Hybrid Multi Attribute Relation Method for Document Clustering for Information Mining

Text clustering has been widely utilized with the aim of partitioning speci?c documents’ collection into different subsets using homogeneity/heterogeneity criteria. It has also become a very complicated area of research, including pattern recognition, information retrieval, and text mining. In the applications of enterprises, information mining faces challenges due to the complex distribution of data by an enormous number of different sources. Most of these information sources are from different domains which create difficulties in identifying the relationships among the information. In this case, a single method for clustering limits related information, while enhancing computational overheadsand processing times. Hence, identifying suitable clustering models for unsupervised learning is a challenge, specifically in the case of MultipleAttributesin data distributions. In recent works attribute relation based solutions are given significant importance to suggest the document clustering. To enhance further, in this paper, Hybrid Multi Attribute Relation Methods (HMARs) are presented for attribute selections and relation analyses of co-clustering of datasets. The proposed HMARs allowanalysis of distributed attributes in documents in the form of probabilistic attribute relations using modified Bayesian mechanisms. It also provides solutionsfor identifying most related attribute model for the multiple attribute documents clustering accurately. An experimental evaluation is performed to evaluate the clustering purity and normalization of the information utilizing UCI Data repository which shows 25% better when compared with the previous techniques

Optimal Material Design for Transport and Multi-Criteria Problems Using Topology Optimization

Optimal multi-material layouts are critical to achieving the desired functionality of structures and devices. Topology optimization, a mathematically driven methodology, has developed into an indispensable tool to obtain optimal material layouts in diverse fields, from engineering to biomedical sciences at scales ranging from large-scale structural applications to nano-scale diagnostic devices. In this dissertation, we present developments in non-linear and multi-criteria topology optimization. The main contributions are: First, we propose a design framework with an alternative objective function, appropriate for all analysis models, to derive optimal designs for flow through porous media. We highlight the effect of pressure, inertia, and viscous shearing stresses on optimal layouts. Second, we develop a design framework to obtain optimal material layouts for structural applications to satisfy multiple objectives at macroscales. For applications at microscales, we investigate the effect of pressure-dependent viscosity, inertial forces, and viscous shear, often ignored by using the simple Darcy model to obtain optimal designs for flow through porous media. Many studies use the minimization of power as an objective function which is not universally applicable. We propose an alternative objective function -- the rate of mechanical dissipation -- valid even for non-linear models. Using canonical examples, we derive analytical solutions, which facilitate verification of computer implementations. We bring out the highly disparate optimal layouts under the non-linear models, which are more likely to reflect the true pressure and velocity fields within the domain. Employing these designs will positively impact the accuracy of microfluidic devices, which is critical to their functionality. At the macroscale, we apply topology optimization to obtain optimal layouts for a structural wall application. Structural elements (e.g., load-bearing walls) having high strength and low thermal conductivity are difficult to construct with a single material. Construction materials having high strength also exhibit high conductivity (e.g., steel), and materials having low conductivity exhibit low strength (e.g., concrete). Hence, it is imperative to utilize more than one material to achieve the requisite property. The design of a domain with materials having conflicting properties poses an enormous challenge for engineers. We use multi-criteria optimization techniques, pioneered by Francis Edgeworth and Vilfredo Pareto, combined with topology optimization using the homogenization technique to simultaneously realize such multi-criteria objectives

Battery storage performance analysis using multiphysics simulation through application builder and data analytics

Advisors: Pradip Majumdhar.Committee members: John Shelton; Donald S. Zinger.Includes illustrations.Includes bibliographical references.Lithium-ion (Li-ion) batteries are becoming increasingly popular for energy storage in electric vehicles, portable electronic devices and in-grid storage. Compared to alternative battery technologies, Li-ion batteries provide one of the best energy-to-weight ratios, and experience low self-discharge when not in use. Electric vehicle industries are increasingly attractive for their potential to reduce greenhouse gases and decrease dependence on oil. For automakers, the key to this huge shift will be lithium-ion batteries. The main objective of this research is to develop a three-dimensional computer simulation model of lithium-ion battery and performance analysis subject to a range of charge and discharge rates, current and voltage profiles associated with varying temperatures, and vehicle load cycles. Temperature is known to have a significant impact on the performance, safety and cycle life time of lithium-ion batteries. In this thesis, Multiphysics simulation analysis is used to evaluate the electro-chemical as well as thermal heat generation and temperature variations in the battery during the load cycle. Objective is to monitor the performance through Multiphysics simulation through Application builder and Data Analytics using COMSOL Multiphysics. Such real time predictive analysis will be of great advantage for efficient and safe operation of the battery storage.M.S. (Master of Science

