Temperature forecasting is important because they are used to protect life and property. Temperature forecasting i s the application of science and technology to predict the state of the temperature for a future time at a given location. Temperature forecasts are made by collecting quantitative data about the current state of the atmosphere. A neural network can learn complex mappings from inpu...

Recent years have witnessed many exciting achievements for object detection using deep learning techniques. Despite achieving significant progresses, most existing detectors are designed to detect objects with relatively lowquality prediction of locations, i.e., often trained with the threshold of Intersection over Union (IoU) set to 0.5 by default, which can yield low-quality or even noisy det...

Aerodynamic parameter estimation is critical in the aviation sector, especially design and development programs of defense-military aircraft. In this paper, new results application Artificial Neural Networks (ANN) to field aircraft are presented. The performances Feedforward Network (FFNN) with Backpropagation FFNN using Recursive Least Square (RLS) investigated for aerodynamic estimation. meth...

Oil-induced mononuclear phagocytes (MN) were quantitatively assayed for various hydrolases as unfractionated suspensions of frozen and thawed cells. They apparently contain two proteases. The first, measured with urea- or acid-denatured hemoglobin, was similar to purified Proteinase I of lung with respect to pH optimum (pH 4), stability, hydrolytic and polymerizing activities, and reactions to ...

From the Vienna Convention for the Protection of the Ozone Layer (VCPOL) held in 1985 to the joint United Nations Convention of Climate Change held in 2010, environmental protection has become increasingly urgent. In 2011, the International Standards Organization launched a new energy management system ISO50001 for improving energy efficiency. As an adjunct to these increasingly stringent inter...

The objective of this paper is to analysis of main soil properties such as organic matter, essential plant nutrients, micronutrient that affects the growth of crops and find out the suitable relationship percentage among those properties using Supervised Learning, Back Propagation Neural Network. Although these parameters can be measured directly, their measurement is difficult and expensive. B...

Precisely and accurately predict the electricity demand is an important task for the government in each country. In addition, establishing the lowest upper bound for the electricity demand also avoids unnecessary power plant investment. To this end, a hybrid fuzzy linear regression (FLR) and back propagation network (BPN) approach is proposed in this study. In the proposed methodology, multiple...

Neurons in the lateral belt areas of rhesus monkey auditory cortex were stimulated with band-passed noise (BPN) bursts of different bandwidths and center frequencies. Most neurons responded much more vigorously to these sounds than to tone bursts of a single frequency, and it thus became possible to elicit a clear response in 85% of lateral belt neurons. Tuning to center frequency and bandwidth...

A combination of oligonucleotide-directed mutagenesis and chemical modification was used to produce reactive site (P1) variants of chymotrypsin inhibitor II (CI2) in an attempt to create more potent inhibitors and examine inhibitory specificity. Mutagenesis to introduce a unique cysteine (CI2M59C) followed by modification to S-carboxamidocysteine with iodoacetamide produced a 7-fold more potent...