Integrating and evaluating neural word embeddings in information retrieval

Recent advances in neural language models have contributed new methods for learning distributed vector representations of words (also called word embeddings). Two such methods are the continuous bag-of-words model and the skipgram model. These methods have been shown to produce embeddings that capture higher order relationships between words that are highly effective in natural language processing tasks involving the use of word similarity and word analogy. Despite these promising results, there has been little analysis of the use of these word embeddings for retrieval. Motivated by these observations, in this paper, we set out to determine how these word embeddings can be used within a retrieval model and what the benefit might be. To this aim, we use neural word embeddings within the well known translation language model for information retrieval. This language model captures implicit semantic relations between the words in queries and those in relevant documents, thus producing more accurate estimations of document relevance. The word embeddings used to estimate neural language models produce translations that differ from previous translation language model approaches; differences that deliver improvements in retrieval effectiveness. The models are robust to choices made in building word embeddings and, even more so, our results show that embeddings do not even need to be produced from the same corpus being used for retrieval.

The role of fruit traits of bird-dispersed plants in invasiveness and weed risk assessment

Aim: Birds play a major role in the dispersal of seeds of many fleshy-fruited invasive plants. The fruits that birds choose to consume are influenced by fruit traits. However, little is known of how the traits of invasive plant fruits contribute to invasiveness or to their use by frugivores. We aim to gain a greater understanding of these relationships to improve invasive plant management. Location: South-east Queensland, Australia. Methods: We measure a variety of fruit morphology, pulp nutrient and phenology traits of a suite of bird-dispersed alien plants. Frugivore richness of these aliens was derived from the literature. Using regressions and multivariate methods, we investigate relationships between fruit traits, frugivore richness and invasiveness. Results: Plant invasiveness was negatively correlated to fruit size, and all highly invasive species had quite similar fruit morphology [smaller fruits, seeds of intermediate size and few (<10) seeds per fruit]. Lower pulp water was the only pulp nutrient trait associated with invasiveness. There were strong positive relationships between the diversity of bird frugivores and plant invasiveness, and in the diversity of bird frugivores in the study region and another part of the plants' alien range. Main conclusions: Our results suggest that weed risk assessments (WRA) and predictions of invasive success for bird-dispersed plants can be improved. Scoring criteria for WRA regarding fruit size would need to be system-specific, depending on the fruit-processing capabilities of local frugivores. Frugivore richness could be quantified in the plant's natural range, its invasive range elsewhere, or predictions made based on functionally similar fruits.

How Good is the Assumption About Visible Surface Reflectance in MODIS Aerosol Retrieval Over Land? A Comparison With Aircraft Measurements Over an Urban Site in India

In this paper, we discuss the measurements of spectral surface reflectance (rho(s)(lambda)) in the wavelength range 350-2500 nm measured using a spectroradiometer onboard a low-flying aircraft over Bangalore (12.95 degrees N, 77.65 degrees E), an urban site in southern India. The large discrepancies in the retrieval of aerosol propertiesover land by the Moderate-Resolution Imaging Spectroradiometer (MODIS), which could be attributed to the inaccurate estimation of surface reflectance at many sites in India and elsewhere, provided motivation for this paper. The aim of this paper was to verify the surface reflectance relationships assumed by the MODIS aerosol algorithm for the estimation of surface reflectance in the visible channels (470 and 660 nm) from the surface reflectance at 2100 nm for aerosol retrieval over land. The variety of surfaces observed in this paper includes green and dry vegetations, bare land, and urban surfaces. The measuredreflectance data were first corrected for the radiative effects of atmosphere lying between the ground and aircraft using the Second Simulation of Satellite Signal in the Solar Spectrum (6S) radiative transfer code. The corrected surface reflectance in the MODIS's blue (rho(s)(470)), red (rho(s)(660)), and shortwave-infrared (SWIR) channel (rho(s)(2100)) was linearly correlated. We found that the slope of reflectance relationship between 660 and 2100 nm derived from the forward scattering data was 0.53 with an intercept of 0.07, whereas the slope for the relationship between the reflectance at 470 and 660 nm was 0.85. These values are much higher than the slope (similar to 0.49) for either wavelengths assumed by the MODIS aerosol algorithm over this region. The reflectance relationship for the backward scattering data has a slope of 0.39, with an intercept of 0.08 for 660 nm, and 0.65, with an intercept of 0.08 for 470 nm. The large values of the intercept (which is very small in the MODIS reflectance relationships) result in larger values of absolute surface reflectance in the visible channels. The discrepancy between the measured and assumed surface reflectances could lead to error in the aerosol retrieval. The reflectance ratio (rho(s)(660)/rho(s)(2100)) showed a clear dependence on the N D V I-SWIR where the ratio increased from 0.5 to 1 with an increase in N V I-SWIR from 0 to 0.5. The high correlation between the reflectance at SWIR wavelengths (2100, 1640, and 1240 nm) indicated an opportunity to derive the surface reflectance and, possibly, aerosol properties at these wavelengths. We need more experiments to characterize the surface reflectance and associated inhomogeneity of land surfaces, which play a critical role in the remote sensing of aerosols over land.

