Improved diagnosis using enhanced fault dominance

Defect diagnosis can benefit from fault dominance relations to reduce the set of defect candidate sites. This paper presents new fault dominance collapsing operators that further reduce the set of candidates considered during the initial phase of diagnosis. In contrast to existing dominance-based methods which operate on pairs of faults, the proposed method operates on sets of faults. Fault-related entities are generated to guide the diagnosis process. The proposed collapsing operators can be used to accelerate effect-cause diagnosis. Experimental results demonstrate that the proposed method achieves a higher collapsing ratio than existing methods.     

WIPO Panels’ interpretation of the Uniform Dispute Resolution Policy (UDRP) three-prong test

The Uniform Dispute Resolution Policy (UDRP) is a unique process that resolves domain name disputes effectively and inexpensively. This paper, through an analysis of the UDRP three-prong test, revealed that even though the UDRP affords a great degree of discretion to the WIPO Panels deciding any given case, there is some consistency and predictability inherent in the UDRP process.     

Europe should stop taxing innovation

After nearly 48 years of failure to create the EU patent, language issues and the design of a centralised patent-litigation court still dominate headlines. But behind these issues there are high financial stakes and control power to play for. The recent EU Council deal on an ‘enhanced’ European patent system does not solve the above problems, and has not eliminated lingering governance issues. The risk for Europe is that a final patent agreement might be reached that does not cure the system of its major ills, and thus does not bring about any significant improvement for those that need it most: entrepreneurs and innovative companies starting out on the innovation process. The creation of an effective single EU patent requires (i) English-only post-grant translation, (ii) the end of nationally granted patents, (iii) phasing-out of the current ‘European patent’, (iv) lower fees for young innovative companies, and (v) a radical shake-up of the governance of the European Patent Office.     

Synthesis of crystalline metal nitride and metal carbide nanostructures by sol–gel chemistry

Attention toward nanosized metal nitrides and carbides is rapidly increasing thanks to their chemical characteristics that make them as valid and sustainable alternatives to noble metals in catalysis and to air-sensitive metals or oxides for applications under harsh conditions. They are mostly used as bulk phase or micron sized powders, due to an intrinsic difficulty to synthesize them as nanoparticles in a systematic and scalable fashion. However, nanosized metal nitrides and carbides could exhibit improved performances, e.g. in catalysis due to a higher surface area, and can be shaped more easily than corresponding larger grains for further specific applications. Recently, sol–gel chemistry has closed this gap and now enables the simple, cheap, and sustainable production of metal nitride and carbide nanoparticles.In the present review we give an overview on recent sol–gel based pathways for the synthesis of metal nitride and carbide nanoparticles, believing that a better knowledge of the potentialities of these still hardly touched materials stimulates research interest and applications.     

Choice of a pertinent color space for color texture characterization using parametric spectral analysis

This article presents a comparison of different color spaces including RGB, IHLS and L?a*b* for color texture characterization. This comparison is based on the fusion of the independent spatial structure and color feature cues. In IHLS and L*a*b*, two channel complex color images are created from the luminance and the chrominance values. For such images, two dimensional complex multichannel linear prediction models are used to perform parametric power spectrum estimation and the structure feature cues are computed from this estimated power spectrum. Quantitative comparison of auto spectra of luminance and combined chrominance channels for different color spaces is done. This comparison is based on the degree of decorrelation between luminance and chrominance information provided by different color space transformations. Three dimensional histograms are used as color feature cues. Then, to classify color textures, Kullback-Leibler divergence based symmetric distance measures are calculated for pure color, luminance structure and chrominance structure feature cues. Individual as well as combined effect of information from all feature cues on classification results is then compared for different color spaces and different color texture data sets. The proposed color texture classification method performs better than the state of the art methods in certain cases. The L*a*b* color space gives us a better characterization of the chrominance spatial structure as well as the overall spatial structure for all of the chosen data sets. Experimental results on pixel classification of color textures are also presented and discussed.     

