Feature Search in the Grassmanian in Online Reinforcement Learning

We consider the problem of finding the best features for value function approximation in reinforcement learning and develop an online algorithm to optimize the mean square Bellman error objective. For any given feature value, our algorithm performs gradient search in the parameter space via a residual gradient scheme and, on a slower timescale, also performs gradient search in the Grassman manifold of features. We present a proof of convergence of our algorithm. We show empirical results using our algorithm as well as a similar algorithm that uses temporal difference learning in place of the residual gradient scheme for the faster timescale updates.

Simultaneous feature selection and clustering using particle swarm optimization

Data clustering groups data so that data which are similar to each other are in the same group and data which are dissimilar to each other are in different groups. Since generally clustering is a subjective activity, it is possible to get different clusterings of the same data depending on the need. This paper attempts to find the best clustering of the data by first carrying out feature selection and using only the selected features, for clustering. A PSO (Particle Swarm Optimization)has been used for clustering but feature selection has also been carried out simultaneously. The performance of the above proposed algorithm is evaluated on some benchmark data sets. The experimental results shows the proposed methodology outperforms the previous approaches such as basic PSO and Kmeans for the clustering problem.

Delineating Ecological Boundaries of Hanuman Langur Species Complex in Peninsular India Using MaxEnt Modeling Approach

Hanuman langur is one of the widely distributed and extensively studied non-human diurnal primates in India. Until recently it was believed to be a single species - Semnopithecus entellus. Recent molecular and morphological studies suggest that the Hanuman langurs consists of at least three species S. entellus, S. hypoleucos and S. priam. Furthermore, morphological studies suggested that both S. hypoleucos and S. priam have at least three subspecies in each. We explored the use of ecological niche modeling (ENM) to confirm the validity of these seven taxa and an additional taxon S. johnii belonging to the same genus. MaxEnt modeling tool was used with 19 bioclimatic, 12 vegetation and 6 hydrological environmental layers. We reduced total environmental variables to 14 layers after testing for collinearity and an independent test for model prediction was done using ENMTools. A total of 196 non-overlapping data points from primary and secondary sources were used as inputs for ENM. Results showed eight distinct ecological boundaries, corroborating the eight taxa mentioned above thereby confirming validity of these eight taxa. The study, for the first time provided ecological variables that determined the ecological requirements and distribution of members of the Hanuman langur species complex in the Indian peninsula.

Biodiversity and ecological assessments of Indian sacred groves

Sacred groves are patches of forests preserved for their spiritual and religious significance. The practice gained relevance with the spread of agriculture that caused large-scale deforestation affecting biodiversity and watersheds. Sacred groves may lose their prominence nowadays, but are still relevant in Indian rural landscapes inhabited by traditional communities. The recent rise of interest in this tradition encouraged scientific study that despite its pan-Indian distribution, focused on India's northeast, Western Ghats and east coast either for their global/regional importance or unique ecosystems. Most studies focused on flora, mainly angiosperms, and the faunal studies concentrated on vertebrates while lower life forms were grossly neglected. Studies on ecosystem functioning are few although observations are available. Most studies attributed watershed protection values to sacred groves but hardly highlighted hydrological process or water yield in comparison with other land use types. The grove studies require diversification from a stereotyped path and must move towards creating credible scientific foundations for conservation. Documentation should continue in unexplored areas but more work is needed on basic ecological functions and ecosystem dynamics to strengthen planning for scientifically sound sacred grove management.

