Optimization of spreading vehicle routing for deicing salt play important roles in improving operational efficiency of snow removal, reducing environmental pollution, and reducing road maintenance cost. In this paper, characteristics of different snow highway removal modes in winter and factors to affect vehicle routing decision making for deicing salt spreading are analyzed. Combined with road network structure, capacity constraints, and load balance constraints, vehicle routing model for spreading deicing salt is constructed, which can be solved by a designed genetic algorithm.
The protection of cultural relics has always been an important issue in the field of museums and archaeology. With the development of Internet of Things technology, the security system of the museum is more intelligent and integrated. In order for the museum display system to keep up with the intelligent age, this article mainly studies the research and realization of the museum showcase system based on the Internet of Things technology in a smart environment. Before the start of the experiment, we developed the overall design of the system, including three functional modules: temperature module, illumination module, and monitoring module. The experiment is done mainly for system testing. The performance test of the sensor module needs to sample the temperature and humidity sensor to verify the accuracy of the temperature and humidity signal collected in the instrument circuit. The light information collection test uses the ADC sampling inside the CC2530 to obtain the required data and judges whether these temperature, humidity, and light intensity values exceed the preset values. The serial port needs to be initialized to carry out data communication and transmission normally. After the receiving end finishes receiving, the sending end will clear the data buffer to prepare for the next data transmission. The experimental data show that the error between the predicted value and measured value of the temperature system is about 3°C, which is within the allowable error range of the experiment. The results show that the system has perfect functions, is safe and reliable, meets the expected requirements, and has good practicability.
The aim of this work was to explore the effects of Gamma nail internal fixation for intertrochanteric fracture of femur by X-ray film classification and recognition method based on artificial intelligence algorithm. The study subjects were 100 elderly patients with intertrochanteric fracture of femur admitted to hospital. The cases were diagnosed as elderly (over 60 years old) femoral intertrochanteric fractures by X-ray or CT. They were divided into two groups, with 50 persons in each group: one group used the X-ray film evaluation image guidance based on the artificial intelligence algorithm (research group), and the other group did not use algorithmic guidance (control group). The results showed that the segmentation effect of the proposed algorithm was similar to the gold standard segmentation result, indicating that the algorithm was effective and feasible in the segmentation of fractures and bones. The global level set algorithm was set as the control. The ultimate measurement accuracy (UMA) value of the algorithm group was ( 1.77 ± 0.22 ), and the UMA value of the global level set algorithm group was ( 3.42 ± 0.36 ), indicating that the image processed by the algorithm group had obvious numerical effect, high accuracy, and good retention of details. The operation time, intraoperative blood loss, incision length, hospital stay, weight-bearing time, and fracture healing time of the two groups were all better than those of the control group. One month after surgery, the Harris score of the algorithm group was 67, and that of the control group was 51, with a 16-point difference between the two groups ( p < 0.05 ). The patient had less pain and fast recovery speed, indicating that it was a good way to treat elderly intertrochanteric fractures with the nursing effect of X-ray Gamma nail internal fixation based on an artificial intelligence algorithm. The artificial intelligence algorithm not only can be applied to the Gamma nail internal fixation of elderly patients with intertrochanteric fractures but also can be applied to the X-ray image processing of other fractures and other surgical methods to provide effective treatment for fracture patients.
Aiming at the dense urban road network vulnerability without structural negative consequences, this paper proposes a novel non-structural road network vulnerability analysis framework. Three aspects of the framework are mainly described: (i) the rationality of non-structural road network vulnerability, (ii) the metrics for negative consequences accounting for variant road conditions, and (iii) the introduction of a new vulnerability index based on user exposure. Based on the proposed methodology, a case study in the Sioux Falls network which was usually threatened by regular heavy snow during wintertime is detailedly discussed. The vulnerability ranking of links of Sioux Falls network with respect to heavy snow scenario is identified. As a result of non-structural consequences accompanied by conceivable degeneration of network, there are significant increases in generalized travel time costs which are measurements for “emotionally hurt” of topological road network.
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