SARA: Smart AI Reading Assistant for Reading Comprehension

SARA integrates Eye Tracking and state-of-the-art large language models in a mixed reality framework to enhance the reading experience by providing personalized assistance in real-time. By tracking eye movements, SARA identifies the text segments that attract the user's attention the most and potentially indicate uncertain areas and comprehension issues. The process involves these key steps: text detection and extraction, gaze tracking and alignment, and assessment of detected reading difficulty. The results are customized solutions presented directly within the user's field of view as virtual overlays on identified difficult text areas. This support enables users to overcome challenges like unfamiliar vocabulary and complex sentences by offering additional context, rephrased solutions, and multilingual help. SARA's innovative approach demonstrates it has the potential to transform the reading experience and improve reading proficiency.Comment: ETRA '2

A genetic-based algorithm for fuzzy unit commitment model

This paper presents a fuzzy model for the unit commitment problem (UCP). The model takes the uncertainties in the forecasted load demand and the spinning reserve constraints in a fuzzy frame. The genetic algorithm (GA) approach is then used to solve the proposed fuzzy UCP model. In the implementation for the GA, coding of the UCP solutions is based on mixing binary and decimal representations. A fitness function is constructed from the total operating cost of the generating units plus a penalty term determined due to the fuzzy load and spinning reserve membership functions. Numerical results showed an improvement in the solutions costs compared to the results reported in the literature and the GA with crisp UCP mode

A genetic-based algorithm for fuzzy unit commitment model

This paper presents a fuzzy model for the unit commitment problem (UCP). The model takes the uncertainties in the forecasted load demand and the spinning reserve constraints in a fuzzy frame. The genetic algorithm (GA) approach is then used to solve the proposed fuzzy UCP model. In the implementation for the GA, coding of the UCP solutions is based on mixing binary and decimal representations. A fitness function is constructed from the total operating cost of the generating units plus a penalty term determined due to the fuzzy load and spinning reserve membership functions. Numerical results showed an improvement in the solutions costs compared to the results reported in the literature and the GA with crisp UCP mode

Efeitos terapêuticos do Allium sativum e Allium cepa na infecção experimental pelo Schistosoma mansoni

The effects of both garlic (Allium sativum) and onion (Allium cepa) on some biochemical parameters in Schistosoma mansoni infected mice individually and mixed either with or without the currently used drug, praziquantel (PZQ) were investigated. These involved some immunological parameters, namely IgM, IgG, interleukins 2 and 6 (IL-2 and 6) and tumor necrosis factor (TNF-α), some antioxidant enzymes [catalase, superoxide dismutase (SOD) and glutathione peroxidase (GPX)]. In addition, parasitological and histopathological investigations were performed. No changes were observed in the normal control mice treated with dry extract of onion or garlic, individually or mixed, with or without PZQ, compared to the normal healthy control group. Infection with S. mansoni showed an increase in IgG, IgM, IL-2, IL-6, TNF-α and catalase enzyme, accompanied with a decrease in GPX and SOD antioxidant enzyme activities. Remarkable amelioration was noticed in the levels of all the measured parameters in S. mansoni infected mice after administration of the studied extracts. Moreover a significant reduction in worm burden, hepatic and intestinal eggs and oogram count was noticed which was reflected in normalization of liver architecture.Os efeitos do alho (Allium sativum) e cebola (Allium cepa) em parâmetros bioquímicos de camundongos infectados pelo Schistosoma mansoni individualmente e misturados seja com ou sem as drogas correntemente usadas como o Praziquantel (PZQ), foram investigados. Isto envolveu parâmetros imunológicos tais como IgM, IgG, Interleucina 2 e 6 (IL-2 e 6), fator de necrose tumoral (TNF-α) e algumas enzimas anti-oxidantes [catalase, super-óxido dismutase (SOD) e glutationa peroxidase (GPX)]. Em adição foram realizadas investigações parasitológicas e histopatológicas. Nenhuma alteração foi observada nos camundongos controles normais tratados com extrato seco de cebola ou alho, individualmente ou misturado, com ou sem PZQ, comparados com os controles normais sadios. Infecção com o Schistosoma mansoni revelou um aumento em IgG, IgM, IL-2, IL-6, TNF-α e catalase, acompanhados de diminuição do GPX e atividade enzimática do anti-oxidante SOD. Melhora acentuada foi notada nos níveis de todos os parâmetros medidos em camundongos infectados com Schistosoma mansoni após administração dos extratos estudados. Mais ainda, significante redução na quantidade de vermes, e ovos no fígado e intestino e na contagem do oograma foi notada refletindo a normalização da arquitetura do fígado

A simulated annealing-based optimal controller for a three phase induction motor

This paper presents a new approach for optimal controller design of a three-phase induction motor (IM), based on using the simulated annealing (SA) method to find the optimal controller gains that satisfy a specific performance criterion. Optimal control requires well-known information about the system dynamics, which will preclude its applicability with systems having partially known or unknown dynamics. Accordingly; the proposed approach is implemented to emulate the structure and hence the characteristics of the optimal controller in spite of the partially known system dynamics, inaccuracy or uncertainties of system parameter. The problem is a hard nonlinear optimization problem in continuous variables. An adaptive cooling schedule and a new method for variables discretization are implemented to enhance the speed and convergence of the original simulated annealing algorithm (SAA). The proposed algorithm comprises structure of the optimal controller, a new error system and vector control of a three phase IM. The IM is described as a three input, three output controlled object. The state equations of IM suitable for voltage control are implemented based on the vector, method. Simulation results show better system performance compared to previously obtained results

A new reactive power optimization algorithm

This paper presents an algorithm for optimizing reactive power using particle swarm algorithm. A new implementation for the particle swarm algorithm has been applied. The objective function of the proposed algorithm is to minimize the system active power loss. The control variables are generator bus voltages, transformer tap positions and switch-able shunt capacitor banks. The proposed algorithm has been applied to practical IEEE 6-bus system. The proposed algorithm shows better results as compared to previous work

A new reactive power optimization algorithm

This paper presents an algorithm for optimizing reactive power using particle swarm algorithm. A new implementation for the particle swarm algorithm has been applied. The objective function of the proposed algorithm is to minimize the system active power loss. The control variables are generator bus voltages, transformer tap positions and switch-able shunt capacitor banks. The proposed algorithm has been applied to practical IEEE 6-bus system. The proposed algorithm shows better results as compared to previous work

Robust tuning of power system stabilizers in multimachine powersystems

Summary form only given as follows. This paper demonstrates the robust tuning of power systems stabilizers for power systems, operating at different loading conditions. A classical lead-lag power system stabilizer is used to demonstrate the technique. The problem of selecting the stabilizer parameters is converted to a simple optimization problem with an eigenvalue-based objective function, which is solved by a tabu search algorithm. The objective function allows the selection of the stabilizer parameters to optimally place the closed-loop eigenvalues in the left-hand side of a vertical line in the complex s-plane. The effectiveness of the stabilizers tuned using the suggested technique, in enhancing the stability of power systems, is confirmed through eigenvalue analysis and simulation result