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This study aims to propose and evaluate the progress in the basic-pixel (a strategy to generate continuous trajectories that fill out the entire surface) algorithm towards performance gain. The objective is also to investigate the operational efficiency and effectiveness of an enhanced version compared with conventional strategies.

For the first objective, the proposed methodology is to apply the improvements proposed in the basic-pixel strategy, test it on three demonstrative parts and statistically evaluate the performance using the distance trajectory criterion. For the second objective, the enhanced-pixel strategy is compared with conventional strategies in terms of trajectory distance, build time and the number of arcs starts and stops (operational efficiency) and targeting the nominal geometry of a part (operational effectiveness).

The results showed that the improvements proposed to the basic-pixel strategy could generate continuous trajectories with shorter distances and comparable building times (operational efficiency). Regarding operational effectiveness, the parts built by the enhanced-pixel strategy presented lower dimensional deviation than the other strategies studied. Therefore, the enhanced-pixel strategy appears to be a good candidate for building more complex printable parts and delivering operational efficiency and effectiveness.

This paper presents an evolution of the basic-pixel strategy (a space-filling strategy) with the introduction of new elements in the algorithm and proves the improvement of the strategy’s performance with this. An interesting comparison is also presented in terms of operational efficiency and effectiveness between the enhanced-pixel strategy and conventional strategies.

As far as the authors know, no research has already been carried out on the multi-floor dynamic facility layout problem (MF-DFLP) in the continuous form regarding the flexible bay structure, the number and the variable location of the elevator. Therefore, the present paper models the given problem and attempts to find a sub-optimal solution for it using a meta-heuristic simulated annealing (SA) algorithm.

The efficient use of resources has always been a prominent matter for decision-makers. Many reasons including land use, construction considerations and proximity of departments have led to the design of multi-floor facilities. On the other hand, their fast-evolving environment calls for dynamic planning. Therefore, in this paper, a model and the SA algorithm for MF-DFLP are presented.

After presenting a mathematical model, the problem was solved precisely in a small size using the GAMS software. Also, a near-optimal solution method using a SA meta-heuristic algorithm is suggested and the proposed algorithm was run in the MATLAB software. To evaluate the presented model and the proposed solution, some test cases were considered in two aspects. The first aspect was the test cases that are newly generated in small, medium and large sizes to compare the exact optimal solution with the results of the meta-heuristic algorithm. Eight test cases with small sizes were solved using the GAMS software, the optimum solutions were obtained in a reasonable time, and the cost of their solutions was equal to that of the SA algorithm. Eight test cases with medium sizes were run in the GAMS software with the time limit of 80,000 s, and the SA algorithm had performed better for these test cases. Two test cases were also considered in large size that GAMS could not solve them, whereas the SA algorithm successfully found a proper solution for each. The second aspect included the test cases from the literature. The result showed that suggested algorithm is more capable of finding best solutions than compared algorithms.

In this paper, an unequal area MF-DFLP was studied in a continuous layout form in which the location and number of the elevators were considered to be variable, and the layouts were considered with flexible bay structure. These conditions were investigated for the first time.

The rapid development of three-dimensional (3D) printing makes it familiar in daily life, especially the fused deposition modeling 3D printers. The process planning of traditional flat layer printing includes slicing and path planning to obtain the boundaries and the filling paths for each layer along the vertical direction. There is a clear division line through the whole fabricated part, inherited in the flat-layer-based printed parts. This problem is brought about by the seam of the boundary in each layer. Hence, the purpose of this paper is to propose a novel helical filling path generation with the ideal surface-plane intersection for a rotary 3D printer.

The detailed algorithm and implementation steps are given with several worked examples to enable readers to understand it better. The adjacent points obtained from the planar slicing are combined to generate each layer's helical points. The contours of all layers are traversed to obtain the helical surface layer and helical path. Meanwhile, the novel rotary four-degree of freedom 3D printer is briefly introduced.

As a proof of concept, this paper presents several examples based on the rotary 3D printer designed in the authors’ previous research and the algorithms illustrated in this paper. The preliminary experiments successfully verify the feasibility and versatility of the proposed slicing method based on a rotary 3D printer.

This paper provides a novel and feasible slicing method for multi-axis rotary 3D printers, making manufacturing thin-wall and complex parts possible. To further broaden the proposed slicing method’s application in further research, adaptive tool path generation for flat and curved layer printing could be applied with a combination of flat and curved layers in the same layer, different layers or even different parts of structures.

This paper focuses on prospective teachers’ (PTs) participation in a lesson study (LS) that prompted them to research their own practice. We seek to describe the dimensions of PTs’ knowledge of student learning developed during the process and the LS features fostering it.

The participants were two PTs, a teacher educator, a cooperating teacher and a researcher. The LS was integrated into a Portuguese initial elementary teacher education program. Following a qualitative approach, we used participant observation.

The PTs developed their knowledge of students’ learning of the concept of area in four dimensions: theories; students’ interests and expectations; ways students interact with the content and students’ strengths and weaknesses in learning the concept. To support this development, the LS design considered follow-up sessions and emphasised collaborative work.

This study focuses on PTs researching their practice and disseminating the results, which has been overlooked in previous research of LS with PTs. The results highlight the potential of LS to motivate PTs to research their practice and emphasise the importance of involving them in disseminating LS results.

