Image processing on encoded video sequences

This paper presents a novel approach to processing encoded video sequences prior to complete decoding. Scene changes are easily detected using DCT coefficients in JPEG and MPEG encoded video sequences. In addition, by analyzing the DCT coefficients, regions of interest may be isolated prior to decompression, increasing the efficiency of any subsequent image processing steps, such as edge detection. The results are currently used in a video browser and are part of an ongoing research project in creating large video databases. The procedure is detailed with several examples presented and studied in depth.     

Impact of technology scaling on thermal behavior of leakage current in sub-quarter micron MOSFETs: perspective of low temperature current testing

The increase in the off-state current for sub-quarter micron CMOS technologies is making conventional I_DDQ testing ineffective. Since natural process variation together with low-V_TH devices can significantly increase the absolute leakage value and the variation, choosing a single threshold for I_DDQ testing is impractical. One of the potential solutions is the cooling of the chip during current testing. In this paper we analyze the impact of CMOS technology scaling on the thermal behavior of different leakage current mechanisms in n-MOSFETs and estimate the effectiveness of low temperature I_DDQ testing. We found that the conventional single threshold low temperature I_DDQ testing is not effective for sub-quarter micron CMOS technologies and propose the low temperature ΔI_DDQ test method. The difference between pass and fail current limits was estimated more than 200× for 0.13-μm CMOS technology.     

Leakage Current in Sub-Quarter Micron MOSFET: A Perspective on Stressed Delta I DDQ Testing

The effectiveness of single threshold I _DDQ measurement for defect detection is eroded owing to higher and more variable background leakage current in modern VLSIs. Delta I _DDQ is identified as one alternative for deep submicron current measurements. Often delta I _DDQ is coupled with voltage and thermal stress in order to accelerate the failure mechanisms. A major concern is the I _DDQ limit setting under normal and stressed conditions. In this article, we investigate the impact of voltage and thermal stress on the background leakage. We calculate I _DDQ limits for normal and stressed operating conditions of 0.18 m n-MOSFETs using a device simulator. Intrinsic leakage current components of transistor are analyzed and the impact of technology scaling on effectiveness of stressed I _DDQ testing is also investigated.     

A som study of DC-PBH laser catastrophic failures

OBIC and PL imaging modes of a SOM have been successfully applied to the failure analysis of catastrophically degraded DC-PBH lasers. High lateral resolution, variable in-depth penetration and selective excitation are the most interesting features. A degradation mechanism has been found due to the development of leakage paths in the confining junctions.     

Blending law for binary blends of fractions of linear polystyrene

The dynamic behaviour of binary blends of linear polystyrene fractions in the terminal zone of the relaxation spectrum presents interesting peculiarities which have been discussed in a previous paper by Montfort. The viscoelastic properties are characterized by a representation in the complex plane of viscosities. In this paper, we propose an empirical blending law which represents such behaviour over a large range of frequencies. The conclusions of this law on the limiting values of η₀ and J⁰_e are compared with those deduced from the blending laws of Graessley and BMEO.     

Petrological control on engineering properties of carbonate rocks in arid regions

Bulletin of Engineering Geology and the Environment - Petrological features of carbonate rocks that exert control on their mechanical and physical properties are examined in the study presented...     

Novel multiferroic La0.95Sb0.05FeO3 orthoferrite

A series of La_1−xSb_xFeO₃ was prepared using the conventional solid state method. XRD revealed the formation of the orthorhombic structure with space group Pbnm. The data showed that, the molar magnetic susceptibility and coercive field H_C were increased from 9.16 × 10⁻³ to 26.9 × 10⁻³ emu g⁻¹ mol and 1196 to 5465 Oe from for LaFeO₃ to La_0.95Sb_0.05FeO₃, respectively. The coercive field (H_C) of the sample with x = 0.05 increased 6 times than that of the parent LaFeO₃ and the saturation magnetization (M_s) was increased from 0.1614 emu g⁻¹ for the parent LaFeO₃ to 0.2654 emu g⁻¹ for the doped sample_. The dielectric constant (?′) was increased with increasing the Sb³⁺ content. The ac conductivity (σ) increases from 2.36 × 10⁻³ Ω⁻¹ m⁻¹ for the LaFeO₃ to 30 × 10⁻³ Ω⁻¹ m⁻¹ for the sample La_0.95Sb_0.05FeO₃ at T = 553 K and frequency 1 MHz. The sample La_0.95Sb_0.05FeO₃ is concluded to be a novel single phase multiferroic material.     

Unsupervised classification of cell images using pyramid nodelinking

In this communication we describe a segmentation technique which combines two properties in an iterative and hierarchial matter to correctly segment and classify the given cell images. The technique is applied to digital images taken from microscope slides of cultured rat liver cells, and the goal is to classify these cells into one of three possible classes. The first class cells (I) are morphologically normal and stain the darkest. The second class cells (II) are slightly damaged showing both nuclear and cytoplasmic swelling with resultant lessening of staining affinity. The third class cells (III) are markedly damaged as demonstrated by the presence of cytoplasmic vacuolization, or are completely disintegrated. First class cells are classified by taking advantage of their staining affinity; the original gray level image is segmented into four gray levels. The darkest is then classified as type I. Type III cells are classified by using high business as a characteristic; the standard deviation of the original image is segmented into four business levels. The highest level is classified as type III cell. Assuming only the three cell types are present in any given image, the remaining non-background unclassified pixels are determined to belong to type II cells.     

The applicability of neural networks in the determination of soil profiles

The drilling of a number of boreholes to determine the soil profile of a given area is time consuming and costly. This paper describes estimated soil profiles obtained using a model based on artificial neural networks (ANN). ANN is a powerful data-modelling tool capable of capturing and representing complex relationships between input and output. It deals with many multi-variate problems for which an exact analytical model does not exist or is very difficult and time consuming to develop. The main settlement in the Adapazari region was selected to demonstrate the capability of such model. The results obtained using ANN are promising when compared with the soil profile obtained from boreholes.      

Adaptive-Network-Based Fuzzy Inference System Analysis to Predict the Temperature and Flow Fields in a Lid-Driven Cavity

Heat transfer behavior in a 2-D square lid-driven cavity has been studied for various pertinent Reynolds and Rayleigh numbers. The lattice Boltzmann method, a numerical tool based on the particle distribution function is applied to simulate a thermal fluid flow problem. Bhatnagar-Gross-Krook (BGK) is combined with the double population thermal Lattice Boltzmann model to solve mixed convection in a square cavity. An adaptive-network-based fuzzy inference system (ANFIS) method is trained and validated using BGK Lattice Boltzmann model results. The results show that the trained ANFIS model successfully predicts the temperature and flow fields in a few seconds with acceptable accuracy.