Significance Of Classification Techniques In Prediction Of Learning Disabilities

The aim of this study is to show the importance of two classification techniques, viz. decision tree and clustering, in prediction of learning disabilities (LD) of school-age children. LDs affect about 10 percent of all children enrolled in schools. The problems of children with specific learning disabilities have been a cause of concern to parents and teachers for some time. Decision trees and clustering are powerful and popular tools used for classification and prediction in Data mining. Different rules extracted from the decision tree are used for prediction of learning disabilities. Clustering is the assignment of a set of observations into subsets, called clusters, which are useful in finding the different signs and symptoms (attributes) present in the LD affected child. In this paper, J48 algorithm is used for constructing the decision tree and K-means algorithm is used for creating the clusters. By applying these classification techniques, LD in any child can be identified

Pattern Analysis Techniques for the Recognition of Unconstrained Handwritten Malayalam Character Images

The objective of the study is to develop a hand written character recognition system that could recognisze all the characters in the mordern script of malayalam language at a high recognition rate

Faster techniques to evolve wavelet coefficients for better fingerprint image compression

In this article, techniques have been presented for faster evolution of wavelet lifting coefficients for fingerprint image compression (FIC). In addition to increasing the computational speed by 81.35%, the coefficients performed much better than the reported coefficients in literature. Generally, full-size images are used for evolving wavelet coefficients, which is time consuming. To overcome this, in this work, wavelets were evolved with resized, cropped, resized-average and cropped-average images. On comparing the peak- signal-to-noise-ratios (PSNR) offered by the evolved wavelets, it was found that the cropped images excelled the resized images and is in par with the results reported till date. Wavelet lifting coefficients evolved from an average of four 256 256 centre-cropped images took less than 1/5th the evolution time reported in literature. It produced an improvement of 1.009 dB in average PSNR. Improvement in average PSNR was observed for other compression ratios (CR) and degraded images as well. The proposed technique gave better PSNR for various bit rates, with set partitioning in hierarchical trees (SPIHT) coder. These coefficients performed well with other fingerprint databases as well.

Development of Hierarchical Clustering Techniques for Gridded Data from Mixed Data Sequences

Knowledge discovery in databases is the non-trivial process of identifying valid, novel potentially useful and ultimately understandable patterns from data. The term Data mining refers to the process which does the exploratory analysis on the data and builds some model on the data. To infer patterns from data, data mining involves different approaches like association rule mining, classification techniques or clustering techniques. Among the many data mining techniques, clustering plays a major role, since it helps to group the related data for assessing properties and drawing conclusions. Most of the clustering algorithms act on a dataset with uniform format, since the similarity or dissimilarity between the data points is a significant factor in finding out the clusters. If a dataset consists of mixed attributes, i.e. a combination of numerical and categorical variables, a preferred approach is to convert different formats into a uniform format. The research study explores the various techniques to convert the mixed data sets to a numerical equivalent, so as to make it equipped for applying the statistical and similar algorithms. The results of clustering mixed category data after conversion to numeric data type have been demonstrated using a crime data set. The thesis also proposes an extension to the well known algorithm for handling mixed data types, to deal with data sets having only categorical data. The proposed conversion has been validated on a data set corresponding to breast cancer. Moreover, another issue with the clustering process is the visualization of output. Different geometric techniques like scatter plot, or projection plots are available, but none of the techniques display the result projecting the whole database but rather demonstrate attribute-pair wise analysis

Automatic Segmentation Framework for Primary Tumors From Brain MRIs Using Morphological Filtering Techniques

This paper describes a novel framework for automatic segmentation of primary tumors and its boundary from brain MRIs using morphological filtering techniques. This method uses T2 weighted and T1 FLAIR images. This approach is very simple, more accurate and less time consuming than existing methods. This method is tested by fifty patients of different tumor types, shapes, image intensities, sizes and produced better results. The results were validated with ground truth images by the radiologist. Segmentation of the tumor and boundary detection is important because it can be used for surgical planning, treatment planning, textural analysis, 3-Dimensional modeling and volumetric analysis

