Expediency of Penetration Ratio and Evaluation of Mean Throughput for Safety and Commercial Applications in VANETs

Vehicular ad hoc network (VANET) applications are principally categorized into safety and commercial applications. Efficient traffic management for routing an emergency vehicle is of paramount importance in safety applications of VANETs. In the first case, a typical example of a high dense urban scenario is considered to demonstrate the role of penetration ratio for achieving reduced travel time between source and destination points. The major requirement for testing these VANET applications is a realistic simulation approach which would justify the results prior to actual deployment. A Traffic Simulator coupled with a Network Simulator using a feedback loop feature is apt for realistic simulation of VANETs. Thus, in this paper, we develop the safety application using traffic control interface (TraCI), which couples SUMO (traffic simulator) and NS2 (network simulator). Likewise, the mean throughput is one of the necessary performance measures for commercial applications of VANETs. In the next case, commercial applications have been considered wherein the data is transferred amongst vehicles (V2V) and between roadside infrastructure and vehicles (I2V), for which the throughput is assessed.

Automatic Recognition of Facial Features and Landmarking of Digital Human Head

Ergonomic design of products demands accurate human dimensions-anthropometric data. Manual measurement over live subjects, has several limitations like long time, required presence of subjects for every new measurement, physical contact etc. Hence the data currently available is limited and anthropometric data related to facial features is difficult to obtain. In this paper, we discuss a methodology to automatically detect facial features and landmarks from scanned human head models. Segmentation of face into meaningful patches corresponding to facial features is achieved by Watershed algorithms and Mathematical Morphology tools. Many Important physiognomical landmarks are identified heuristically.

A comparative study of erbium oxide and gadolinium oxide high-k dielectric thin films grown by low-pressure metalorganic chemical vapour deposition (MOCVD) using beta-Diketonates as precursors

In this paper, a comparative study of thin films of Er2O3 and Gd2O3 grown on n-type Si(100) by low-pressure metalorganic chemical vapour deposition (MOCVD) under the identical conditions has been presented. beta-Diketonate complex of rate earth metals was used as precursor. Description on the evolution of the morphology, structure, optical, and electrical characteristics of films with respect to growth parameters and post-deposition annealing process has been presented. As-gown Gd2O3 films grow with <111> texture, whereas the texture of Er2O3 films strongly depends on the growth temperature (either <100> or <111>). Compositional analysis reveals that the Gd2O3 films grown at or above 500degreesC are carbon free whereas Er2O3 films at upto 525degreesC show the presence of heteroatoms and Er2O3 films grown above 525degreesC are carbon five. The effective dielectric constant is in the range of 7-24, while the fixed charge density is in the range - 10(11) to 10(10) CM-2 as extracted from the C-V characteristics. DC I-V study was carried out to examine the leakage behaviour of films. It reveals that the as-grown Gd2O3 film was very leakey in nature. Annealing of the films in oxidizing ambient for a period of 20 min results in a drastic improvement in the leakage behaviour. The presence of heteroatoms (such as carbon) and their effect on the properties of films are discussed.

Observation of pseudo-gap and Kondo behaviour in Al70Pd30−xMnx quasicrystals

We report here the electrical and magnetic properties of Al70Pd30−xMnx quasicrystals (x=9 and 11), from resistivity and point contact spectroscopy measurements. Electrical resistivity shows a resistivity maximum for both of these compositions. The positive TCR at lower temperature is attributed to spin–orbit scattering. For x=11, we observe an upturn in the resistivity below 20 K, which follows a lnT dependence indicating Kondo-like behaviour. In the point contact spectroscopy studies we observe two regimes showing a V2 dependence at low bias voltages (for V<10 meV) crossing over to the V0.5 dependence at higher voltages. This is attributed to the signature of a pseudo-gap in the density of states at zero bias. We suggest that this V2 dependence can also arise due to magnetic scattering effects, which are signatures of the Kondo-like behaviour.

