Classification of Cardiotocography Data with WEKA

Cardiotocography (CTG) records fetal heart rate (FHR) and uterine contractions (UC) simultaneously. Cardiotocography trace patterns help doctors to understand the state of the fetus. Even after the introduction of cardiotocograph, the capacity to predict is still inaccurate. This paper evaluates some commonly used classification methods using WEKA. Precision,Recall, F-Measrue and ROC curve have been used as the metric to evaluate the performance of classifiers. As opposed to some of the earlier research works that were unable to identify Suspicious and Pathologic patterns, the results obtained from the study in this paper could precisely identify pathologic and Suspicious cases. Best results were obtained from J48, Random Forest and Classification via Regression

An efficient model for secure data publishing

Data Mining is the field of extracting and analyzing the data from large datasets. Exchange of databases is very important to get financial benefits now a day. To review business strategies and to get maximum benefit data analytics is needed. Data stored at distributed sites are integrated and published by data publisher. Data Publishing is the technique in which the data is released to others for the use. In addition to privacy preserving data size and security is also a challenge while publishing and transmitting the database. So there is a requirement of a technique which can reduce the size of database efficiently and transfer it in a secure manner. This paper proposes an efficient model for secure data publishing by using both compression and color encryption thus introducing a new approach. A new algorithm is designed and a tool is developed for implementing the proposed work

Hydrogels for Regenerative Medicine

Regenerative medicine requires materials that are biodegradable, biocompatible, structurally and chemically stable, and that can mimic the properties of the native extracellular matrix (ECM). Hydrogels are hydrophilic three-dimensional networks that have long received attention in the field of regenerative medicine due to their unique properties. Hydrogels have a potential to be the future of regenerative medicine due to their desirable mechanical and chemical properties, ease of their synthesis, and their multiple applicability as drug delivery vehicles, scaffolds, and constructs for cell culture. In this chapter, we have described hydrogels in terms of their cross-linking and then discussed the most recent developments in the use of hydrogels for peripheral nerve regeneration, tooth regeneration, and 3D bioprinting

Classification of Cardiotocography Data with WEKA

Cardiotocography (CTG) records fetal heart rate (FHR) and uterine contractions (UC) simultaneously. Cardiotocography trace patterns help doctors to understand the state of the fetus. Even after the introduction of cardiotocograph, the capacity to predict is still inaccurate. This paper evaluates some commonly used classification methods using WEKA. Precision,Recall, F-Measrue and ROC curve have been used as the metric to evaluate the performance of classifiers. As opposed to some of the earlier research works that were unable to identify Suspicious and Pathologic patterns, the results obtained from the study in this paper could precisely identify pathologic and Suspicious cases. Best results were obtained from J48, Random Forest and Classification via Regression

Performance Evaluation of Anonymized Data Stream Classifiers

Data stream is a continuous and changing sequence of data that continuously arrive at a system to store or process. It is vital to find out useful information from large enormous amount of data streams generated from different applications viz. organization record, call center record, sensor data, network traffic, web searches etc. Privacy preserving data mining techniques allow generation of data for mining and preserve the private information of the individuals. In this paper, classification algorithms were applied on original data set as well as privacy preserved data set. Results were compared to evaluate the performance of various classification algorithms on the data streams that had been privacy preserved using anonymization techniques. The paper proposes an effective approach for classification of anonymized data streams. Intensive experiments were performed using appropriate data mining and anonymization tools. Experimental result shows that the proposed approach improves accuracy of classification and increases the utility, i.e. accuracy of classification while minimizing the mean absolute error. The proposed work presents the anonymization technique effective in terms of information loss and the classifiers efficient in terms of response time anddata usability

A MATRIX MODEL FOR MINING FREQUENT PATTERNS IN LARGE DATABASES

Abstract: This paper proposes a model for mining frequent patterns in large databases by implementing a matrix approach. The whole database is scanned only once and the data is compressed in the form of a matrix. The frequent patterns are then mined from this compressed database which brings efficiency in data mining, as the number of database scans is effectively less than two. The computation time is reduced as some of the patterns are mined simultaneously and searching is minimized. Appropriate mathematical operations are designed and performed on matrices to achieve this efficiency

An efficient model for secure data publishing

Data Mining is the field of extracting and analyzing the data from large datasets. Exchange of databases is very important to get financial benefits now a day. To review business strategies and to get maximum benefit data analytics is needed. Data stored at distributed sites are integrated and published by data publisher. Data Publishing is the technique in which the data is released to others for the use. In addition to privacy preserving data size and security is also a challenge while publishing and transmitting the database. So there is a requirement of a technique which can reduce the size of database efficiently and transfer it in a secure manner. This paper proposes an efficient model for secure data publishing by using both compression and color encryption thus introducing a new approach. A new algorithm is designed and a tool is developed for implementing the proposed work

