A Survey on Particle Swarm Optimization for Association Rule Mining

Association rule mining (ARM) is one of the core techniques of data mining to discover potentially valuable association relationships from mixed datasets. In the current research, various heuristic algorithms have been introduced into ARM to address the high computation time of traditional ARM. Although a more detailed review of the heuristic algorithms based on ARM is available, this paper differs from the existing reviews in that we expected it to provide a more comprehensive and multi-faceted survey of emerging research, which could provide a reference for researchers in the field to help them understand the state-of-the-art PSO-based ARM algorithms. In this paper, we review the existing research results. Heuristic algorithms for ARM were divided into three main groups, including biologically inspired, physically inspired, and other algorithms. Additionally, different types of ARM and their evaluation metrics are described in this paper, and the current status of the improvement in PSO algorithms is discussed in stages, including swarm initialization, algorithm parameter optimization, optimal particle update, and velocity and position updates. Furthermore, we discuss the applications of PSO-based ARM algorithms and propose further research directions by exploring the existing problems.publishedVersio

Development of aircraft lavatory compartments with improved fire resistance characteristics. Phase 4: Sandwich panel decorative ink development

Five chemically different resin systems with improved fire resistance properties were studied for a possible screenprinting ink application. Fire resistance is hereby defined as the cured ink possessing improvements in flammability, smoke emission, and thermal stability. The developed ink is for application to polyvinyl fluoride film. Only clear inks without pigments were considered. Five formulations were evaluated compared with KC4900 clear acrylic ink, which was used as a baseline. The tests used in the screening evaluation included viscosity, smoke and toxic gas emission, limiting oxygen index (LOI), and polyvinyl fluoride film (PVF) printability. A chlorofluorocarbon resin (FPC461) was selected for optimization studies. The parameters for optimization included screenprinting process performance, quality of coating, and flammability of screenprinted 0.051-mm (0.002-in.) white Tedlar. The quality of the screenprinted coating on Tedlar is dependent on viscosity, curing time, adhesion to polyvinyl fluoride film, drying time (both inscreen and as an applied film), and silk screen mesh material and porosity

SciTech News Volume 71, No. 1 (2017)

Columns and Reports From the Editor 3 Division News Science-Technology Division 5 Chemistry Division 8 Engineering Division Aerospace Section of the Engineering Division 9 Architecture, Building Engineering, Construction and Design Section of the Engineering Division 11 Reviews Sci-Tech Book News Reviews 12 Advertisements IEEE

05441 Abstracts Collection -- Managing and Mining Genome Information: Frontiers in Bioinformatics

From 30.10.05 to 04.11.05, the Dagstuhl Seminar 05441 ``Managing and Mining Genome Information: Frontiers in Bioinformatics\u27\u27 was held in the International Conference and Research Center (IBFI), Schloss Dagstuhl. During the seminar, several participants presented their current research, and ongoing work and open problems were discussed. Abstracts of the presentations given during the seminar as well as abstracts of seminar results and ideas are put together in this paper. The first section describes the seminar topics and goals in general. Links to extended abstracts or full papers are provided, if available

Preservation of DNA Privacy During the Large Scale Detection of COVID-19

As humanity struggles to contain the global COVID-19 pandemic, privacy concerns are emerging regarding confinement, tracing and testing. The scientific debate concerning privacy of the COVID-19 tracing efforts has been intense, especially focusing on the choice between centralised and decentralised tracing apps. The privacy concerns regarding COVID-19 testing, however, have not received as much attention even though the privacy at stake is arguably even higher. COVID-19 tests require the collection of samples. Those samples possibly contain viral material but inevitably also human DNA. Patient DNA is not necessary for the test but it is technically impossible to avoid collecting it. The unlawful preservation, or misuse, of such samples at a massive scale may hence disclose patient DNA information with far-reaching privacy consequences. Inspired by the cryptographic concept of "Indistinguishability under Chosen Plaintext Attack", this paper poses the blueprint of novel types of tests allowing to detect viral presence without leaving persisting traces of the patient's DNA. Authors are listed in alphabetical order.Comment: 10 pages, 1 figur