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81.
The conventional autonomous cruise and tracking system cannot transition and change its motion mode according to the underwater environment during operation, so it is of great significance to study the multi-mode switching of cruise control for Autonomous Underwater Vehicles (AUVs). In this paper, a Multi-Mode Adaptive Switching (MMAS) strategy for the Spherical Underwater Robot with Hybrid Thruster (HPSUR) was proposed, which provided the possibility for the robot to choose optimal control mode according to the unpredictable operating environment. Then, the dynamic and force of the hybrid thruster are analyzed to improve the accuracy of multi-mode switching, and the MMAS strategy is developed linking the attitude adjustment and switching problems. Furthermore, a series of multi-mode switching experiments were conducted using water-jet mode, propeller mode and hybrid mode. Finally, the experimental result was discussed, which verified the effectiveness and accuracy of the proposed MMAS strategy. The proposed control strategy has a certain reference value for the multi-mode switching of propulsion devices. 相似文献
82.
Water-rail intermodal transportation can reduce cargo losses and transportation transferring costs. However, the imbalance between the capacity of the scheduled railway network and the large container freight demand greatly reduces operational efficiency. To minimize the total transportation cost and relocation cost, a railcar reallocation stochastic optimization model is formulated to deal with uncertain congestion in the railway network. To capture the uncertain busyness and queuing pattern, a hypercube spatial queue model is embedded in the optimization model by estimating the expected queue length and waiting time. To solve the proposed nonlinear nonconcave stochastic model, an approximate hypercube based iterative algorithm is proposed. A real-world case study is presented to show the effectiveness and efficiency of the proposed method. The proposed model outperforms the comparable deterministic model in the objective value. Sensitivity analyses on the ratio of the unit waiting cost and the unit travel cost for empty cars, and the total number of freight cars show the robustness of the proposed method. 相似文献
83.
Virtual Reality (VR)-based training has gained attention from the scientific community in the Architecture, Engineering, and Construction (AEC) industry as a cost-effective and safe method that eliminates the safety risks that may impose on workers during the training compared to traditional training methods (e.g., in-person hands-on training, apprenticeship). Although researchers have developed VR-based training for construction workers, some have recruited students rather than workers to understand the effect of their VR-based training. However, students are different from construction workers in many ways, which can threaten the validity of such studies. Hence, research is needed to investigate the extent to which the findings of a VR-based training study are contingent on whether students or construction workers were used as the study sample. This paper strives to compare the effectiveness of VR-based training on university students’ and construction workers’ knowledge acquisition, trust in the robot, and robot operation self-efficacy in remote operation of a construction robot. Twenty-five construction workers and twenty-five graduate construction engineering students were recruited to complete a VR-based training for remote operating a demolition robot. We used quantitative analyses to answer our research questions. Our study shows that the results are dependent on the target sample in that students gained more knowledge, whereas construction workers gained more trust in the robot and more self-efficacy in robot operation. These findings suggest that the effectiveness of VR-based training on students may not necessarily associate with its effectiveness on construction workers. 相似文献
84.
Earthwork operations are crucial parts of most construction projects. Heavy construction equipment and workers are often required to work in limited workspaces simultaneously. Struck-by accidents resulting from poor worker and equipment interactions account for a large proportion of accidents and fatalities on construction sites. The emerging technologies based on computer vision and artificial intelligence offer an opportunity to enhance construction safety through advanced monitoring utilizing site cameras. A crucial pre-requisite to the development of safety monitoring applications is the ability to identify accurately and localize the position of the equipment and its critical components in 3D space. This study proposes a workflow for excavator 3D pose estimation based on deep learning using RGB images. In the proposed workflow, an articulated 3D digital twin of an excavator is used to generate the necessary data for training a 3D pose estimation model. In addition, a method for generating hybrid datasets (simulation and laboratory) for adapting the 3D pose estimation model for various scenarios with different camera parameters is proposed. Evaluations prove the capability of the workflow in estimating the 3D pose of excavators. The study concludes by discussing the limitations and future research opportunities. 相似文献
85.
86.