Land use/land cover (LULC) classification using deep-LSTM for hyperspectral images

Land Use/Land Cover (LULC) classification using hyperspectral images in remote sensing is a leading technology. However, LULC classification using hyperspectral images is a difficult task and time-consuming process because it has fewer training samples. To overcome these issues, we proposed a deep-Long Short-Term Memory (deep-LSTM) to classify the LULC. Before classifying the LULC, extracting valuable features from an image is needed, and after extracting the features, selecting the bands which are helpful for classification should be done. In this work, we have proposed an auto-encoder model for feature extraction, a ranking-based band selection model to select the bands, and deep-LSTM for classification. We have used three publicly available benchmark datasets; they are Pavia University (PU), Kennedy Space Centre (KSC), and Indian Pines (IP). Average Accuracy (AA), Overall Accuracy (OA), and Kappa Coefficient (KC) are used to measure the classification accuracy. The suggested technique has provided the top outcomes compared to the other state-of-the-art methods

Synergistic effects of silicon and seaweed extract on growth and leaf nutrient content of papaya cv Red Lady

Silicon is crucial in the process of absorbing and transporting nutrients to the plants, which in turn helps to decrease the toxicity of iron (Fe), aluminium (Al), and manganese (Mn). Plants can better endure drought and salt stress because it strengthens their tissues. Seaweed extracts serve as biostimulants and are considered vital nutrients for sustainable agriculture due to their organic nature and ability to decompose naturally. The present study aimed to compare the nutritional content and growth rate of papaya cv. Red Lady after being treated with silicon and seaweed extract. The papaya plants were moved to new spots 1.5m x 1.5m apart. A Factorial Randomised Block Design with nine treatments and three replications was used for the field experiments. At 6, 7, 8, and 9 months after replanting, silicon (potassium silicate at 0.3% and 0.5%) and seaweed extract at 3% and 5% were made through foliar application. The study showed that the plant's height (278.66 cm), stem width (174.8 cm), number of leaves per plant (33.17), petiole length (127.3 cm), and leaf length (123 cm) were all higher in T8 (SE 5%+PS 0.5%) than in T7 (SE 5%+PS 0.3%) or T5 (SE 3%+PS 0.5%). A study of leaf minerals in synchrony showed that the highest levels of N, P, K, S, Ca, and Mg were found in the leaves nine months after the crop was transplanted.  Thus , using modest concentrations of silicon and seaweed extracts topically enhances growth, nutritional content in leaves, and resistance to biotic and abiotic stress, as well as Papaya Ring Spot Virus (PRSV), collar rot, and anthracnose.

Assessment of stress distribution with 3 taper design preparation of root canal using finite element analysis

Aim: Present research was done to assess stress distribution in three different taper design preparation of root canal with the help of finite element analysis. Materials and Methods: Lower incisors teeth having single canals that were cleaned and shaped with the help of NeoEndo Flex Titanium (NiTi) rotary file and later three designs were created such as 4%, 6%, and 8% canal preparation taper. Cone beam computed tomography (CBCT) was done for all teeth and subjected to finite element analysis for stresses. The collected data were statistically analyzed. Results: Highest stress was found in the coronal followed by the middle and least in the apical part in all three designs. The highest stress value was found in enamel than dentin (MPa). The highest stress value was found with design 3 (8% taper) followed by designs 2 (6% taper) and 1 (4% taper) for enamel and dentin with either oblique or vertical stress loading. Conclusion: All canals preparation exhibited maximum enamel stress at the coronal load points compared to apical and middle portions. The stress increases with increase in canal tapering

Estimation of Correlation and Path Coefficient Analysis for Quantitative Characters in Chickpea at Uttar Pradesh (Cicer arietinum L.)