NOVEL ACCESSIBILITY METRICS BASED ON HIERARCHICAL DECOMPOSITION OF TRANSPORT NETWORKS

Scientific analysis of public transport systems at the urban, regional, and national levels is vital in this contemporary, highly connected world. Quantifying the accessibility of nodes (locations) in a transport network is considered a holistic measure of transportation and land use and an important research area. In recent years, complex networks have been employed for modeling and analyzing the topology of transport systems and services networks. However, the design of network hierarchy-based accessibility measures has not been fully explored in transport research. Thus, we propose a set of three novel accessibility metrics based on the k-core decomposition of the transport network. Core-based accessibility metrics leverage the network topology by eliciting the hierarchy while accommodating variations like travel cost, travel time, distance, and frequency of service as edge weights. The proposed metrics quantify the accessibility of nodes at different geographical scales, ranging from local to global. We use these metrics to compute the accessibility of geographical locations connected by air transport services in India. Finally, we show that the measures are responsive to changes in the topology of the transport network by analyzing the changes in accessibility for the domestic air services network for both pre-covid and post-covid times

Identification, Functional Characterization, and Regulon Prediction of the Zinc Uptake Regulator (zur) of Bacillus anthracis – An Insight Into the Zinc Homeostasis of the Pathogen

Zinc has an abounding occurrence in the prokaryotes and plays paramount roles including catalytic, structural, and regulatory. Zinc uptake regulator (Zur), a Fur family transcriptional regulator, is connoted in maintaining zinc homeostasis in the pathogenic bacteria by binding to zinc and regulating the genes involved in zinc uptake and mobilization. Zinc homeostasis has been marginally scrutinized in Bacillus anthracis, the top-rated bio-terror agent, with no decipherment of the role of Zur. Of the three Fur family regulators in B. anthracis, BAS4181 is annotated as a zinc-specific transcriptional regulator. This annotation was further substantiated by our stringent computational and experimental analyses. The residues critical for zinc and DNA binding were delineated by homology modeling and sequence/structure analysis. ba zur existed as a part of a three-gene operon. Purified BaZur prodigiously existed in the dimeric form, indicated by size exclusion chromatography and blue native-polyacrylamide gel electrophoresis (PAGE). Computational and manual strategies were employed to decipher the putative regulon of ba zur, comprising of 11 genes, controlled by six promoters, each harboring at least one Zur box. The DNA binding capability of the purified BaZur to the upstream regions of the ba zur operon, yciC, rpmG, znuA, and genes encoding a GTPase cobalamine synthesis protein and a permease was ascertained by electrophoretic mobility shift assays. The regulon genes, implicated in zinc uptake and mobilization, were mostly negatively regulated by BaZur. The ba zur expression was downregulated upon exposure of cells to an excess of zinc. Conversely, it exhibited a marked upregulation under N, N, N′, N′-Tetrakis (2-pyridylmethyl) ethylenediamine (TPEN) mediated zinc-depleted environment, adding credence to its negative autoregulation. Moreover, an increase in the transcript levels of the regulon genes znuA, rpmG, and yciC upon exposure of cells to TPEN connoted their role in combating hypo-zincemic conditions by bringing about zinc uptake and mobilization. Thus, this study functionally characterizes Zur of B. anthracis and elucidates its role in maintaining zinc homeostasis

Heat Shock Proteins (Hsps) Mediated Signalling Pathways During Abiotic Stress Conditions

The perception of abiotic stress and signal transduction to switch on adaptive innate responses are crucial steps in plant persistence under adverse environmental conditions. The ability of plants to respond to different stresses by maintaining protein in functional active form is of high importance and essential for cell survival. This is possible with the functional activity of heat shock proteins (Hsps), which play a role in maintaining the cellular homeostasis, and preserving the nonnative protein in a competent state for further remodeling as well as in signal transduction. Hsps mediate the stress signals either directly or indirectly, and play an important role in maintaining the homeostasis of plant cells under adverse stress conditions. Much research has been conducted to understand the complex mechanisms of the Hsps including Hsp70/90, ATPase-coupled conformational modifications, and interactions with cochaperones. In addition to this, several signaling proteins including MAP kinases, Ca2+ regulated proteins, Hsfs, reactive oxygen species are seen to be interacting with Hsps. In this study, we discuss the signal transduction of different Hsps, and their role in different signaling mechanisms