Search for New Physics with a Dijet Plus Missing ET Signature in pp̅ Collisions at √s=1.96 TeV

We present results of a signature-based search for new physics using a dijet plus missing transverse energy data sample collected in 2 fb-1 of p-pbar collisions at sqrt(s) = 1.96 TeV with the CDF II detector at the Fermilab Tevatron. We observe no significant event excess with respect to the standard model prediction and extract a 95% C.L. upper limit on the cross section times acceptance for a potential contribution from a non-standard model process. Based on this limit the mass of a first or second generation scalar leptoquark is constrained to be above 187 GeV/c^2.

Search for Bs0→μ+μ- and B0→μ+μ- Decays with 2 fb-1 of pp̅ Collisions

We have performed a search for Bs0→μ+μ- and B0→μ+μ- decays in pp̅ collisions at √s=1.96  TeV using 2  fb-1 of integrated luminosity collected by the CDF II detector at the Fermilab Tevatron Collider. The observed number of Bs0 and B0 candidates is consistent with background expectations. The resulting upper limits on the branching fractions are B(Bs0→μ+μ-)<5.8×10-8 and B(B0→μ+μ-)<1.8×10-8 at 95% C.L.

Search for Exclusive Z-Boson Production and Observation of High-Mass pp̅ →pγγp̅ →pl+l-p̅ Events in pp̅ Collisions at √s=1.96 TeV

We present a search for exclusive Z boson production in proton-antiproton collisions at sqrt(s) = 1.96 TeV, using the CDF II detector at Fermilab. We observe no exclusive Z->ll candidates and place the first upper limit on the exclusive Z cross section in hadron collisions, sigma(exclu) gammagamma->p+ll+pbar, and measure the cross section for M(ll) > 40 GeV/c2 and |eta(l)|

Search for new particles decaying into dijets in proton-antiproton collisions at √s=1.96 TeV

We present a search for new particles whose decays produce two jets (dijets) using proton-antiproton collision data corresponding to an integrated luminosity of 1.13 fb-1 collected with the CDF II detector. The measured dijet mass spectrum is found to be consistent with next-to-leading-order perturbative QCD predictions, and no significant evidence of new particles is found. We set upper limits at the 95% confidence level on cross sections times the branching fraction for the production of new particles decaying into dijets with both jets having a rapidity magnitude |y|

Search for Bs0→μ+μ- and B0→μ+μ- Decays with 2 fb-1 of pp̅ Collisions

We have performed a search for Bs-->mu+mu- and Bd-->mu+mu- decays in ppbar collisions at sqrt(s) = 1.96TeV using 2fb-1 of integrated luminosity collected by the CDF II detector at the Fermilab Tevatron Collider. The observed number of Bs and Bd candidates is consistent with background expectations. The resulting upper limits on the branching fractions are B(Bs-->mu+mu-) mu+mu-)

Search for new color-octet vector particle decaying to t tbar in p pbar collisions at sqrt{s} = 1.96 TeV

We present the result of a search for a massive color-octet vector particle, (e.g. a massive gluon) decaying to a pair of top quarks in proton-antiproton collisions with a center-of-mass energy of 1.96 TeV. This search is based on 1.9 fb$^{-1}$ of data collected using the CDF detector during Run II of the Tevatron at Fermilab. We study $t\bar{t}$ events in the lepton+jets channel with at least one $b$-tagged jet. A massive gluon is characterized by its mass, decay width, and the strength of its coupling to quarks. These parameters are determined according to the observed invariant mass distribution of top quark pairs. We set limits on the massive gluon coupling strength for masses between 400 and 800 GeV$/c^2$ and width-to-mass ratios between 0.05 and 0.50. The coupling strength of the hypothetical massive gluon to quarks is consistent with zero within the explored parameter space.

Search for the Decays B(s)0→e+μ- and B(s)0→e+e- in CDF Run II

We report results from a search for the lepton flavor violating decays $B^0_{(s)}\to e^+\mu^-$, and the flavor-changing neutral-current decays $B^0_{(s)} \to e^+ e^-$. The analysis uses data corresponding to ${\rm 2 fb^{-1}}$ of integrated luminosity of $p \bar{p}$ collisions at $\sqrt{s}=1.96 {\rm TeV}$ collected with the upgraded Collider Detector (CDF II) at the Fermilab Tevatron. The observed number of $B^0_{(s)}$ candidates is consistent with background expectations. The resulting Bayesian upper limits on the branching ratios at 90% credibility level are $\mathcal{B}(B^0_s \to e^{+}\mu^{-}) e^{+}\mu^{-})e^{+}\mu^{-}) 47.8 {\rm TeV/c^2}$, and ${M_{LQ}}(B^0\to e^+ \mu^-) > 59.3 {\rm TeV/c^2}$, at 90% credibility level.

Resolving Ambiguities in Confused Online Tamil Characters with Post Processing Algorithms

This paper addresses the problem of resolving ambiguities in frequently confused online Tamil character pairs by employing script specific algorithms as a post classification step. Robust structural cues and temporal information of the preprocessed character are extensively utilized in the design of these algorithms. The methods are quite robust in automatically extracting the discriminative sub-strokes of confused characters for further analysis. Experimental validation on the IWFHR Database indicates error rates of less than 3 % for the confused characters. Thus, these post processing steps have a good potential to improve the performance of online Tamil handwritten character recognition.

