Using topic models for OCR correction

Despite several decades of research in document analysis, recognition of unconstrained handwritten documents is still considered a challenging task. Previous research in this area has shown that word recognizers perform adequately on constrained handwritten documents which typically use a restricted vocabulary (lexicon). But in the case of unconstrained handwritten documents, state-of-the-art word recognition accuracy is still below the acceptable limits. The objective of this research is to improve word recognition accuracy on unconstrained handwritten documents by applying a post-processing or OCR correction technique to the word recognition output. In this paper, we present two different methods for this purpose. First, we describe a lexicon reduction-based method by topic categorization of handwritten documents which is used to generate smaller topic-specific lexicons for improving the recognition accuracy. Second, we describe a method which uses topic-specific language models and a maximum-entropy based topic categorization model to refine the recognition output. We present the relative merits of each of these methods and report results on the publicly available IAM database.     

Etched multimode microfiber knot-type loop interferometer refractive index sensor

We propose a novel refractive index sensor based on multimode microfiber knot-type loop (NL) interferometer. The middle portion (~5 cm) of a 15 cm long multimode fiber is etched in 48% hydrofluoric acid to reduce its diameter to ~12 μm. A NL of diameter <1 mm is made from the etched fiber. The ends of etched fiber are spliced with single-mode fibers for launching and detecting light from the NL interferometer. The NL introduces path differences to produce interferometric spectra with free spectral range ~16 nm. The spectrum shifts as the surrounding refractive index of the loop is changed by adding chemicals. We observe the highest sensitivity of the NL interferometer ~172 nm/RIU (refractive index unit) at a refractive index value 1.370 as obtained experimentally using commonly available chemicals. The design could be used as simple, low cost, and highly sensitive biological and chemical sensor.     

Recognition and Classification of Pomegranate Leaves Diseases by Image Processing and Machine Learning Techniques

Disease recognition in plants is one of the essential problems in agricultural image processing. This article focuses on designing a framework that can recognize and classify diseases on pomegranate plants exactly. The framework utilizes image processing techniques such as image acquisition, image resizing, image enhancement, image segmentation, ROI extraction (region of interest), and feature extraction. An image dataset related to pomegranate leaf disease is utilized to implement the framework, divided into a training set and a test set. In the implementation process, techniques such as image enhancement and image segmentation are primarily used for identifying ROI and features. An image classification will then be implemented by combining a supervised learning model with a support vector machine. The proposed framework is developed based on MATLAB with a graphical user interface. According to the experimental results, the proposed framework can achieve 98.39% accuracy for classifying diseased and healthy leaves. Moreover, the framework can achieve an accuracy of 98.07% for classifying diseases on pomegranate leaves.     

Simple Method to Evaluate the Ballistic Properties for Gas Generant Compositions

Combustion, Explosion, and Shock Waves - The study of the ballistic properties of energetic materials remains vital to ensure safety during their transportation, handling, storage, and processing....     

Investigation on the working performance of partitionable-space enhanced coagulation reactor

In this study, the phosphorous removal efficiency of partitionable-space enhanced coagulation (PEC) technology has been investigated. A series of continuous experiments was conducted to find out the influence of operating parameters. With increase in the elapsed treatment time, the phosphorus removal rates improved progressively during 1.5–3 h and the reactor reached a steady state after 4 h. This improved performance is mainly attributed to the partitionable-space and “flocculation filter” in the PEC reactor which enhanced the coagulation process. The flocs formed exhibited excellent settling characteristics by quickly settling out within the first 15 min.     

Three-Dimensional Electromechanical Impedance Model. I: Formulation of Directional Sum Impedance

Piezoceramic transducers (PZTs) are extensively used in vibration and noise control, and damage detection of various engineering structures. In the last decade, its application has been extended to include their interactions with the host structure in electromechanical impedance models. The interaction between the host structure and PZT is governed by both the extensional and longitudinal vibrations of the transducer. However, the interaction models developed in the last decade consider only the one-dimension or two-dimension extensional actuations, ignoring the longitudinal actuations. This study examines the three-dimensional (3D) interaction of a transducer with the host structure, considering both the extensional and the longitudinal actuations of the transducer. It does not impose any restriction on the shape, size, and electrical properties of the PZT and thus contains additional features over the existing PZT-structure interaction models. This paper is Part I of a two-part paper, which presents a new “directional sum” numerical–analytical admittance formulation with experimental verification. Part II of this paper will elaborate on the damage analysis and characterization of PZT properties for the new 3D model.     

Flexural bond strength of masonry using various blocks and mortars

This paper deals with an experimental study on flexural bond strength of masonry using various blocks in combination with different mortars. Flexural bond strength of masonry has been determined by testing stack-bonded prisms using a modified bond wrench test set-up. The effect of mortar composition and strength on the masonry's flexural bond strength using three types of masonry units (stabilized mud blocks, stabilized soil-sand blocks and burnt brick) has been examined. The effect of the masonry unit's moisture content on flexural bond strength has also been studied. Increases in mortar strength lead to increased flexural bond strength for cement mortar, irrespective of the type of masonry unit. It has been found that combination mortars, such as soil-cement mortar and cement-lime mortar, lead to better bond strength compared to cement mortars. The moisture content of the masonry unit at the time of casting has displayed significant influence on the flexural bond strength of the masonry. It has been found that for each type of masonry unit, an optimum moisture content exists, beyond which the flexural bond strength falls off quickly.     

Phrase-based correction model for improving handwriting recognition accuracies

We propose a method for increasing word recognition accuracies by correcting the output of a handwriting recognition system. We treat the handwriting recognizer as a black box, such that there is no access to its internals. This enables us to keep our algorithm general and independent of any particular system. We use a novel method for correcting the output based on a “phrase-based” system in contrast to traditional source-channel models. We report the accuracies of two in-house handwritten word recognizers before and after the correction. We achieve highly encouraging results for a large synthetically generated dataset. We also report results for a commercially available OCR on real data.     

Treatment of non-extractable common bile duct stones with combination ursodeoxycholic acid plus endoprostheses

To assess the effect of timing of human chorionic gonadotrophin (HCG) administration in ovarian stimulation cycles, the serum oestradiol concentration and follicle profile were compared with the clinical pregnancy rate in 582 ovarian stimulation-intra-uterine insemination (OS-IUI) cycles and 3917 in-vitro fertilization-embryo transfer (IVF-ET) cycles. The pregnancy rates increased exponentially with increasing oestradiol in both OS-IUI and IVF-ET cycles (R2 = 0.720, P < 0.001) but then decreased in OS-IUI cycles when the oestradiol concentration exceeded 5000 pmol/l (R2 = 0.936, P < 0.004) at HCG administration. In OS-IUI cycles the percentages of cycles with three or more mature follicles (> or = 18 mm diameter) increased up to an oestradiol concentration of 5000 pmol/l then declined, mirroring the pregnancy rate (R2 = 0.900, P = 0.01). The exponential increase in pregnancy rate with increasing oestradiol concentration in IVF-ET cycles suggests that high oestradiol concentration does not have a deleterious effect on endometrial receptivity. The decrease in pregnancy rate in OS-IUI cycles when oestradiol concentration exceeded 5000 pmol/l reflected fewer mature follicles, resulting from premature administration of HCG to avoid severe ovarian hyperstimulation syndrome (OHSS). We recommend that HCG administration be delayed until multiple follicles have reached maturity, and reducing the risk of severe OHSS by converting high risk OS-IUI cycles to IVF-ET, or if funds or facilities are unavailable, transvaginally draining all but four or five mature follicles.