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The purpose of this paper is to propose an efficient path and trajectory planning method to solve online robotic multipoint assembly.

A path planning algorithm called policy memorized adaptive dynamic programming (PM-ADP) combines with a trajectory planning algorithm called adaptive elite genetic algorithm (AEGA) for online time-optimal path and trajectory planning.

Experimental results and comparative study show that the PM-ADP is more efficient and accurate than traditional algorithms in a smaller assembly task. Under the shortest assembly path, AEGA is used to plan the time-optimal trajectories of the robot and be more efficient than GA.

The proposed method builds a new online and efficient path planning arithmetic to cope with the uncertain and dynamic nature of the multipoint assembly path in the Cartesian space. Moreover, the optimized trajectories of the joints can make the movement of the robot continuously and efficiently.

The proposed method is a combination of time-optimal path planning with trajectory planning. The traveling salesman problem model of assembly path is established to transfer the assembly process into a Markov decision process (MDP). A new dynamic programming (DP) algorithm, termed PM-ADP, which combines the memorized policy and adaptivity, is developed to optimize the shortest assembly path. GA is improved, termed AEGA, which is used for online time-optimal trajectory planning in joints space.

This purpose of this paper is to provide an overview of the theoretical background and applications of inverse reinforcement learning (IRL).

Reinforcement learning (RL) techniques provide a powerful solution for sequential decision making problems under uncertainty. RL uses an agent equipped with a reward function to find a policy through interactions with a dynamic environment. However, one major assumption of existing RL algorithms is that reward function, the most succinct representation of the designer's intention, needs to be provided beforehand. In practice, the reward function can be very hard to specify and exhaustive to tune for large and complex problems, and this inspires the development of IRL, an extension of RL, which directly tackles this problem by learning the reward function through expert demonstrations. In this paper, the original IRL algorithms and its close variants, as well as their recent advances are reviewed and compared.

This paper can serve as an introduction guide of fundamental theory and developments, as well as the applications of IRL.

This paper surveys the theories and applications of IRL, which is the latest development of RL and has not been done so far.

This study aims to propose a two-element multi-input-multi-output (MIMO) antenna for cognitive radio MIMO applications to avoid the complexities involved in reconfigurable antennas and improve the spectrum utilization efficiency.

The proposed MIMO antenna system comprises a wideband antenna that operates at 2 GHz–12 GHz for sensing the spectrum and four pairs of antennas for communication, which are single and dual-band antennas. Each pair of antennas meant for communication consists of two similar antennas. Moreover, the antennas meant for communication cover 93% of the bandwidth of the sensing antenna.

The first pair of antennas accessible at ports P2 and P6 and the second pair of antennas accessible at ports P4 and P8, which are dual-band antennas, operate at 3.05 GHz–3.85 GHz, 5.8 GHz–8 GHz and 2.05 GHz–2.55 GHz, 4.7 GHz–6.1 GHz, respectively. While the third pair of antennas accessible at ports P3 and P7 and the fourth pair of antennas accessible at ports P5 and P9 are single-band antennas and operate at 3.85 GHz–4.7 GHz and 8 GHz–11 GHz, respectively. Minimum isolations of 20 dB and 15 dB are attained between every two similar antennas for communication and between the sensing antenna and the antennas meant for communication, respectively. The correctness of the proposed antenna is verified with a fine match between the results obtained from simulations and measurements.

The proposed MIMO antenna possesses salient features, such as polarization diversity and performing a maximum of four communication tasks when all the white spaces are detected.

The objective of this study is to examine the drivers of retail apps satisfaction and continuance intention. An integrative theoretical framework was developed based on the IS success model, E-S-QUAL and expectancy and disconfirmation model to explain retail apps users’ satisfaction and continuance intention.

A total of 359 useable data were collected from the targeted Malaysian respondents who had experience in using retail apps services. Data were analysed using the partial least squares technique.

The results indicate that system quality and e-service quality positively influence retail apps usage satisfaction and have positive direct and indirect effects through satisfaction on continuance intention. The price level has a negative effect on retail apps usage satisfaction. Even though price level has no direct effect on continuance intention to use retail apps, it has an indirect effect on continuance intention through satisfaction.