Two-agent cooperative search using game models with endurance-time constraints

In this article, the problem of two Unmanned Aerial Vehicles (UAVs) cooperatively searching an unknown region is addressed. The search region is discretized into hexagonal cells and each cell is assumed to possess an uncertainty value. The UAVs have to cooperatively search these cells taking limited endurance, sensor and communication range constraints into account. Due to limited endurance, the UAVs need to return to the base station for refuelling and also need to select a base station when multiple base stations are present. This article proposes a route planning algorithm that takes endurance time constraints into account and uses game theoretical strategies to reduce the uncertainty. The route planning algorithm selects only those cells that ensure the agent will return to any one of the available bases. A set of paths are formed using these cells which the game theoretical strategies use to select a path that yields maximum uncertainty reduction. We explore non-cooperative Nash, cooperative and security strategies from game theory to enhance the search effectiveness. Monte-Carlo simulations are carried out which show the superiority of the game theoretical strategies over greedy strategy for different look ahead step length paths. Within the game theoretical strategies, non-cooperative Nash and cooperative strategy perform similarly in an ideal case, but Nash strategy performs better than the cooperative strategy when the perceived information is different. We also propose a heuristic based on partitioning of the search space into sectors to reduce computational overhead without performance degradation.

Cascade PSI-BLAST web server: a remote homology search tool for relating protein domains

Owing to high evolutionary divergence, it is not always possible to identify distantly related protein domains by sequence search techniques. Intermediate sequences possess sequence features of more than one protein and facilitate detection of remotely related proteins. We have demonstrated recently the employment of Cascade PSI-BLAST where we perform PSI-BLAST for many 'generations', initiating searches from new homologues as well. Such a rigorous propagation through generations of PSI-BLAST employs effectively the role of intermediates in detecting distant similarities between proteins. This approach has been tested on a large number of folds and its performance in detecting superfamily level relationships is similar to 35% better than simple PSI-BLAST searches. We present a web server for this search method that permits users to perform Cascade PSI-BLAST searches against the Pfam, SCOP and SwissProt databases. The URL for this server is http://crick.mbu.iisc.ernet.in/similar to CASCADE/CascadeBlast.html.

Self assessment schemes for multi-agent cooperative search

In this paper, we present self assessment schemes (SAS) for multiple agents performing a search mission on an unknown terrain. The agents are subjected to limited communication and sensor ranges. The agents communicate and coordinate with their neighbours to arrive at route decisions. The self assessment schemes proposed here have very low communication and computational overhead. The SAS also has attractive features like scalability to large number of agents and fast decision-making capability. SAS can be used with partial or complete information sharing schemes during the search mission. We validate the performance of SAS using simulation on a large search space consisting of 100 agents with different information structures and self assessment schemes. We also compare the results obtained using SAS with that of a previously proposed negotiation scheme. The simulation results show that the SAS is scalable to large number of agents and can perform as good as the negotiation schemes with reduced communication requirement (almost 20% of that required for negotiation).

Glowworm-inspired robot swarm for simultaneous taxis towards multiple radiation sources

This paper presents a glowworm metaphor based distributed algorithm that enables a collection of minimalist mobile robots to split into subgroups, exhibit simultaneous taxis-behavior towards, and rendezvous at multiple radiation sources such as nuclear/hazardous chemical spills and fire-origins in a fire calamity. The algorithm is based on a glowworm swarm optimization (GSO) technique that finds multiple optima of multimodal functions. The algorithm is in the same spirit as the ant-colony optimization (ACO) algorithms, but with several significant differences. The agents in the glowworm algorithm carry a luminescence quantity called luciferin along with them. Agents are thought of as glowworms that emit a light whose intensity is proportional to the associated luciferin. The key feature that is responsible for the working of the algorithm is the use of an adaptive local-decision domain, which we use effectively to detect the multiple source locations of interest. The glowworms have a finite sensor range which defines a hard limit on the local-decision domain used to compute their movements. Extensive simulations validate the feasibility of applying the glowworm algorithm to the problem of multiple source localization. We build four wheeled robots called glowworms to conduct our experiments. We use a preliminary experiment to demonstrate the basic behavioral primitives that enable each glowworm to exhibit taxis behavior towards source locations and later demonstrate a sound localization task using a set of four glowworms.

Genetic algorithm for satellite customer assignment

The problem of assigning customers to satellite channels is considered. Finding an optimal allocation of customers to satellite channels is a difficult combinatorial optimization problem and is shown to be NP-complete in an earlier study. We propose a genetic algorithm (GA) approach to search for the best/optimal assignment of customers to satellite channels. Various issues related to genetic algorithms such as solution representation, selection methods, genetic operators and repair of invalid solutions are presented. A comparison of this approach with the standard optimization method is presented to show the advantages of this approach in terms of computation time

Adaptive load control of the central processor in a distributed system with a star topology

The author presents adaptive control techniques for controlling the flow of real-time jobs from the peripheral processors (PPs) to the central processor (CP) of a distributed system with a star topology. He considers two classes of flow control mechanisms: (1) proportional control, where a certain proportion of the load offered to each PP is sent to the CP, and (2) threshold control, where there is a maximum rate at which each PP can send jobs to the CP. The problem is to obtain good algorithms for dynamically adjusting the control level at each PP in order to prevent overload of the CP, when the load offered by the PPs is unknown and varying. The author formulates the problem approximately as a standard system control problem in which the system has unknown parameters that are subject to change. Using well-known techniques (e.g., naive-feedback-controller and stochastic approximation techniques), he derives adaptive controls for the system control problem. He demonstrates the efficacy of these controls in the original problem by using the control algorithms in simulations of a queuing model of the CP and the load controls.