Christian del Carpio

Anemia is a common problem that affects a significant part of the world’s population, especially in impoverished countries. This work aims to improve the accessibility of remote diagnostic tools for underserved populations. Our proposal involves implementing algorithms to estimate hemoglobin levels using images of the eyelid conjunctiva and a calibration label captured with a mid-range cell phone. We propose three algorithms: one for calibration label segmentation, another for palpebral conjunctiva segmentation, and the last one for estimating hemoglobin levels based on the segmented images from the previous algorithms. Experiments were performed using a data set of children’s eyelid images and calibration stickers. An L1 norm error of 0.72 g/dL was achieved using the SLIC-GAT model to estimate the hemoglobin level. In conclusion, the integration of these segmentation and regression methods improved the estimation accuracy compared to current approaches, considering that the source of the images was a mid-range commercial camera. The proposed method has the potential for mass screening in low-income rural populations as it is non-invasive, and its simplicity makes it feasible for community health workers with basic training to perform the test. Therefore, this tool could contribute significantly to efforts aimed at combating childhood anemia.

The high competitiveness and variability of demand in the commercial sector has led companies to efficiently manage their inventory management to optimize their warehouse stocks. The main problem that occurs most frequently in the sector is the excess inventory in its main warehouse. This is due to inadequate inventory management that allows a balance in the level of inventory without neglecting the estimated demand. Because of this, we propose an inventory management model and design a simulation system to evaluate the viability of this. From the results obtained, it is concluded that the proposed inventory management model will reduce inventory costs by 30.66%, avoiding excess inventories and optimizing costs.

Small craft beer producers do not have the adequate equipment nor the precise process control for malt maceration, which is a fundamental step in beer fabrication. In this stage, different temperature levels are used to degrade the malt starch into simpler sugars; thus, it is necessary to have structurally functional containers (durable materials). Moreover, since temperature regulation is critical because it regulates the activity of the enzymes that generate fermentable sugars (alpha amilases), it is necessary for the temperature monitoring to be automatic and not manual, to avoid inhibition of their activity. Thus, an automatic equipment for craft beer maceration is proposed. Testing was done in a stainless-steel cylindrical tank with a 45 L net production. Operation temperature is 65°C, which is the temperature at which alpha amilases activate. The method consisted of the structural design of the tank and the implementation of a temperature controller in a Programmable Logic Controller (PLC) S7-1200. The equipment efficiency after maceration was over 65