Isolation, Stabilization and Characterization of Xanthophyll from Marigold Flower- Tagetes Erecta-L

The present paper deals with the chemistry, isolation, separation, characterisation and stabilisation of the Marigold oleoresin and its application as a natural food colorant. Marigold (Tagetes Erecta L), an ornamental plant belonging to the composite family, has a rich source of natural antioxidant-Lutein. A natural pigment, xanthophylls offer an alternative to synthetic dyes as a food colorant, due to its non-toxicity. Chromatographic separations of saponified and unsaponified oleoresin were performed and Trans-Lutein identified as the major constituent. Well-preserved flowers exhibit a high yield of Xanthophyll content (105.19 g/Kg) in contrast to the unpreserved flower sample (54.87 g/Kg), emphasizing the significance of flower preservation in the extraction of xanthophyll. The stability and amount of xanthophyll also increased from 105.19 g/Kg to 226.88 g/Kg on saponification and subsequent purification with Ethylene Dichloride

Development of Directionally Adaptive Techniques for Single Image Super-Resolution

Super Resolution problem is an inverse problem and refers to the process of producing a High resolution (HR) image, making use of one or more Low Resolution (LR) observations. It includes up sampling the image, thereby, increasing the maximum spatial frequency and removing degradations that arise during the image capture namely aliasing and blurring. The work presented in this thesis is based on learning based single image super-resolution. In learning based super-resolution algorithms, a training set or database of available HR images are used to construct the HR image of an image captured using a LR camera. In the training set, images are stored as patches or coefficients of feature representations like wavelet transform, DCT, etc. Single frame image super-resolution can be used in applications where database of HR images are available. The advantage of this method is that by skilfully creating a database of suitable training images, one can improve the quality of the super-resolved image. A new super resolution method based on wavelet transform is developed and it is better than conventional wavelet transform based methods and standard interpolation methods. Super-resolution techniques based on skewed anisotropic transform called directionlet transform are developed to convert a low resolution image which is of small size into a high resolution image of large size. Super-resolution algorithm not only increases the size, but also reduces the degradations occurred during the process of capturing image. This method outperforms the standard interpolation methods and the wavelet methods, both visually and in terms of SNR values. Artifacts like aliasing and ringing effects are also eliminated in this method. The super-resolution methods are implemented using, both critically sampled and over sampled directionlets. The conventional directionlet transform is computationally complex. Hence lifting scheme is used for implementation of directionlets. The new single image super-resolution method based on lifting scheme reduces computational complexity and thereby reduces computation time. The quality of the super resolved image depends on the type of wavelet basis used. A study is conducted to find the effect of different wavelets on the single image super-resolution method. Finally this new method implemented on grey images is extended to colour images and noisy images

Development of 2-D MRT based Image Compression Techniques

The thesis explores the area of still image compression. The image compression techniques can be broadly classified into lossless and lossy compression. The most common lossy compression techniques are based on Transform coding, Vector Quantization and Fractals. Transform coding is the simplest of the above and generally employs reversible transforms like, DCT, DWT, etc. Mapped Real Transform (MRT) is an evolving integer transform, based on real additions alone. The present research work aims at developing new image compression techniques based on MRT. Most of the transform coding techniques employ fixed block size image segmentation, usually 8×8. Hence, a fixed block size transform coding is implemented using MRT and the merits and demerits are analyzed for both 8×8 and 4×4 blocks. The N2 unique MRT coefficients, for each block, are computed using templates. Considering the merits and demerits of fixed block size transform coding techniques, a hybrid form of these techniques is implemented to improve the performance of compression. The performance of the hybrid coder is found to be better compared to the fixed block size coders. Thus, if the block size is made adaptive, the performance can be further improved. In adaptive block size coding, the block size may vary from the size of the image to 2×2. Hence, the computation of MRT using templates is impractical due to memory requirements. So, an adaptive transform coder based on Unique MRT (UMRT), a compact form of MRT, is implemented to get better performance in terms of PSNR and HVS The suitability of MRT in vector quantization of images is then experimented. The UMRT based Classified Vector Quantization (CVQ) is implemented subsequently. The edges in the images are identified and classified by employing a UMRT based criteria. Based on the above experiments, a new technique named “MRT based Adaptive Transform Coder with Classified Vector Quantization (MATC-CVQ)”is developed. Its performance is evaluated and compared against existing techniques. A comparison with standard JPEG & the well-known Shapiro’s Embedded Zero-tree Wavelet (EZW) is done and found that the proposed technique gives better performance for majority of images

