False Error Study of On-line Soft Error Detection Mechanisms

With technology scaling, vulnerability to soft errors in random logic is increasing. There is a need for on-line error detection and protection for logic gates even at sea level. The error checker is the key element for an on-line detection mechanism. We compare three different checkers for error detection from the point of view of area, power and false error detection rates. We find that the double sampling checker (used in Razor), is the simplest and most area and power efficient, but suffers from very high false detection rates of 1.15 times the actual error rates. We also find that the alternate approaches of triple sampling and integrate and sample method (I&S) can be designed to have zero false detection rates, but at an increased area, power and implementation complexity. The triple sampling method has about 1.74 times the area and twice the power as compared to the Double Sampling method and also needs a complex clock generation scheme. The I&S method needs about 16% more power with 0.58 times the area as double sampling, but comes with more stringent implementation constraints as it requires detection of small voltage swings.

On the Average Case Communication Complexity for Detection in Sensor Networks

The problem of sensor-network-based distributed intrusion detection in the presence of clutter is considered. It is argued that sensing is best regarded as a local phenomenon in that only sensors in the immediate vicinity of an intruder are triggered. In such a setting, lack of knowledge of intruder location gives rise to correlated sensor readings. A signal-space viewpoint is introduced in which the noise-free sensor readings associated to intruder and clutter appear as surfaces $\mathcal{S_I}$ and $\mathcal{S_C}$ and the problem reduces to one of determining in distributed fashion, whether the current noisy sensor reading is best classified as intruder or clutter. Two approaches to distributed detection are pursued. In the first, a decision surface separating $\mathcal{S_I}$ and $\mathcal{S_C}$ is identified using Neyman-Pearson criteria. Thereafter, the individual sensor nodes interactively exchange bits to determine whether the sensor readings are on one side or the other of the decision surface. Bounds on the number of bits needed to be exchanged are derived, based on communication complexity (CC) theory. A lower bound derived for the two-party average case CC of general functions is compared against the performance of a greedy algorithm. The average case CC of the relevant greater-than (GT) function is characterized within two bits. In the second approach, each sensor node broadcasts a single bit arising from appropriate two-level quantization of its own sensor reading, keeping in mind the fusion rule to be subsequently applied at a local fusion center. The optimality of a threshold test as a quantization rule is proved under simplifying assumptions. Finally, results from a QualNet simulation of the algorithms are presented that include intruder tracking using a naive polynomial-regression algorithm.

Optimal sleep-wake scheduling for quickest intrusion detection using sensor networks

We consider the problem of quickest detection of an intrusion using a sensor network, keeping only a minimal number of sensors active. By using a minimal number of sensor devices, we ensure that the energy expenditure for sensing, computation and communication is minimized (and the lifetime of the network is maximized). We model the intrusion detection (or change detection) problem as a Markov decision process (MDP). Based on the theory of MDP, we develop the following closed loop sleep/wake scheduling algorithms: (1) optimal control of Mk+1, the number of sensors in the wake state in time slot k + 1, (2) optimal control of qk+1, the probability of a sensor in the wake state in time slot k + 1, and an open loop sleep/wake scheduling algorithm which (3) computes q, the optimal probability of a sensor in the wake state (which does not vary with time), based on the sensor observations obtained until time slot k. Our results show that an optimum closed loop control on Mk+1 significantly decreases the cost compared to keeping any number of sensors active all the time. Also, among the three algorithms described, we observe that the total cost is minimum for the optimum control on Mk+1 and is maximum for the optimum open loop control on q.

