Characters Extraction for Traffic Sign Destination boards in video and still images

Traffic Control Signs or destination boards on roadways offer significant information for drivers. Regulation signs tell something like your speed, turns, etc; Warning signs warn drivers of conditions ahead to help them avoid accidents; Destination signs show distances and directions to various locations; Service signs display location of hospitals, gas and rest areas etc. Because the signs are so important and there is always a certain distance from them to drivers, to let the drivers get information clearly and easily even in bad weather or other situations. The idea is to develop software which can collect useful information from a special camera which is mounted in the front of a moving car to extract the important information and finally show it to the drivers. For example, when a frame contains on a destination drive sign board it will be text something like "Linkoping 50",so the software should extract every character of "Linkoping 50", compare them with the already known character data in the database. if there is extracted character match "k" in the database then output the destination name and show to the driver. In this project C++ will be used to write the code for this software.

Online character recognition using regression techniques

This paper introduces a scheme for classification of online handwritten characters based on polynomial regression of the sampled points of the sub-strokes in a character. The segmentation is done based on the velocity profile of the written character and this requires a smoothening of the velocity profile. We propose a novel scheme for smoothening the velocity profile curve and identification of the critical points to segment the character. We also porpose another method for segmentation based on the human eye perception. We then extract two sets of features for recognition of handwritten characters. Each sub-stroke is a simple curve, a part of the character, and is represented by the distance measure of each point from the first point. This forms the first set of feature vector for each character. The second feature vector are the coeficients obtained from the B-splines fitted to the control knots obtained from the segmentation algorithm. The feature vector is fed to the SVM classifier and it indicates an efficiency of 68% using the polynomial regression technique and 74% using the spline fitting method.

Molecular phylogenetics and character evolution of the ""sacaca"" clade: Novel relationships of Croton section Cleodora (Euphorbiaceae)

Phylogenetic relationships of Croton section Cleodora (Klotzsch) Baill. were evaluated using the nuclear ribosomal ITS and the chloroplast trnl-F and trnH-psbA regions. Our results show a strongly supported clade containing most previously recognized section Cleodora species, plus some other species morphologically similar to them. Two morphological synapomorphies that support section Cleodora as a clade include pistillate flowers in which the sepals overlap to some degree, and styles that are connate at the base to varying degrees. The evolution of vegetative and floral characters that have previously been relied on for taxonomic decisions within this group are evaluated in light of the phylogenetic hypotheses. Within section Cleodora there are two well-supported clades, which are proposed here as subsections (subsection Sphaerogyni and subsection Spruceani). The resulting phylogenetic hypothesis identifies the closest relatives of the medicinally important and essential oil-rich Croton cajucara Benth. as candidates for future screening in phytochemical and pharmacological studies. (C) 2011 Elsevier Inc. All rights reserved.

Organic geochemical character of selected cores at DSDP Hole 75-530A

The Albian/Cenomanian strata in Hole 530A are organically richer than are the post-Cenomanian strata. Organic matter is thermally immature and appears to be of dominantly marine origin with either variable levels of oxidation or variable amounts of terrestrial input. Geochemical data alone cannot establish whether the black shales present in Hole 530A represent deposition within a stagnant basin or within an expanded oxygen-minimum layer

Organic geochemical character and hydrocarbon source potential of selected black shales at DSDP Hole 93-603B

LECO analysis, pyrolysis assay, and bitumen and elemental analysis were used to characterize the organic matter of 23 black shale samples from Deep Sea Drilling Project Leg 93, Hole 603B, located in the western North Atlantic. The organic matter is dominantly gas-prone and/or refractory. Two cores within the Turonian and Cenomanian, however, contained significant quantities of well-preserved, hydrogen-enriched, organic matter. This material is thermally immature and represents a potential oil-prone source rock. These sediments do not appear to have been deposited within a stagnant, euxinic ocean as would be consistent with an "oceanic anoxic event." Their organic geochemical and sedimentary character is more consistent with deposition by turbidity currents originating on the continental shelf and slope.

Character of the Mr. Appleton, 1804 November 12

Small leaf containing a handwritten extract from a November 12, 1804 letter by Rev. Joseph Lathrop to Rev. John Lathrop recommending Rev. Jesse Appleton as the successor to Dr. Tappan.

The theory of moral sentiments, or, An essay towards an analysis of the principles by which men naturally judge concerning the conduct and character, first of their neighbors, and afterwards of themselves : to which is added, A dissertation on the origin of languages /

Extract from An account of the life and writings of Dr. Adam Smith, by Dugald Stewart: p. ii.

Classification of Data to Extract Knowledge from Neural Networks

A major drawback of artificial neural networks is their black-box character. Therefore, the rule extraction algorithm is becoming more and more important in explaining the extracted rules from the neural networks. In this paper, we use a method that can be used for symbolic knowledge extraction from neural networks, once they have been trained with desired function. The basis of this method is the weights of the neural network trained. This method allows knowledge extraction from neural networks with continuous inputs and output as well as rule extraction. An example of the application is showed. This example is based on the extraction of average load demand of a power plant.

How to extract and expand randomness : a summary and explanation of existing results

We examine the use of randomness extraction and expansion in key agreement (KA) pro- tocols to generate uniformly random keys in the standard model. Although existing works provide the basic theorems necessary, they lack details or examples of appropriate cryptographic primitives and/or parameter sizes. This has lead to the large amount of min-entropy needed in the (non-uniform) shared secret being overlooked in proposals and efficiency comparisons of KA protocols. We therefore summa- rize existing work in the area and examine the security levels achieved with the use of various extractors and expanders for particular parameter sizes. The tables presented herein show that the shared secret needs a min-entropy of at least 292 bits (and even more with more realistic assumptions) to achieve an overall security level of 80 bits using the extractors and expanders we consider. The tables may be used to �nd the min-entropy required for various security levels and assumptions. We also �nd that when using the short exponent theorems of Gennaro et al., the short exponents may need to be much longer than they suggested.