The maintainability of source code is a key quality characteristic for software quality. Many approaches have been proposed to quantitatively measure code maintainability. Such approaches rely heavily on code metrics, e.g., the number of Lines of Code and McCabe’s Cyclomatic Complexity. The employed code metrics are essentially statistics regarding code elements, e.g., the numbers of tokens, lines, references, and branch statements. However, natural language in source code, especially identifiers, is rarely exploited by such approaches. As a result, replacing meaningful identifiers with nonsense tokens would not significantly influence their outputs, although the replacement should have significantly reduced code maintainability. To this end, in this paper, we propose a novel approach (called DeepM) to measure code maintainability by exploiting the lexical semantics of text in source code. DeepM leverages deep learning techniques (e.g., LSTM and attention mechanism) to exploit these lexical semantics in measuring code maintainability. Another key rationale of DeepM is that measuring code maintainability is complex and often far beyond the capabilities of statistics or simple heuristics. Consequently, DeepM leverages deep learning techniques to automatically select useful features from complex and lengthy inputs and to construct a complex mapping (rather than simple heuristics) from the input to the output (code maintainability index). DeepM is evaluated on a manually-assessed dataset. The evaluation results suggest that DeepM is accurate, and it generates the same rankings of code maintainability as those of experienced programmers on 87.5% of manually ranked pairs of Java classes. 相似文献
87.
随着大规模定制的市场需求日趋显著,赛如生产系统(Seru production system,SPS)应运而生,逐渐成为研究和应用领域的热点.本文针对带有资源冲突的Seru在线并行调度问题进行研究,即需要在有限的空间位置上安排随动态需求而构建的若干Seru,以总加权完工时间最小为目标,决策Seru的构建顺序及时间.先基于平均延迟最短加权处理时间(Average delayed shortest weighted processing time,AD-SWPT)算法,针对其竞争比不为常数的局限性,引入调节参数,得到竞争比为常数的无资源冲突的Seru在线并行调度算法.接下来,引入冲突处理机制,得到有资源冲突的Seru在线并行调度算法,αAD-I(α-average delayed shortest weighted processing time-improved)算法,特殊实例下可通过实例归约的方法证明其竞争比与无资源冲突的情况相同.最后,通过实验,验证了在波动的市场环境下算法对于特殊实例与一般实例的优越性. 相似文献
88.
《Information & Management》2022,59(3):103626
With the popularity of social media, extracting consumer preferences from online consumer-generated content is of vital importance for product/service providers to develop tailored marketing strategies. However, existing approaches face difficulties analyzing consumer preferences over different attributes of alternatives (restaurants, hotels, etc.), which hinders product/service providers from comprehensively understanding consumer choice decisions. To address this issue, we solve for the consumer preferences over the attributes represented by attribute weights based on consumers’ historical data, including text comments and overall ratings. Specifically, for each comment and a corresponding rating, we first employ sentiment analysis to calculate values of the attributes, and then develop a quadratic programming model to solve for the weights. Based on a stream of a consumer’s text comments and overall ratings, we can correspondingly obtain a stream of weights indexed by the comment time. We then model this stream of weights as hesitant judgments and employ a hesitant multiplicative programming method to solve for the final weights that fit the consumer’s preferences over attributes at the highest satisficing level. In the application of recommendation, our approach not only provides insights into the consumer’s preferences but also has higher prediction power compared with some state-of-the-art methods. 相似文献
89.
Fenfen Xiong Wei Chen Ying Xiong Shuxing Yang 《Structural and Multidisciplinary Optimization》2011,43(6):837-849
Conventional stochastic response surface methods (SRSM) based on polynomial chaos expansion (PCE) for uncertainty propagation
treat every sample point equally during the regression process and may produce inaccurate estimations of PCE coefficients.
To address this issue, a new weighted stochastic response surface method (WSRSM) that considers the sample probabilistic weights
in regression is studied in this work. Techniques for determining sample probabilistic weights for three sampling approaches
Gaussian Quadrature point (GQ), Monomial Cubature Rule (MCR), and Latin Hypercube Design (LHD) are developed. The advantage
of the proposed method is demonstrated through mathematical and engineering examples. It is shown that for various sampling
techniques WSRSM consistently achieves higher accuracy of uncertainty propagation without introducing extra computational
cost compared to the conventional SRSM. Insights into the relative accuracy and efficiency of various sampling techniques
in implementation are provided as well. 相似文献
90.