A group theoretic approach to multidimensional filter banks: theoryand applications

In this paper, we provide a new method for analyzing multidimensional filter banks. This method enables us to solve various open problems in multidimensional filter bank characterization and design. The essential element in this new approach is the redefinition of polyphase components. It will be shown that a rich set of mathematical tools, in particular algebraic group theory, will become available for use in the analysis of filter banks. We demonstrate the elegance and power of the tool set by employing it for the characterization of multidimensional filter banks and applying it to two open problems. The first problem is concerned with the development of a general method to design multichannel (⩾2), multidimensional filter banks using transformations, while the second problem is concerned with the derivation of general restrictions on group delays in linear phase filter banks. The treatment of these problems is only an illustration of the power of the tool set of algebraic group theory, employed for the first time in the context of multidimensional filter banks     

Lowpass and bandpass transadmittance filter using operational amplifier pole

A new topology simultaneously implementing lowpass (LP) and bandpass (BP) transadmittance filtering signals using a single operational amplifier (OA), one capacitor, and two resistors is presented. The input impedance is very high which is essential for cascading without employment of buffers. The circuit uses absolute minimum number of active and passive components. The filter employs pole-model of OA and as such has acquired suitability for extended frequency operation. The circuit permits separate adjustment of natural frequency (ω₀) and quality factor (Q) in an orthogonal manner. The circuit has low sensitivity figures unlike the reported single amplifier biquads. The PSPICE simulation results are included.     

皮革防霉剂研制探讨

本文通过不同杀菌组分对皮革上常生长的霉菌作抑菌实验比较,寻找原料易得,合成容易,对环境污染小,高效、广谱低毒的杀菌组分,从而筛选出比较有前途的防毒剂品种     

An effective back‐off selection technique for reliable beacon reception in VANETs

In safety‐critical scenarios, reliable reception of beacons transmitted by a subject vehicle is critical to avoid vehicle collision. According to the employed contention window sizes in IEEE 802.11p, beacons are transmitted with a small contention window size. As a result, multiple vehicles contend for the shared channel access by selecting the same back‐off slot. This is a perfect recipe for synchronous collisions wherein reliable beacon delivery cannot be guaranteed for any vehicle. We consider the problem of selecting the back‐off slots from the current contention window to provide reliable delivery of beacons transmitted by a subject vehicle to its neighbors. Given a safety scenario, we propose a Pseudo‐Random Number Generator (PRNG)‐inspired back‐off selection (PBS) technique. The proposed technique works on the hypothesis that synchronous collisions of beacons transmitted by a subject vehicle can be reduced if all its neighbors select different back‐off slots (ie, not the back‐off slot selected by the subject vehicle). The discrete‐event simulations demonstrate that PBS can increase the overall message reception from a subject vehicle, in comparison with the uniform random probability back‐off selection in IEEE 802.11p.     

Sinh-Domain multiphase sinusoidal oscillator

A Multiphase Sinusoidal Oscillator (MSO) configuration derived by employing appropriate non-linear transconductors which implement lossy integrators in the Sinh-Domain is introduced in this paper. Owing to its companding nature, the oscillator offers the benefits of electronic tuning of the oscillation frequency and the capability for operating in a low-voltage environment. In addition, the condition of oscillation could be electronically adjusted without disturbing the oscillation frequency. This has been achieved by introducing a novel Sinh-Domain lossy integrator topology. The performance of the proposed oscillator has been evaluated through a design example, where a six-phase topology has been simulated by utilizing the Analog Design Environment of the Cadence software.     

SDN-based wireless user management system

The degradation of end-to-end quality of service (QoS) on mobile users is becoming a common issue for IEEE 802.11 infrastructure-based networks in crowded areas. This research tackles the issue by employing an SDN framework on an integrated wireless/wired environment. Thereby, we present the development and implementation of a system that performs user management by analyzing the network load from the OpenFlow statistics, as well as the wireless information collected from the associated users. In order to analyse the behaviour of the proposed user migration algorithm, we evaluate the system under scenarios with different traffic load and user session duration. From the experiments, we observed that in several cases wireless users get a considerable QoS improvement at the application layer (up to 30% improvement in throughput and up to 20% in delay in our simulations) once the system is activated. Based on the results, we present an analysis on how and when user migration in multi-access point IEEE 802.11 networks can be most effective.     

