RESUMEN
In the new age of illumination, light emitting diodes (LEDs) have been proven to be the most efficient alternative to conventional light sources. Yet, in comparison to other lighting systems, LEDs operate at low temperatures while junction temperature (Tj) is is among the main factors dictating their lifespan, reliability, and performance. This indicates that accurate measurement of LED temperature is of great importance to better understand the thermal effects over a system and improve performance. Over the years, various Tj measurement techniques have been developed, and existing methods have been improved in many ways with technological and scientific advancements. Correspondingly, in order to address the governing phenomena, benefits, drawbacks, possibilities, and applications, a wide range of measurement techniques and systems are covered. This paper comprises a large number of published studies on junction temperature measurement approaches for LEDs, and a summary of the experimental parameters employed in the literature are given as a reference. In addition, some of the corrections noted in non-ideal thermal calibration processes are discussed and presented. Finally, a comparison between methods will provide the readers a better insight into the topic and direction for future research.
RESUMEN
While junction temperature control is an indispensable part of having reliable solid-state lighting, there is no direct method to measure its quantity. Among various methods, temperature-sensitive optical parameter-based junction temperature measurement techniques have been used in practice. Researchers calibrate different spectral power distribution behaviors to a specific temperature and then use that to predict the junction temperature. White light in white LEDs is composed of blue chip emission and down-converted emission from photoluminescent particles, each with its own behavior at different temperatures. These two emissions can be combined in an unlimited number of ways to produce diverse white colors at different brightness levels. The shape of the spectral power distribution can, in essence, be compressed into a correlated color temperature (CCT). The intensity level of the spectral power distribution can be inferred from the luminous flux as it is the special weighted integration of the spectral power distribution. This paper demonstrates that knowing the color characteristics and power level provide enough information for possible regressor trainings to predict any white LED junction temperature. A database from manufacturer datasheets is utilized to develop four machine learning-based models, viz., k-Nearest Neighbor (KNN), Radius Near Neighbors (RNN), Random Forest (RF), and Extreme Gradient Booster (XGB). The models were used to predict the junction temperatures from a set of dynamic opto-thermal measurements. This study shows that machine learning algorithms can be employed as reliable novel prediction tools for junction temperature estimation, particularly where measuring equipment limitations exist, as in wafer-level probing or phosphor-coated chips.
RESUMEN
BACKGROUND: Protein-energy malnutrition (PEM) results from food insufficiency as well as from poor social and economic conditions. Development of PEM is due to insufficient nutrition. Children with PEM lose their resistance to infections because of a disordered immune system. It has been reported that the changes occurring in mediators referred to as cytokines in the immune system may be indicators of the disorders associated with PEM. AIMS: To determine the concentrations of pro-inflammatory cytokines in children with PEM, and to find out whether there was an association with the clinical presentation of PEM. METHODS: The levels of serum total protein, albumin, tumour necrosis factor-alpha, and interleukin-6 were measured in 25 patients with PEM and in 18 healthy children as a control group. PEM was divided into two groups as kwashiorkor and marasmus. The kwashiorkor group consisted of 15 children and the marasmus group consisted of 10 children. RESULTS: Levels of serum total protein and albumin of the kwashiorkor group were significantly lower than both the marasmus group and controls (p < 0.05). In view of tumour necrosis factor-alpha levels, there was no difference between groups (p > 0.05). While levels of interleukin-6 in both the marasmus group and the kwashiorkor group were significantly higher compared with controls (p < 0.05), there was no significant difference between the groups of marasmus and kwashiorkor (p > 0.05). CONCLUSIONS: It was observed that the inflammatory response had increased in children with malnutrition.