A fast parallel (23, 12, 7) QR decoder based on syndrome-weight determination

In this paper, a time-area efficient hardware decoder of the (23, 12, 7) quadratic residue code, or Golay code, is presented. The key feature of this proposed algorithm lies in fast determination of error positions through the analysis on the weight of syndromes without large operations in finite fields. Comparing with the algorithm using one syndrome, the proposed algorithm is more suitable for the parallel hardware design by using two syndromes. Based on an Altera Cyclone II field-programmable gate array (FPGA) device (EP2C35F484C6), the area cost and the time delay of the complete system are reduced by up to 86.4% and 22.5%, respectively. Using the Taiwan Semiconductor Manufacturing Company (TSMC) 0.18-μm complementary metal-oxide-semiconductor (CMOS) standard cell library, the proposed decoder is 91.8% smaller and 8.3% faster.     

Additive noise removal using a novel fuzzy-based filter

The paper proposes a new fuzzy-based two-step filter for restoring images corrupted with additive noise. The goal of the first step is to compute the difference between the central pixel and its neighborhood in a selected window and to compute a fuzzy membership degree for each difference value using a Gaussian membership function. Computed fuzzy membership values are appropriately utilized as weights for each pixel and then computes the weighted average representing the modified value for the current central pixel. The second step is used as an augmented step to the first one and its goal is to improve the result obtained in the first step by reducing the noise in the color component differences without destroying the fine details of the image. The experimental analysis shows that the proposed method gives better results compared to existing advanced filters for additive noise reduction. Both visual, quantitative and qualitative analysis have been done to prove the efficiency and effectiveness of the proposed method.     

An approximation method of origin–destination flow traffic from link load counts

Traffic matrix (TM) is a key input of traffic engineering and network management. However, it is significantly difficult to attain TM directly, and so TM estimation is so far an interesting topic. Though many methods of TM estimation are proposed, TM is generally unavailable in the large-scale IP backbone networks and is difficult to be estimated accurately. This paper proposes a novel method of TM estimation in large-scale IP backbone networks, which is based on the generalized regression neural network (GRNN), called GRNN TM estimation (GRNNTME) method. Firstly, building on top of GRNN, we present a multi-input and multi-output model of large-scale TM estimation. Because of the powerful capability of learning and generalizing of GRNN, the output of our model can sufficiently capture the spatio-temporal correlations of TM. This ensures that the estimation of TM can accurately be attained. And then GRNNTME uses the procedure of data posttreating further to make the output of our model closer to real value. Finally, we use the real data from the Abilene Network to validate GRNNTME. Simulation results show that GRNNTME can perform well the accurate and fast estimation of TM, track its dynamics, and holds the stronger robustness and lower estimation errors.     

Crypt analysis of two time pads in case of compressed speech

Keystream reuse, also known as the two time pad problem, is a well known weakness in stream ciphers. The implementers of the cryptographic algorithms are still underestimating this threat. The keystream reuse exploitation techniques presented so far assume the underlying plaintext to be textual data and all the heuristics presented previously are based on the language characteristics of the underlying text based data, which fail when compression is applied on the plaintext before encryption. This paper presents exploitation techniques for two time pads in case of stream ciphered digitized and compressed speech signals. In this paper we show that how an adversary can automatically recover the digitized speech signals encrypted under the same keystream provided the language (e.g. English) and digital encoding/compression scheme details of the underlying speech signals are known. Our technique of cryptanalysis is based on the modeling of the speech parameters by exploiting the inter frame correlations between each components of the speech vectors in different frames and then using these models to decode the two speech signals in the keystream reuse scenario. The technique is flexible enough to incorporate all modern speech coding schemes based on parameter or hybrid encoding and compression techniques. The simulation experiments have showed promising results for most of the present day speech digitization and compression techniques.