Microhabitat selection in an assemblage of crickets (Orthoptera: Ensifera) of a tropical evergreen forest in Southern India

1. Habitat selection is a universal aspect of animal ecology that has important fitness consequences and may drive patterns of spatial organisation in ecological communities. 2. Measurements of habitat selection have mostly been carried out on single species and at the landscape level. Quantitative studies examining microhabitat selection at the community level are scarce, especially in insects. 3. In this study, microhabitat selection in a natural assemblage of cricket species was examined for the first time using resource selection functions (RSF), an approach more commonly applied in studies of macrohabitat selection. 4. The availability and differential use of six microhabitats by 13 species of crickets inhabiting a tropical evergreen forest in southern India was examined. The six available microhabitats included leaf litter-covered ground, tree trunks, dead logs, brambles, understorey and canopy foliage. The area offered by the six microhabitats was estimated using standard methods of forest structure measurement. Of the six microhabitats, the understorey and canopy accounted for approximately 70% of the total available area. 5. The use of different microhabitats by the 13 species was investigated using acoustic sampling of crickets to locate calling individuals. Using RSF, it was found that of 13 cricket species examined, 10 showed 100% selection for a specific microhabitat. Of these, two species showed fairly high selection for brambles and dead logs, which were rare microhabitats, highlighting the importance of preserving all components of forest structure.

Coordination driven self-assembly of metallamacrocycles using ambidentate linkers and self-selection of single linkage isomer

Nicotinate-N-oxide and isonicotinate-N-oxide have been employed to synthesize four heterometallic metallamacrocycles (dppf)(2)Pd-2(nicotinate-N-oxide)(2)](OTf)(2) (1), (dppf)(2)Pt-2(nicotinate-N-oxide)(2)](OTf)(2) (2), (dppf) 2Pd2(isonicotinate-N-oxide)(2)](OTf)(2) (3) and (dppf)(2)Pt-2(isonicotinate-N-oxide)(2)](OTf)(2) (4). The complexes represent the first examples of metallamacrocycles driven by solely Pd(II)/Pt(II)-O coordination using carboxylate-N-oxide donor. All the complexes 1-4 are characterized by IR, UV-Vis, multinuclear NMR spectroscopic and ESI-MS studies. The molecular structures of the complexes 1 and 3 are unambiguously determined by single crystal X-ray diffraction analysis. Despite the possibility of formation of several linkage isomers due to ambidentate nature of the donors, exclusive formation of 2 + 2] self-assembled single isomeric metallamacrocycle in each case is interesting observation. (C) 2011 Elsevier B.V. All rights reserved.

Reverse flotation of silica from Kudremukh iron ore .1. Selection of cationic reagents

Four types of cationic collectors were tested and evaluated for their performance in the reverse flotation of silica from the spiral preconcentrate of Kudremukh iron ore. A stagewise flotation was conducted by adding the reagent in three stages. Starch was used to depress hematite. Silica flotation was found to be very sensitive to the amount of cationic reagent added. The performance of the reagents was evaluated based on the percentage of silica and iron in the concentrate and percent recovery of iron obtained in the concentrate. Tests of significance, namely, t-test and F-test were performed to select the best two reagents for further investigations.

On Training and Training Voids for Receive Antenna Subset Selection in Time-Varying Channels

Antenna selection (AS) provides most of the benefits of multiple-antenna systems at drastically reduced hardware costs. In receive AS, the receiver connects a dynamically selected subset of N available antennas to the L available RF chains. The "best" subset to be used for data reception is determined by means of channel estimates acquired using training sequences. Due to the nature of AS, the channel estimates at different antennas are obtained from different transmissions of the pilot sequence, and are, thus, outdated by different amounts in a time-varying channel. We show that a linear weighting of the estimates is optimum for the subset selection process, where the weights are related to the temporal correlation of the channel variations. When L is not an integer divisor of N, we highlight a new issue of "training voids", in which the last pilot transmission is not fully exploited by the receiver. We present a "void-filling" method for fully exploiting these voids, which essentially provides more accurate training for some antennas, and derive the optimal subset selection rule for any void-filling method. We also derive new closed-form equations for the performance of receive AS with optimal subset selection.

A Complete Characterization of an Optimal Timer Based Selection Scheme

Timer-based mechanisms are often used in several wireless systems to help a given (sink) node select the best helper node among many available nodes. Specifically, a node transmits a packet when its timer expires, and the timer value is a function of its local suitability metric. In practice, the best node gets selected successfully only if no other node's timer expires within a `vulnerability' window after its timer expiry. In this paper, we provide a complete closed-form characterization of the optimal metric-to-timer mapping that maximizes the probability of success for any probability distribution function of the metric. The optimal scheme is scalable, distributed, and much better than the popular inverse metric timer mapping. We also develop an asymptotic characterization of the optimal scheme that is elegant and insightful, and accurate even for a small number of nodes.

