An improved multi-leader comprehensive learning particle swarm optimisation based on gravitational search algorithm

Multi-leader comprehensive learning particle swarm optimiser possesses strong exploitation ability, by randomly selecting and assigning best-ranked particles as leaders during optimisation. However, it lacks the ability to preserve diversity by mainly focusing on exploitation, and adopting random selection to choose leaders also hinders its performance. To overcome these deficiencies, an improved multi-leader comprehensive learning particle swarm optimiser is proposed based on Karush-Kuhn-Tucker proximity measure and Gravitational Search Algorithm. Karush-Kuhn-Tucker proximity measure is employed to determine the best-ranked particles’ contribution to the swarm’s convergence to influence their selection as guides for other particles. Gravitational Search Algorithm is introduced to preserve the algorithm’s ability to maintain diversity. To curb premature convergence and particles getting trapped in a local optimum, an adaptive reset velocity strategy is incorporated to activate stagnated particles. Some benchmark test functions are employed to compare the proposed algorithm with seven other peer algorithms. The results verify that our proposed algorithm possesses a better capability to elude local optima with faster convergence than other algorithms. Furthermore, to prove the efficacy of the application of our proposed algorithm in real-life, the algorithms are used to train a Feedforward neural network for epilepsy detection, of which our proposed algorithm outperforms the others

Evaluation of various drying approaches on the physicochemical properties, rehydration kinetics, mathematical modeling and quality of tiger nut (Cyperus esculentum)

In this study, the quality and physicochemical properties as well as rehydration kinetics of dried tiger nuts were examined in relation to four different drying techniques. Tiger nuts were dried using the infrared dryer (ID), hot air dryer (HA-D), electric oven dryer (EOD), and sun dryer (SD). Effects of models on the rehydration kinetics of tiger nuts processing (drying) under various drying processes were tested, along with the antioxidation, sensory qualities, total phenolic content (TPC), moisture content (MC), and chromatic aspects of the dried slices. The Weibull model had the highest coefficient of determination (R2) > 0.99, residual sum of squares (RSS), reduced chi-square (2), and root mean square error (RMSE). In terms of chromatic characteristics, antioxidation, DPPH (83.55 mgTE/g db) and TPC (72.28 mg GAE/g db), the ID-tiger nut samples had the highest retention rates with lowest MC (5.67%). The dried samples varied significantly from HA-D, EOD, and SD in terms of their rehydration ratio (RR) and rehydration kinetics (p  HA-D > EOD >SD

Investing in Food Safety for Developing Countries: Opportunities and Challenges in Applying Whole-Genome Sequencing for Food Safety Management

FOODBORNE PATHOGENS AND DISEASE, Volume 16, Number 7, 2019Whole-genome sequencing (WGS) has become a significant tool in investigating foodborne disease outbreaks and some countries have incorporated WGS into national food control systems. However, WGS poses technical chal- lenges that deter developing countries from incorporating it into their food safety management system. A rapid scoping review was conducted, followed by a focus group session, to understand the current situation regarding the use of WGS for foodborne disease surveillance and food monitoring at the global level and identify key limiting factors for developing countries in adopting WGS for their food control systems. The results showed that some developed nations routinely use WGS in their food surveillance systems resulting in more precise understanding of the causes of outbreaks. In developing nations, knowledge of WGS exists in the academic/research sectors; however, there is limited understanding at the government level regarding the usefulness of WGS for food safety regulatory activities. Thus, incorporation of WGS is extremely limited in most developing nations. While some countries lack the capacity to collect and analyze the data generated from WGS, the most significant technical gap in most developing countries is in data interpretation using bioinformatics. The gaps in knowledge and capacities between developed and developing nations regarding use of WGS likely introduce an inequality in international food trade, and thus, relevant international organizations, as well as the countries that are already proficient in the use of WGS, have significant roles in assisting developing nations to be able to fully benefit from the technology and its applications in food safety management