Multiple UAV Coalitions for a Search and Prosecute Mission

Unmanned aerial vehicles (UAVs) have the potential to carry resources in support of search and prosecute operations. Often to completely prosecute a target, UAVs may have to simultaneously attack the target with various resources with different capacities. However, the UAVs are capable of carrying only limited resources in small quantities, hence, a group of UAVs (coalition) needs to be assigned that satisfies the target resource requirement. The assigned coalition must be such that it minimizes the target prosecution delay and the size of the coalition. The problem of forming coalitions is computationally intensive due to the combinatorial nature of the problem, but for real-time applications computationally cheap solutions are required. In this paper, we propose decentralized sub-optimal (polynomial time) and decentralized optimal coalition formation algorithms that generate coalitions for a single target with low computational complexity. We compare the performance of the proposed algorithms to that of a global optimal solution for which we need to solve a centralized combinatorial optimization problem. This problem is computationally intensive because the solution has to (a) provide a coalition for each target, (b) design a sequence in which targets need to be prosecuted, and (c) take into account reduction of UAV resources with usage. To solve this problem we use the Particle Swarm Optimization (PSO) technique. Through simulations, we study the performance of the proposed algorithms in terms of mission performance, complexity of the algorithms and the time taken to form the coalition. The simulation results show that the solution provided by the proposed algorithms is close to the global optimal solution and requires far less computational resources.

Bounds on the Lifetime of Wireless Sensor Networks Employing Multiple Data Sinks

Employing multiple base stations is an attractive approach to enhance the lifetime of wireless sensor networks. In this paper, we address the fundamental question concerning the limits on the network lifetime in sensor networks when multiple base stations are deployed as data sinks. Specifically, we derive upper bounds on the network lifetime when multiple base stations are employed, and obtain optimum locations of the base stations (BSs) that maximize these lifetime bounds. For the case of two BSs, we jointly optimize the BS locations by maximizing the lifetime bound using a genetic algorithm based optimization. Joint optimization for more number of BSs is complex. Hence, for the case of three BSs, we optimize the third BS location using the previously obtained optimum locations of the first two BSs. We also provide simulation results that validate the lifetime bounds and the optimum locations of the BSs.

A compact proof of Fisher�s Fundamental Theorem for multiple loci

A systematic method is formulated to carry out theoretical analysis in a multilocus multiallele genetic system. As a special application, the Fundamental Theorem of Natural Selection is proved (in the continuous time model) for a multilocus multiallele system if all pairwise linkage disequilibria are zero.

Mycobacterium tuberculosis Expresses ftsE Gene Through Multiple Transcripts

Bacterial FtsE gene codes for the ATP-binding protein, FtsE, which in complex with the transmembrane protein, FtsX, participates in diverse cellular processes. Therefore, regulated expression of FtsE and FtsX might be critical to the human pathogen, Mycobacterium tuberculosis, under stress conditions. Although ftsX gene of M. tuberculosis (MtftsX) is known to be transcribed from a promoter inside the upstream gene, ftsE, the transcriptional status of ftsE gene of M. tuberculosis (MtftsE) remains unknown. Therefore, the authors initiated transcriptional analyses of MtftsE, using total RNA from M. tuberculosis cells that were grown under stress conditions, which the pathogen is exposed to, in granuloma in tuberculosis patients. Primer extension experiments showed the presence of putative transcripts, T1, T2, T3, and T4. T1 originated from the intergenic region between the upstream gene, MRA_3135, and MtftsE. T2 and T3 were found initiated from within MRA_3135. T4 was transcribed from a region upstream of MRA_3135. RT-PCR confirmed co-transcription of MRA_3135 and MtftsE. The cloned putative promoter regions for T1, T2, and T3 elicited transcriptional activity in Mycobacterium smegmatis transformants. T1, T2, and T3, but no new transcript, were present in the M. tuberculosis cells that were grown under the stress conditions, which the pathogen is exposed to in granuloma in tuberculosis patients. It showed lack of modulation of MtftsE transcripts under the stress conditions tested, indicating that ftsE may not have a stress response-specific function in M. tuberculosis.

