder image sequences, typically for videophone applications. However, they lead to poor image quality in significant areas of the face such as the eyes and mouth. To overcome this problem, a hybrid system could be perceived where the facial features were represented using traditional statistical techniques and the remaining of the head and shoulder sequences using highly efficient model-based methods, therefore utilising more bits to code the sensitive areas and fewer for the rest. In the paper, the method of principal component analysis to code the dynamic changes in a sequence is presented