Measuring ranked list robustness for query performance prediction

We introduce the notion of ranking robustness, which refers to a property of a ranked list of documents that indicates how stable the ranking is in the presence of uncertainty in the ranked documents. We propose a statistical measure called the robustness score to quantify this notion. Our initial motivation for measuring ranking robustness is to predict topic difficulty for content-based queries in the ad-hoc retrieval task. Our results demonstrate that the robustness score is positively and consistently correlation with average precision of content-based queries across a variety of TREC test collections. Though our focus is on prediction under the ad-hoc retrieval task, we observe an interesting negative correlation with query performance when our technique is applied to named-page finding queries, which are a fundamentally different kind of queries. A side effect of this different behavior of the robustness score between the two types of queries is that the robustness score is also found to be a good feature for query classification.      

Applications, techniques, and microfluidic interfacing for nanoscale biosensing

Biosensors based on nanotechnology are rapidly developing and are becoming widespread in the biomedical field and analytical chemistry. For these nanobiosensors to reach their potential, they must be integrated with appropriate packaging techniques, which are usually based on nano/microfluidics. In this review we provide a summary of the latest developments in nanobiosensors with a focus on label-based (fluorescence and nanoparticle) and label-free methods (surface plasmon resonance, micro/nanocantilever, nanowires, and nanopores). An overview on how these sensors interface with nano/microfluidics is then presented and the latest papers in the area summarized.     

Collaborative writing in multiple discourse contexts

Research in computer-supported writing has traditionally compared electronic communication with oral, face-to-face communication to identify the benefits and weaknesses of each, as if they entailed dichotomous choices. In this article, we challenge that view and argue instead that any form of communication and its educational usefulness is shaped by the situation in which it is used, the backgrounds and goals of the participants, the institutional and technological setup, and the intended purpose of the medium. Three modes of communication in one graduate course are examined — oral discussion, synchronous written discussion on a local area network, and asynchronous written postings on an email list set up for the class. It was found that patterns of participation, topic introduction, and topic development differed across the three communication modes, but that the three were interwoven with each other and embedded within the larger classroom context and forms of knowledge creation in the class. Thus, rather than examining different communication media separately, researchers interested in understanding computer-supported collaborative writing need to look at how different media are used to create a meta-medium, which is established by the discourse community involved.     

Parametric study of the absorption cross section for a moderately conducting thin cylinder

Asystem has been developed to measure the absorption cross section for a single carbon fiber at 35 GHz as a functio of length, orientation, and diameter. Typical lengths of the fibers considered ranged from 1 to 20 mm, and diameters ranged from 3 to 8 μm. The results were compared with the modified integra equation calculations of Waterman and Pedersen that describe the scattering and absorption behavior for a wire of finite length and conductivity. Good agreement was found for all lengths, orientations, and diameters studied.     

Valorisation of mango seed via extraction of starch: preliminary techno-economic analysis

Reducing environmental impacts and obtaining economic benefits based on utilisation of waste materials are drivers for the implementation of cleaner production policies and technologies in food processing industries. Starch is a very versatile material with a wide range of applications in the food, pharmaceutical, textile, paper, cosmetic and construction industries. In Ethiopia, starch is widely used in the textile industry. To meet the starch demand, the country imports approximately 45% of the starch used in the country. Consequently, it is imperative to find additional sources of starch that could substitute for the amount of starch that is currently being imported. Mango seeds, a waste material that is disposed of after consumption of mangos, were studied for potential use as an alternative resource for starch production. The results showed that starch extraction from mango seeds was facile and a good quality product was obtained. The present study is concerned with a techno-economic analysis for industrial production of starch from mango seeds. The study shows that extraction of starch from waste mango seeds is feasible: the project is financially viable with an accounting rate of return of 83% and a break-even analysis of 78% with a payback period of 2 years.     

Parabolic curves of evolving surfaces

In this article we show how certain geometric structures which are also associated with a smooth surface evolve as the shape of the surface changes in a 1-parameter family. We concentrate on the parabolic set and its image under the Gauss map, but the same techniques also classify the changes in the dual of the surface. All these have significance for computer vision, for example through their connection with specularities and apparent contours. With the aid of our complete classification, which includes all the phenomena associated with multi-contact tangent planes as well as those associated with parabolic sets, we re-examine examples given by J. Koenderink in his book (1990) under the title of Morphological Scripts.We also explain some of the connections between parabolic sets and ridges of a surface, where principal curvatures achieve turning values along lines of curvature.The point of view taken is the analysis of the contact between surfaces and their tangent planes. A systematic investigation of this yields the results using singularity theory. The mathematical details are suppressed here and appear in Bruce et al. (1993).The third author was supported by the Esprit grant VIVA while this paper was in preparation.     

