Hybrid Time-Power Switching Protocol of Energy Harvesting Bidirectional Relaying Network: Throughput and Ergodic Capacity Analysis

In this paper, we investigate system performance in term of throughput and ergodic capacity of the hybrid time-power switching protocol of energy harvesting bidirectional relaying network. In the first stage, the analytical expression of the system throughput and ergodic capacity of the model system is proposed and derived. In this analysis, both delay-limited and delay-tolerant transmission modes are presented and considered. After that, the effect of various system parameters on the proposed system is investigated and demonstrated by Monte-Carlo simulation. Finally, the results show that the analytical mathematical and simulated results match for all possible parameter values for both schemes

Decentralized High-Dimensional Bayesian Optimization with Factor Graphs

This paper presents a novel decentralized high-dimensional Bayesian optimization (DEC-HBO) algorithm that, in contrast to existing HBO algorithms, can exploit the interdependent effects of various input components on the output of the unknown objective function f for boosting the BO performance and still preserve scalability in the number of input dimensions without requiring prior knowledge or the existence of a low (effective) dimension of the input space. To realize this, we propose a sparse yet rich factor graph representation of f to be exploited for designing an acquisition function that can be similarly represented by a sparse factor graph and hence be efficiently optimized in a decentralized manner using distributed message passing. Despite richly characterizing the interdependent effects of the input components on the output of f with a factor graph, DEC-HBO can still guarantee no-regret performance asymptotically. Empirical evaluation on synthetic and real-world experiments (e.g., sparse Gaussian process model with 1811 hyperparameters) shows that DEC-HBO outperforms the state-of-the-art HBO algorithms.Comment: 32nd AAAI Conference on Artificial Intelligence (AAAI 2018), Extended version with proofs, 13 page

Enhancement of the Tracking Performance for Robot Manipulator by Using the Feed-forward Scheme and Reasonable Switching Mechanism

Robot manipulator has become an exciting topic for many researchers during several decades. They have investigated the advanced algorithms such as sliding mode control, neural network, or genetic scheme to implement these developments. However, they lacked the integration of these algorithms to explore many potential expansions. Simultaneously, the complicated system requires a lot of computational costs, which is not always supported. Therefore, this paper presents a novel design of switching mechanisms to control the robot manipulator. This investigation is expected to achieve superior performance by flexibly adjusting various strategies for better selection. The Proportional-Integral-Derivative (PID) scheme is well-known, easy to implement, and ensures rapid computation while it might not have much control effect. The advanced interval type-2 fuzzy sliding mode control properly deals with nonlinear factors and disturbances. Consequently, the PID scheme is switched when the tracking error is less than the threshold or is far from the target. Otherwise, the interval type-2 fuzzy sliding mode control scheme is activated to cope with unknown factors. The main contributions of this paper are (i) the recommendation of a suitable switching mechanism to drive the robot manipulator, (ii) the successful integration of the interval type-2 fuzzy sliding mode control to track the desired trajectory, and (iii) the launching of several tests to validate the proposed controller with robot model. From these achievements, it would be stated that the proposed approach is effective in tracking performance, robust in disturbance-rejection, and feasible in practical implementation

EFL Students’ Attitudes towards Integrating Teaching Cross-Cultural Issues and Teaching Listening Skill

Teaching cross-cultural knowledge in English teaching is drawing more and more attention nowadays. This study investigated students’ attitudes towards the integration of teaching cross-cultural issues and teaching listening skill. This study based on qualitative analysis of a questionnaire done by 30 EFL students who participated in the course on Listening 2 in the second year of their MBA program in Kien Giang University, Vietnam. During the course, besides helping students master the language and listening skill, the researcher helped cultivate their cross-cultural competence by explaining some cross-culture notes related to the content of the lesson. At the end of the course, a questionnaire has been conducted to the students to gain information about the effectiveness of integrating teaching cross-culture knowledge and teaching listening. The finding revealed that students found the cross-cultural issues effective in helping them understand the lessons better and form healthy cross-cultural awareness. They also enjoyed learning the cultural differences to develop their cross-cultural knowledge and got useful experience to widen their world

TRANSFORMING EXTENDED ENTITY-RELATIONSHIP MODEL INTO OWL ONTOLOGY IN TEMPORAL DATABASES

Many previous systems were built based on the ER model, so the upgrading and transforming the ER model into ontology for reducing cost is really necessary. There are several studies aim at transforming from ER and EER model into ontology. However, these studies have not classified the semantic of the recursive relationship in ER model, so the semantic of the recursive relationship will be easily lost during the transformation. Also, the studies have not mentioned the designing of the ontology that supports temporal attributes based on the temporal ER model. This paper discusses the semantic classification of the recursive relationship and TimeER model (extended EER in temporal databases) and OWL ontology. And propose a method to transform into OWL ontology

Energy harvesting over Rician fading channel: A performance analysis for half-duplex bidirectional sensor networks under hardware impairments

In this paper, a rigorous analysis of the performance of time-switching energy harvesting strategy that is applied for a half-duplex bidirectional wireless sensor network with intermediate relay over a Rician fading channel is presented to provide the exact-form expressions of the outage probability, achievable throughput and the symbol-error-rate (SER) of the system under the hardware impairment condition. Using the proposed probabilistic models for wireless channels between mobile nodes as well as for the hardware noises, we derive the outage probability of the system, and then the throughput and SER can be obtained as a result. Both exact analysis and asymptotic analysis at high signal-power-to-noise-ratio regime are provided. Monte Carlo simulation is also conducted to verify the analysis. This work confirms the effectiveness of energy harvesting applied in wireless sensor networks over a Rician fading channel, and can provide an insightful understanding about the effect of various parameters on the system performance.Web of Science186art. no. 1781