Improved recognition of aged Kannada documents by effective segmentation of merged characters

In optical character recognition of very old books, the recognition accuracy drops mainly due to the merging or breaking of characters. In this paper, we propose the first algorithm to segment merged Kannada characters by using a hypothesis to select the positions to be cut. This method searches for the best possible positions to segment, by taking into account the support vector machine classifier's recognition score and the validity of the aspect ratio (width to height ratio) of the segments between every pair of cut positions. The hypothesis to select the cut position is based on the fact that a concave surface exists above and below the touching portion. These concave surfaces are noted down by tracing the valleys in the top contour of the image and similarly doing it for the image rotated upside-down. The cut positions are then derived as closely matching valleys of the original and the rotated images. Our proposed segmentation algorithm works well for different font styles, shapes and sizes better than the existing vertical projection profile based segmentation. The proposed algorithm has been tested on 1125 different word images, each containing multiple merged characters, from an old Kannada book and 89.6% correct segmentation is achieved and the character recognition accuracy of merged words is 91.2%. A few points of merge are still missed due to the absence of a matched valley due to the specific shapes of the particular characters meeting at the merges.

Miscellaneous translations on oyster biology (contents page only - individual articles held as separate documents)

This is a translation of selected articles from the Japanese language publication Hiroshimaken Suisan Shikenjo Hokoku (Report of Hirshima Prefectural Fisheries Experimental Station), Hiroshima City, Japan, vol.22, no. 1, 1960, pages 1-76. Articles translated are: Haematological study of bacteria affected oysters, The distribution of oyster larvae and spatfalls in the Hiroshima City perimeter, On the investigation of the timing of spatfalls, On the prediction of oyster seeding at inner Hiroshima Bay, Oyster growth and its environment at the oyster farm in Hiroshima Bay

Adaptive Scalable SVD Unit for Fast Processing of Large LSE Problems

Singular Value Decomposition (SVD) is a key linear algebraic operation in many scientific and engineering applications. In particular, many computational intelligence systems rely on machine learning methods involving high dimensionality datasets that have to be fast processed for real-time adaptability. In this paper we describe a practical FPGA (Field Programmable Gate Array) implementation of a SVD processor for accelerating the solution of large LSE problems. The design approach has been comprehensive, from the algorithmic refinement to the numerical analysis to the customization for an efficient hardware realization. The processing scheme rests on an adaptive vector rotation evaluator for error regularization that enhances convergence speed with no penalty on the solution accuracy. The proposed architecture, which follows a data transfer scheme, is scalable and based on the interconnection of simple rotations units, which allows for a trade-off between occupied area and processing acceleration in the final implementation. This permits the SVD processor to be implemented both on low-cost and highend FPGAs, according to the final application requirements.

What is coastal climate?

Historical definitions of what determines whether one lives in a coastal area or not have varied over time. According to Culliton (1998), a “coastal county” is defined as a county with at least 15% of its total land area located within a nation’s coastal watershed. This emphasizes the land areas within which water flows into the ocean or Great Lakes, but may be better suited for ecosystems or water quality research (Crowell et al. 2007). Some Federal Emergency Management Agency (FEMA) documents suggest that “coastal” includes shoreline-adjacent coastal counties, and perhaps even counties impacted by flooding from coastal storms. An accurate definition of “coastal” is critical in this regard since FEMA uses such definitions to revise and modernize their Flood Insurance Rate Maps (Crowell et al. 2007). A recent map published by the National Oceanic and Atmospheric Administration’s (NOAA) Coastal Services Center for the Coastal Change Analysis Program shows that the “coastal” boundary covers the entire state of New York and Michigan, while nearly all of South Carolina is considered “coastal.” The definition of “coastal” one chooses can have major implications, including a simple count of coastal population and the influence of local or state coastal policies. There is, however, one aspect of defining what is “coastal” that has often been overlooked; using atmospheric long-term climate variables to define the inland extent of the coastal zone. This definition, which incorporates temperature, precipitation, wind speed, and relative humidity, is furthermore scalable and globally applicable - even in the face of shifting shorelines. A robust definition using common climate variables should condense the large broad definition often associated with “coastal” such that completely landlocked locations would no longer be considered “coastal.” Moreover, the resulting definition, “coastal climate” or “climatology of the coast”, will help coastal resource managers make better-informed decisions on a wide range of climatologically-influenced issues. The following sections outline the methodology employed to derive some new maps of coastal boundaries in the United States. (PDF contains 3 pages)

Scalable Methods for Deterministic Integration of Quantum Emitters in Photonic Crystal Cavities

We investigated four unique methods for achieving scalable, deterministic integration of quantum emitters into ultra-high Q{V photonic crystal cavities, including selective area heteroepitaxy, engineered photoemission from silicon nanostructures, wafer bonding and dimensional reduction of III-V quantum wells, and cavity-enhanced optical trapping. In these areas, we were able to demonstrate site-selective heteroepitaxy, size-tunable photoluminescence from silicon nanostructures, Purcell modification of QW emission spectra, and limits of cavity-enhanced optical trapping designs which exceed any reports in the literature and suggest the feasibility of capturing- and detecting nanostructures with dimensions below 10 nm. In addition to process scalability and the requirement for achieving accurate spectral- and spatial overlap between the emitter and cavity, these techniques paid specific attention to the ability to separate the cavity and emitter material systems in order to allow optimal selection of these independently, and eventually enable monolithic integration with other photonic and electronic circuitry.

We also developed an analytic photonic crystal design process yielding optimized cavity tapers with minimal computational effort, and reported on a general cavity modification which exhibits improved fabrication tolerance by relying exclusively on positional- rather than dimensional tapering. We compared several experimental coupling techniques for device characterization. Significant efforts were devoted to optimizing cavity fabrication, including the use of atomic layer deposition to improve surface quality, exploration into factors affecting the design fracturing, and automated analysis of SEM images. Using optimized fabrication procedures, we experimentally demonstrated 1D photonic crystal nanobeam cavities exhibiting the highest Q/V reported on substrate. Finally, we analyzed the bistable behavior of the devices to quantify the nonlinear optical response of our cavities.