Motion-compensated DCT temporal filters for efficient spatio-temporal scalable video coding

Although most of the proposals for implementing motion-compensated temporal filtering (MCTF) schemes are based on the wavelet transform, in this paper, we propose an MCTF framework based on the discrete cosine transform (DCT). Using DCT decimation and interpolation, several temporal decomposition structures named motion-compensated DCT temporal filters (MCDCT-TF) are introduced. These structures are able to employ filters of any length with particular emphasis on 5/3 DCT and 7/4 DCT. The proposed MCDCT-TF and the two-dimensional (2D) DCT decimation technique are incorporated into H.264/AVC to provide spatio-temporal scalability. Compared with the current MCTF-based lifting schemes such as Haar, and 5/3 wavelet filters, simulation results show that the proposed MCDCT-TF utilizing longer tap DCT filters achieves a significant improvement in coding gain. The impact of odd/even group of frames, the decimation/interpolation ratios, and motion-compensated connectivity on the MCDCT-TF performance are also analyzed. Moreover, simulation results show that the performance of the presented scalable video coding is close to the single layer H.264/AVC and is slightly inferior to the temporal scalability supported in JSVM, the state-of-the-art scalable video coding standard, that gets its gain from Hierarchical B-pictures. However, our spatio-temporal coding scheme outperforms the spatio-temporal supported in JSVM even if it uses hierarchical B-pictures to improve its gain.     

Targeted Delivery of Anesthetic Agents to Bone Tissues using Conductive Microneedles Enhanced Iontophoresis for Painless Dental Anesthesia

Pain management during dental procedures is a cornerstone for successful daily practice. In current practice, the traditional needle and syringe injection is used to administer local anesthesia. However, the appearance of long needles and the pain associated with it often leads to dental anxiety deterring timely interventions. Microneedles (MNs) have emerged as a minimally invasive alternative to hypodermic needles and shown to be effective in transdermal drug delivery applications. In this article, the potential use of MNs for local anesthesia delivery in dentistry is explored. The development of a novel conductive MN array that can be used in combination with iontophoresis technique to achieve drug penetration through the oral mucosa and the underlying bone tissue is presented. The conductive MN array plays a dual-role, creating micro-conduits and lowering the resistance of the oral mucosa. The reduced tissue resistance further enhances the application of a low-voltage current that is able to direct and accelerate the drug molecules to target the sensory nerves supplying teeth. The successful delivery of lidocaine using this new strategy in a clinically relevant rabbit incisor model is shown to be as effective as the current gold standard.     

All two-input logic gates by a single-stage single electron box

In this paper, the design of all two-input logic gates is presented by only a single-stage single electron box (SEB) for the first time. All gates are constructed based on a same circuit. We have used unique periodic characteristics of SEB to design these gates and present all two-input logic gates (monotonic/non-monotonic, symmetric/non-symmetric) by a single-stage design. In conventional monotonic devices, such as MOSFETs, implementing non-monotonic logic gates such as XOR and XNOR is impossible by only a single-stage design, and a multistage design is required which leads to more complexity, higher power consumption and less speed of the gates. We present qualitative design at first and then detailed designs are investigated and optimised by using our previous works. All designs are verified by a single electron simulator which shows correct operation of the gates.     

Underlay Device to Device Communication with Imperfect Interference Channel Knowledge

The objective of any night vision system is to enable a person to see in the dark. A low-contrast image puts a contrast constraint on the human observer visibility at night. This is the basic reason for the large number of accidents at night. This research presents two proposed approaches to enhance the visibility of the infrared (IR) night vision images through an efficient histogram processing. The first approach is based on contrast limited adaptive histogram equalization. The second proposed approach depends on histogram matching. The histogram matching uses a reference visual image for converting night vision images into good quality images. The obtained results are evaluated with quality metrics such as entropy, average gradient, contrast improvement factor and sobel edge magnitude.     

Efficient Pattern Generation for Small-Delay Defects Using Selection of Critical Faults

Testing for small-delay defects (SDDs) has become necessary as technology further scales. Existing tools and methodologies for generating SDD patterns suffer from: limited long-paths sensitization capability, overwhelming pattern volume, time-consuming pattern generation process, and vague evaluations of pattern quality. Such situation places patterns in a dilemma where the generation and application effort are huge yet the results cannot reflect the physical phenomena clearly enough for correct binning and diagnosis. In this paper, we focus on establishing a pattern generation flow that produces patterns of high application value. Firstly, critical faults are identified in order to generate high-quality original pattern repository with n-detect ATPG.A novelpattern evaluation and selection method that further minimizes pattern count while maintaining the SDD detection ability is then presented. Top-off ATPG is then performed to ensure meeting the target fault coverage. Along with the flow, multiple evaluation metrics are also proposed to measure the pattern’s efficiency on SDD coverage, unique SDD detection, detectable SDD size, long path distribution, etc. Experimental results demonstrate that the proposed critical fault-based method improves long path sensitization efficiency by 2.5× without impairing its average delay and saves approximately 80 % CPU runtime compared with total fault-based method. Comparing with timing-aware ATPG, the generated pattern set detects equivalent or even more SDDs with significantly reduced pattern count.     