Thiourea based novel chromogenic sensor for selective detection of fluoride and cyanide anions in organic and aqueous media

Novel chromogenic thiourea based sensors 4,4'-bis-[3-(4-nitrophenyl) thiourea] diphenyl ether 1 and 4,4'-bis-[3-(4-nitrophenyl) thiourea] diphenyl methane 2 having nitrophenyl group as signaling unit have been synthesized and characterized by spectroscopic techniques and X-ray crystallography. The both sensors show visual detection, UV-vis and NMR spectral changes in presence of fluoride and cyanide anions in organic solvent as well as in aqueous medium. The absorption spectra indicated the formation of complex between host and guest is in 1:2 stoichiometric ratios. (C) 2010 Elsevier B.V. All rights reserved.

Multiple excitation nano-spot generation and confocal detection for far-field microscopy

An imaging technique is developed for the controlled generation of multiple excitation nano-spots for far-field microscopy. The system point spread function (PSF) is obtained by interfering two counter-propagating extended depth-of-focus PSF (DoF-PSF), resulting in highly localized multiple excitation spots along the optical axis. The technique permits (1) simultaneous excitation of multiple planes in the specimen; (2) control of the number of spots by confocal detection; and (3) overcoming the point-by-point based excitation. Fluorescence detection from the excitation spots can be efficiently achieved by Z-scanning the detector/pinhole assembly. The technique complements most of the bioimaging techniques and may find potential application in high resolution fluorescence microscopy and nanoscale imaging.

Novel fluorescence detection technique for non-contact temperature sensing in microchip PCR

DNA amplification using Polymerase Chain Reaction (PCR) in a small volume is used in Lab-on-a-chip systems involving DNA manipulation. For few microliters of volume of liquid, it becomes difficult to measure and monitor the thermal profile accurately and reproducibly, which is an essential requirement for successful amplification. Conventional temperature sensors are either not biocompatible or too large and hence positioned away from the liquid leading to calibration errors. In this work we present a fluorescence based detection technique that is completely biocompatible and measures directly the liquid temperature. PCR is demonstrated in a 3 ILL silicon-glass microfabricated device using non-contact induction heating whose temperature is controlled using fluorescence feedback from SYBR green I dye molecules intercalated within sensor DNA. The performance is compared with temperature feedback using a thermocouple sensor. Melting curve followed by gel electrophoresis is used to confirm product specificity after the PCR cycles. (c) 2007 Elsevier B.V. All rights reserved.

Self-Assembly of a Nanoscopic Prism via a New Organometallic Pt3 Acceptor and Its Fluorescent Detection of Nitroaromatics

A nanoscale-sized cage with a trigonal prismatic shape is prepared by coordination-driven self-assembly of a predesigned organometallic Pt-3 acceptor with an organic clip-type ligand. This trigonal prism is fluorescent and undergoes efficient fluorescence quenching by nitroaromatics, which are the chemical signatures of many explosives.

Target reliability based design optimization of anchored cantilever sheet pile walls

In this study, the stability of anchored cantilever sheet pile wall in sandy soils is investigated using reliability analysis. Targeted stability is formulated as an optimization problem in the framework of an inverse first order reliability method. A sensitivity analysis is conducted to investigate the effect of parameters influencing the stability of sheet pile wall. Backfill soil properties, soil - steel pile interface friction angle, depth of the water table from the top of the sheet pile wall, total depth of embedment below the dredge line, yield strength of steel, section modulus of steel sheet pile, and anchor pull are all treated as random variables. The sheet pile wall system is modeled as a series of failure mode combination. Penetration depth, anchor pull, and section modulus are calculated for various target component and system reliability indices based on three limit states. These are: rotational failure about the position of the anchor rod, expressed in terms of moment ratio; sliding failure mode, expressed in terms of force ratio; and flexural failure of the steel sheet pile wall, expressed in terms of the section modulus ratio. An attempt is made to propose reliability based design charts considering the failure criteria as well as the variability in the parameters. The results of the study are compared with studies in the literature.

