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Obstacle and wind field are common environmental factors for mini unmanned helicopter (MUH) flight. This paper aims to develop a trajectory planning approach guiding MUH to avoid static and dynamic obstacles and to fly in steady uniform or boundary-layer wind field.

An optimal control model including a nonlinear flight dynamics model and a cubic obstacle model is established for MUH trajectory planning. Radau pseudospectral method is used to generate the optimal trajectory.

The approach can plan reasonable obstacle-avoiding trajectories in obstacle and windy environments. The simulation results show that high-speed wind fields increase the flight time and fluctuation of control inputs. If boundary-layer wind field exists, the trajectory deforms significantly and gets closer to the ground to escape from the strong wind.

The key innovations in this paper include a cubic obstacle model which is straightforward and practical for trajectory planning and MUH trajectory planning in steady uniform wind field and boundary-layer wind field. This study provides an efficient solution to the trajectory planning for MUH in obstacle and windy environments.

The control of weld penetration in gas tungsten arc welding (GTAW) is required for a “teach and playback” robot to overcome the gap variation in the welding process. This paper aims to investigate this subject.

This paper presents a robotic system based on the real‐time vision measurement. The primary objective has been to demonstrate the feasibility of using vision‐based image processing to measure the seam gap in real‐time and adjust welding current and wire‐feed rate to realize the penetration control during the robot‐welding process.

The paper finds that vision‐based measurement of the seam gap can be used in the welding robot, in real‐time, to control weld penetration. It helps the “teach and playback” robot to adjust the welding procedures according to the gap variation.

The system requires that the seam edges can be accurately identified using a correlation method.

The system is applicable to storage tank welding of a rocket.

The control algorithm based on the knowledge base has been set up for continuous GTAW. A novel visual image analysis method has been developed in the study for a welding robot.

The purpose of this study is to develop a model to understand the relationships among technology, organizational and environmental (TOE) contexts, intention to adopt cloud computing (IACC) and actual usage of cloud computing (AUCC) in small and medium enterprises (SMEs) in Malaysia as a developing country. More specifically, this paper seeks to explore the mediation effect of IACC on the relationship between TOE context and AUCC.

A positivist research approach was selected for this study. Drawing largely upon the TOE framework, this study uses survey data from 209 Malaysian SMEs. Structural equation modelling (SEM) based on partial least squares (PLS) was used to assess the structural relations of the research model.

The results of the structural model show that data security, technology readiness, top management support, competitive pressure and innovativeness are the most significant factors in predicting the adoption of cloud computing in Malaysian SMEs. Further, the results indicate that intention to adopt cloud computing can play a mediating role between TOE factors and the actual usage of cloud computing.

The focus upon Malaysian SMEs may diminish the generalizability of the findings. This study provides profound insight into the management and foundation of cloud computing, different types of cloud services and deployment models that could facilitate the management of enterprise strategic resources and contribute to the performance improvement. This study also provides another important implication for practitioners regarding the absolute necessity of value drivers’ identification within enterprise and understand the causal relationships, which are vital in driving those values.

This study provides several practical guidance for practitioners in deploying cloud services which are most suitable option for their specific technology requirement in their enterprise to enjoy the full benefits of their intangible assets. Another significant implication of this study lies in the fact that it may require a different emphasis on nature and adoption design when there is a higher level of stress on technology-related and cloud computing resources.

This study contributes to the extant literature by developing an integrative model to identify how a wide set of contextual factors can determine the intention to adopt cloud computing and, in turn, influence the actual usage of cloud computing in SMEs in Malaysia as a developing country.

Since 2007, the cloud computing term had been introduced to the information technology (IT) dictionary. The theme is attracting growing interest from both the IT world and the business players, who need to enhance information systems agility, reduced costs, or even less dependence on internal IT teams when they are judged too slow. However, the fact that cloud computing, as presented by providers, increases the agility, is unclear. Business Managers; IT professional, and academics are querying about relationship between cloud computing and IT agility. This chapter aims to answer two major concerns: Factors that influence cloud computing adoption in medium and large organizations, and the cloud computing role to improve the agility of information systems. This chapter argues that cloud computing impacts Information System (IS) performance by organizational capabilities (agility). One of the primary motivations of this chapter is the lack of fieldwork when considering how cloud computing improves the information systems’ agility.

Big data has posed problems for businesses, the Information Technology (IT) sector and the science community. The problems posed by big data can be effectively addressed using cloud computing and associated distributed computing technology. Cloud computing and big data are two significant past-year problems that allow high-efficiency and competitive computing tools to be delivered as IT services. The paper aims to examine the role of the cloud as a tool for managing big data in various aspects to help businesses.

This paper delivers solutions in the cloud for storing, compressing, analyzing and processing big data. Hence, articles were divided into four categories: articles on big data storage, articles on big data processing, articles on analyzing and finally, articles on data compression in cloud computing. This article is based on a systematic literature review. Also, it is based on a review of 19 published papers on big data.

From the results, it can be inferred that cloud computing technology has features that can be useful for big data management. Challenging issues are raised in each section. For example, in storing big data, privacy and security issues are challenging.

There were limitations to this systematic review. The first limitation is that only English articles were reviewed. Also, articles that matched the keywords were used. Finally, in this review, authoritative articles were reviewed, and slides and tutorials were avoided.

The research presents new insight into the business value of cloud computing in interfirm collaborations.