A study of the techniques of the Hindi drama: Post Prasad Period (1935 - 1965)

HINDI

Spatially Adaptive Image Denoising Techniques Using Directionlets

The aim of the thesis was to design and develop spatially adaptive denoising techniques with edge and feature preservation, for images corrupted with additive white Gaussian noise and SAR images affected with speckle noise. Image denoising is a well researched topic. It has found multifaceted applications in our day to day life. Image denoising based on multi resolution analysis using wavelet transform has received considerable attention in recent years. The directionlet based denoising schemes presented in this thesis are effective in preserving the image specific features like edges and contours in denoising. Scope of this research is still open in areas like further optimization in terms of speed and extension of the techniques to other related areas like colour and video image denoising. Such studies would further augment the practical use of these techniques.

Effect of market-driven minigrids on the frequency stabilization process of isolated middle-sized power grids

Neueste Entwicklungen in Technologien für dezentrale Energieversorgungsstrukturen, erneuerbare Energien, Großhandelsenergiemarkt, Mini- und Mikronetze, verteilte Intelligenz, sowie Informations- und Datenübertragungstechnologien werden die zukünftige Energiewelt maßgeblich bestimmen. Die derzeitigen Forschungsbemühungen zur Vernutzung aller dieser Technologien bilden die Voraussetzungen für ein zukünftiges, intelligentes Stromnetz. Dieses neue Konzept gründet sich auf die folgenden Säulen: Die Versorgung erfolgt durch dezentrale Erzeugungsanlagen und nicht mehr durch große zentrale Erzeuger; die Steuerung beeinflusst nicht mehr allein die Versorgung sondern ermöglich eine auch aktive Führung des Bedarf; die Eingabeparameter des Systems sind nicht mehr nur mechanische oder elektrische Kenngrößen sondern auch Preissignale; die erneuerbaren Energieträger sind nicht mehr nur angeschlossen, sondern voll ins Energienetz integriert. Die vorgelegte Arbeit fügt sich in dieses neue Konzept des intelligenten Stromnetz ein. Da das zukünftige Stromnetz dezentral konfiguriert sein wird, ist eine Übergangsphase notwendig. Dieser Übergang benötigt Technologien, die alle diese neue Konzepte in die derzeitigen Stromnetze integrieren können. Diese Arbeit beweist, dass ein Mininetz in einem Netzabschnitt mittlerer Größe als netzschützende Element wirken kann. Hierfür wurde ein neues Energiemanagementsystem für Mininetze – das CMS (englisch: Cluster Management System) – entwickelt. Diese CMS funktioniert als eine von ökonomischorientierte Betriebsoptimierung und wirkt wie eine intelligente Last auf das System ein, reagierend auf Preissignale. Sobald wird durch eine Frequenzsenkung eine Überlastung des Systems bemerkt, ändert das Mininetz sein Verhalten und regelt seine Belastung, um die Stabilisierung des Hauptnetzes zu unterstützen. Die Wirksamkeit und die Realisierbarkeit des einwickelten Konzept wurde mit Hilfe von Simulationen und erfolgreichen Laborversuchen bewiesen.