Correction to: Enhanced TOA Estimation Using OFDM over Wide-Band Transmission Based on a Simulated Model

Wireless Personal Communications -     

Reduction of PAPR in coded OFDM using fast Reed-Solomon codes over prime Galois fields

In this work, two new techniques using Reed–Solomon (RS) codes over GF(257) and GF(65,537) are proposed for peak-to-average power ratio (PAPR) reduction in coded orthogonal frequency division multiplexing (OFDM) systems. The lengths of these codes are well-matched to the length of OFDM frames. Over these fields, the block lengths of codes are powers of two and we fully exploit the radix-2 fast Fourier transform algorithms. Multiplications and additions are simple modulus operations. These codes provide desirable randomness with a small perturbation in information symbols that is essential for generation of different statistically independent candidates. Our simulations show that the PAPR reduction ability of RS codes is the same as that of conventional selected mapping (SLM), but contrary to SLM, we can get error correction capability. Also for the second proposed technique, the transmission of side information is not needed. To the best of our knowledge, this is the first work using RS codes for PAPR reduction in single-input single-output systems.     

A 24-channel implantable neural recording based on time and frequency-division multiplexing

This paper presents a novel approach to encapsulate prerecorded neural signals in implantable neural recording microsystems. We have increased the number of channels and the reconstructed neural signal quality in the receiver by combining time-division-multiplexing (TDM) and frequency-division-multiplexing (FDM) method. Reducing the number of channels in each TDM module is the fundamental advantage of this method that leads to reduced crosstalk noise. We evaluate some possible configurations and propose an optimized system that has less power dissipation and area occupation than other configurations. A 24-channel implantable neural recording based on the optimized system is designed in both system and circuit level. In this system, first, channels are divided into three 8-channel groups then after multiplexing in the time domain, they are combined together by FDM method. Finally, a frequency modulator wirelessly transmits neural signals to an external setup. In addition, we adjust local carrier frequencies and the bandwidth of TDM to synchronize detection without transmitting pilot carrier. To justify the system operation, using 0.18 μm CMOS technology, we design the system in circuit level. The designed circuit consumes a power of 1.39 mW at a supply voltage of 1.8 V. This leads to a power consumption of 58 μW per channel.     

Two new low-power Full Adders based on majority-not gates

Two novel low-power 1-bit Full Adder cells are proposed in this paper. Both of them are based on majority-not gates, which are designed with new methods in each cell. The first cell is only composed of input capacitors and CMOS inverters, and the second one also takes advantage of a high-performance CMOS bridge circuit. These kinds of designs enjoy low power consumption, a high degree of regularity, and simplicity. Low power consumption is targeted in implementation of our designs. Eight state-of-the-art 1-bit Full Adders and two proposed Full Adders are simulated using 0.18 μm CMOS technology at many supply voltages. Simulation results demonstrate improvement in terms of power consumption and power-delay product (PDP).     

Emerging gallium nitride based devices

Wide bandgap GaN has long been sought for its applications to blue and UV emitters and high temperature/high power electronic devices. Recent introduction of commercial blue and blue-green LED's have led to a plethora of activity in all three continents into the heterostructures based on GaN and its alloys with AlN and InN. In this review, the status and future prospects of emerging wide bandgap gallium nitride semiconductor devices are discussed. Recent successes in p-doping of GaN and its alloys with InN and AlN, and in n-doping with much reduced background concentrations have paved the way for the design, fabrication, and characterization of devices such as MESFET's, MISFET's, HBT's, LED's, and optically pumped lasers. We discuss the electrical properties of these devices and their drawbacks followed by future prospects. After a short elucidation of materials characteristics of the nitrides, we explore their electrical transport properties in detail. Recent progress in processing such as formation of low-resistance ohmic contacts and etching is also presented. The promising features of quarternaries and double heterostructures in relation to possible current injection lasers, LED's, and photodetectors are also elaborated on