Evaluation of dynamic voltage and frequency scaling for stream programs

Dynamic Voltage and Frequency Scaling (DVFS) offers a huge potential for designing trade-offs involving energy, power, temperature and performance of computing systems. In this paper, we evaluate three different DVFS schemes - our enhancement of a Petri net performance model based DVFS method for sequential programs to stream programs, a simple profile based Linear Scaling method, and an existing hardware based DVFS method for multithreaded applications - using multithreaded stream applications, in a full system Chip Multiprocessor (CMP) simulator. From our evaluation, we find that the software based methods achieve significant Energy/Throughput2(ET−2) improvements. The hardware based scheme degrades performance heavily and suffers ET−2 loss. Our results indicate that the simple profile based scheme achieves the benefits of the complex Petri net based scheme for stream programs, and present a strong case for the need for independent voltage/frequency control for different cores of CMPs, which is lacking in most of the state-of-the-art CMPs. This is in contrast to the conclusions of a recent evaluation of per-core DVFS schemes for multithreaded applications for CMPs.

Relative roles of instruction count and cycles per instruction in WCET estimation

Most of the existing WCET estimation methods directly estimate execution time, ET, in cycles. We propose to study ET as a product of two factors, ET = IC * CPI, where IC is instruction count and CPI is cycles per instruction. Considering directly the estimation of ET may lead to a highly pessimistic estimate since implicitly these methods may be using worst case IC and worst case CPI. We hypothesize that there exists a functional relationship between CPI and IC such that CPI=f(IC). This is ascertained by computing the covariance matrix and studying the scatter plots of CPI versus IC. IC and CPI values are obtained by running benchmarks with a large number of inputs using the cycle accurate architectural simulator, Simplescalar on two different architectures. It is shown that the benchmarks can be grouped into different classes based on the CPI versus IC relationship. For some benchmarks like FFT, FIR etc., both IC and CPI are almost a constant irrespective of the input. There are other benchmarks that exhibit a direct or an inverse relationship between CPI and IC. In such a case, one can predict CPI for a given IC as CPI=f(IC). We derive the theoretical worst case IC for a program, denoted as SWIC, using integer linear programming(ILP) and estimate WCET as SWIC*f(SWIC). However, if CPI decreases sharply with IC then measured maximum cycles is observed to be a better estimate. For certain other benchmarks, it is observed that the CPI versus IC relationship is either random or CPI remains constant with varying IC. In such cases, WCET is estimated as the product of SWIC and measured maximum CPI. It is observed that use of the proposed method results in tighter WCET estimates than Chronos, a static WCET analyzer, for most benchmarks for the two architectures considered in this paper.

Exploiting coherence for the simultaneous discovery of latent facets and associated sentiments

Facet-based sentiment analysis involves discovering the latent facets, sentiments and their associations. Traditional facet-based sentiment analysis algorithms typically perform the various tasks in sequence, and fail to take advantage of the mutual reinforcement of the tasks. Additionally,inferring sentiment levels typically requires domain knowledge or human intervention. In this paper, we propose aseries of probabilistic models that jointly discover latent facets and sentiment topics, and also order the sentiment topics with respect to a multi-point scale, in a language and domain independent manner. This is achieved by simultaneously capturing both short-range syntactic structure and long range semantic dependencies between the sentiment and facet words. The models further incorporate coherence in reviews, where reviewers dwell on one facet or sentiment level before moving on, for more accurate facet and sentiment discovery. For reviews which are supplemented with ratings, our models automatically order the latent sentiment topics, without requiring seed-words or domain-knowledge. To the best of our knowledge, our work is the first attempt to combine the notions of syntactic and semantic dependencies in the domain of review mining. Further, the concept of facet and sentiment coherence has not been explored earlier either. Extensive experimental results on real world review data show that the proposed models outperform various state of the art baselines for facet-based sentiment analysis.