Remote sensing of leaf area index: enhanced retrieval from close-range and remotely sensed optical observations

A wide range of models used in agriculture, ecology, carbon cycling, climate and other related studies require information on the amount of leaf material present in a given environment to correctly represent radiation, heat, momentum, water, and various gas exchanges with the overlying atmosphere or the underlying soil. Leaf area index (LAI) thus often features as a critical land surface variable in parameterisations of global and regional climate models, e.g., radiation uptake, precipitation interception, energy conversion, gas exchange and momentum, as all areas are substantially determined by the vegetation surface. Optical wavelengths of remote sensing are the common electromagnetic regions used for LAI estimations and generally for vegetation studies. The main purpose of this dissertation was to enhance the determination of LAI using close-range remote sensing (hemispherical photography), airborne remote sensing (high resolution colour and colour infrared imagery), and satellite remote sensing (high resolution SPOT 5 HRG imagery) optical observations. The commonly used light extinction models are applied at all levels of optical observations. For the sake of comparative analysis, LAI was further determined using statistical relationships between spectral vegetation index (SVI) and ground based LAI. The study areas of this dissertation focus on two regions, one located in Taita Hills, South-East Kenya characterised by tropical cloud forest and exotic plantations, and the other in Gatineau Park, Southern Quebec, Canada dominated by temperate hardwood forest. The sampling procedure of sky map of gap fraction and size from hemispherical photographs was proven to be one of the most crucial steps in the accurate determination of LAI. LAI and clumping index estimates were significantly affected by the variation of the size of sky segments for given zenith angle ranges. On sloping ground, gap fraction and size distributions present strong upslope/downslope asymmetry of foliage elements, and thus the correction and the sensitivity analysis for both LAI and clumping index computations were demonstrated. Several SVIs can be used for LAI mapping using empirical regression analysis provided that the sensitivities of SVIs at varying ranges of LAI are large enough. Large scale LAI inversion algorithms were demonstrated and were proven to be a considerably efficient alternative approach for LAI mapping. LAI can be estimated nonparametrically from the information contained solely in the remotely sensed dataset given that the upper-end (saturated SVI) value is accurately determined. However, further study is still required to devise a methodology as well as instrumentation to retrieve on-ground green leaf area index . Subsequently, the large scale LAI inversion algorithms presented in this work can be precisely validated. Finally, based on literature review and this dissertation, potential future research prospects and directions were recommended.

