Effect of heat‐moisture treatment of proso millet flour on the quality of gluten‐free cake was investigated. Millet flour was treated with two different moisture contents (20% and 30%) at two temperatures (100C and 120C), and then different amounts (0–100%) of treated flours were used in cake formulation. The physicochemical and sensory properties of batters and cakes containing treated flours were studied. Results showed that using of heat‐moisture treated flour decreased specific gravity and increased consistency of batter. Incorporation of treated flour in cake formulation resulted in increased volume and subsequently decreased hardness of cake samples. However, utilization of heat‐moisture treated flour prepared at 30% moisture and 120C impaired the quality of cake. The cake sample containing 100% of this flour, was evaluated as unacceptable by panelists. However, utilization of 75% flour treated at 30% moisture and 100C could improve volume, color and texture of millet cakes without destroying of sensory acceptance.
Practical Applications
Development of gluten‐free bakery products has a growing market worldwide. Then food scientists are trying to improve the quality of these products. Results of the present study revealed the capability of heat‐moisture treatment to modify underused cereal (such as millet) flours for utilization in formulations of gluten‐free goods, improving their nutritional value and quality characteristics. The results of this study could be useful and applicable for the bakery industry.
A-priori individual interconnect length estimates can be used to make placement efficient and reduce delay and power consumption in a circuit. However, finding lengths of individual interconnects before their terminals have been placed can be a daunting task. In this thesis, the main characteristics that need to be considered while designing an individual a-priori length estimation technique for today's integrated circuits are discussed. Then, a technique for estimating individual interconnect lengths for mixed-size circuits based on Radial Basis Functions (RBFs) is proposed. The advantage of using RBFs, is that the given data do not need to be fitted into a pre-defined model such as a polynomial. In this thesis, a method is proposed to calculate a suitable variance parameter of the RBFs. An application of the length estimator is proposed where a predictor-corrector framework for clustering that can be used to improve the results of placement is implemented.
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