Sensing motion using spectral and spatial analysis of WLAN RSSI

In this paper we present how motion sensing can be obtained just by observing the WLAN radio signal strength and its fluctuations. The temporal, spectral and spatial characteristics of WLAN signal are analyzed. Our analysis confirms our claim that ’signal strength from access points appear to jump around more vigorously when the device is moving compared to when it is still and the number of detectable access points vary considerably while the user is on the move’. Using this observation, we present a novel motion detection algorithm, Spectrally Spread Motion Detection (SpecSMD) based on the spectral analysis of WLAN signal’s RSSI. To benchmark the proposed algorithm, we used Spatially Spread Motion Detection (SpatSMD), which is inspired by the recent work of Sohn et al. Both algorithms were evaluated by carrying out extensive measurements in a diverse set of conditions (indoors in different buildings and outdoors - city center, parking lot, university campus etc.,) and tested against the same data sets. The 94% average classification accuracy of the proposed SpecSMD is outperforming the accuracy of SpatSMD (accuracy 87%). The motion detection algorithms presented in this paper provide ubiquitous methods for deriving the state of the user. The algorithms can be implemented and run on a commodity device with WLAN capability without the need of any additional hardware support

Using time-of-flight for WLAN localization: feasibility study

Although signal strength based techniques are widely employed for WLAN localization, they generally suffer from providing highly accurate location information. In this paper, we first present the general shortcomings of the signal strength based approaches used for WLANbased localization and then state reasons why time-of-flight could be an attractive alternative. We subsequently analyze the feasibility of using time-of-flight technique for WLAN localization by synchronizing the clock using Network Time Protocol (NTP) as well as measuring the time at (i) network layer level, (ii) data link layer level, and (iii) firmware level. We conclude that at present using TOF is not a feasible approach because of the limitation of current hardware and protocols

Managing Risk of Bidding in Display Advertising

In this paper, we deal with the uncertainty of bidding for display advertising. Similar to the financial market trading, real-time bidding (RTB) based display advertising employs an auction mechanism to automate the impression level media buying; and running a campaign is no different than an investment of acquiring new customers in return for obtaining additional converted sales. Thus, how to optimally bid on an ad impression to drive the profit and return-on-investment becomes essential. However, the large randomness of the user behaviors and the cost uncertainty caused by the auction competition may result in a significant risk from the campaign performance estimation. In this paper, we explicitly model the uncertainty of user click-through rate estimation and auction competition to capture the risk. We borrow an idea from finance and derive the value at risk for each ad display opportunity. Our formulation results in two risk-aware bidding strategies that penalize risky ad impressions and focus more on the ones with higher expected return and lower risk. The empirical study on real-world data demonstrates the effectiveness of our proposed risk-aware bidding strategies: yielding profit gains of 15.4% in offline experiments and up to 17.5% in an online A/B test on a commercial RTB platform over the widely applied bidding strategies

Stochastic Budget Optimization in Internet Advertising

Internet advertising is a sophisticated game in which the many advertisers "play" to optimize their return on investment. There are many "targets" for the advertisements, and each "target" has a collection of games with a potentially different set of players involved. In this paper, we study the problem of how advertisers allocate their budget across these "targets". In particular, we focus on formulating their best response strategy as an optimization problem. Advertisers have a set of keywords ("targets") and some stochastic information about the future, namely a probability distribution over scenarios of cost vs click combinations. This summarizes the potential states of the world assuming that the strategies of other players are fixed. Then, the best response can be abstracted as stochastic budget optimization problems to figure out how to spread a given budget across these keywords to maximize the expected number of clicks. We present the first known non-trivial poly-logarithmic approximation for these problems as well as the first known hardness results of getting better than logarithmic approximation ratios in the various parameters involved. We also identify several special cases of these problems of practical interest, such as with fixed number of scenarios or with polynomial-sized parameters related to cost, which are solvable either in polynomial time or with improved approximation ratios. Stochastic budget optimization with scenarios has sophisticated technical structure. Our approximation and hardness results come from relating these problems to a special type of (0/1, bipartite) quadratic programs inherent in them. Our research answers some open problems raised by the authors in (Stochastic Models for Budget Optimization in Search-Based Advertising, Algorithmica, 58 (4), 1022-1044, 2010).Comment: FINAL versio