Using Mathematical Morphology for Geometric Music Retrieval

The usual task in music information retrieval (MIR) is to find occurrences of a monophonic query pattern within a music database, which can contain both monophonic and polyphonic content. The so-called query-by-humming systems are a famous instance of content-based MIR. In such a system, the user's hummed query is converted into symbolic form to perform search operations in a similarly encoded database. The symbolic representation (e.g., textual, MIDI or vector data) is typically a quantized and simplified version of the sampled audio data, yielding to faster search algorithms and space requirements that can be met in real-life situations. In this thesis, we investigate geometric approaches to MIR. We first study some musicological properties often needed in MIR algorithms, and then give a literature review on traditional (e.g., string-matching-based) MIR algorithms and novel techniques based on geometry. We also introduce some concepts from digital image processing, namely the mathematical morphology, which we will use to develop and implement four algorithms for geometric music retrieval. The symbolic representation in the case of our algorithms is a binary 2-D image. We use various morphological pre- and post-processing operations on the query and the database images to perform template matching / pattern recognition for the images. The algorithms are basically extensions to classic image correlation and hit-or-miss transformation techniques used widely in template matching applications. They aim to be a future extension to the retrieval engine of C-BRAHMS, which is a research project of the Department of Computer Science at University of Helsinki.

Spatial and temporal determinants of Finnish farmland bird populations

During the past decades agricultural intensification has caused dramatic population declines in a wide range of taxa related to farmland habitats, including farmland birds. In this thesis, I studied how boreal farmland landscape characteristics and agricultural land use affect the abundance and diversity of farmland birds using extensive field data collected by territory mapping of breeding farmland birds in various parts of Finland. My results show that the area and openness of agricultural areas are key determinants of farmland bird abundance and distribution. A landscape composition with enough open farmland combined with key habitats such as farmyards and wetland is likely to provide essential prerequisites for the occurrence of a rich farmland avifauna. In Finland, the majority of large areas suitable for open habitat specialists are located in southern and western parts of the country. However, the diversity of the species with an unfavourable conservation status in Europe (SPECs) had notable hotspot areas in northern and north-western agricultural areas. I found that in boreal agroecosystems farmland birds favour fields with springtime vegetative cover, especially agricultural grasslands and set-asides. Hence, in the spring cereal dominated Finnish agroecosystems it is the absence of field vegetation that may limit populations of many farmland bird species. It is likely that the decrease of crops providing vegetative cover in the spring, such as permanent grasslands, cultivated grass, and autumn-sown cereals, has greatly contributed to the declines of Finnish farmland birds. Grass crops have persistently declined in Finland as a consequence of specialization in crop production and the large-scale decline in livestock husbandry. Small-scale non-crop habitats, especially ditches and ditch margins, are also important for many bird species in the Finnish agroecosystems, but have dramatically declined during the last decades. A major problem for farmland bird conservation in Finland is the conflict between landscape structure and agricultural management. Areas with mixed and cattle farming are virtually absent from the large agricultural plains of southern and south-western Finland, where the landscape structure is more likely to be favourable for rich farmland bird assemblages. On the other hand, mixed and cattle farming is still rather frequent in northern and central parts of the country, where the landscape structure is not suitable for many farmland specialist birds requiring open landscapes. My results provide useful guidelines for farmland bird conservation, and imply that considerable attention needs to be paid to landscape factors when selecting areas for various conservational management actions, such as agri-environment schemes. Actions promoting the abundance of set-asides, grass crops, and ditches would markedly benefit Finnish farmland bird populations. Organic farming may benefit farmland birds, but it is not clear how general its beneficial effect is in boreal agroecosystems. The most urgent action aiming to preserve farmland biodiversity would be to support re-introducing and sustaining cattle farming by environmental subsidies. This would be especially beneficial in the southern parts of Finland, where the landscape characteristics and abundance of agricultural areas are most suitable for farmland birds and where cattle farming is currently rare.