Delineating Ecological Boundaries of Hanuman Langur Species Complex in Peninsular India Using MaxEnt Modeling Approach

Hanuman langur is one of the widely distributed and extensively studied non-human diurnal primates in India. Until recently it was believed to be a single species - Semnopithecus entellus. Recent molecular and morphological studies suggest that the Hanuman langurs consists of at least three species S. entellus, S. hypoleucos and S. priam. Furthermore, morphological studies suggested that both S. hypoleucos and S. priam have at least three subspecies in each. We explored the use of ecological niche modeling (ENM) to confirm the validity of these seven taxa and an additional taxon S. johnii belonging to the same genus. MaxEnt modeling tool was used with 19 bioclimatic, 12 vegetation and 6 hydrological environmental layers. We reduced total environmental variables to 14 layers after testing for collinearity and an independent test for model prediction was done using ENMTools. A total of 196 non-overlapping data points from primary and secondary sources were used as inputs for ENM. Results showed eight distinct ecological boundaries, corroborating the eight taxa mentioned above thereby confirming validity of these eight taxa. The study, for the first time provided ecological variables that determined the ecological requirements and distribution of members of the Hanuman langur species complex in the Indian peninsula.

Quantifying Vocal Mimicry in the Greater Racket-Tailed Drongo: A Comparison of Automated Methods and Human Assessment

Objective identification and description of mimicked calls is a primary component of any study on avian vocal mimicry but few studies have adopted a quantitative approach. We used spectral feature representations commonly used in human speech analysis in combination with various distance metrics to distinguish between mimicked and non-mimicked calls of the greater racket-tailed drongo, Dicrurus paradiseus and cross-validated the results with human assessment of spectral similarity. We found that the automated method and human subjects performed similarly in terms of the overall number of correct matches of mimicked calls to putative model calls. However, the two methods also misclassified different subsets of calls and we achieved a maximum accuracy of ninety five per cent only when we combined the results of both the methods. This study is the first to use Mel-frequency Cepstral Coefficients and Relative Spectral Amplitude - filtered Linear Predictive Coding coefficients to quantify vocal mimicry. Our findings also suggest that in spite of several advances in automated methods of song analysis, corresponding cross-validation by humans remains essential.

Early Warning Signals of Ecological Transitions: Methods for Spatial Patterns

A number of ecosystems can exhibit abrupt shifts between alternative stable states. Because of their important ecological and economic consequences, recent research has focused on devising early warning signals for anticipating such abrupt ecological transitions. In particular, theoretical studies show that changes in spatial characteristics of the system could provide early warnings of approaching transitions. However, the empirical validation of these indicators lag behind their theoretical developments. Here, we summarize a range of currently available spatial early warning signals, suggest potential null models to interpret their trends, and apply them to three simulated spatial data sets of systems undergoing an abrupt transition. In addition to providing a step-by-step methodology for applying these signals to spatial data sets, we propose a statistical toolbox that may be used to help detect approaching transitions in a wide range of spatial data. We hope that our methodology together with the computer codes will stimulate the application and testing of spatial early warning signals on real spatial data.

The opportunity for sampling: the ecological context of female mate choice

Female mate choice decisions, which influence sexual selection, involve complex interactions between the 2 sexes and the environment. Theoretical models predict that male movement and spacing in the field should influence female sampling tactics, and in turn, females should drive the evolution of male movement and spacing to sample them optimally. Theoretically, simultaneous sampling of males using the best-of-n or comparative Bayes strategy should yield maximum mating benefits to females. We examined the ecological context of female mate sampling based on acoustic signals in the tree cricket Oecanthus henryi to determine whether the conditions for such optimal strategies were met in the field. These strategies involve recall of the quality and location of individual males, which in turn requires male positions to be stable within a night. Calling males rarely moved within a night, potentially enabling female sampling strategies that require recall. To examine the possibility of simultaneous acoustic sampling of males, we estimated male acoustic active spaces using information on male spacing, call transmission, and female hearing threshold. Males were found to be spaced far apart, and active space overlap was rare. We then examined female sampling scenarios by studying female spacing relative to male acoustic active spaces. Only 15% of sampled females could hear multiple males, suggesting that simultaneous mate sampling is rare in the field. Moreover, the relatively large distances between calling males suggest high search costs, which may favor threshold strategies that do not require memory.

