The Threat of Plant Toxins and Bioterrorism: A Review

The intentional use of highly pathogenic microorganisms, such as bacteria, viruses or their toxins, to spread mass-scale diseases that destabilize populations (with motivations of religious or ideological belief, monetary implications, or political decisions) is defined as bioterrorism. Although the success of a bioterrorism attack is not very realistic due to technical constraints, it is not unlikely and the threat of such an attack is higher than ever before. It is now a fact that the capability to create panic has allured terrorists for the use of biological agents (BAs) to cause terror attacks. In the era of biotechnology and nanotechnology, accessibility in terms of price and availability has spread fast, with new sophisticated BAs often being produced and used. Moreover, there are some BAs that are becoming increasingly important, such as toxins produced by bacteria (e.g., Botulinum toxin, BTX), or Enterotoxyn type B, also known as Staphylococcal Enterotoxin B (SEB)) and extractions from plants. The most increasing records are with regards to the extraction / production of ricin, abrin, modeccin, viscumin and volkensin, which are the most lethal plant toxins known to humans, even in low amounts. Moreover, ricin was also developed as an aerosol biological warfare agent (BWA) by the US and its allies during World War II, but was never used. Nowadays, there are increasing records that show how easy it can be to extract plant toxins and transform them into biological weapon agents (BWAs), regardless of the scale of the group of individuals

Handling Class Imbalance Using Swarm Intelligence Techniques, Hybrid Data and Algorithmic Level Solutions

This research focuses mainly on the binary class imbalance problem in data mining. It investigates the use of combined approaches of data and algorithmic level solutions. Moreover, it examines the use of swarm intelligence and population-based techniques to combat the class imbalance problem at all levels, including at the data, algorithmic, and feature level. It also introduces various solutions to the class imbalance problem, in which swarm intelligence techniques like Stochastic Diffusion Search (SDS) and Dispersive Flies Optimisation (DFO) are used. The algorithms were evaluated using experiments on imbalanced datasets, in which the Support Vector Machine (SVM) was used as a classifier. SDS was used to perform informed undersampling of the majority class to balance the dataset. The results indicate that this algorithm improves the classifier performance and can be used on imbalanced datasets. Moreover, SDS was extended further to perform feature selection on high dimensional datasets. Experimental results show that SDS can be used to perform feature selection and improve the classifier performance on imbalanced datasets. Further experiments evaluated DFO as an algorithmic level solution to optimise the SVM kernel parameters when learning from imbalanced datasets. Based on the promising results of DFO in these experiments, the novel approach was extended further to provide a hybrid algorithm that simultaneously optimises the kernel parameters and performs feature selection

Intelligent Circuits and Systems

ICICS-2020 is the third conference initiated by the School of Electronics and Electrical Engineering at Lovely Professional University that explored recent innovations of researchers working for the development of smart and green technologies in the fields of Energy, Electronics, Communications, Computers, and Control. ICICS provides innovators to identify new opportunities for the social and economic benefits of society.　 This conference bridges the gap between academics and R&D institutions, social visionaries, and experts from all strata of society to present their ongoing research activities and foster research relations between them. It provides opportunities for the exchange of new ideas, applications, and experiences in the field of smart technologies and finding global partners for future collaboration. The ICICS-2020 was conducted in two broad categories, Intelligent Circuits & Intelligent Systems and Emerging Technologies in Electrical Engineering

CACIC 2015 : XXI Congreso Argentino de Ciencias de la Computación. Libro de actas

Actas del XXI Congreso Argentino de Ciencias de la Computación (CACIC 2015), realizado en Sede UNNOBA Junín, del 5 al 9 de octubre de 2015.Red de Universidades con Carreras en Informática (RedUNCI