On resampling detection and its application to detect image tampering

Usually digital image forgeries are created by copy-pasting a portion of an image onto some other image. While doing so, it is often necessary to resize the pasted portion of the image to suit the sampling grid of the host image. The resampling operation changes certain characteristics of the pasted portion, which when detected serves as a clue of tampering. In this paper, we present deterministic techniques to detect resampling, and localize the portion of the image that has been tampered with. Two of the techniques are in pixel domain and two others in frequency domain. We study the efficacy of our techniques against JPEG compression and subsequent resampling of the entire tampered image.

Transient signal detection using wigner-ville distribution and wavelet denoising

The problem of detecting an unknown transient signal in noise is considered. The SNR of the observed data is first enhanced using wavelet domain filter The output of the wavelet domain filter is then transformed using a Wigner-Ville transform,which separates the spectrum of the observed signal into narrow frequency bands. Each subband signal at the output of the Wigner-ville block is subjected kto wavelet based level dependent denoising (WBLDD)to supress colored noise A weighted sum of the absolute value of outputs of WBLDD is passed through an energy detector, whose output is used as test statistic to take the final decision. By assigning weights proportional to the energy of the corresponding subband signals, the proposed detector approximates a frequency domain matched filter Simulation results are presented to show that the performance of the proposed detector is better than that of the wavelet packet transform based detector.

Comparative study of filter-bank mean-energy distance for automated segmentation of speech signals

This paper describes a method of automated segmentation of speech assuming the signal is continuously time varying rather than the traditional short time stationary model. It has been shown that this representation gives comparable if not marginally better results than the other techniques for automated segmentation. A formulation of the 'Bach' (music semitonal) frequency scale filter-bank is proposed. A comparative study has been made of the performances using Mel, Bark and Bach scale filter banks considering this model. The preliminary results show up to 80 % matches within 20 ms of the manually segmented data, without any information of the content of the text and without any language dependence. 'Bach' filters are seen to marginally outperform the other filters.

Language independent automated segmentation of speech using Bach scale filter-banks

This correspondence describes a method for automated segmentation of speech. The method proposed in this paper uses a specially designed filter-bank called Bach filter-bank which makes use of 'music' related perception criteria. The speech signal is treated as continuously time varying signal as against a short time stationary model. A comparative study has been made of the performances using Mel, Bark and Bach scale filter banks. The preliminary results show up to 80 % matches within 20 ms of the manually segmented data, without any information of the content of the text and without any language dependence. The Bach filters are seen to marginally outperform the other filters.

Pressure sensor based tsunami detection system: A laboratory study

In this paper, we present the study and implementation of a low-cost system to detect the occurrences of tsunamis at significantly smaller laboratory scale. The implementation is easily scalable for real-time deployment. Information reported in this paper includes the experimentally recorded response from the pressure sensor giving an indication as well as an alarm at remote place for the detection of water turbulence similar to the case of tsunami. It has been found that the system developed works very well in the laboratory scale.

Acoustic emission technique for leak detection in an end shield of a pressurised heavy water reactor

This paper discusses a successful application of the Acoustic Emission Technique (AET) for the detection and location of leak paths present on an inaccessible side of an end shield of a Pressurised Heavy Water Reactor (PHWR). The methodology was based on the fact that air- and water-leak AE signals have different characteristic features. Baseline data was generated from a sound end shield of a PHWR for characterising the background noise. A mock-up end shield system with saw-cut leak paths was used to verify the validity of the methodology. It was found that air-leak signals under pressurisation (as low as 3 psi) could be detected by frequency domain analysis. Signals due to air leaks from various locations of defective end shield were acquired and analysed. It was possible to detect and locate leak paths. The presence of detected leak paths was further confirmed by an alternative test.

Detection of Tsunami Wave Generation and Propagation Using Fiber Bragg Grating Sensors

This paper describes the design and development of a Fiber Bragg Grating (FBG) sensor system for monitoring tsunami waves generated in the deep ocean. An experimental setup was designed and fabricated to simulate the generation and propagation of a tsunami wave. The characteristics and efficiency of the developed FBG sensor was evaluated with a standard commercial Digiquartz sensor. For real time monitoring of tsunami waves, FBG sensors bonded to a cantilever is used and the wavelength shifts (Delta lambda(B)) in the reflected spectra resulting from the strain/pressure imparted on the FBGs have been recorded using a high-speed Micron Optics FBG interrogation system. The parameters sensed are the signal burst during tsunami generation and pressure variations at different places as the tsunami wave propagates away from the source of generation. The results obtained were compared with the standard commercial sensor used in tsunami detection. The observations suggest that the FBG sensor was highly sensitive and free from many of the constraints associated with the commercial tsunameter.