Performance of RT-PCR-ELISA for the detection of peste des petits ruminants virus

A highly sensitive and specific reverse transcription polymerase chain reaction enzyme linked immunosorbent assay (RT-PCR-ELISA) was developed for the objective detection of nucleoprotein (N) gene of peste des petits ruminants (PPR) virus from field outbreaks or experimentally infected sheep. Two primers (IndF and Np4) and one probe (Sp3) available or designed for the amplification/probing of the 'N' gene of PPR virus, were chosen for labeling and use in RT-PCR-ELISA based on highest analytical sensitivity of detection of infective virus or N-gene containing recombinant plasmid, higher nucleotide homology at the primer binding sites of the 'N' gene sequences available and the ability to amplify PPR viral genome from different sources of samples. RT-PCR was performed with unlabeled IndF and Np4 digoxigenin labeled primers followed by a microplate hybridization probe reaction with biotin labeled Sp3 probe. RT-PCR-ELISA was found to be 10-fold more sensitive than the conventional RT-PCR followed by agarose gel based detection of PCR product. Based on the Mean (mean +/- 3S.D.) optical density (OD) values of 47 RT-PCR negative samples, OD values above 0.306 were considered positive in RT-PCR-ELISA. A total of 82 oculo-nasal swabs and tissue samples from suspected PPR cases were analyzed by RT-PCR and RT-PCR-ELISA, which revealed 54.87 and 58.54% positivity, respectively. From an experimentally infected sheep, both RT-PCR and RT-PCR-ELISA could detect the virus from 6 days post-infection up to 9 days in oculo-nasal swabs. On post-mortem, PPR viral genome was detected in spleen, lymph node, lung, heart and liver. The correlation co-efficient between RT-PCR-ELISA OD values and either TCID50 of virus or molecules of DNA was 0.622 and 0.657, respectively. The advantages of RT-PCR-ELISA over the conventional agarose gel based detection of RT-PCR products are discussed. (c) 2006 Elsevier B.V. All rights reserved.

Usefulness of DARPA dataset for intrusion detection system evaluation

The MIT Lincoln Laboratory IDS evaluation methodology is a practical solution in terms of evaluating the performance of Intrusion Detection Systems, which has contributed tremendously to the research progress in that field. The DARPA IDS evaluation dataset has been criticized and considered by many as a very outdated dataset, unable to accommodate the latest trend in attacks. Then naturally the question arises as to whether the detection systems have improved beyond detecting these old level of attacks. If not, is it worth thinking of this dataset as obsolete? The paper presented here tries to provide supporting facts for the use of the DARPA IDS evaluation dataset. The two commonly used signature-based IDSs, Snort and Cisco IDS, and two anomaly detectors, the PHAD and the ALAD, are made use of for this evaluation purpose and the results support the usefulness of DARPA dataset for IDS evaluation.

KAT5 (Tip60) is a potential therapeutic target in malignant pleural mesothelioma

Malignant pleural mesothelioma (MPM) is a rare aggressive cancer of the pleura. Asbestos exposure (through inhalation) is the most well established risk factor for mesothelioma. The current standard of care for patients suffering from MPM is a combination of cisplatin and pemetrexed (or alternatively cisplatin and raltitrexed). Most patients, however, die within 24 months of diagnosis. New therapies are therefore urgently required for this disease. Lysine acetyltransferases (KATs) including KAT5 have been linked with the development of cisplatin resistance. This gene may therefore be altered in MPM and could represent a novel candidate target for intervention. Using RT-PCR screening the expression of all known KAT5 variants was found to be markedly increased in malignant tumors compared to benign pleura. When separated according to histological subtype, KAT5 was significantly overexpressed in both the sarcomatoid and biphasic subgroups for all transcript variants. A panel of MPM cell lines including the normal pleural cells LP9 and Met5A was screened for expression of KAT5 variants. Treatment of cells with a small molecule inhibitor of KAT5 (MG-149) caused significant inhibition of cellular proliferation (p<0.0001), induction of apoptosis and was accompanied by significant induction of pro-inflammatory cytokines/chemokines.