An Empirical Study on Different Ranking Methods for Effective Data Classification

Ranking is the attribute selection technique used in the pre-processing phase to emphasize the most relevant attributes which allow models of classification simpler and easy to understand. It is a very important and a central task for information retrieval, such as web search engines, recommendation systems, and advertisement systems. A comparison between eight ranking methods was conducted. Ten different learning algorithms (NaiveBayes, J48, SMO, JRIP, Decision table, RandomForest, Multilayerperceptron, Kstar) were used to test the accuracy. The ranking methods with different supervised learning algorithms give different results for balanced accuracy. It was shown the selection of ranking methods could be important for classification accuracy

Secure and Robust Fragile Watermarking Scheme for Medical Images

Over the past decade advances in computer-based communication and health services, the need for image security becomes urgent to address the requirements of both safety and non-safety in medical applications. This paper proposes a new fragile watermarking based scheme for image authentication and self-recovery for medical applications. The proposed scheme locates image tampering as well as recovers the original image. A host image is broken into 4×4 blocks and Singular Value Decomposition (SVD) is applied by inserting the traces of block wise SVD into the Least Significant Bit (LSB) of the image pixels to figure out the transformation in the original image. Two authentication bits namely block authentication and self-recovery bits were used to survive the vector quantization attack. The insertion of self-recovery bits is determined with Arnold transformation, which recovers the original image even after a high tampering rate. SVD-based watermarking information improves the image authentication and provides a way to detect different attacked area. The proposed scheme is tested against different types of attacks such are text removal attack, text insertion attack, and copy and paste attack

Identification and Characterization of 2′-Deoxyadenosine Adducts Formed by Isoprene Monoepoxides in Vitro

Isoprene, the 2-methyl analog of 1,3-butadiene, is ubiquitous in the environment, with major contributions to total isoprene emissions stemming from natural processes despite the compound being a bulk industrial chemical. Additionally, isoprene is a combustion product and a major component in cigarette smoke. Isoprene has been classified as possibly carcinogenic to humans (group 2B) by IARC and as reasonably anticipated to be a human carcinogen by the National Toxicology Program. Isoprene, like butadiene, requires metabolic activation to reactive epoxides to exhibit its carcinogenic properties. The mode of action has been postulated to be that of a genotoxic carcinogen, with formation of promutagenic DNA adducts being essential for mutagenesis and carcinogenesis. In rodents, isoprene-induced tumors show unique point mutations (A→T transversions) in the K-ras protooncogene at codon 61. Therefore, we investigated adducts formed after reaction of 2′-deoxyadenosine (dAdo1) with the two monoepoxides of isoprene, 2-ethenyl-2-methyloxirane (IP-1,2-O) and propen-2-yloxirane (IP-3,4-O), under physiological conditions. The formation of N1–2′-deoxyinosine (N1-dIno) due to deamination of N1-dAdo adducts was of particular interest, since N1-dIno adducts are suspected to have high mutagenic potential based on in vitro experiments. Major stable adducts were identified by HPLC, UV-Spectrometry and LC-MS/MS and characterized by 1H and 1H,13C HSQC and NMR experiments. Adducts of IP-1,2-O that were fully identified are: R,S-C1-N6-dAdo, R-C2-N6-dAdo, and S-C2-N6-dAdo; adducts of IP-3,4-O are: S-C3-N6-dAdo, R-C3-N6-dAdo, R,S-C4-N6-dAdo, S-C4-N1-dIno, R-C4-N1-dIno, R-C3-N1-dIno, S-C3-N1-dIno, and C3-N7-Ade. Both monoepoxides formed adducts on the external and internal oxirane carbons. This is the first study to describe adducts of isoprene monoepoxides with dAdo. Characterization of adducts formed by isoprene monoepoxides with deoxynucleosides and subsequently with DNA represent the first step toward evaluating their potential for being converted into a mutation, or as biomarkers of isoprene metabolism and exposure

Cognitive IoT system with intelligence techniques in sustainable computing environment

Forest border crossing animals creates major societal related issues, in addition to endangering their own lives. This is the objective focused in this paper targeting the species “The Elephant”, incorporating with technical methodologies namely, multi-sensor data fusion, cognition theories and computational intelligence techniques. Multi-sensor data fusion provides three level detection of target, along with its related outputs, which improves performance metrics. Cognition theory resulted in obtaining other interesting features about the target. Computational intelligence techniques integrate and conclude the presence of the target in the pseudo-boundary. The technical combination enhances the novelty of the research work, resulting in achieving remarkable accuracy and minimized false alert. An IoT kit was designed and deployed in the real time wild environment in Hosur forest region for collecting the data of Elephant. Further, the notification is sent to the registered mobile of the forest authority, as an early warning for chasing the pachyderm back to the forest

A Framework for Assessing Reusability Using Package Cohesion Measure in Aspect Oriented Systems

Due to better modularization of crosscutting concerns, the Aspect oriented programming approach enhances the quality of the system as it results in less complex and more readable implementation of the system. As the software applications grow in size and complexity, they require some kind of high level organization. For high level organization of software system, packages are required. A lot of work has been carried out for measuring cohesion in Aspect Oriented Systems (AOS) at class level but very less research has been done for designing package level cohesion metric. Package cohesion metrics plays an important role in analyzing quality of software at package level. According to object oriented design principle, a good software design must have high cohesion with high reusability. Thus a relationship must therefore exist between cohesion and reusability. Number of attempts has been made to evaluate effect of cohesion on external attributes but at class level only. Impact of package level cohesion metrics on reusability for AOS is not yet explored. (a) To implement the proposed package cohesion measure, PCohA, on AspectJ sample packages, (b) to theoretically validate the proposed measure and (c) to find the impact of package cohesion on measuring reusability for AOS. Theoretical validation has been done by proving its validity on four theorems given by Briand et al. For finding the impact of proposed measure on external attributes, correlation has been found between package cohesion, PCohA, and external attribute—reusability. After theoretical validation, it has been proved that the proposed measure is suitable for measuring cohesion at package level. Correlation between package cohesion metric (PCohA) and reusability is calculated by using Karl Pearson Product Moment correlation. The computed values show a strong positive relation between PCohA and Reusability. The proposed package cohesion measure is found to be a useful indicator of external quality factors such as reusability. The proposed metric is also established as a better predictor of code reusability than the existing cohesion measures. The work discussed in this paper can be used for designing high quality software by developing new package level metrics for other quality attributes such as maintainability, changeability etc. as a future wor