Analyzing the Impact of Bootstrapped ADC with Augmented NMOS Sleep Transistors Configuration on Performance Parameters

This paper represents an efficient bootstrapped analog to digital converter with augmented NMOS sleep transistors. The newly designed MOS-based bootstrapped circuit is implemented to provide controlled input supply for analog to digital converter to develop the enhancing capability of circuit. This will reduce the effective leakage of the circuit. In the second stage, the NMOS sleep transistors are augmented as pull-up and pull-down transistors. Due to augmentation of transistors, controlled power supply ( \(V_{\mathrm{DD}})\) is obtained. Because of this, current driving capability in MOS transistors is improved and minimum sub-threshold leakage current is formed. Due to this, reduction of leakage power dissipation occurs much effectively. The whole simulation has been done at 45 nm (nanometer) technology. It is realized that the leakage power is reduced till 50 % approximately and delay performance is improved. It means that speed is improved using bootstrapped circuit with augmented sleep transistors NMOS. In this paper, different consecutive designs with Analog to Digital converter are represented.     

Preprogramming Floating Time of Liquid Marble

Non-sticking droplets wrapped with fine hydrophobic particles, namely liquid marbles, can be transported both on solid and water pool without an undesired spill of the inner encapsulated liquid. While the stimuli-responsive release of the inner liquid in the target area is proposed, the time-programmed release is not yet achieved. Herein, the hydrophobicity of nanoclay is modulated via a catalyst-free 1,4-conjugate addition reaction to form liquid marbles. This nanoclay liquid marble is robust and stable in air but collapses on the liquid pool with a specific lifetime. The lifetime of the liquid marble can be modulated over seconds to hours scale depending on the selection of chemically modulated wettability of the nanoclay. The critical mechanism of lifetime modulation is responsible for controlling the coalescence kinetics between the water pool and inner liquid by nanoclays’ high diffusion length and chemically varied water spreading potential. The NC liquid marble's programmable lifetime to ‘time-bomb’ type drug release and cascade chemical reaction is applied—without requiring any external intervention.     

Interference suppression by biased nonlinearities

It is shown that, when the input signal-to-interference ratio (SIR) is small, a biased nonlinearity that has a dead zone below some threshold value can provide a large enhancement in output SIR and signal-to-interference-plus-intermodulation ratio (SIIMR) if the threshold is set equal or close to the amplitude of the strong interference. In the absence of noise, the output SIR and SIIMIR are virtually independent of the input SIR, however low the latter may be. It Is shown that, for a dead-zone limiter, the output SIIMR in this case is -4.93 dB regardless of the input SIR. Under strong interference, any noise present in the input reduces the SIR and SIIMR improvement, but a biased nonlinearity can still provide an output SIR and SIIMR superior to the input SIR, i.e. an output SIIMR 6.35 dB below the input signal-to-noise ratio (SNR) instead of 6.02 dB below the input SIR as is the case with hard limiting     

Low leakage and high CMRR CMOS differential amplifier for biomedical application

In order to increase user experience in using near field communication smartcard, analog front-end (AFE) module is required to provide a sufficient and a well-regulated voltage regardless the distance between the card and the reader. A highly stable AFE design for energy harvesting purpose is introduced in this paper. The design consists of antenna, rectifier, voltage limiter, bandgap reference, and low-dropout (LDO) voltage regulator circuit. The antenna is designed to resonate at 13.56 MHz as regulated by ISO/IEC 14443-2. In order to simplify the implementation using 0.18 μm CMOS process, a full-wave rectifier circuit is built of all low-threshold-voltage diode-connected PMOS transistors. To protect the system from undesired excessive input voltages, a voltage limiter circuit is included in the module. Moreover, control and maintain a stable supply voltage for the whole system, a robust LDO voltage regulator and bandgap circuits are specially designed for this purpose. The LDO is able to provide a stable 1.8 V of supply voltage with a sub-1% ripple factor even under a low input current as low as 20 mA.     

A 100-MHz 64-tap FIR digital filter in 0.8-μm BiCMOS gate array

A 64-tap FIR (finite impulse response) digital filter that has been designed using a newly developed filter compiler and fabricated in a 0.8-μm triple-level interconnect BiCMOS gate array technology is presented. The filter has been tested and is fully functional at a 100-MHz clock rate. These results are obtained by combining an optimized architecture and gate array floorplan with submicrometer BiCMOS technology. The filter occupies 49 mm², which is approximately two-thirds of the 100 K gate array core. The design uses an equivalent of 55 K gates (two-input NAND gates). The device input/output are 100 K emitter-coupled-logic (ECL) compatible     

A Novel Self-Organizing Approach to Automatic Traffic Light Management System for Road Traffic Network

Wireless Personal Communications - Traffic network is basically a “network of networks” consisting of mainly two types of networks: road network and a travel network. Due to drastic...     