Cross-Document Pattern Matching

We study a new variant of the string matching problem called cross-document string matching, which is the problem of indexing a collection of documents to support an efficient search for a pattern in a selected document, where the pattern itself is a substring of another document. Several variants of this problem are considered, and efficient linear-space solutions are proposed with query time bounds that either do not depend at all on the pattern size or depend on it in a very limited way (doubly logarithmic). As a side result, we propose an improved solution to the weighted level ancestor problem

SYNTHESIS OF SILVER NANOPARTICLES FROM Ruellia tuberose Linn PLANT

Nanobiotechnology is emerging as a field of applied biological sciences and nanotechnology. The synthesis of nanoparticles is done by various physical and chemical methods, But biological methods are relatively simple, inexpensive, nontoxic and environmentally friendly methods. The current review focuses on the synthesis of nanoparticles, with particular emphasis on the use of parts of plants for the synthesis process, its applications and future prospectus

ANTIBACTERIAL PLANT EXTRACTS AND FORMULATION OF MOUTHWASH

In this study, we examined the medicinal properties of medicinal plants Achyranthes aspera Linn and Jatropha gossypifolia individually as well as their synergism. Different solvents system used to extract the principle compound present in these selected plants and solvent were chosen based on their polarity from high polar solvent to low polar. The ethanol extract of Achyranthes aspera and Jatropha gossypifolia has maximum activity against the microorganism Staphylococcus aureus. The effective compounds present in the extracted sample were evaluated by generating chromatogram in Thin Layer Chromatography technique. The quality and purity were confirmed by HPLC. The synergistic activity of ethanolic extract of these plants shows significant antibacterial activity

Theory of the optical absorption of light carrying orbital angular momentum by semiconductors

We develop a free-carrier theory of the optical absorption of light carrying orbital angular momentum (twisted light) by bulk semiconductors. We obtain the optical transition matrix elements for Bessel-mode twisted light and use them to calculate the wave function of photo-excited electrons to first-order in the vector potential of the laser. The associated net electric currents of first and second-order on the field are obtained. It is shown that the magnetic field produced at the center of the beam for the $\ell=1$ mode is of the order of a millitesla, and could therefore be detected experimentally using, for example, the technique of time-resolved Faraday rotation.Comment: Submitted to Phys. Rev. Lett. (23 Jan 2008

Cuticular protein with a low complexity sequence becomes cross-linked during insect cuticle sclerotization and is required for the adult molt

Citation: Mun, S., Noh, M. Y., Dittmer, N. T., Muthukrishnan, S., Kramer, K. J., Kanost, M. R., & Arakane, Y. (2015). Cuticular protein with a low complexity sequence becomes cross-linked during insect cuticle sclerotization and is required for the adult molt. Scientific Reports, 5, 11. doi:10.1038/srep10484In the insect cuticle, structural proteins (CPs) and the polysaccharide chitin are the major components. It has been hypothesized that CPs are cross-linked to other CPs and possibly to chitin by quinones or quinone methides produced by the laccase2-mediated oxidation of N-acylcatechols. In this study we investigated functions of TcCP30, the third most abundant CP in protein extracts of elytra (wing covers) from Tribolium castaneum adults. The mature TcCP30 protein has a low complexity and highly polar amino acid sequence. TcCP30 is localized with chitin in horizontal laminae and vertically oriented columnar structures in rigid cuticles, but not in soft and membranous cuticles. Immunoblot analysis revealed that TcCP30 undergoes laccase2-mediated cross-linking during cuticle maturation in vivo, a process confirmed in vitro using recombinant rTcCP30. We identified TcCPR27 and TcCPR18, the two most abundant proteins in the elytra, as putative crosslinking partners of TcCP30. RNAi for the TcCP30 gene had no effect on larval and pupal growth and development. However, during adult eclosion, similar to 70% of the adults were unable to shed their exuvium and died. These results support the hypothesis that TcCP30 plays an integral role as a cross-linked structural protein in the formation of lightweight rigid cuticle of the beetle