Detection of moisture stress by indicator plots — A simulation

The possibility of advanced indication of moisture stress in a crop by small prepared plots with compacted or partially sand-substituted soils is examined by an analytical simulation. A series of soils and three crops are considered for the simulation. The moisture characteristics of the soils are calculated with an available model. Using average potential evapotranspiration values and a simple actual evapotranspiration model, the onset of moisture stress in the natural and indicator plots is calculated for different degrees of sand substitution and compaction. Cases where sand substitution fails are determined. The effect of intervening rainfall and limited root depth on the beginning of moisture stress is investigated.

Narrowband Detection of Acoustic Source in Shallow Ocean using Vector Sensor Array

The problem of narrowband CFAR (constant false alarm rate) detection of an acoustic source at an unknown location in a range-independent shallow ocean is considered. If a target is present, the received signal vector at an array of N sensors belongs to an M-dimensional subspace if N exceeds the number of propagating modes M in the ocean. A subspace detection method which utilises the knowledge of the signal subspace to enhance the detector performance is presented in thisMpaper. It is shown that, for a given number of sensors N, the performance of a detector using a vector sensor array is significantly better than that using a scalar sensor array. If a target is detected, the detector using a vector sensor array also provides a concurrent coarse estimate of the bearing of the target.

sRNAscanner: A Computational Tool for Intergenic Small RNA Detection in Bacterial Genomes

Background:Bacterial non-coding small RNAs (sRNAs) have attracted considerable attention due to their ubiquitous nature and contribution to numerous cellular processes including survival, adaptation and pathogenesis. Existing computational approaches for identifying bacterial sRNAs demonstrate varying levels of success and there remains considerable room for improvement. Methodology/Principal Findings: Here we have proposed a transcriptional signal-based computational method to identify intergenic sRNA transcriptional units (TUs) in completely sequenced bacterial genomes. Our sRNAscanner tool uses position weight matrices derived from experimentally defined E. coli K-12 MG1655 sRNA promoter and rho-independent terminator signals to identify intergenic sRNA TUs through sliding window based genome scans. Analysis of genomes representative of twelve species suggested that sRNAscanner demonstrated equivalent sensitivity to sRNAPredict2, the best performing bioinformatics tool available presently. However, each algorithm yielded substantial numbers of known and uncharacterized hits that were unique to one or the other tool only. sRNAscanner identified 118 novel putative intergenic sRNA genes in Salmonella enterica Typhimurium LT2, none of which were flagged by sRNAPredict2. Candidate sRNA locations were compared with available deep sequencing libraries derived from Hfq-co-immunoprecipitated RNA purified from a second Typhimurium strain (Sittka et al. (2008) PLoS Genetics 4: e1000163). Sixteen potential novel sRNAs computationally predicted and detected in deep sequencing libraries were selected for experimental validation by Northern analysis using total RNA isolated from bacteria grown under eleven different growth conditions. RNA bands of expected sizes were detected in Northern blots for six of the examined candidates. Furthermore, the 5'-ends of these six Northern-supported sRNA candidates were successfully mapped using 5'-RACE analysis. Conclusions/Significance: We have developed, computationally examined and experimentally validated the sRNAscanner algorithm. Data derived from this study has successfully identified six novel S. Typhimurium sRNA genes. In addition, the computational specificity analysis we have undertaken suggests that similar to 40% of sRNAscanner hits with high cumulative sum of scores represent genuine, undiscovered sRNA genes. Collectively, these data strongly support the utility of sRNAscanner and offer a glimpse of its potential to reveal large numbers of sRNA genes that have to date defied identification. sRNAscanner is available from: http://bicmku.in:8081/sRNAscanner or http://cluster.physics.iisc.ernet.in/sRNAscanner/.