Location Estimation Based on Semi-Supervised Locally Linear Embedding (SSLLE) Approach for Indoor Wireless Networks

Location aware computing is popularized and location information use has important due to huge application of mobile computing devices and local area wireless networks. In this paper, we have proposed a method based on Semi-supervised Locally Linear Embedding for indoor wireless networks. Previous methods for location estimation in indoor wireless networks require a large amount of labeled data for learning the radio map. However, labeled instances are often difficult, expensive, or time consuming to obtain, as they require great efforts, meanwhile unlabeled data may be relatively easy to collect. So, the use of semi-supervised learning is more feasible. In the experiment 101 access points (APs) have been deployed so, the RSS vector received by the mobile station has large dimensions (i.e. 101). At first, we use Locally Linear Embedding to reduce the dimensions of data, and then we use semi-supervised learning algorithm to learn the radio map. The algorithm performs nonlinear mapping between the received signal strengths from nearby access points and the user??s location. It is shown that the proposed scheme has the advantage of robustness and scalability, and is easy in training and implementation. In addition, the scheme exhibits superior performance in the nonline-of-sight (NLOS) situation. Experimental results are presented to demonstrate the feasibility of the proposed SSLLE algorithm.     

Scalability enhancement of AODV using local link repairing

Dynamic change in the topology of an ad hoc network makes it difficult to design an efficient routing protocol. Scalability of an ad hoc network is also one of the important criteria of research in this field. Most of the research works in ad hoc network focus on routing and medium access protocols and produce simulation results for limited-size networks. Ad hoc on-demand distance vector (AODV) is one of the best reactive routing protocols. In this article, modified routing protocols based on local link repairing of AODV are proposed. Method of finding alternate routes for next-to-next node is proposed in case of link failure. These protocols are beacon-less, means periodic hello message is removed from the basic AODV to improve scalability. Few control packet formats have been changed to accommodate suggested modification. Proposed protocols are simulated to investigate scalability performance and compared with basic AODV protocol. This also proves that local link repairing of proposed protocol improves scalability of the network. From simulation results, it is clear that scalability performance of routing protocol is improved because of link repairing method. We have tested protocols for different terrain area with approximate constant node densities and different traffic load.     

Engineering New Microvascular Networks On-Chip: Ingredients,Assembly, and Best Practices

Tissue engineered grafts show great potential as regenerative implants for diseased or injured tissues within the human body. However, these grafts suffer from poor nutrient perfusion and waste transport, thus decreasing their viability post-transplantation. Graft vascularization is therefore a major area of focus within tissue engineering because biologically relevant conduits for nutrient and oxygen perfusion can improve viability post-implantation. Many researchers used microphysiological systems as testing platforms for potential grafts owing to an ability to integrate vascular networks as well as biological characteristics such as fluid perfusion, 3D architecture, compartmentalization of tissue-specific materials, and biophysical and biochemical cues. Although many methods of vascularizing these systems exist, microvascular self-assembly has great potential for bench-to-clinic translation as it relies on naturally occurring physiological events. In this review, the past decade of literature is highlighted, and the most important and tunable components yielding a self-assembled vascular network on chip are critically discussed: endothelial cell source, tissue-specific supporting cells, biomaterial scaffolds, biochemical cues, and biophysical forces. This paper discusses the bioengineered systems of angiogenesis, vasculogenesis, and lymphangiogenesis and includes a brief overview of multicellular systems. It concludes with future avenues of research to guide the next generation of vascularized microfluidic models.     

A Markov random field model for classification of multisourcesatellite imagery

A general model for multisource classification of remotely sensed data based on Markov random fields (MRF) is proposed. A specific model for fusion of optical images, synthetic aperture radar (SAR) images, and GIS (geographic information systems) ground cover data is presented in detail and tested. The MRF model exploits spatial class dependencies (spatial context) between neighboring pixels in an image, and temporal class dependencies between different images of the same scene. By including the temporal aspect of the data, the proposed model is suitable for detection of class changes between the acquisition dates of different images. The performance of the proposed model is investigated by fusing Landsat TM images, multitemporal ERS-1 SAR images, and GIS ground-cover maps for land-use classification, and on agricultural crop classification based on Landsat TM images, multipolarization SAR images, and GIS crop field border maps. The performance of the MRF model is compared to a simpler reference fusion model. On an average, the MRF model results in slightly higher (2%) classification accuracy when the same data is used as input to the two models. When GIS field border data is included in the MRF model, the classification accuracy of the MRF model improves by 8%. For change detection in agricultural areas, 75% of the actual class changes are detected by the MRF model, compared to 62% for the reference model. Based on the well-founded theoretical basis of Markov random field models for classification tasks and the encouraging experimental results in our small-scale study, the authors conclude that the proposed MRF model is useful for classification of multisource satellite imagery