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Hydrodynamic parameter estimation is significant for the velocity prediction of unmanned surface vehicles. Considering the field data’s uncertain nonlinearities (environmental disturbances and measurement noise), this paper aims to propose a hybrid adaptive parameter estimation (HAPE) strategy.

First, a rough estimation of hydrodynamic parameters is used by the least squares method. Second, an improved adaptive parameter estimation algorithm is applied to compensate for the influence of uncertain nonlinearities and adjust the parameters within the rough range. Finally, it is proved that the calculated velocity asymptotically converges to the actual value during the parameter estimation procedure.

The numerical simulation and pool experiments are conducted in two scenarios of steady turning and sinusoidal thrust to verify the effectiveness of the proposed HAPE method. The results validate that the accuracy of the predicted velocity using the hydrodynamic model obtained by the HAPE strategy is better than the APE algorithm. In addition, the hydrodynamic parameters estimated with the sinusoidal thrust data are more applicable than the steady turning data.

This study proposes a HAPE strategy that considers the uncertain nonlinearities of the field data. This method provides a more accurate predicted velocity. Besides, as far as we know, it is the first time to analyze the influence of different test conditions on the accuracy of the predicted velocity.

The disinfection robot developed by the authors and team focuses on achieving fast and precise disinfection under a given or specific disinfection zone. This looks to solve problems with traditional robots that pay less attention to the level, efficiency and zones of disinfection. To effectively support and guarantee normal running for the whole system, a digital twin system is applied to the disinfection robot. This study aims to achieve fast, precise and thorough disinfection via the developed mobile robot.

The designed robot is composed primarily of the following three parts: a mobile platform, a six-axis robotic arm and a ultraviolet-C (UVC) LED array. The UVC LED array is installed on the end-effector to achieve large-scale, precise manipulation. The adoption of all types of advanced sensors and the development of an intuitive and user-friendly client interface are helpful in achieving remote control, path planning, data monitoring and custom disinfection functions.

Disinfection of three different locations in the laboratory was performed; the dosage distribution of the surface as radiated by the UVC robot was detected; and feasibility of development was validated.

The developed disinfection robot achieved fast, precise and thorough disinfection for a given or specific disinfection zone.

Broiler meat is the most commonly used meat product worldwide. Although China is regarded as one of the three largest broiler producers, the per capita chicken consumption remains low. Consumers' cognitive bias and the information acquisition channels are believed to be the main factors contributing to this. This paper aims to discuss the aforementioned issue.

To explore the phenomenon empirically, the current study uses the survey data of 1,056 consumers from China and analyses them using ordered logistic regression.

The results revealed that consumers' cognitive bias significantly affects their behaviour toward broiler products, and the order of influence is cognitive bias regarding industry cognitive > product nutrition and taste > food safety. The study further revealed that the more diverse the information acquisition channels, the more likely they are to promote consumer behaviour toward broiler chickens. The order of influence of the channels was self-organising > new media > traditional media.

Overall, the findings suggest that the government and enterprises should strengthen and upgrade information channels to boost both the broiler industry and consumer consumption behaviour regarding poultry products.

Rather than the usual focus on the impact of consumer cognition on consumer behaviour, this study examines the impact of cognitive bias on consumer behaviour. Further, centring on broiler products with high protein, low fat and feed-to-meat ratios, this study explores the reasons the per capita consumption of broiler products in China is far lower than the national average.

The purpose of this paper is to investigate how a second-phase doping may affect Al₂O₃ ceramic parts deposited by additive manufacturing (AM) with a laser-engineered net shaping system. Direct fabrication of engineering ceramic components by AM is a relatively new method for producing complex mechanical structures.

In this study, ZrO₂ and Y₂O₃ powders are, respectively, doped into Al₂O₃ powders at the eutectic ratio as second phases to improve the quality of a deposited part. The deposited Al₂O₃, Al₂O₃/ZrO₂ and Al₂O₃/YAG (yttrium aluminum garnet) parts are examined for their micro-structures and micro-hardness, as well as defects.

The experimental results show that doping of ZrO₂ or Y₂O₃ as a second phase performs a significant role in suppressing cracks and in refining grains of the laser-deposited parts. The micro-hardness investigation reveals that the second-phase doping does not result in much hardness reduction in Al₂O₃ and the two eutectic ceramics are both harder than 1,500 Hv.

The study concludes that the second-phase doping of ZrO₂ and Y₂O₃ is good for improving laser-deposited Al₂O₃ ceramic parts.

The purpose of this paper is to provide scientific guidance for the integration of industrialization and information (TIOII). In recent years, TIOII has promoted the development of intelligent manufacturing in China. However, many enterprises blindly invest in TIOII, which affects their normal production and operation.

This study establishes an efficiency evaluation model for TIOII. In this paper, entropy analytic hierarchy process (AHP) constraint cone and cross-efficiency are added based on traditional data envelopment analysis (DEA) model, and entropy AHP–cross-efficiency DEA model is proposed. Then, statistical analysis is carried out on the integration efficiency of enterprises in Guangzhou using cross-sectional data, and the traditional DEA model and entropy AHP–cross-efficiency DEA model are used to analyze the integration efficiency of enterprises.

The data show that the efficiency of enterprise integration is at a medium level in Guangzhou. The efficiency of enterprise integration has no significant relationship with enterprise size and production type but has a low negative correlation with the development level of enterprise integration. In addition, the improved DEA model can better reflect the real integration efficiency of enterprises and obtain complete ranking results.

By adding the entropy AHP constraint cone and cross-efficiency, the traditional DEA model is improved. The improved DEA model can better reflect the real efficiency of TIOII and obtain complete ranking results.