Actuator fault detection and isolation in linear systems

A scheme for the detection and isolation of actuator faults in linear systems is proposed. A bank of unknown input observers is constructed to generate residual signals which will deviate in characteristic ways in the presence of actuator faults. Residual signals are unaffected by the unknown inputs acting on the system and this decreases the false alarm and miss probabilities. The results are illustrated through a simulation study of actuator fault detection and isolation in a pilot plant doubleeffect evaporator.

Design and fabrication of an automated temperature programmed reaction system to evaluate 3-way catalysts Ce1-x-y(La/Y)(x)PtyO2-delta

A completely automated temperature-programmed reaction (TPR) system for carrying out gas-solid catalytic reactions under atmospheric flow conditions is fabricated to study CO and hydrocarbon oxidation, and NO reduction. The system consists of an all-stainless steel UHV system, quadrupole mass spectrometer SX200 (VG Scientific), a tubular furnace and micro-reactor, a temperature controller, a versatile gas handling system, and a data acquisition and analysis system. The performance of the system has been tested under standard experimental conditions for CO oxidation over well-characterized Ce1-x-y(La/Y)(y)O2-delta catalysts. Testing of 3-way catalysis with CO, NO and C2H2 to convert to CO2, N-2 and H2O is done with this catalyst which shows complete removal of pollutants below 325 degrees C. Fixed oxide-ion defects in Pt substituted Ce1-y(La/Y)(y)O2-y/2 show higher catalytic activity than Pt ion-substituted CeO2

A Training-Based Iterative Detection/Channel Estimation Scheme for Large Non-Orthogonal STBC MIMO Systems

In this paper, we propose a training-based channel estimation scheme for large non-orthogonal space-time block coded (STBC) MIMO systems.The proposed scheme employs a block transmission strategy where an N-t x N-t pilot matrix is sent (for training purposes) followed by several N-t x N-t square data STBC matrices, where Nt is the number of transmit antennas. At the receiver, we iterate between channel estimation (using an MMSE estimator) and detection (using a low-complexity likelihood ascent search (LAS) detector) till convergence or for a fixed number of iterations. Our simulation results show that excellent bit error rate and nearness-to-capacity performance are achieved by the proposed scheme at low complexities. The fact that we could show such good results for large STBCs (e.g., 16 x 16 STBC from cyclic division algebras) operating at spectral efficiencies in excess of 20 bps/Hz (even after accounting for the overheads meant for pilot-based channel estimation and turbo coding) establishes the effectiveness of the proposed scheme.

Direct detection of atmospheric particle formation using the Neutral cluster and Air Ion Spectrometer

Aerosol particles play an important role in the Earth s atmosphere and in the climate system: they scatter and absorb solar radiation, facilitate chemical processes, and serve as seeds for cloud formation. Secondary new particle formation (NPF) is a globally important source of these particles. Currently, the mechanisms of particle formation and the vapors participating in this process are, however, not truly understood. In order to fully explain atmospheric NPF and subsequent growth, we need to measure directly the very initial steps of the formation processes. This thesis investigates the possibility to study atmospheric particle formation using a recently developed Neutral cluster and Air Ion Spectrometer (NAIS). First, the NAIS was calibrated and intercompared, and found to be in good agreement with the reference instruments both in the laboratory and in the field. It was concluded that NAIS can be reliably used to measure small atmospheric ions and particles directly at the sizes where NPF begins. Second, several NAIS systems were deployed simultaneously at 12 European measurement sites to quantify the spatial and temporal distribution of particle formation events. The sites represented a variety of geographical and atmospheric conditions. The NPF events were detected using NAIS systems at all of the sites during the year-long measurement period. Various particle formation characteristics, such as formation and growth rates, were used as indicators of the relevant processes and participating compounds in the initial formation. In a case of parallel ion and neutral cluster measurements, we also estimated the relative contribution of ion-induced and neutral nucleation to the total particle formation. At most sites, the particle growth rate increased with the increasing particle size indicating that different condensing vapors are participating in the growth of different-sized particles. The results suggest that, in addition to sulfuric acid, organic vapors contribute to the initial steps of NPF and to the subsequent growth, not just later steps of the particle growth. As a significant new result, we found out that the total particle formation rate varied much more between the different sites than the formation rate of charged particles. The results infer that the ion-induced nucleation has a minor contribution to particle formation in the boundary layer in most of the environments. These results give tools to better quantify the aerosol source provided by secondary NPF in various environments. The particle formation characteristics determined in this thesis can be used in global models to assess NPF s climatic effects.