An island called India: phylogenetic patterns across multiple taxonomic groups reveal endemic radiations

Island systems from around the world have provided fascinating opportunities for studies pertaining to various evolutionary processes. One recurring feature of isolated islands is the presence of endemic radiations. In this regard, the Indian subcontinent is an interesting entity given it has been an island during much of its history following separation from Madagascar and currently is isolated from much of Eurasia by the Himalayas in the north and the Indian Ocean in the south. Not surprisingly, recent molecular studies on a number of endemic taxa from India have reported endemic radiations. These studies suggest that the uniqueness of Indian biota is not just due to its diverse origin, but also due to evolution in isolation. The isolation of India has generated some peculiarities typically seen on oceanic islands. However, these patterns might be confined to, groups with low dispersal ability.

An Optical How Feature and McFIS Based Approach for 3-Dimensional Human Action Recognition

We propose to develop a 3-D optical flow features based human action recognition system. Optical flow based features are employed here since they can capture the apparent movement in object, by design. Moreover, they can represent information hierarchically from local pixel level to global object level. In this work, 3-D optical flow based features a re extracted by combining the 2-1) optical flow based features with the depth flow features obtained from depth camera. In order to develop an action recognition system, we employ a Meta-Cognitive Neuro-Fuzzy Inference System (McFIS). The m of McFIS is to find the decision boundary separating different classes based on their respective optical flow based features. McFIS consists of a neuro-fuzzy inference system (cognitive component) and a self-regulatory learning mechanism (meta-cognitive component). During the supervised learning, self-regulatory learning mechanism monitors the knowledge of the current sample with respect to the existing knowledge in the network and controls the learning by deciding on sample deletion, sample learning or sample reserve strategies. The performance of the proposed action recognition system was evaluated on a proprietary data set consisting of eight subjects. The performance evaluation with standard support vector machine classifier and extreme learning machine indicates improved performance of McFIS is recognizing actions based of 3-D optical flow based features.

Differences in host species relationships and biogeographic influences produce contrasting patterns of prevalence, community composition and genetic structure in two genera of avian malaria parasites in southern Melanesia

1. Host-parasite interactions have the potential to influence broadscale ecological and evolutionary processes, levels of endemism, divergence patterns and distributions in host populations. Understanding the mechanisms involved requires identification of the factors that shape parasite distribution and prevalence. 2. A lack of comparative information on community-level host-parasite associations limits our understanding of the role of parasites in host population divergence processes. Avian malaria (haemosporidian) parasites in bird communities offer a tractable model system to examine the potential for pathogens to influence evolutionary processes in natural host populations. 3. Using cytochrome b variation, we characterized phylogenetic diversity and prevalence of two genera of avian haemosporidian parasites, Plasmodium and Haemoproteus, and analysed biogeographic patterns of lineages across islands and avian hosts, in southern Melanesian bird communities to identify factors that explain patterns of infection. 4. Plasmodium spp. displayed isolation-by-distance effects, a significant amount of genetic variation distributed among islands but insignificant amounts among host species and families, and strong local island effects with respect to prevalence. Haemoproteus spp. did not display isolation-by-distance patterns, showed marked structuring of genetic variation among avian host species and families, and significant host species prevalence patterns. 5. These differences suggest that Plasmodium spp. infection patterns were shaped by geography and the abiotic environment, whereas Haemoproteus spp. infection patterns were shaped predominantly by host associations. Heterogeneity in the complement and prevalence of parasite lineages infecting local bird communities likely exposes host species to a mosaic of spatially divergent disease selection pressures across their naturally fragmented distributions in southern Melanesia. Host associations for Haemoproteus spp. indicate a capacity for the formation of locally co-adapted host-parasite relationships, a feature that may limit intraspecific gene flow or range expansions of closely related host species.