Previous research has often examined other aspects of big data in the cloud. This article takes a new approach to the subject. It allows big data researchers to comprehend the various aspects of big data management in the cloud. In addition, setting an agenda for future research saves time and effort for readers searching for topics within big data.

Since surface runoff clogs stormwater grates, leading to deterioration of drainage capacity, and also it is difficult to complete the study with actual dimensions in experiments, a numerical simulation work was established in this study to investigate the surface runoff clogging stormwater grate patterns. The purpose of this study is to describe the mechanisms of storm grate clogging and storm well deposition for different flow rate floods and granular materials.

In the work of this study, the volume of fluid (VOF) method and the discrete element method (DEM) are used to solve the gas–liquid and particle flows. In order to solve the evolution of the gas–liquid interface during surface runoff, the VOF was used. To simulate the rain grate and set up different material particles to represent the surface floating materials, the DEM was utilized.

The research results show that the clogging distribution and clogging rate of the rainwater grate are closely related to the fluid flow velocity and the physical characteristics of the particles, and the higher the clogging rate of the rainwater grate and the higher the number of particles deposited in the rainwater well at the same surface runoff velocity, the higher the density of the clogged particles. The surface runoff velocity (0.5 m/s, 1 m/s) shows that the rapid change of particle movement state at high runoff velocity makes the particle clogging more obvious.

A multi-scale CFD-DEM approach was used to simulate the particulate motion of the road surface with different incoming runoff velocities. The innovative use of DEM to model the storm grate simulation ensures the accuracy of the traction model.

There are various temperature measuring systems presented in the literature and on the market today. Over the past number of years a range of luminescent‐based optical fibre sensors have been reported and developed which include fluorescence and optical scattering. These temperature sensors incorporate materials that emit wavelength shifted light when excited by an optical source. The majority of commercially available systems are based on fluorescent properties.Design/methodology/approach – Many published journal articles and conference papers were investigated and existing temperature sensors in the market were examined.Findings – In optical thermometry, the light is used to carry temperature information. In many cases optical fibres are used to transmit and receive this light. Optical fibres are immune to electromagnetic interference and are small in size, which allows them to make very localized measurements. A temperature sensitive material forms a sensor and the subsequent optical data are transmitted via optical fibres to electronic detection systems. Two keys areas were investigated namely fluorescence based temperature sensors and temperature sensors involving optical scattering.Originality/value – An overview of optical fibre temperature sensors based on luminescence is presented. This review provides a summary of optical temperature sensors, old and new which exist in today's world of sensing.

The cross-docking strategy has a significant influence on supply chain and logistics efficiency. This paper aims to investigate the most suitable and efficient way to schedule the transfer of logistics activities and present a meta-heuristic method of the truck scheduling problem in cross-docking logistics. A truck scheduling problem with products time window is investigated with objectives of minimizing the total product transshipment time and earliness and tardiness cost of outbound trucks.

This research proposed a meta-heuristic method for the truck scheduling problem with products time window. To solve the problem, a lower bound of the problem is built through a novel two-stage Lagrangian relaxation problem and on account of the NP-hard nature of the truck scheduling problem, the novel red deer algorithm with the mechanism of the heuristic oscillating local search algorithm, as well as adaptive memory programming was proposed to overcome the inferior capability of the original red deer algorithm in the aspect of local search and run time.

Theory analysis and simulation experiments on an industrial case of a cross-docking center with a product’s time window are conducted in this paper. Satisfactory results show that the performance of the red deer algorithm is enhanced due to the mechanism of heuristic oscillating local search algorithm and adaptive memory programming and the proposed method efficiently solves the real-world size case of truck scheduling problems in cross-docking with product time window.

The consideration of products time window has very realistic significance in different logistics applications such as cold-chain logistics and pharmaceutical supply chain. Furthermore, the novel adaptive memory red deer algorithm could be modified and applied to other complex optimization scheduling problems such as scheduling problems considering energy-efficiency or other logistics strategies.

For the first time in the truck scheduling problem with the cross-docking strategy, the product’s time window is considered. Furthermore, a mathematical model with objectives of minimizing the total product transshipment time and earliness and tardiness cost of outbound trucks is developed. To solve the proposed problem, a novel adaptive memory red deer algorithm with the mechanism of heuristic oscillating local search algorithm was proposed to overcome the inferior capability of genetic algorithm in the aspect of local search and run time.

The purpose of this paper is to set a framework for strategic management of credit card fraud, by mapping its stakeholders within a card issuer and outlining its ideal strategies.

The objectives are attained via case study. Primary data was collected by interviewing two fraud risk managers at the card issuer, while secondary data was collected by gathering all investor reports released from 2015 to 2019 by the financial institution. All data were submitted to content analysis and further analyzed using Mendelow’s power/interest matrix.

Seven groups of stakeholders were identified, the expectations of each group uncovered and KPIs proposed to measure how well the financial institution meets those expectations. Strategies to deal with and prioritize groups were outlined, while highlighting the need for repositioning stakeholders identified as potential blockers or facilitators of strategic initiatives and pressure factors in times of low performance.

Strategic management of stakeholders is essential for fraud risk managers and researchers to understand what is relevant and what is not. This paper creates a framework for addressing managerial and academic efforts based on stakeholders mapping. Further initiatives in research and practice should consider the following question: “Which stakeholder expectation will be better satisfied?” In case the answer is “none”, it is advised that the initiative be reconsidered.

Previous literature focusses mostly on the technical challenges, leaving a gap in both literature and practice for using Strategic Management. For the first time in literature, this research combines theories and terminologies from fraud risk management and strategic management.