This paper aims to develop a new method of fuselage drag optimization that can obtain results faster than the conventional methods based on full computational fluid dynamics (CFD) calculations and can be used to improve the efficiency of preliminary design.

An efficient method for helicopter fuselage shape optimization based on surrogate-based optimization is presented. Two numerical simulation methods are applied in different stages of optimization according to their relative advantages. The fast panel method is used to calculate the sample data to save calculation time for a large number of sample points. The initial solution is obtained by combining the Kriging surrogate model and the multi-island genetic algorithm. Then, the accuracy of the solution is determined by using the infill criteria based on CFD corrections. A parametric model of the fuselage is established by several characteristic sections and guiding curves.

It is demonstrated that this method can greatly reduce the calculation time while ensuring a high accuracy in the XH-59A helicopter example. The drag coefficient of the optimized fuselage is reduced by 13.3%. Because of the use of different calculation methods for samples, this novel method reduces the total calculation time by almost fourfold compared with full CFD calculations.

To the best of the authors’ knowledge, this is the first study to provide a novel method of fuselage drag optimization by combining different numerical simulation methods. Some suggestions on fuselage shape optimization are given for the XH-59A example.

The purpose of this study is to address the issue that the traditional V-shaped ball valve profile shape is limiting the flow control characteristics in a series structure and to optimize the design profile by proposing an open-hole profile.

This paper proposes a Gaussian process regression surrogate model based on the genetic algorithm optimization of swarm intelligence, combined with the Expected Improvement point addition criterion, to optimize and correct the design profile. The flow regulation performance of the optimized V-shaped regulating ball valve is verified through a combination of numerical simulation and experiment.

The results demonstrate that the optimized V-shaped regulating ball valve has higher flow regulation accuracy and a more stable flow regulation process. After optimization, the flow characteristic curve of the spool is closer to the ideal equal percentage characteristic. The simulation results of the flow field are consistent with the experimental results.

The proposed method significantly reduces the optimization time, has higher efficiency and solves the problem that traditional optimization methods struggle with, which is ensuring optimal flow regulation performance. Compared to the traditional trial-and-error optimization method, the proposed method is more effective. The feasibility of the method is supported by experimental results.

Smart cities are concepts much loved by politicians and technologists but are very difficult to bring about in practice. There are many isolated applications in cities such as operating streetlamps, but very few, if any, examples of integrated applications sharing data and managing the city as a holistic entity rather than a set of disparate and unconnected applications. This is despite hundreds of trials and indicates how difficult bringing about a smart city will be. The key challenge is the wide range of interested parties in a city including the elected city authority, subcontractors and suppliers to the authority, emergency services, transport providers, businesses, residents, workers, tourists, and other visitors. Some of these entities will be primarily driven by finance, such as businesses and transport providers. Some will be driven by political considerations. Some will be concerned with the quality of life as well as financial costs. In some cases, there will be conflicting interests – the city may want as much information as possible on people in the city, whereas individuals may want privacy and the minimum data stored concerning their movements and attributes. COVID-19 does not change any of these issues, but it does increase the importance of some applications such as smart health, logistics, people surveillance, data security, and crisis management, while reducing the importance of others such as traffic management. It may result in more willingness for monitoring and data sharing if this can be shown to result in better control of the virus.

Food markets have gathered a growing attention by tourism researchers and practitioners in recent years. Many destinations have placed food markets as a tourism attraction which allows visitors to discover a territory through its food. Drawing on the understanding of markets as identity and tourism icons, this paper aims to analyze the role of urban food markets in the different stages of the tourist experience from a visitor perspective.

To achieve this, a qualitative design was implemented to interview 18 tourists who visited for the first time the city of Palermo, the capital of the Mediterranean island of Sicily, Italy.

The results of this study show the factors that drive the motivations, the experiences and the satisfaction of visitors to food markets and provide relevant perspectives into the management and marketing of food tourism in urban environments.

The originality of this paper lies on the understanding of the relationships between visitor experiences and urban food markets.

Employees play an essential role in interactive innovation activities in Open Innovation Communities (OICs). Nevertheless, the factors influencing employees' innovation behavior in OICs have not been studied in depth. This study selects personality traits and social network characteristics to explain why and how these two factors affect employees' innovation behavior in OICs.

Three regression models were constructed to test the relationship between personality traits, social network characteristics, and interactive innovation behaviors. The authors examined how employees' personality traits (Big Five personality traits) influence employees' innovative behavior (initiating and supporting innovation) directly in OICs and explored whether social network characteristics (social group) mediate the relationship between employees' personality traits and employees' innovation behavior.

Using empirical data on 162 employees from Salesforce's IdeaExchange, the authors found that extraversion and openness to experience have significant positive effects on employees' interactive innovation behaviors, while conscientiousness has a significant negative effect on employees' interactive innovation behaviors in OICs. Furthermore, the mediation effect test results indicated that social network characteristics have a mediating effect on the relationship between extraversion and innovative behavior, and between openness and innovative behavior.

This study analyzes how personality traits influence innovation behavior in an open innovation environment, thus enriching research related to the factors influencing interactive innovation behavior. Meanwhile, the study integrates personality, social network, and innovative behavior research streams and clearly explains the relationship between the three variables. The research findings assist firms in selecting suitable employees to participate in interactive innovation behaviors in OICs.