Recent freshwater Ostracoda and Bivalvia from Indo-Nepal border (Tethys Himalaya): Ecological implications

We report for the first time Recent ostracods and bivalves from Central Tethys Himalaya, collected from Changru village, which is situated in the Tinker valley of northwestern Nepal near the Indo-Nepal border. The specimens were collected from the surface sediments of a small pond, shaped by a small tributary of the glacier fed Tinker River. The ostracod species belonging to the families Ilyocyprididae, Cyprididae and Candonidae and one bivalve (Pisidium sp., Family Pisidiidae) have been identified. Psychrodromus olivaccus and Potamocypris villosa are being reported for the first time from India and Nepal. Several broken and unidentifiable gyrogonites of charophyta were also recovered. The ostracod sample, as a whole, points to a shallow freshwater lake environment influenced by slowly running carbonate rich waters under cool temperatures, low mineralization and sparse vegetation. This is in accordance with the occurrence of Pisidium, which is commonly associated with ostracods in the freshwater lakes and streams. The ostracod fauna shows affinity with the fossil and extant forms recovered from the Higher and Tethys Himalaya of NW India. This opens a new opportunity for studying ostracods in the Indian Central Himalaya - a region which otherwise has been ignored until now.

Primates, Provisioning and Plants: Impacts of Human Cultural Behaviours on Primate Ecological Functions

Human provisioning of wildlife with food is a widespread global practice that occurs in multiple socio-cultural circumstances. Provisioning may indirectly alter ecosystem functioning through changes in the eco-ethology of animals, but few studies have quantified this aspect. Provisioning of primates by humans is known to impact their activity budgets, diets and ranging patterns. Primates are also keystone species in tropical forests through their role as seed dispersers; yet there is no information on how provisioning might affect primate ecological functions. The rhesus macaque is a major human-commensal species but is also an important seed disperser in the wild. In this study, we investigated the potential impacts of provisioning on the role of rhesus macaques as seed dispersers in the Buxa Tiger Reserve, India. We studied a troop of macaques which were provisioned for a part of the year and were dependent on natural resources for the rest. We observed feeding behaviour, seed handling techniques and ranging patterns of the macaques and monitored availability of wild fruits. Irrespective of fruit availability, frugivory and seed dispersal activities decreased when the macaques were provisioned. Provisioned macaques also had shortened daily ranges implying shorter dispersal distances. Finally, during provisioning periods, seeds were deposited on tarmac roads that were unconducive for germination. Provisioning promotes human-primate conflict, as commensal primates are often involved in aggressive encounters with humans over resources, leading to negative consequences for both parties involved. Preventing or curbing provisioning is not an easy task as feeding wild animals is a socio-cultural tradition across much of South and South-East Asia, including India. We recommend the initiation of literacy programmes that educate lay citizens about the ill-effects of provisioning and strongly caution them against the practice.

A Bacterial Foraging Optimization and Learning Automata Based Feature Selection for Motor Imagery EEG Classification

Selection of relevant features is an open problem in Brain-computer interfacing (BCI) research. Sometimes, features extracted from brain signals are high dimensional which in turn affects the accuracy of the classifier. Selection of the most relevant features improves the performance of the classifier and reduces the computational cost of the system. In this study, we have used a combination of Bacterial Foraging Optimization and Learning Automata to determine the best subset of features from a given motor imagery electroencephalography (EEG) based BCI dataset. Here, we have employed Discrete Wavelet Transform to obtain a high dimensional feature set and classified it by Distance Likelihood Ratio Test. Our proposed feature selector produced an accuracy of 80.291% in 216 seconds.

Effects of the Spanwise Characteristic Length on the Transition Feature in the Wake of a Cylinder

The transition features of the wake behind a uniform circular cylinder at Re = 200, which is just beyond the critical Reynolds number of 3-D transition, are investigated in detail by direct numerical simulations of 3-D incompressible Navier-Stokes equations. The spanwise characteris-tic length determines the transition features and global properties of the wake.