E3 : Keyphrase based News Event Exploration Engine

This paper presents a novel system E3 for extracting keyphrases from news content for the purpose of offering the news audience a broad overview of news events, with especially high content volume. Given an input query, E3 extracts keyphrases and enrich them by tagging, ranking and finding role for frequently associated keyphrases. Also, E3 finds the novelty and activeness of keyphrases using news publication date, to identify the most interesting and informative keyphrases

Estimation of Missing Attribute Value in Time Series Database in Data Mining

Missing data is a widely recognized problem affecting large database in data mining. The substitution of mean values for missing data is commonly suggested and used in many statistical software packages, however, mean substitution lead to large errors in correlation matrix and therefore degrading the performance of statistical modeling. The problems arises are biasness of result data base, inefficient data in missing data when anomalous data is also present. In proposed work there is proper handling of missing data values and their analysis with removal of the anomalous data.This method provides more accurate and efficient result and reduces biasness of result for filling in missing data. Theoretical analysis and experimental results shows that proposed methodology is better

A Merging System for Integrated Person-Centric Information Systems

Large-scale integrated information systems correlate equivalent or related information from multiple data sources to provide a unified view of data. This report describes the design and implementation of a tool called xMerger that provides a unified view from multiple matching records, which could be multi-source duplicates and overlapping records. To achieve this xMerger provides a merging process that generates a complete and accurate merged record from conflicting and incomplete records. This report also discusses the challenges present in the process of merging and xMerger’s solutions. xMerger’s design and implementation was validated by adapting it to CHARM, a real world integrated system currently in use at the Utah Department of Health

Photoluminescence study of cadmium zinc telluride

In this thesis, I present a detailed study of Cd1-xZn xTe crystals with 0 ≤ x ≤ 0.14 using photoluminescence (PL) spectroscopy in the temperature range from 5 K to 300 K with the purpose of: (1) identifying various radiative transitions that are signatures of various point defects in bulk CdZnTe, (2) determining the zinc concentration in these crystals, and (3) identifying the nature of room-temperature PL. PL spectra at 5 K was used to determine the bandgap and hence the zinc concentrations. In the current state-of-the-art CZT grown for radiation detectors, it is common to observe 5-K PL spectra dominated by donor-bound exciton emission (D 0, X). Also, a deep acceptor-bound exciton (A0, X) related to a complex associated with Cd vacancies is usually detected. Thus, it was of interest to determine whether the new trend in bulk CZT growth would produce a different conclusion about the origin of the 300-K PL

Hemodialysis and Oral Health

Changing lifestyle and sedentary schedule have led to the substantial increase in major noncommunicable diseases (NCDs) such as cardiac problems, cancers, diabetes, psychiatric disorders, and chronic respiratory diseases. Recent times have shown increased trends in incidence as well as prevalence of renal diseases. Hemodialysis is the most opted treatment modality for the patients of chronic renal diseases. Hence, the aim of the current chapter is to address the effect of renal diseases and its treatment on oral health. An extensive literature search from the year 2000 till 2015 was conducted to assess the effect of hemodialysis and renal diseases on various clinical parameters associated with oral health like dental caries, periodontal diseases, prevalence of calculus, etc. The literature review revealed that the dental health is compromised in the patients undergoing hemodialysis therapy. The oral health-related parameters get worsened with increasing duration of hemodialysis as well. The primary reason behind the debilitated periodontal condition among the patients may be attributed to the neglect of proper oral hygiene practices by the patient as they are preoccupied by more time-consuming and life-threatening kidney disease. A strong relation between oral health and hemodialysis has been observed. There is a need for further interdisciplinary research with emphasis on preventive dental treatment for the patients undergoing hemodialysis ensuring optimum outcome

Optimization of Investments in Cybersecurity: A Linear Programming Approach

Cyber-attacks have globally escalated by 125% after the onset of the pandemic as businesses transitioned to online work setups. These cybercrimes incur significant costs. Consequently, organizations are giving heightened priority to cybersecurity investments, integrating them into their strategic decision-making. However, due to limited resources, a judicious approach is necessary, focusing on selective investment in effective mitigation strategies. This study addresses the challenge of optimally allocating investments among diverse cybersecurity measures to enhance cybersecurity efficacy while minimizing the risk of cyberattacks. Specifically, the study aims to anticipate potential losses based on breach likelihood and determine the optimal investment levels. The study employs a combination of machine learning (ML) and linear programming (LP) to determine suitable mitigation strategies for investment, considering constrained monetary resources. ML techniques, including Naïve Bayes and Decision Tree, assess breach likelihood and consequent losses. Subsequently, LP is employed to ascertain the most effective allocation of investments across different cybersecurity mitigation strategies, considering the constraints of monetary resources