Composition and stability of organic matter fractions in soils under different land use regimes

Soil organic matter (SOM) vitally impacts all soil functions and plays a key role in the global carbon (C) cycle. More than 70% of the terrestric C stocks that participate in the active C cycle are stored in the soil. Therefore, quantitative knowledge of the rates of C incorporation into SOM fractions of different residence time is crucial to understand and predict the sequestration and stabilization of soil organic carbon (SOC). Consequently, there is a need of fractionation procedures that are capable of isolating functionally SOM fractions, i.e. fractions that are defined by their stability. The literature generally refers to three main mechanisms of SOM stabilization: protection of SOM from decomposition by (i) its structural composition, i.e. recalcitrance, (ii) spatial inaccessibility and/or (iii) interaction with soil minerals and metal ions. One of the difficulties in developing fractionation procedures for the isolation of functional SOM fractions is the marked heterogeneity of the soil environment with its various stabilization mechanisms – often several mechanisms operating simultaneously – in soils and soil horizons of different texture and mineralogy. The overall objective of the present thesis was to evaluate present fractionation techniques and to get a better understanding of the factors of SOM sequestration and stabilization. The first part of this study is attended to the structural composition of SOM. Using 13C cross-polarization magic-angle spinning (CPMAS) nuclear magnetic resonance (NMR) spectroscopy, (i) the effect of land use on SOM composition was investigated and (ii) examined whether SOM composition contributes to the different stability of SOM in density and aggregate fractions. The second part of the present work deals with the mineral-associated SOM fraction. The aim was (iii) to evaluate the suitability of chemical fractionation procedures used in the literature for the isolation of stable SOM pools (stepwise hydrolysis, treatments using oxidizing agents like Na2S2O8, H2O2, and NaOCl as well as demineralization of the residue obtained by the NaOCl treatment using HF (NaOCl+HF)) by pool sizes, 13C and 14C data. Further, (iv) the isolated SOM fractions were compared to the inert organic matter (IOM) pool obtained for the investigated soils using the Rothamsted Carbon Model and isotope data in order to see whether the tested chemical fractionation methods produce SOM fractions capable to represent this pool. Besides chemical fractionation, (v) the suitability of thermal oxidation at different temperatures for obtaining stable SOC pools was evaluated. Finally, (vi) the short-term aggregate dynamics and the factors that impact macroaggregate formation and C stabilization were investigated by means of an incubation study using treatments with and without application of 15N labeled maize straw of different degradability (leaves and coarse roots). All treatments were conducted with and without the addition of fungicide. Two study sites with different soil properties and land managements were chosen for these investigations. The first one, located at Rotthalmünster, is a Stagnic Luvisol (silty loam) under different land use regimes. The Ah horizons of a spruce forest and continuous grassland and the Ap and E horizons of two plots with arable crops (continuous maize and wheat cropping) were examined. The soil of the second study site, located at Halle, is a Haplic Phaeozem (loamy sand) where the Ap horizons of two plots with arable crops (continuous maize and rye cropping) were investigated. Both study sites had a C3-/C4-vegetational change on the maize plot for the purpose of tracing the incorporation of the younger, maize-derived C into different SOM fractions and the calculation of apparent C turnover times of these. The Halle site is located near a train station and industrial areas, which caused a contamination with high amounts of fossil C. The investigation of aggregate and density fractions by 13C CPMAS NMR spectroscopy revealed that density fractionation isolated SOM fractions of different composition. The consumption of a considerable part (10–20%) of the easily available O-alkyl-C and the selective preservation of the more recalcitrant alkyl-C when passing from litter to the different particulate organic matter (POM) fractions suggest that density fractionation was able to isolate SOM fractions with different degrees of decomposition. The spectra of the aggregate fractions resembled those