Regional variation in the composition and structure of mixed-species bird flocks in the Western Ghats and Sri Lanka

Mixed-species bird flocks are attractive models for the investigation of geographical variation in animal communities, as they represent a subset of the avifauna in most forested regions of the world. Yet studies of the regional variation in flock size and the composition of flocks are few, due to the predominance of studies carried out at single study site. Here, we review nine studies of mixed-species flocks conducted at 16 sites along the Western Ghats in India and in Sri Lanka. We find that flock size varies as much within this region as it does globally, with observation time being a confounding variable. Flock composition, however, is predictably related to elevation. Flocks at high elevations (>1200 m) in the Western Ghats strongly resemble flocks at high elevations in the mountain ranges of Sri Lanka in their composition, especially at the family level. We compare these flocks to flocks of other regions and make recommendations on study methodology that can facilitate comparisons across studies.

Using multi-label classification for acoustic pattern detection and assisting bird species surveys

Acoustics is a rich source of environmental information that can reflect the ecological dynamics. To deal with the escalating acoustic data, a variety of automated classification techniques have been used for acoustic patterns or scene recognition, including urban soundscapes such as streets and restaurants; and natural soundscapes such as raining and thundering. It is common to classify acoustic patterns under the assumption that a single type of soundscapes present in an audio clip. This assumption is reasonable for some carefully selected audios. However, only few experiments have been focused on classifying simultaneous acoustic patterns in long-duration recordings. This paper proposes a binary relevance based multi-label classification approach to recognise simultaneous acoustic patterns in one-minute audio clips. By utilising acoustic indices as global features and multilayer perceptron as a base classifier, we achieve good classification performance on in-the-field data. Compared with single-label classification, multi-label classification approach provides more detailed information about the distributions of various acoustic patterns in long-duration recordings. These results will merit further biodiversity investigations, such as bird species surveys.

Prospecting for alternate sources of shikimic acid, a precursor of Tamiflu, a bird-flu drug

Shikimic acid, more commonly known by its anionic form, shikimate, is an important intermediate compound of the ‘shikimate pathway’ in plants and microorganisms1. It is the principal precursor for the synthesis of aromatic amino acids, phenylalanine, tryptophan and tyrosine and other compounds such as alkaloids, phenolics and phenyl propanoids2. It is used extensively as a chiral building block for the synthesis of a number of compounds in both pharmaceutical and cosmetic industries3. In the recent past, the focus on shikimic acid has increased since it is the key precursor for the synthesis of Tamiflu, the only drug against avian flu caused by the H5N1 virus4,5. Shikimic acid is converted to a diethyl ketal intermediate, which is then reduced in two steps to an epoxide that is finally transformed to Tamiflu6.

Efficient content-based image retrieval based on multi-feature fusion

The increased availability of image capturing devices has enabled collections of digital images to rapidly expand in both size and diversity. This has created a constantly growing need for efficient and effective image browsing, searching, and retrieval tools. Pseudo-relevance feedback (PRF) has proven to be an effective mechanism for improving retrieval accuracy. An original, simple yet effective rank-based PRF mechanism (RB-PRF) that takes into account the initial rank order of each image to improve retrieval accuracy is proposed. This RB-PRF mechanism innovates by making use of binary image signatures to improve retrieval precision by promoting images similar to highly ranked images and demoting images similar to lower ranked images. Empirical evaluations based on standard benchmarks, namely Wang, Oliva & Torralba, and Corel datasets demonstrate the effectiveness of the proposed RB-PRF mechanism in image retrieval.

Storage and retrieval of individual genomes

A repetitive sequence collection is one where portions of a base sequence of length n are repeated many times with small variations, forming a collection of total length N. Examples of such collections are version control data and genome sequences of individuals, where the differences can be expressed by lists of basic edit operations. Flexible and efficient data analysis on a such typically huge collection is plausible using suffix trees. However, suffix tree occupies O(N log N) bits, which very soon inhibits in-memory analyses. Recent advances in full-text self-indexing reduce the space of suffix tree to O(N log σ) bits, where σ is the alphabet size. In practice, the space reduction is more than 10-fold, for example on suffix tree of Human Genome. However, this reduction factor remains constant when more sequences are added to the collection. We develop a new family of self-indexes suited for the repetitive sequence collection setting. Their expected space requirement depends only on the length n of the base sequence and the number s of variations in its repeated copies. That is, the space reduction factor is no longer constant, but depends on N / n. We believe the structures developed in this work will provide a fundamental basis for storage and retrieval of individual genomes as they become available due to rapid progress in the sequencing technologies.