Although the success of a marketing channel mainly depends on its continuance usage rather than first-time usage, few studies have paid attention to retail apps services. This study contributes to the advancement of knowledge on retail apps by explaining the roles of system quality, e-service quality and price level on retail apps satisfaction and continuance intention. Interestingly, the findings of multi-group analysis imply that female Gen Y app users are more satisfied than males while such differences do not impact their continuance intention to use the retail apps. The findings also suggested that frequency of using apps has no relevance to retail apps user satisfaction, but highly relevant to their continuance intention to use retail Apps services.

The significant role of universities in generating and diffusing new knowledge in the interest of society has positioned faculty as knowledge creators. The present study contributes to the domain of positive psychology by heeding the happiness call in academia. The research intends to develop and validate a scale for measuring happiness at work (HAW) for knowledge creators.

The study is systematically designed across a series of four independent studies: (1) Dimensionality and item analysis, (2) scale purification, (3) scale refinement and nomological validation and (4) generalizability. Additionally, common method bias (CMB) was checked utilizing the marker variable technique.

HAW has been established as a second-order reflective-reflective construct with six factors, namely work satisfaction, self-directedness, self-love, positive thinking, positive social relationships and work-family balance. The nomological validity and generalizability of the scale have also been established.

The study is an attempt to address an important topic of HAW among knowledge creators. By conceptualizing HAW as a combination of intraindividual and organizational factors, this study offers a comprehensive measure of HAW that was previously absent in the literature. The results of the study will assist management in making strategic decisions to ensure the HAW of knowledge creators.

Knowledge creators’ happiness is a major concern in academia and has received little attention till date. The primary contribution of this study is the conceptualization and development of a validated scale for measuring knowledge creators’ HAW. A valid and reliable scale for measuring HAW would enable researchers to gain fresh perspectives on the essence, attributes and quantification of this particularly noteworthy construct.

The purpose of this paper is to investigate the effects of minor addition of the rare earth (RE) element cerium, Ce, on the microstructures and creep properties of Sn-Ag-Cu solder alloys.

The pure Sn, Sn-Cu alloy, Sn-Ag alloy and Cu-Ce alloy were used as raw materials. Sn-Ag-Cu alloys with different contents of RE Ce were chosen to compare with Sn-Ag-Cu. The raw materials of Sn, Sn-Cu alloy, Sn-Ag alloy, Cu-Ce alloy were melted in a ceramic crucible, and were melted at 550°C ± 1°C for 40 minutes. To homogenize the solder alloy, mechanical stirring was performed every ten minutes using a glass rod. During the melting, KC1 + LiCI (1.3:1), were used over the surface of liquid solder to prevent oxidation. The melted solder was chill cast into a rod.

It is found that the microstructure exhibits smaller grains and the Ag₃Sn/Cu₆Sn₅ intermetallic compound (IMC) phases are modified in matrix with the addition of Ce. In particular, the addition of 0.03 wt.% Ce to the Sn-Ag-Cu solder can refine the microstructures and decrease the thickness of the IMC layers of Sn-Ag-Cu solder alloys. Meanwhile, thermodynamic analysis showed that these phenomena could be attributed to the reduction of the driving force for Cu-Sn IMC formation due to the addition of Ce. Results calculated using the thermodynamic method are close to the above experimental data. Thus, the optimum content of Ce in Sn-Ag-Cu solder alloys should be about 0.030 percent. Additionally, the effect of Ce on the creep rupture life of Sn-Ag-Cu soldered joints was studied. It was found that the creep rupture life may be increased up to 7.5 times more than that of the original Sn-Ag-Cu alloy, when Ce accounts for 0.030 percent.

This paper usefully investigates the effects of the RE cerium (Ce), on the microstructures and creep properties of Sn-Ag-Cu solder alloys, optimizing the quantity of Ce in the Sn-Ag-Cu solder alloy through a thermodynamic method and by creep-rupture life testing.