of the mineral-associated SOM fraction obtained by density fractionation and no considerable differences were observed between aggregate size classes. Comparison of plant litter, density and aggregate size fractions from soil under different land use showed that the type of land use markedly influenced the composition of SOM. While SOM of the acid forest soil was characterized by a large content (> 50%) of POM, which contained high amounts of spruce-litter derived alkyl-C, the organic matter in the biologically more active grassland and arable soils was dominated by mineral-associated SOM (> 95%). This SOM fraction comprised greater proportions of aryl- and carbonyl-C and is considered to contain a higher amount of microbially-derived organic substances. Land use can alter both, structure and stability of SOM fractions. All applied chemical treatments induced considerable SOC losses (> 70–95% of mineral-associated SOM) in the investigated soils. The proportion of residual C after chemical fractionation was largest in the arable Ap and E horizons and increased with decreasing C content in the initial SOC after stepwise hydrolysis as well as after the oxidative treatments with H2O2 and Na2S2O8. This can be expected for a functional stable pool of SOM, because it is assumed that the more easily available part of SOC is consumed first if C inputs decrease. All chemical treatments led to a preferential loss of the younger, maize-derived SOC, but this was most pronounced after the treatments with Na2S2O8 and H2O2. After all chemical fractionations, the mean 14C ages of SOC were higher than in the mineral-associated SOM fraction for both study sites and increased in the order: NaOCl < NaOCl+HF ≤ stepwise hydrolysis << H2O2 ≈ Na2S2O8. The results suggest that all treatments were capable of isolating a more stable SOM fraction, but the treatments with H2O2 and Na2S2O8 were the most efficient ones. However, none of the chemical fractionation methods was able to fit the IOM pool calculated using the Rothamsted Carbon Model and isotope data. In the evaluation of thermal oxidation for obtaining stable C fractions, SOC losses increased with temperature from 24–48% (200°C) to 100% (500°C). In the Halle maize Ap horizon, losses of the young, maize-derived C were considerably higher than losses of the older C3-derived C, leading to an increase in the apparent C turnover time from 220 years in mineral-associated SOC to 1158 years after thermal oxidation at 300°C. Most likely, the preferential loss of maize-derived C in the Halle soil was caused by the presence of the high amounts of fossil C mentioned above, which make up a relatively large thermally stable C3-C pool in this soil. This agrees with lower overall SOC losses for the Halle Ap horizon compared to the Rotthalmünster Ap horizon. In the Rotthalmünster soil only slightly more maize-derived than C3-derived SOC was removed by thermal oxidation. Apparent C turnover times increased slightly from 58 years in mineral-associated SOC to 77 years after thermal oxidation at 300°C in the Rotthalmünster Ap and from 151 to 247 years in the Rotthalmünster E horizon. This led to the conclusion that thermal oxidation of SOM was not capable of isolating SOM fractions of considerably higher stability. The incubation experiment showed that macroaggregates develop rapidly after the addition of easily available plant residues. Within the first four weeks of incubation, the maximum aggregation was reached in all treatments without addition of fungicide. The formation of water-stable macroaggregates was related to the size of the microbial biomass pool and its activity. Furthermore, fungi were found to be crucial for the development of soil macroaggregates as the formation of water-stable macroaggregates was significantly delayed in the fungicide treated soils. The C concentration in the obtained aggregate fractions decreased with decreasing aggregate size class, which is in line with the aggregate hierarchy postulated by several authors for soils with SOM as the major binding agent. Macroaggregation involved incorporation of large amounts maize-derived organic matter, but macroaggregates did not play the most important role in the stabilization of maize-derived SOM, because of their relatively low amount (less than 10% of the soil mass). Furthermore, the maize-derived organic matter was quickly incorporated into all aggregate size classes. The microaggregate fraction stored the largest quantities of maize-derived C and N – up to 70% of the residual maize-C and -N were stored in this fraction.

