Microarchitectures for Managing Chip Revenues under Process Variations

As transistor feature sizes continue to shrink intothe sub-90nm range and beyond, the effects of process variationson critical path delay and chip yields have amplified. A commonconcept to remedy the effects of variation is speed-binning, bywhich chips from a single batch are rated by a discrete range offrequencies and sold at different prices. In this paper, we discussstrategies to modify the number of chips in different bins andhence enhance the profits obtained from them. Particularly, wepropose a scheme that introduces a small Substitute Cacheassociated with each cache way to replicate the data elementsthat will be stored in the high latency lines. Assuming a fixedpricing model, this method increases the revenue by as much as13.8% without any impact on the performance of the chips.     

Generic visual analysis for multi- and hyperspectral image data

Multi- and hyperspectral imaging and data analysis has been investigated in the last decades in the context of various fields of application like remote sensing or microscopic spectroscopy. However, recent developments in sensor technology and a growing number of application areas require a more generic view on data analysis, that clearly expands the current, domain-specific approaches. In this context, we address the problem of interactive exploration of multi- and hyperspectral data, consisting of (semi-)automatic data analysis and scientific visualization in a comprehensive fashion. In this paper, we propose an approach that enables a generic interactive exploration and easy segmentation of multi- and hyperspectral data, based on characterizing spectra of an individual dataset, the so-called endmembers. Using the concepts of existing endmember extraction algorithms, we derive a visual analysis system, where the characteristic spectra initially identified serve as input to interactively tailor a problem-specific visual analysis by means of visual exploration. An optional outlier detection improves the robustness of the endmember detection and analysis. An adequate system feedback of the costly unmixing procedure for the spectral data with respect to the current set of endmembers is ensured by a novel technique for progressive unmixing and view update which is applied at user modification. The progressive unmixing is based on an efficient prediction scheme applied to previous unmixing results. We present a detailed evaluation of our system in terms of confocal Raman microscopy, common multispectral imaging and remote sensing.     

Krylov projection framework for Fourier model reduction

This paper analyzes the Fourier model reduction (FMR) method from a rational Krylov projection framework and shows how the FMR reduced model, which has guaranteed stability and a global error bound, can be computed in a numerically efficient and robust manner. By monitoring the rank of the Krylov subspace that underlies the FMR model, the projection framework also provides an improved criterion for determining the number of Fourier coefficients that are needed, and hence the size of the resulting reduced-order model. The advantages of applying FMR in the rational Krylov projection framework are demonstrated on a simple example.     

A Model for Cross-Domain Opinion Target Extraction in Sentiment Analysis

Opinion target extraction is one of the core tasks in sentiment analysis on text data. In recent years, dependency parser–based approaches have been commonly studied for opinion target extraction. However, dependency parsers are limited by language and grammatical constraints. Therefore, in this work, a sequential pattern-based rule mining model, which does not have such constraints, is proposed for cross-domain opinion target extraction from product reviews in unknown domains. Thus, knowing the domain of reviews while extracting opinion targets becomes no longer a requirement. The proposed model also reveals the difference between the concepts of opinion target and aspect, which are commonly confused in the literature. The model consists of two stages. In the first stage, the aspects of reviews are extracted from the target domain using the rules automatically generated from source domains. The aspects are also transferred from the source domains to a target domain. Moreover, aspect pruning is applied to further improve the performance of aspect extraction. In the second stage, the opinion target is extracted among the aspects extracted at the former stage using the rules automatically generated for opinion target extraction. The proposed model was evaluated on several benchmark datasets in different domains and compared against the literature. The experimental results revealed that the opinion targets of the reviews in unknown domains can be extracted with higher accuracy than those of the previous works.     

Nonlinear L2-by-3 transform for PAPR reduction in OFDM systems

Orthogonal frequency division multiplexing (OFDM), the multicarrier modulation technique with high bandwidth efficiency and robustness against multipath fading, is used in several high-speed broadband communication systems including digital video broadcasting (DVB), digital audio broadcasting (DAB), asymmetric digital subscriber line (ADSL), wireless local area network (WLAN IEEE 802.11a,g), high performance radio local area network (HIPERLAN 2), and worldwide interoperability for microwave access (WiMAX IEEE 802.16). However, the transmit signal in OFDM system has a high peak-to-average power ratio (PAPR), one of the major drawbacks of multicarrier transmission, and therefore high dynamic range is required in both the digital to analog converter (DAC) and the power amplifier (PA) for proper operation. Otherwise, the nonlinearities of PA cause out-of-band distortion and increase in bit error rate (BER). Therefore, the reduction in PAPR in OFDM system is desirable in order to obtain power efficiency and increase BER performance. In this paper, a new parametric PAPR reduction technique, L₂-by-3 transform from sliding norm transform (SNT) family is proposed. Based on its parameter, a significant PAPR reduction is obtained. This paper presents the analysis of power saving and computational complexity of the proposed method L₂-by-3 and comparison to two other methods; selected mapping and partial transmit sequence.     

Particle-based simulation of the interaction between fluid and knitwear

We present a particle-based method to simulate and visualize the interaction of knitwear with fluids. The knitwear is modeled using spring-mass systems and the fluid is modeled using the smoothed particle hydrodynamics method. Two-way coupling is achieved by considering surface tension, capillary, and interparticle forces between the fluid and knitwear. The simulation of fluid and knitwear particles is performed on the graphics processing unit. Photorealistic rendering of knitwear and fluid is achieved by using a hardware-accelerated rasterization-based rendering technique. Our method is able to simulate and visualize the macro- and microstructure of free-form knitwear and reflective and refractive characteristics of the fluid surface.     

A comparative study of AISC-360 and EC3 strength limit states

A study has been undertaken to evaluate the similarities and differences between the steel building design specifications used in the United States and Europe. Expressions for nominal strength presented in the AISC-360 Specification and the Eurocode 3 Specification were compared for fundamental limit states. In particular, rules for cross-section classification, tension members, compression members, I-shaped members subjected to flexure, I-shaped members subjected to shear, and fasteners were studied. Results of the investigation revealed that, in general, both specifications provide nominal capacities that are close to each other. Significant differences were reported for some limit states such as flexure in I-shaped members with non-compact flanges, shear and lateral torsional buckling in I-shaped members, and bearing strength at bolt holes. In this paper, the details of the comparative study are presented along with observations that are useful for practicing engineers.     

Effects and modelling of ultrasonic waste‐activated sludge disintegration

Sonication is a well‐known sludge pretreatment technique with the advantages of simple operation and high efficiency. However, it is an energy‐intensive process. Hence, it is very important to predetermine its sludge disintegration efficiency at varying pretreatment conditions in order to minimize the ultrasonic energy consumption. In this study, it was found that the ultrasonic sludge disintegration occurred in two stages: rapid and subsequent slow disintegration stages. For this reason, it was aimed to develop a simple and accurate mathematical model to describe the two‐stage sludge disintegration as a function of pretreatment conditions. Sludge concentration and ultrasonic density along with sonication period were involved in this model as independent variables. It was determined that the mathematical model can predict accurately the degree of sludge disintegration. Thus, the proposed model was seen to be very useful for evaluating the disintegration efficiency and/or for process design using the operating parameters under different conditions.