In order to study the energy distribution of the tandem hybrid tractor and achieve optimal fuel economy under the whole operating condition, an energy distribution strategy based on PMP (Pontryagin minimum principle) is proposed. The performance parameters of the relevant power components are obtained by constructing the test bench of the tandem hybrid tractor. At the same time, the mathematical model of energy distribution is established from the aspects of energy distribution objective function, state variable, and variable constraint. Based on the external characteristic test of the hub motor and the resistance analysis, the transport operation condition of the tractor is selected as the simulation target condition. The ADVISOR2002 and Simulink software are used to jointly simulate the three energy distribution strategies: the thermostat type, the power-following type, and the PMP type. The simulation results show that, compared with the other two, the fuel economy and battery power loss of the PMP-based energy distribution strategy are significantly improved. The fuel consumption per 100 km is decreased by 32.91% and 26.10%, respectively, which verifies the feasibility of the strategy. This study is of great significance for improving the production efficiency and reducing fuel consumption of hybrid tractors.

Binary-only bug search has already drawn a lot attentions recently, due to the increasing growth of security breaches. Most of existing work focuses on searching by checking the similarity of code snippets. It is further required to check whether the function is patched or not. Unfortunately, this is still a manual effort for all existing code search based approaches. In this paper, we propose a novel approach for automatic patch detection. we build a patch detector by learning the feature representation from the patched code in the binary format. We utilize the feature encoding technique to make the binary code trainable, and build our neural network model to learn the patch feature for increasing detection accuracy. We have implemented a prototype called PATCHDETECTOR, and systematically evaluated its performance in terms of the accuracy and efficiency by using 1,600 OpenSSL binaries of 216,000 functions. Experimental results have shown that PATCHDETECTOR can effectively detect whether the target binary function is patched or not with the detection accuracy of 92% on average.

Accurate characterization of real-world operating behaviours of high-horsepower agricultural tractors is a fundamental challenge for subsequent modelling, analysis, and system design. The highly variable and multi-modal nature of field-road operations makes it difficult to construct operating cycles that faithfully represent measured dynamics while preserving statistical distributions and temporal correlation characteristics. This study proposes a data-driven framework for constructing representative operating cycles of high-horsepower tractors based on extensive field-road measurements. The framework integrates K -means clustering guided by multiple clustering validity indices, including the Davies–Bouldin index and Silhouette coefficient, with vehicle specific power per unit mileage as a physically informed descriptor. A reduced-dimensional feature space is established to characterize measured tractor dynamics, enabling the extraction of representative kinematic fragments from complex operational datasets. These fragments are then synthesized into a unified operating cycle that preserves the intrinsic statistical structure of the measured data. The representativeness of the constructed cycle is quantitatively evaluated using both characteristic parameter deviation and autocorrelation function (ACF) analysis. The average deviation of key kinematic features is 5.28%, while the root mean square error between the measured and synthesized ACF curves is only 0.0312, indicating strong consistency in both statistical distribution and temporal continuity. To further assess practical applicability, Cruise-based energy consumption simulations are conducted under three distinct load conditions. The predicted fuel consumption differs from experimental measurements by less than 10%, confirming that the synthesized cycle effectively reproduces real operating behaviour within acceptable measurement uncertainty. The proposed framework provides a systematic approach for measurement-based representation and validation of operating profiles of high-horsepower agricultural machinery, supporting further developments in modelling, evaluation, and control of agricultural vehicle systems.