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LT codes can be used for adaptive data transmission without feedback, but there exists a high error floor for LT codes in additive white Gaussian noise (AWGN) channels. Therefore, an improved encoding scheme is designed to eliminate the low-degree information nodes which caused the error floor. Firstly, the conventional scheme is used to provide an initial information degree distribution. Then, the threshold is introduced, and the information nodes are classified according to their degrees. The information nodes whose degree is less than the threshold will reconnect check nodes. Finally, all the information nodes will obtain a reliable degree not less than the threshold. Simulation results show that the proposed scheme increases the decoding success probabilities, and thereby the bit error rate (BER) performance is significantly improved. For example, the error floor can be reduced by nearly 4 orders of magnitude when the code length is 256.

Based on the YOLO v3 target detection framework, this paper trains and learns the public remote sensing image aircraft target data, and optimizes the defects of the YOLO v3 loss function, and introduces the IoU (intersection ratio) between the ground-true box and the prediction box, experimental results show that the precision, recall ratio and F1 value of the YOLO v3 model for aircraft target detection in remote sensing images are 95.12%, 86.21% and 0.9045, respectively. Compared with the previous ones, the network precision, recall rate and F1 value of the optimized loss function have been improved by 12.57%, 5.11% and 0.0863 respectively.

In this paper, an improved encoding scheme for LT codes is designed to reduce the error floor. The main idea of the proposed LT code is to classify the information nodes according to their degrees. Then the low-degree information nodes will be forced to frequently connect to check nodes, which enables all information nodes to obtain enough degrees to be restored successfully. Besides, the information degree distribution and convergence behavior of the proposed scheme are analyzed. Simulation results show that the proposed LT code can significantly reduce the error floor, and outperform the other two improved schemes, particularly for short length codes.

When the rocket uses low-orbit satellite space-based measurement and control, due to the relatively large Doppler shift in relative motion, a spread spectrum system is needed to improve anti-interference; the spread spectrum signal under high dynamic conditions often uses partial matched filtering based on FFT (PMF-FFT) algorithm, but due to the introduction of FFT, this algorithm has serious scallop loss, which affects the system’s capture performance. Through the improved method of adding a Hamming window to the system, theoretical analysis and simulation show that it effectively suppresses scallops. Loss has a certain meaning for the acquisition of spread spectrum signals.

While the process of producing ethanol from corn has been well established for over a decade, the process profitability still eludes the industry investors. In particular, uncertainties exist in both the feedstock and the product spot prices. To manage the sophisticated price uncertainty, current practice in industry is to negotiate long-term fixed rate prices with both the suppliers of the feedstock and the purchasers of the product. Although this practice completely eliminates the price uncertainty and simplifies production decisions, it entails the potential loss of profit. Stochastic programming methods provide a framework which takes into account the uncertainties and determines the decisions that are optimal under this uncertain future. Therefore, in this study, a stochastic optimization model is presented to determine the weekly production level and swap hedging portfolios over a year's planning horizon with the objective of maximizing the process profit. The approach is also used in a back-testing perspective to compare the profit obtained from applying the optimal decisions with the negotiated profit derived from using the current practice. This comparison in turn validates the effectiveness of the proposed model framework, in particular during times of high price uncertainty.

While bioethanol has become a promising candidate for replacing fossil based transportation fuels, its economic feasibility still eludes industry investors. In particular, uncertainties exist in both production processes and associated markets. Hence, it is critical to develop process technology and strategize the operation and hedging decisions that improve financial viability. This paper considers long-term production scheduling under the impact of carbon tax constraints and ethanol spot price uncertainty, as well as risk management via ethanol swap contracts. More specifically, a framework consisting of a two-stage stochastic program and a two-factor time series model is presented to determine the weekly production rate and swap portfolios to maximize the process profit under spot price uncertainty.

The development of an environmentally sustainable and financially viable replacement for fossil fuels continues to elude industry investors even though the benefits of replacing them is undisputed. Biofuels are among the promising replacements for fossil fuels. However, the development and production process for bio-based fuels creates uncertainty for industry investors. In order to increase process profitability, financial tools can be implemented with current technology. This paper proposes the use of forward contracts to mitigate risk, and it also considers the impact of carbon tax constraints and price uncertainty. Specifically, a stochastic optimization approach is implemented to develop strategies, which increases the net present value (NPV) of a production facility through determination of an optimal production schedule, as well as the creation of a portfolio of forward contracts to reduce product price risk. Results of numerical case studies show that if the policymaker is risk averse, production is higher in the early planning period rather than the later period. This paper also investigates the ability to maintain inventory in order to create additional financial benefit.