An integrated model for optimal reservoir operation for irrigation of multiple crops

An integrated model is developed, based on seasonal inputs of reservoir inflow and rainfall in the irrigated area, to determine the optimal reservoir release policies and irrigation allocations to multiple crops. The model is conceptually made up of two modules, Module 1 is an intraseasonal allocation model to maximize the sum of relative yields of all crops, for a given state of the system, using linear programming (LP). The module takes into account reservoir storage continuity, soil moisture balance, and crop root growth with time. Module 2 is a seasonal allocation model to derive the steady state reservoir operating policy using stochastic dynamic programming (SDP). Reservoir storage, seasonal inflow, and seasonal rainfall are the state variables in the SDP. The objective in SDP is to maximize the expected sum of relative yields of all crops in a year. The results of module 1 and the transition probabilities of seasonal inflow and rainfall form the input for module 2. The use of seasonal inputs coupled with the LP-SDP solution strategy in the present formulation facilitates in relaxing the limitations of an earlier study, while affecting additional improvements. The model is applied to an existing reservoir in Karnataka State, India.

Blind separation of multiple co-channel BPSK signals arriving at an antenna array

In this letter, we propose a method for blind separation of d co-channel BPSK signals arriving at an antenna array. Our method involves two steps. In the first step, the received data vectors at the output of the array is grouped into 2d clusters. In the second step, we assign the 2d d-tuples with ±1 elements to these clusters in a consistent fashion. From the knowledge of the cluster to which a data vector belongs, we estimate the bits transmitted at that instant. Computer simulations are used to study the performance of our method

Cascades of Selective Pulses on Connected Single-Quantum Transitions Leading to the Selective Excitation of Multiple-Quantum Coherences

A symmetric cascade of selective pulses applied on connected transitions leads to the excitation of a selected multiple-quantum coherence by a well-defined angle. This cascade selectively operates on the subspace of the multiple-quantum coherence and acts as a generator of rotation selectively on the multiple-quantum subspace. Single-transition operator algebra has been used to explain these experiments. Experiments have been performed on two- and three-spin systems. It is shown that such experiments can be utilized to measure the relaxation times of selected multiple-quantum coherences or of a specifically prepared initial longitudinal state of the spin system.

Quasicrystals, crystals and multiple twins in rapidly solidified Al-Cr-Si, Al-Mn-Si and Al-Mn-Cr-Si alloys

The coexistence of quasicrystals and rational approximant structures (RAS) has been observed in melt-spun Al80Cr14Si6, Al80Mn14Si6 and Al75Mn10Cr5Si10 alloys. The presence of a b.c.c. alpha-AlMnSi phase in Al-Mn-Si and alpha-AlMnSi(Cr) phase in Al-Mn-Cr-Si has been seen. A multiple twinning around an irrational axis of the RAS has been reported in an aggregate of fine size cubic crystallites in all three alloys. Selected area diffraction patterns show that the crystalline aggregate symmetry is linked to the icosahedral point group symmetry (m35). Various ways of expressing the twin relationship in the cubic crystalline aggregates have been discussed. The thermal stability of the icosahedral phase at high temperatures reveals that the icosahedral phase in Al-Mn-Si and Al-Mn-Cr-Si alloys transforms to alpha-AlMnSi at temperatures of 690 and 670 K, respectively. In Al-Cr-Si alloy, heating to a high temperature (615 K) leads to the transformation of the icosahedral phase into a new metastable phase having an ordered cubic structure equivalent to alpha-AlMnSi. The occurrence of multiple twinning leading to icosahedral symmetry in the as-spun Al-Cr-Si alloy is presumably due to this metastable phase. Copyright (C) 1996 Acta Metallurgica Inc.

The Folding Mechanism of Barstar: Evidence for Multiple Pathways and Multiple Intermediates

The mechanism of folding of the small protein barstar in the pre-transition zone at pH 7, 25 degrees C has been characterized using rapid mixing techniques. Earlier studies had established the validity of the three-state U-S reversible arrow U-F reversible arrow N mechanism for folding and unfolding in the presence of guanidine hydrochloride (GdnHCl) at concentrations greater than 2.0 M, where U-S and U-F are the slow-refolding and fast-refolding unfolded forms, respectively, and N is the fully folded form. It is now shown that early intermediates, I-S1 and I-S2 as well as a late native-like intermediate, I-N, are present on the folding pathways of U-S, and an early intermediate I-F1 on the folding pathway of U-F, when bars tar is refolded in concentrations of GdnHCl below 2.0 M. The rates of formation and disappearance of I-N, and the rates of formation of N at three different concentrations of GdnHCl in the pre-transition zone have been measured. The data indicate that in 1.5 M GdnHCl, I-N is not fully populated on the U-S --> I-S1 --> I-N --> N pathway because the rate of its formation is so slow that the U-S reversible arrow U-F reversible arrow N pathway can effectively compete with that pathway. In 1.0 M GdnHCl, the U-S --> I-S1 --> I-N transition is so fast that I-N is fully populated. In 0.6 M GdnHCl, I-N appears not to be fully populated because an alternative folding pathway, U-S --> I-S2 --> N, becomes available for the folding of U-S, in addition to the U-S --> I-S1 --> I-N --> N pathway Measurement of the binding of the hydrophobic dye 1-anilino-8-naphthalenesulphonate (ANS) during folding indicates that ANS binds to two distinct intermediates, I-M1 and I-M2, that form within 2 ms on the U-S --> I-M1 --> I-S1 --> I-N --> N and U-S --> I-M2 --> I-S2 --> N pathways. There is no evidence for the accumulation of intermediates that can bind ANS on the folding pathway of U-F.