An experiment was conducted and data were pooled for 22 genotypes including one check variety Uday in Field Experimentation Centre at Department of Genetics and Plant breeding, SHUATS, Prayagraj. The data was recorded for 11 quantitative traits to study the amount of variability, heritability, correlation analysis, direct and indirect effects of quantitative traits in chickpea genotypes. All the eleven quantitative traits under study displayed significant differences in Analysis of variance which indicates ample scope for selecting promising lines for further breeding programs. The genotypes ICC 8058, ICC 16796, and ICC 14199 were identified as the best genotypes for seed yield per plant among 22 genotypes under study. GCV values are slightly lesser compared to PCV values specifies the minor impact of environment on studied traits. The traits seed index, harvest index exhibited highly positive phenotypic and genotypic correlation for seed yield, which are the principal traits where selection can be operated for developing superior lines. Path coefficient analysis revealed that traits harvest index, biological yield, and the number of pods per plant showed highly positive direct effects at both genotypic and phenotypic levels on seed yield per plant. From the above results and outcomes traits seed index, harvest index, and biological yield, could be contemplated for selection criteria and yield improvement in chickpea

Unearthing the Nutritional and Agricultural Value through Scientific Innovation in the Natural Gene Pool of Millets

This delves into the exploration of millets' natural gene pool, highlighting the pivotal role of scientific innovation in unlocking their nutritional and agricultural value. Millets, often overlooked, have demonstrated remarkable resilience to adverse environmental conditions, making them essential crops for ensuring food security in a changing climate. Their adaptability, deep root systems, and drought tolerance position millets as reliable sources of sustenance in water-stressed regions. Moreover, millets are nutritional powerhouses, offering essential nutrients such as protein, dietary fiber, B-complex vitamins, iron, and zinc. Their gluten-free nature enhances their accessibility and inclusivity in diverse dietary regimes. Millet farming practices align with sustainability goals by promoting biodiversity conservation, reducing chemical inputs, and fostering economic development for smallholder farmers. Governments worldwide are recognizing the potential of millets, implementing policies and initiatives to support their production and market development. As the global community seeks solutions to nutritional security and hidden hunger, millets emerge as a resilient and nourishing ally. The integration of millets into food systems, driven by research, investment, and policy support, offers a pathway to a sustainable, nourished, and equitable future

A comprehensive review of anti-diabetic activity of vanadium-based complexes via PTP-1B inhibition mechanism

Inorganic salts of the vanadium have been found to mimic insulin in treating diabetic mellitus. In comparison to inorganic vanadium salts, complexes of vanadium with appropriate organic ligands can improve tissue absorption, efficacy, and reduce toxicity of the metal. An organic vanadyl derivative [bis(ethylmaltolato)oxovanadium(IV)] has been reported as a potential diabetes medication and is currently undergoing phase II clinical trials. The mechanism suggests that vanadium complexes inhibit the enzyme protein tyrosine phosphatase-1B(PTP-1B). Pharmacological, Biochemical and genetic evidences strongly suggest that inhibiting the PTP-1B enzyme could treat both diabetes and obesity, making PTP-1B an interesting target for drug development. Studies have also showed that the over expression of PTP-1B is involved in diabetic and obese patients and its inhibition may be an effective strategy in their treatment. Despite the fact that many natural PTP-1B inhibitors demonstrated promising clinical potential, there is no clinically used PTP-1B inhibitor, most likely due to low activity or a lack of selectivity. Search for more potent and selective PTP-1B inhibitors is still going on. As a result, inhibiting protein tyrosine 1B could be a new therapeutic option for patients at risk of type II diabetes mellitus and obesity. Many vanadium compounds are available as of now, as experimental probes for examining the mechanism of altered insulin action. However more studies are needed to establish its clinical use. Hence it has been proposed to prepare and characterize novel vanadium metal complexes with different coordination environments around vanadyl ion and check their anti diabetes activity

An in-vitro comparative evaluation for detection of residual gutta-percha after root canal retreatment with four different files using stereo microscope

Background: Removal of gutta-percha using hand files with or without solvent is tedious and time consuming process especially when the root filling material is well compacted8. Therefore, the use of NiTi rotary instruments in the root canal retreatment might decrease patient and operator fatigue and various studies have reported their efficacy, cleaning ability and safety. Several NiTi rotary instruments also were been used to remove gutta-percha. Here in this study four file systems were used to assess the efficacy of each file system in retreatment procedures.Materials & methods: The study samples comprised of 80 extracted anteriors having single root canals with fully formed apices were collected. The crowns were de-coronated with a diamond disc to leave a 16-mm root. A size 10 K-file was introduced into the canal until it was visible at the apical foramen. The working length was determined by subtracting 1mm from this measurement. During shaping, each canal was irrigated with 3% sodium hypochlorite then smear layer was removed with 17% EDTA and 1 ml of 3% sodium hypochlorite. After one month the teeth were divided into following groups with 20 specimens each as follows.&nbsp