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Ultrasonic image reconstruction using inverse problems has recently appeared as an alternative to enhance ultrasound imaging over beamforming methods. This approach depends on the accuracy of the acquisition model used to represent transducers, reflectivity, and medium physics. Iterative methods, well known in general sparse signal reconstruction, are also suited for imaging. In this paper, a discrete acquisition model is assessed by solving a linear system of equations by an ℓ1-regularized least-squares minimization, where the solution sparsity may be adjusted as desired. The paper surveys 11 variants of four well-known algorithms for sparse reconstruction, and assesses their optimization parameters with the goal of finding the best approach for iterative ultrasound imaging. The strategy for the model evaluation consists of using two distinct datasets. We first generate data from a synthetic phantom that mimics real targets inside a professional ultrasound phantom device. This dataset is contaminated with Gaussian noise with an estimated SNR, and all methods are assessed by their resulting images and performances. The model and methods are then assessed with real data collected by a research ultrasound platform when scanning the same phantom device, and results are compared with beamforming. A distinct real dataset is finally used to further validate the proposed modeling. Although high computational effort is required by iterative methods, results show that the discrete model may lead to images closer to ground-truth than traditional beamforming. However, computing capabilities of current platforms need to evolve before frame rates currently delivered by ultrasound equipments are achievable.

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Pressure injuries (LPP) are one of the biggest adverse events foundin health services and consist of damage to the body tissues ofbedridden patients, resulting from prolonged pressure on the skin.This situation impacts on the quality of life of people who developthe condition, causing physical and emotional damage to the bedridden,in addition to increasing the time and costs of hospitalization.Based on this problem, software was developed that shows thepoints of greatest pressure between the body of a bedridden patientand the bed in which he is. This software receives information fromhardware, under development, built specifically for this project.The points of greatest pressure are made available on the screenof a monitoring application, in an organized and intuitive manner.For each person, a pressure map image is generated with the valuesread and decubitus change times are suggested through alarms. Inaddition, this image can be analyzed by a health professional whocan take steps to relieve pressure points and prevent the appearanceof LPP. As a result, in tests carried out during the research, the systembuilt showed the information successfully and the objectiveswere achieved.

The current reality of the energy market requires generation, control, distribution and consumption to become more efficient. Recent arrangements with electric energy stored in accumulators appear as strategic tools in the environment where the cost of energy supplied by the concessionaires and permission holders has accumulated successive increases, indirectly enabling the control and management of applications of micro or local minigeneration, from renewable sources in general. Systems with energy storage (e.g. batteries) and local demand management (many consumer units) achieve great efficiency by allowing the optimized consumption of the available energy, both by the local power grid and by the accumulated grid. Other advantages are presented for the distributors, allowing the relief of the electricity network, remunerating the investment in reduced intervals of time. Consideration should be given to the possibility of local autonomy, even if partially, by providing energy from the storage to the local loads in eventual failures in the supply of energy by the distribution network or at times where supply has a higher cost.