A chip set for lossless image compression

The authors describe two chips which form the basis of a high-speed lossless image compression/decompression system. They present the transform and coding algorithms and the main architectural features of the chips and outline some performance specifications. Lossless compression can be achieved by a transformation process followed by entropy coding. The two application-specific integrated circuits (ASICs) perform S-transform image decomposition and the Lempel-Ziv (L-Z) type of entropy coding. The S-transform, besides decorrelating the image, provides a convenient method of hierarchical image decomposition. The data compressor/decompressor IC is a fast and efficient implementation of the L-Z algorithm. The chips can be used independently or together for image compression     

Multimodal image/video fusion rule using generalized pixel significance based on statistical properties of the neighborhood

Image fusion has been receiving increasing attention in the research community with the aim of investigating general formal solutions to a wide spectrum of applications such as multifocus, multiexposure, multispectral ( $IR$ -visible) and multimodal medical (CT and MRI) image and video fusion. While there exist many fusion techniques for each of these applications, it is difficult to formulate a common fusion technique that works equally well for all these applications. This is mainly because of the different characteristics of the images involved in various applications and the correspondingly different requirements on the fused image. In this work, we propose a common generalized fusion framework for all these classes, based on the statistical properties of local neighborhood of a pixel. As the eigenvalue of the unbiased estimate of the covariance matrix of an image block depends on the strength of edges in that block, we propose to employ it to compute a quantity we call as the significance of a pixel. This generalized pixel significance in turn can be used as a measure of the useful information content in that block, and hence can be used in the fusion process. Several data sets were fused to compare the results with various recently published methods. The analysis shows that for all the image types into consideration, the proposed methods improve the quality of the fused image, both visually and quantitatively, by preserving all the relevant information.     

Improving PAPR performance of filtered OFDM for 5G communications using PTS

The filtered orthogonal frequency division multiplexing (F-OFDM) system has been recommended as a waveform candidate for fifth-generation (5G) communications. The suppression of out-of-band emission (OOBE) and asynchronous transmission are the distinctive features of the filtering-based waveform frameworks. Meanwhile, the high peak-to-average power ratio (PAPR) is still a challenge for the new waveform candidates. Partial transmit sequence (PTS) is an effective technique for mitigating the trend of high PAPR in multicarrier systems. In this study, the PTS technique is employed to reduce the high PAPR value of an F-OFDM system. Then, this system is compared with the OFDM system. In addition, the other related parameters such as frequency localization, bit error rate (BER), and computational complexity are evaluated and analyzed for both systems with and without PTS. The simulation results indicate that the F-OFDM based on PTS achieves higher levels of PAPR, BER, and OOBE performances compared with OFDM. Moreover, the BER performance of F-OFDM is uninfluenced by the use of the PTS technique.     

Embedding topic discovery in conditional random fields model for segmenting nuclei using multispectral data

Segmentation of cells/nuclei is a challenging problem in 2-D histological and cytological images. Although a large number of algorithms have been proposed, newer efforts continue to be devoted to investigate robust models that could have high level of adaptability with regard to considerable amount of image variability. In this paper, we propose a multiclassification conditional random fields (CRFs) model using a combination of low-level cues (bottom-up) and high-level contextual information (top-down) for separating nuclei from the background. In our approach, the contextual information is extracted by an unsupervised topic discovery process, which efficiently helps to suppress segmentation errors caused by intensity inhomogeneity and variable chromatin texture. In addition, we propose a multilayer CRF, an extension of the traditional single-layer CRF, to handle high-dimensional dataset obtained through spectral microscopy, which provides combined benefits of spectroscopy and imaging microscopy, resulting in the ability to acquire spectral images of microscopic specimen. The approach is evaluated with color images, as well as spectral images. The overall accuracy of the proposed segmentation algorithm reaches 95% when applying multilayer CRF model to the spectral microscopy dataset. Experiments also show that our method outperforms seeded watershed, a widely used algorithm for cell segmentation.