Cortical hierarchies, sleep, and the extraction of knowledge from memory

Odin the Allfather had in his service two great ravens. These ravens' names were Hugin (Thought) and Munin (Memory) and every morning at dawn they would fly off over Midgard (the world) in search of news and information to learn more about humans and their activities. At sundown, they would return to Odin where they would perch one on each of Odin's shoulders, and whisper into his ears all that they had seen and heard.Experience, stored in the brain as memory, is the raw material for intelligence and thought. It has been suggested that at sundown (i.e., during sleep) the brain adjusts its own synaptic matrix to enable adaptive responses to future events by a process of gradient descent optimization, involving repeated reactivations of recent and older memories and gradual adjustment of the synaptic weights. Memory retrieval, thought, and the generation of adaptive behavioral responses involve globally coordinated trajectories through the neuronal state-space, mediated by appropriate synaptic linkages. Artificial neural networks designed to implement even the most rudimentary forms of memory and knowledge extraction and adaptive behavior incorporate massively and symmetrically interconnected nodes; yet, in the cerebral cortex, the probability of a synaptic connection between any two arbitrarily chosen cells is on the order of 10⁻⁶, i.e., so close to zero that a naive modeler might neglect this parameter altogether. The probability of a symmetric connection is even smaller (10⁻¹²). How then, are thought and memory even possible? The solution appears to have been in the evolution of a modular, hierarchical cortical architecture, in which the modules are internally highly connected but only weakly interconnected with other modules. Appropriate inter-modular linkages are mediated indirectly via common linkages with higher level modules collectively known as association cortex. The hippocampal formation in the temporal lobe is the highest level of association cortex. It generates sequentially coupled patterns unique to the location and content of experience, but which do not contain the actual stored data. Rather, the patterns serve as pointers or ‘links’ to the data. Spontaneous reactivation of these linking patterns during sleep may enable the retrieval of recent sequences of experience stored in the lower levels of the cortex and the gradual extraction of knowledge from them. In this essay I explore these ideas, their implications, and the neuroscientific evidence for them.     

AdaBoost-based face detection for embedded systems

Face detection is a widely studied topic in computer vision, and recent advances in algorithms, low cost processing, and CMOS imagers make it practical for embedded consumer applications. As with graphics, the best cost-performance ratio is achieved with dedicated hardware. In this paper, we design an embedded face detection system for handheld digital cameras or camera phones. The challenges of face detection in embedded environments include an efficient pipeline design, bandwidth constraints set by low cost memory, a need to find parallelism, and how to utilize the available hardware resources efficiently. In addition, consumer applications require reliability which calls for a hard real-time approach to guarantee that processing deadlines are met. Specifically, the main contributions of the paper include: (1) incorporation of a Genetic Algorithm in the AdaBoost training to optimize the detection performance given the number of Haar features; (2) a complexity control scheme to meet hard real-time deadlines; (3) a hardware pipeline design for Haar-like feature calculation and a system design exploiting several levels of parallelism. The proposed architecture is verified by synthesis to Altera’s low cost Cyclone II FPGA. Simulation results show the system can achieve about 75–80% detection rate for group portraits.     

Using LiDAR and quickbird data to model plant production and quantify uncertainties associated with wetland detection and land cover generalizations

Spatiotemporal data from satellite remote sensing and surface meteorology networks have made it possible to continuously monitor global plant production, and to identify global trends associated with land cover/use and climate change. Gross primary production (GPP) and net primary production (NPP) are routinely derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard satellites Terra and Aqua, and estimates generally agree with independent measurements at validation sites across the globe. However, the accuracy of GPP and NPP estimates in some regions may be limited by the quality of model input variables and heterogeneity at fine spatial scales. We developed new methods for deriving model inputs (i.e., land cover, leaf area, and photosynthetically active radiation absorbed by plant canopies) from airborne laser altimetry (LiDAR) and Quickbird multispectral data at resolutions ranging from about 30 m to 1 km. In addition, LiDAR-derived biomass was used as a means for computing carbon-use efficiency. Spatial variables were used with temporal data from ground-based monitoring stations to compute a six-year GPP and NPP time series for a 3600 ha study site in the Great Lakes region of North America. Model results compared favorably with independent observations from a 400 m flux tower and a process-based ecosystem model (BIOME-BGC), but only after removing vapor pressure deficit as a constraint on photosynthesis from the MODIS global algorithm. Fine-resolution inputs captured more of the spatial variability, but estimates were similar to coarse-resolution data when integrated across the entire landscape. Failure to account for wetlands had little impact on landscape-scale estimates, because vegetation structure, composition, and conversion efficiencies were similar to upland plant communities. Plant productivity estimates were noticeably improved using LiDAR-derived variables, while uncertainties associated with land cover generalizations and wetlands in this largely forested landscape were considered less important.     

The influence of epiphylls on remote sensing of humid forests

Epiphylls - lichens, fungi, liverworts, etc. infesting leaf surfaces - are found throughout humid forests of the world. It is well understood that epiphylls inhibit light interception by host plants, but their effect on remote sensing of colonized forests has not been examined. Incorporating leaf-level spectra from Terra Firme (primary forest) and Amazonian Caatinga (woodlands/forest growing on nutrient-deficient sandy soils), we used the GeoSAIL model to propagate leaf-level measurements to the canopy level and determine their effect on commonly used vegetation indices. In Caatinga, moderate infestations (50% leaf area epiphyll cover), lowered simulated Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) values by 6.1% and 20.4%, respectively, largely due to near infrared dampening. Heavy infestation (100% cover) simulations exhibited decreases 1.5-2 times greater than those of moderate infestations. For Terra Firme, which are generally less affected by epiphylls, moderate (20% leaf area) and heavy infestations (40%) lowered EVI by 4.4% (S.D. 0.8%) and 8.1% (S.D. 1.5%), respectively. Near infrared and green reflectance were most affected at the canopy level, showing mean decreases of 10.6% (S.D. 2.25%) and 9.5% (S.D. 3.49%), respectively, in heavy Terra Firme infestations. Time series of Moderate Resolution Imaging Spectrometer (MODIS) data corroborated the modeling results, suggesting a degree of coupling between epiphyll cover and the EVI and NDVI. These results suggest that, without explicit consideration of the presence of epiphylls, remote sensing-based methodologies may underestimate leaf area index, biomass and productivity in humid forests.