The modeling and optimization of a weld bead in the middle of the weld are often simple, as the forming process is dynamically balanced. However, the arc striking (AS) and arc extinguishing (AE) areas of weld beads are generally abnormal because the dynamic processes at these areas are unstable. The purpose of this paper is to investigate the abnormal areas of the weld bead with optimization modeling methods in wire and arc additive manufacturing (WAAM).

A burning-back method was proposed to fill the slanted plane in the AE area. To optimize the welding parameters and obtain the optimal design, a response surface methodology was proposed to build the relationships between the input parameters and response variables.

The proposed burning-back method could fill the slanted plane in the AE area. Second-order models of abnormal areas were developed and the optimization effects were analyzed. The experimental results indicated that the relationship models at both ends were applicable and preferable for the optimization of weld beads.

In this paper, a burning-back method was proposed to optimize the slanted plane in the AE area. Second-order models of abnormal areas were established. The methods and models were preferable in the optimization of the abnormal areas in WAAM.

The purpose of this paper is to investigate the dynamic responses of a spur gear pair with unloaded static transmission error (STE) excitation numerically and experimentally and the influences of the system factors including mesh stiffness, error excitation and torque on the dynamic transmission error (DTE).

A simple lumped parameters dynamic model of a gear pair considering time-varying mesh stiffness, backlash and unloaded STE excitation is developed. The STE is calculated from the measured tooth profile deviation under the unloaded condition. A four-square gear test rig is designed to measure and analyze the DTE and vibration responses of the gear pair. The dynamic responses of the gear transmission are studied numerically and experimentally.

The predicted numerical DTE matches well with the experimental results. When the real unloaded STE excitation without any approximation is used, the dynamic response is dominated by the mesh frequency and its high order harmonic components, which may not be result caused by the assembling error. The sub-harmonic and super-harmonic resonant behaviors are excited because of the high order harmonic components of STE. It will not certainly prevent the separations of mesh teeth when the gear pair is under the condition of high speed and heavy load.

This study helps to improve the modeling method of the dynamic analysis of spur gear transmission and provide some reference for the understanding of the influence of mesh stiffness, STE excitation and system torque on the vibration behaviors.

This paper aims to analyze and provide insight on the algorithms for the optimization of construction site layout planning (CSLP). It resolves problems, such as the selection of suitable algorithms, considering the optimality, optimization objectives and representation of layout solutions. The approaches for the better utilization of optimization algorithms are also presented.

To achieve the above, existing records (results = 200) were selected from three databases: Web of Science, ScienceDirect and Scopus. By implementing a systematic protocol, the articles related to the optimization algorithms for the CLSP (results = 75) were identified. Moreover, various related themes were collated and analyzed according to a coding structure.

The results indicate the consistent and increasing interest on the optimization algorithms for the CLSP, revealing that the trend in shifting to smart approaches in the construction industry is significant. Moreover, the interest in metaheuristic algorithms is dominant because 65.3% of the selected articles focus on these algorithms. The optimality, optimization objectives and solution representations are also important in algorithm selection. With the employment of other algorithms, self-developed applications and commercial software, optimization algorithms can be better utilized for solving CSLP problems. The findings also identify the gaps and directions for future research.

The selection of articles in this review does not consider the industrial perspective and practical applications of commercial software. Further comparative analyses of major algorithms are necessary because this review only focuses on algorithm types.

This paper presents a comprehensive systematic review of articles published in the recent decade. It significantly contributes to the demonstration of the status and selection of CLSP algorithms and the benefit of using these algorithms. It also identifies the research gaps in knowledge and reveals potential improvements for future research.

This study aims to investigate the impact of cross-functional coordination (cross-functional system, process and team coordination) on customer coordination (customer strategic and operational coordination) and operational performance. Following the lens of information processing theory (IPT), this study examines the diverse mechanisms of cross-functional coordination practices in enhancing firms’ information processing capabilities (IPCs) to cope with the higher information processing demands resulting from customer coordination, finally improving operational performance.

Based on data collected from 410 Chinese manufacturers, the authors use the structural equation modeling method to test the theoretical model.

The authors found that cross-functional system coordination is positively associated with customer operational coordination (COC) but not customer strategic coordination (CSC). Cross-functional process coordination increases both customer strategic and operational coordination. Cross-functional team coordination significantly promotes CSC but not COC. Both customer operational and strategic coordination facilitate operational performance.

This research pioneers in identifying three dimensions of cross-functional coordination based on IPT and examine their distinct impacts on various customer coordination activities. The authors distinguish two customer coordination dimensions and reveal their effects on operational performance. This research contributes to the development of IPT. Additionally, this study provides guidelines for managers to coordinate internal departments and collaborate with external customers to enhance firms’ operational performance.

The use of aviation incident data to carry out aviation risk prediction is of great significance for improving the initiative of accident prevention and reducing the occurrence of accidents. Because of the nonlinearity and periodicity of incident data, it is challenging to achieve accurate predictions. Therefore, this paper aims to provide a new method for aviation risk prediction with high accuracy.

This paper proposes a hybrid prediction model incorporating Prophet and long short-term memory (LSTM) network. The flight incident data are decomposed using Prophet to extract the feature components. Taking the decomposed time series as input, LSTM is employed for prediction and its output is used as the final prediction result.

The data of Chinese civil aviation incidents from 2002 to 2021 are used for validation, and Prophet, LSTM and two other typical prediction models are selected for comparison. The experimental results demonstrate that the Prophet–LSTM model is more stable, with higher prediction accuracy and better applicability.

This study can provide a new idea for aviation risk prediction and a scientific basis for aviation safety management.

The innovation of this work comes from combining Prophet and LSTM to capture the periodic features and temporal dependencies of incidents, effectively improving prediction accuracy.