An object is to provide a semiconductor device of which a manufacturing process is not complicated and by which cost can be suppressed, by forming a thin film transistor using an oxide semiconductor film typified by zinc oxide, and a manufacturing method thereof. For the semiconductor device, a gate electrode is formed over a substrate; a gate insulating film is formed covering the gate electrode; an oxide semiconductor film is formed over the gate insulating film; and a first conductive film and a second conductive film are formed over the oxide semiconductor film. The oxide semiconductor film has at least a crystallized region in a channel region.

Semiconductor device, and manufacturing method thereof

We present a simple and usable noise model for the raw-data of digital imaging sensors This signal-dependent noise model, which gives the pointwise standard-deviation of the noise as a function of the expectation of the pixel raw-data output, is composed of a Poissonian part, modeling the photon sensing, and Gaussian part, for the remaining stationary disturbances in the output data We further explicitly take into account the clipping of the data (over- and under-exposure), faithfully reproducing the nonlinear response of the sensor We propose an algorithm for the fully automatic estimation of the model parameters given a single noisy image Experiments with synthetic images and with real raw-data from various sensors prove the practical applicability of the method and the accuracy of the proposed model

/pdf/practical-poissonian-gaussian-noise-modeling-and-fitting-for-4cn04dppj4.pdf

Practical Poissonian-Gaussian Noise Modeling and Fitting for Single-Image Raw-Data

Systems and methods for applying time-dependent algorithmic compensation functions to data output from a continuous analyte sensor. Some embodiments determine a time since sensor implantation and/or whether a newly initialized sensor has been used previously.

Systems and methods for processing analyte sensor data

Despite their increasing sophistication, wireless sensor networks still do not exploit the most powerful of the human senses: vision. Indeed, vision provides humans with unmatched capabilities to distinguish objects and identify their importance. Our work seeks to provide sensor networks with similar capabilities by exploiting emerging, cheap, low-power and small form factor CMOS imaging technology. In fact, we can go beyond the stereo capabilities of human vision, and exploit the large scale of sensor networks to provide multiple, widely different perspectives of the physical phenomena. To this end, we have developed a small camera device called Cyclops that bridges the gap between the computationally constrained wireless sensor nodes such as Motes, and CMOS imagers which, while low power and inexpensive, are nevertheless designed to mate with resource-rich hosts. Cyclops enables development of new class of vision applications that span across wireless sensor network. We describe our hardware and software architecture, its temporal and power characteristics and present some representative applications.

Cyclops: In Situ Image Sensing and Interpretation in Wireless Sensor Networks

Despite their increasing sophistication, wireless sensor networks still do not exploit the most powerful of the human senses: vision. Indeed, vision provides humans with unmatched capabilities to distinguish objects and identify their importance. Our work seeks to provide sensor networks with similar capabilities by exploiting emerging, cheap, low-power and small form factor CMOS imaging technology. In fact, we can go beyond the stereo capabilities of human vision, and exploit the large scale of sensor networks to provide multiple, widely different perspectives of the physical phenomena.To this end, we have developed a small camera device called Cyclops that bridges the gap between the computationally constrained wireless sensor nodes such as Motes, and CMOS imagers which, while low power and inexpensive, are nevertheless designed to mate with resource-rich hosts. Cyclops enables development of new class of vision applications that span across wireless sensor network. We describe our hardware and software architecture, its temporal and power characteristics and present some representative applications.

http://www.kilopixel.net/publications/sensys2005.pdf

Cyclops: in situ image sensing and interpretation in wireless sensor networks

The invention includes optical signal conduits having rare earth elements incorporated therein. The optical signal conduits can, for example, contain rare earth elements incorporated within a dielectric material matrix. For instance, erbium or cerium can be within silicon nanocrystals dispersed throughout dielectric material of optical signal conduits. The dielectric material can define a path for the optical signal, and can be wrapped in a sheath which aids in keeping the optical signal along the path. The sheath can include any suitable barrier material, and can, for example, contain one or more metallic materials. The invention also includes methods of forming optical signal conduits, with some of such methods being methods in which the optical signal conduits are formed to be part of semiconductor constructions.

Constructions and light-conducting conduits

A memory device includes an array of memory cells and peripheral devices. At least some of the individual memory cells include carbonated portions that contain SiC. At least some of the peripheral devices do not include any carbonated portions. A transistor includes a first source/drain, a second source/drain, a channel including a carbonated portion of a semiconductive substrate that contains SiC between the first and second sources/drains and a gate operationally associated with opposing sides of the channel.

Memory devices, transistors, and memory cells

Light-conducting conduits

Some embodiments include vertical stacks of memory units, with individual memory units each having a memory element, a wordline, a bitline and at least one diode. The memory units may correspond to cross-point memory, and the diodes may correspond to band-gap engineered diodes containing two or more dielectric layers sandwiched between metal layers. Tunneling properties of the dielectric materials and carrier injection properties of the metals may be tailored to engineer desired properties into the diodes. The diodes may be placed between the bitlines and the memory elements, or may be placed between the wordlines and memory elements. Some embodiments include methods of forming cross-point memory arrays. The memory arrays may contain vertical stacks of memory unit cells, with individual unit cells containing cross-point memory and at least one diode.

Chandra Mouli

Papers

Constructions and light-conducting conduits

Memory devices, transistors, and memory cells

Light-conducting conduits

Semiconductor Constructions, and Methods of Forming Cross-Point Memory Arrays

Transistors comprising a SiC-containing channel