Rearrangement approaches to sesquiterpenes containing multiple contiguous quaternary carbon atoms. Total synthesis of (+/-)-myltayl-8(12)-ene and (+/-)-6-epijunicedranol

Details of the first total syntheses of the sesquiterpenes myltayl-8(12)-ene and 6-epijunicedran-8-ol are described. The aldehyde 13, obtained by Claisen rearrangement of cyclogeraniol, was transformed into the dienones 12 and 18. Boron trifluoride-diethyl ether mediated cyclization and rearrangement transformed the dienones 12 and 18 into the tricyclic ketones 16 and 17, efficiently creating three and four contiguous quaternary carbon atoms, respectively. Wittig methylenation of 16 furnished (+/-)-myltayl-8(12)-ene (11), whereas reduction of the ketone 17 furnished (+/-)-6-epijunicedranol (23).

A game theoretical multiple resource interaction approach to resource allocation in an air campaign

In this paper we propose a multiple resource interaction model in a game-theoretical framework to solve resource allocation problems in theater level military campaigns. An air raid campaign using SEAD aircraft and bombers against an enemy target defended by air defense units is considered as the basic platform. Conditions for the existence of saddle point in pure strategies is proved and explicit feedback strategies are obtained for a simplified model with linear attrition function limited by resource availability. An illustrative example demonstrates the key features.

Novel subspace methods for blind estimation of multiple CFOs in MIMO-OFDM systems

The problem of estimating multiple Carrier Frequency Offsets (CFOs) in the uplink of MIMO-OFDM systems with Co-Channel (CC) and OFDMA based carrier allocation is considered. The tri-linear data model for generalized, multiuser OFDM system is formulated. Novel blind subspace based estimation of multiple CFOs in the case of arbitrary carrier allocation scheme in OFDMA systems and CC users in OFDM systems based on the Khatri-Rao product is proposed. The method works where the conventional subspace method fails. The performance of the proposed methods is compared with pilot based Least-Squares method.

Quasi-Orthogonal Design and Performance Analysis of Amplify-And-Forward Relay Networks with Multiple-Antennas

This paper is on the design and performance analysis of practical distributed space-time codes for wireless relay networks with multiple antennas terminals. The amplify-andforward scheme is used in a way that each relay transmits a scaled version of the linear combination of the received symbols. We propose distributed generalized quasi-orthogonal space-time codes which are distributed among the source antennas and relays, and valid for any number of relays. Assuming M-PSK and M-QAM signals, we derive a formula for the symbol error probability of the investigated scheme over Rayleigh fading channels. For sufficiently large SNR, this paper derives closed-form average SER expression. The simplicity of the asymptotic results provides valuable insights into the performance of cooperative networks and suggests means of optimizing them. Our analytical results have been confirmed by simulation results, using full-rate full-diversity distributed codes.

Efficient algorithms for learning kernels from multiple similarity matrices with general convex loss functions

In this paper we consider the problem of learning an n × n kernel matrix from m(1) similarity matrices under general convex loss. Past research have extensively studied the m = 1 case and have derived several algorithms which require sophisticated techniques like ACCP, SOCP, etc. The existing algorithms do not apply if one uses arbitrary losses and often can not handle m > 1 case. We present several provably convergent iterative algorithms, where each iteration requires either an SVM or a Multiple Kernel Learning (MKL) solver for m > 1 case. One of the major contributions of the paper is to extend the well knownMirror Descent(MD) framework to handle Cartesian product of psd matrices. This novel extension leads to an algorithm, called EMKL, which solves the problem in O(m2 log n 2) iterations; in each iteration one solves an MKL involving m kernels and m eigen-decomposition of n × n matrices. By suitably defining a restriction on the objective function, a faster version of EMKL is proposed, called REKL,which avoids the eigen-decomposition. An alternative to both EMKL and REKL is also suggested which requires only an SVMsolver. Experimental results on real world protein data set involving several similarity matrices illustrate the efficacy of the proposed algorithms.