Downtime reduction analysis of the Australia Post flat mail optical character reader

Machine downtime, whether planned or unplanned, is intuitively costly to manufacturing organisations, but is often very difficult to quantify. The available literature showed that costing processes are rarely undertaken within manufacturing organisations. Where cost analyses have been undertaken, they generally have only valued a small proportion of the affected costs, leading to an overly conservative estimate. This thesis aimed to develop a cost of downtime model, with particular emphasis on the application of the model to Australia Post’s Flat Mail Optical Character Reader (FMOCR). The costing analysis determined a cost of downtime of $5,700,000 per annum, or an average cost of $138 per operational hour. The second section of this work focused on the use of the cost of downtime to objectively determine areas of opportunity for cost reduction on the FMOCR. This was the first time within Post that maintenance costs were considered along side of downtime for determining machine performance. Because of this, the results of the analysis revealed areas which have historically not been targeted for cost reduction. Further exploratory work was undertaken on the Flats Lift Module (FLM) and Auto Induction Station (AIS) Deceleration Belts through the comparison of the results against two additional FMOCR analysis programs. This research has demonstrated the development of a methodical and quantifiable cost of downtime for the FMOCR. This has been the first time that Post has endeavoured to examine the cost of downtime. It is also one of the very few methodologies for valuing downtime costs that has been proposed in literature. The work undertaken has also demonstrated how the cost of downtime can be incorporated into machine performance analysis with specific application to identifying high costs modules. The outcome of this report has both been the methodology for costing downtime, as well as a list of areas for cost reduction. In doing so, this thesis has outlined the two key deliverables presented at the outset of the research.

Kava Anxiety Depression Spectrum Study (KADSS): a mixed methods RCT using an aqueous extract of Piper methysticum

Objectives: To report on the design, significance and potential impacts of the first documented human clinical trial assessing the anxiolytic and thymoleptic efficacy of an aqueous monoextract of Piper methysticum (kava). The significance of the qualitative element of our clinical trial is also explored. The Kava Anxiety Depression Spectrum Study (KADSS) is a 3-week placebocontrolled, double-blind, cross-over trial involving 60 adult participants (18—65) with elevated stable anxiety and varying levels of depressive symptoms. Aims: The aims of KADSS are: (1) to determine whether an aqueous standardised extract of kava is effective for the treatment of anxiety; (2) to assess the effects of kava on differing levels of depression; and (3) to explore participants’ experience of taking kava via qualitative research. The study also provides preliminary assessment of the safety of an aqueous extract of kava in humans. Conclusion: If results reveal that the aqueous kava preparation exerts significant anxiolytic effects and appears safe, potentially beneficial impacts may occur. Data supporting a safe and effective kava extract may encourage a re-introduction of kava to Europe, UK and Canada. This may provide a major socioeconomic benefit to Pacific Island nations, and to sufferers of anxiety disorders.

The Kava Anxiety Depression Spectrum Study (KADSS): A randomized, placebo-controlled, cross-over trial using an aqueous extract of Piper methysticum.

Rationale: Piper methysticum (Kava) has been withdrawn in European, British, and Canadian markets due to concerns over hepatotoxic reactions. The WHO recently recommended research into “aqueous” extracts of Kava. Objective: The objective of this study was to conduct the first documented human clinical trial assessing the anxiolytic and antidepressant efficacy of an aqueous extract of Kava. Design and participants: The Kava Anxiety Depression Spectrum Study was a 3-week placebo-controlled, double-blind crossover trial that recruited 60 adult participants with 1 month or more of elevated generalized anxiety. Five Kava tablets per day were prescribed containing 250 mg of kavalactones/day. Results: The aqueous extract of Kava reduced participants' Hamilton Anxiety Scale score in the first controlled phase by −9.9 (CI = 7.1, 12.7) vs. −0.8 (CI = −2.7, 4.3) for placebo and in the second controlled phase by −10.3 (CI = 5.8, 14.7) vs. +3.3 (CI = −6.8, 0.2). The pooled effect of Kava vs. placebo across phases was highly significant (p < 0.0001), with a substantial effect size (d = 2.24, η² [sub]p[sub] = 0.428). Pooled analyses also revealed highly significant relative reductions in Beck Anxiety Inventory and Montgomery–Asberg Depression Rating Scale scores. The aqueous extract was found to be safe, with no serious adverse effects and no clinical hepatotoxicity. Conclusions: The aqueous Kava preparation produced significant anxiolytic and antidepressant activity and raised no safety concerns at the dose and duration studied. Kava appears equally effective in cases where anxiety is accompanied by depression. This should encourage further study and consideration of globally reintroducing aqueous rootstock extracts of Kava for the management of anxiety.

Bengali handwritten character recognition using modified syntactic method

Several approaches have been proposed to recognize handwritten Bengali characters using different curve fitting algorithms and curvature analysis. In this paper, a new algorithm (Curve-fitting Algorithm) to identify various strokes of a handwritten character is developed. The curve-fitting algorithm helps recognizing various strokes of different patterns (line, quadratic curve) precisely. This reduces the error elimination burden heavily. Implementation of this Modified Syntactic Method demonstrates significant improvement in the recognition of Bengali handwritten characters.