Fast computation of concept lattices using data mining techniques

We present a new algorithm called TITANIC for computing concept lattices. It is based on data mining techniques for computing frequent itemsets. The algorithm is experimentally evaluated and compared with B. Ganter's Next-Closure algorithm.

Effects of different tillage treatments on labile soil organic matter pools and stabilization processes

An improved understanding of soil organic carbon (Corg) dynamics in interaction with the mechanisms of soil structure formation is important in terms of sustainable agriculture and reduction of environmental costs of agricultural ecosystems. However, information on physical and chemical processes influencing formation and stabilization of water stable aggregates in association with Corg sequestration is scarce. Long term soil experiments are important in evaluating open questions about management induced effects on soil Corg dynamics in interaction with soil structure formation. The objectives of the present thesis were: (i) to determine the long term impacts of different tillage treatments on the interaction between macro aggregation (>250 µm) and light fraction (LF) distribution and on C sequestration in plots differing in soil texture and climatic conditions. (ii) to determine the impact of different tillage treatments on temporal changes in the size distribution of water stable aggregates and on macro aggregate turnover. (iii) to evaluate the macro aggregate rebuilding in soils with varying initial Corg contents, organic matter (OM) amendments and clay contents in a short term incubation experiment. Soil samples were taken in 0-5 cm, 5-25 cm and 25-40 cm depth from up to four commercially used fields located in arable loess regions of eastern and southern Germany after 18-25 years of different tillage treatments with almost identical experimental setups per site. At each site, one large field with spatially homogenous soil properties was divided into three plots. One of the following three tillage treatments was carried in each plot: (i) Conventional tillage (CT) with annual mouldboard ploughing to 25-30 cm (ii) mulch tillage (MT) with a cultivator or disc harrow 10-15 cm deep, and (iii) no tillage (NT) with direct drilling. The crop rotation at each site consisted of sugar beet (Beta vulgaris L.) - winter wheat (Triticum aestivum L.) - winter wheat. Crop residues were left on the field and crop management was carried out following the regional standards of agricultural practice. To investigate the above mentioned research objectives, three experiments were conducted: Experiment (i) was performed with soils sampled from four sites in April 2010 (wheat stand). Experiment (ii) was conducted with soils sampled from three sites in April 2010, September 2011 (after harvest or sugar beet stand), November 2011 (after tillage) and April 2012 (bare soil or wheat stand). An incubation study (experiment (iii)) was performed with soil sampled from one site in April 2010. Based on the aforementioned research objectives and experiments the main findings were: (i) Consistent results were found between the four long term tillage fields, varying in texture and climatic conditions. Correlation analysis of the yields of macro aggregate against the yields of free LF ( ≤1.8 g cm-3) and occluded LF, respectively, suggested that the effective litter translocation in higher soil depths and higher litter input under CT and MT compensated in the long term the higher physical impact by tillage equipment than under NT. The Corg stocks (kg Corg m−2) in 522 kg soil, based on the equivalent soil mass approach (CT: 0–40 cm, MT: 0–38 cm, NT: 0–36 cm) increased in the order CT (5.2) = NT (5.2) < MT (5.7). Significantly (p ≤ 0.05) highest Corg stocks under MT were probably a result of high crop yields in combination with reduced physical tillage impact and effective litter incorporation, resulting in a Corg sequestration rate of 31 g C-2 m-2 yr-1. (ii) Significantly higher yields of macro aggregates (g kg-2 soil) under NT (732-777) and MT (680-726) than under CT (542-631) were generally restricted to the 0-5 cm sampling depth for all sampling dates. Temporal changes on aggregate size distribution were only small and no tillage induced net effect was detectable. Thus, we assume that the physical impact by tillage equipment was only small or the impact was compensated by a higher soil mixing and effective litter translocation into higher soil depths under CT, which probably resulted in a high re aggregation. (iii) The short term incubation study showed that macro aggregate yields (g kg-2 soil) were higher after 28 days in soils receiving OM (121.4-363.0) than in the control soils (22.0-52.0), accompanied by higher contents of microbial biomass carbon and ergosterol. Highest soil respiration rates after OM amendments within the first three days of incubation indicated that macro aggregate formation is a fast process. Most of the rebuilt macro aggregates were formed within the first seven days of incubation (42-75%). Nevertheless, it was ongoing throughout the entire 28 days of incubation, which was indicated by higher soil respiration rates at the end of the incubation period in OM amended soils than in the control soils. At the same time, decreasing carbon contents within macro aggregates over time indicated that newly occluded OM within the rebuilt macro aggregates served as Corg source for microbial biomass. The different clay contents played only minor role in macro aggregate formation under the particular conditions of the incubation study. Overall, no net changes on macro aggregation were identified in the short term. Furthermore, no indications for an effective Corg sequestration on the long term under NT in comparison to CT were found. The interaction of soil disturbance, litter distribution and the fast re aggregation suggested that a distinct steady state per tillage treatment in terms of soil aggregation was established. However, continuous application of MT with a combination of reduced physical tillage impact and effective litter incorporation may offer some potential in improving the soil structure and may therefore prevent incorporated LF from rapid decomposition and result in a higher C sequestration on the long term.