On optimal timer-based distributed selection for rate-adaptive multi-user diversity systems

We develop an optimal, distributed, and low feedback timer-based selection scheme to enable next generation rate-adaptive wireless systems to exploit multi-user diversity. In our scheme, each user sets a timer depending on its signal to noise ratio (SNR) and transmits a small packet to identify itself when its timer expires. When the SNR-to-timer mapping is monotone non-decreasing, timers of users with better SNRs expire earlier. Thus, the base station (BS) simply selects the first user whose timer expiry it can detect, and transmits data to it at as high a rate as reliably possible. However, timers that expire too close to one another cannot be detected by the BS due to collisions. We characterize in detail the structure of the SNR-to-timer mapping that optimally handles these collisions to maximize the average data rate. We prove that the optimal timer values take only a discrete set of values, and that the rate adaptation policy strongly influences the optimal scheme's structure. The optimal average rate is very close to that of ideal selection in which the BS always selects highest rate user, and is much higher than that of the popular, but ad hoc, timer schemes considered in the literature.

Training and Voids in Receive Antenna Subset Selection in Time-Varying Channels

Receive antenna selection (AS) provides many benefits of multiple-antenna systems at drastically reduced hardware costs. In it, the receiver connects a dynamically selected subset of N available antennas to the L available RF chains. Due to the nature of AS, the channel estimates at different antennas, which are required to determine the best subset for data reception, are obtained from different transmissions of the pilot sequence. Consequently, they are outdated by different amounts in a time-varying channel. We show that a linear weighting of the estimates is necessary and optimum for the subset selection process, where the weights are related to the temporal correlation of the channel variations. When L is not an integer divisor of N , we highlight a new issue of ``training voids'', in which the last pilot transmission is not fully exploited by the receiver. We then present new ``void-filling'' methods that exploit these voids and greatly improve the performance of AS. The optimal subset selection rules with void-filling, in which different antennas turn out to have different numbers of estimates, are also explicitly characterized. Closed-form equations for the symbol error probability with and without void-filling are also developed.

Machine-tool selection and operation allocation in FMS: solving a fuzzy goal-programming model using a genetic algorithm

The decision-making process for machine-tool selection and operation allocation in a flexible manufacturing system (FMS) usually involves multiple conflicting objectives. Thus, a fuzzy goal-programming model can be effectively applied to this decision problem. The paper addresses application of a fuzzy goal-programming concept to model the problem of machine-tool selection and operation allocation with explicit considerations given to objectives of minimizing the total cost of machining operation, material handling and set-up. The constraints pertaining to the capacity of machines, tool magazine and tool life are included in the model. A genetic algorithm (GA)-based approach is adopted to optimize this fuzzy goal-programming model. An illustrative example is provided and some results of computational experiments are reported.

Multipath routing to provide quality of service in mobile ad hoc networks

Because of frequent topology changes and node failures, providing quality of service routing in mobile ad hoc networks becomes a very critical issue. The quality of service can be provided by routing the data along multiple paths. Such selection of multiple paths helps to improve reliability and load balancing, reduce delay introduced due to route rediscovery in presence of path failures. There are basically two issues in such a multipath routing Firstly, the sender node needs to obtain the exact topology information. Since the nodes are continuously roaming, obtaining the exact topology information is a tough task. Here, we propose an algorithm which constructs highly accurate network topology with minimum overhead. The second issue is that the paths in the path set should offer best reliability and network throughput. This is achieved in two ways 1) by choice of a proper metric which is a function of residual power, traffic load on the node and in the surrounding medium 2) by allowing the reliable links to be shared between different paths.

Performance analysis of TCM with generalized selection combining on Rayleigh fading channels

We derive the computational cutoff rate, R-o, for coherent trellis-coded modulation (TCM) schemes on independent indentically distributed (i.i.d.) Rayleigh fading channels with (K, L) generalized selection combining (GSC) diversity, which combines the K paths with the largest instantaneous signal-to-noise ratios (SNRs) among the L available diversity paths. The cutoff rate is shown to be a simple function of the moment generating function (MGF) of the SNR at the output of the (K, L) GSC receiver. We also derive the union bound on the bit error probability of TCM schemes with (K, L) GSC in the form of a simple, finite integral. The effectiveness of this bound is verified through simulations.

Research bed for unit selection based text to speech synthesis

The paper describes a modular, unit selection based TTS framework, which can be used as a research bed for developing TTS in any new language, as well as studying the effect of changing any parameter during synthesis. Using this framework, TTS has been developed for Tamil. Synthesis database consists of 1027 phonetically rich prerecorded sentences. This framework has already been tested for Kannada. Our TTS synthesizes intelligible and acceptably natural speech, as supported by high mean opinion scores. The framework is further optimized to suit embedded applications like mobiles and PDAs. We compressed the synthesis speech database with standard speech compression algorithms used in commercial GSM phones and evaluated the quality of the resultant synthesized sentences. Even with a highly compressed database, the synthesized output is perceptually close to that with uncompressed database. Through experiments, we explored the ambiguities in human perception when listening to Tamil phones and syllables uttered in isolation,thus proposing to exploit the misperception to substitute for missing phone contexts in the database. Listening experiments have been conducted on sentences synthesized by deliberately replacing phones with their confused ones.