Systematic bias in MODIS dust aerosol retrieval at Kanpur (AERONET), Indo-Gangetic Basin - art.no.640816

We have compared the spectral aerosol optical depth (AOD) and aerosol fine mode fraction (AFMF) derived from Moderate Resolution Imaging Spectroradiometer (MODIS) with those of Aerosol Robotic Network (AERONET) at Kanpur (26.45N, 80.35E), northern India for the pre-monsoon season (March to June, 2001-2005). We found that MODIS systematically overestimates AOD during pre-monsoon season (known to be influenced by dust transport from north-west of India). The errors in AOD were correlated with the MODIS top-of-atmosphere apparent surface reflectance in 2.1 mu m channel (rho*(2.1)). MODIS aerosol algorithm uses p*(2.1) to derive the surface reflectance in visible channels (rho(0.47), rho(0.66)) using an empirical mid IR-visible correlation (rho(0.47) = rho(2.1)/4, rho(0.66) = rho(2.1)/2). The large uncertainty in estimating surface reflectance in visible channels (Delta rho(0.66)+/- 0.04, Delta rho(0.47)+/- 0.02) at higher values of p*(2.1) (p*(2.1) > 0.18) leads to higher aerosol contribution in the total reflected radiance at top-of atmosphere to compensate for the reduced surface reflectance in visible channels and thus leads to overestimation of AOD. This was also reflected in the very low values of AFMF during pre-monsoon whose accuracy depends on the aerosol path radiance in 0.47 and 0.66 mu m channels and aerosol models. The errors in AOD were also high in the scattering angle range 110 degrees-140 degrees, where the effect of dust non-spherity on its optical properties is significant. The direct measurements of spectral surface reflectance are required over the Indo-Gangetic basin in order to validate the mid IR-visible relationship. MODIS aerosol models should also be modified to incorporate the effect of non-spherity of dust aerosols.

Retrieval of dust aerosols during night: improved assessment of long wave dust radiative forcing over Afro-Asian regions

Several investigators in the past have used the radiance depression (with respect to clear-sky infrared radiance), resulting from the presence of mineral dust aerosols in the atmosphere, as an index of dust aerosol load in the atmosphere during local noon. Here, we have used a modified approach to retrieve dust index during night since assessment of diurnal average infrared dust forcing essentially requires information on dust aerosols during night. For this purpose, we used infrared radiance (10.5-12.5 mu m), acquired from the METEOSAT-5 satellite (similar to 5 km resolution). We found that the `dust index' algorithm, valid for daytime, will no longer hold during the night because dust is then hotter than the theoretical dust-free reference. Hence we followed a `minimum reference' approach instead of a conventional `maximum reference' approach. A detailed analysis suggests that the maximum dust load occurs during the daytime. Over the desert regions of India and Africa, maximum change in dust load is as much as a factor of four between day and night and factor of two variations are commonly observed. By realizing the consequent impact on long wave dust forcing, sensitivity studies were carried out, which indicate that utilizing day time data for estimating the diurnally averaged long-wave dust radiative forcing results in significant errors (as much as 50 to 70%). Annually and regionally averaged long wave dust radiative forcing (which account for the diurnal variation of dust) at the top of the atmosphere over Afro-Asian region is 2.6 +/- 1.8 W m(-2), which is 30 to 50% lower than those reported earlier. Our studies indicate that neglecting diurnal variation of dust while assessing its radiative impact leads to an overestimation of dust radiative forcing, which in turn result in underestimation of the radiative impact of anthropogenic aerosols.