Joint Fractional Time Allocation and Beamforming for Downlink Multiuser MISO Systems

It is well-known that the traditional transmit beamforming at a base station (BS) to manage interference in serving multiple users is effective only when the number of users is less than the number of transmit antennas at the BS. Non-orthogonal multiple access (NOMA) can improve the throughput of users with poorer channel conditions by compromising their own privacy because other users with better channel conditions can decode the information of users in poorer channel state. NOMA still prefers that the number of users is less than the number of antennas at the BS transmitter. This paper resolves such issues by allocating separate fractional time slots for serving the users with similar channel conditions. This enables the BS to serve more users within the time unit while the privacy of each user is preserved. The fractional times and beamforming vectors are jointly optimized to maximize the system's throughput. An efficient path-following algorithm, which invokes a simple convex quadratic program at each iteration, is proposed for the solution of this challenging optimization problem. Numerical results confirm its versatility.Comment: IEEE Communications Letters (To Appear

Performance Analysis of Hybrid ALOHA/CDMA RFID Systems with Quasi-decorrelating Detector in Noisy Channels

In this paper we investigate the performance of a hybrid Aloha/CDMA radio frequency identification (RFID) system with quasi-decorrelating detector (QDD). Motivated by the fact that the QDD outperforms the conventional decorrelating detector (DD) in noisy network scenarios, we study and propose using QDD as one of the most promising candidates for the structure of RFID readers. Performance analysis in terms of bit error rate and the RFID system efficiency is considered considering CDMA code collision and detection error. Computer simulations are also performed, and the obtained results of QDD-based structure are compared with those of DD-based one to confirm the correctness of the design suggestion in different practical applications of tag identification and missing-tag detection

Numerical and Experimental Study on the Grinding Performance of Ti-Based Super-Alloy

The experiments of the surface grinding of Ti-6Al-4V grade 5 alloy (Ti-64) with a resin-bonded cubic Boron Nitride (cBN) grinding wheel are performed in this research to estimate the influence of cutting parameters named workpiece infeed speed, Depth of Cut (DOC), cooling condition on the grinding force, force ratio, and specific energy. A finite element simulation model of single-grain grinding of Ti-64 is also implemented in order to predict the values of grinding forces and temperature. The experimental results show that an increase of workpiece infeed speed creates higher intensified cutting forces than the DOC. The grinding experiments under wet conditions present slightly lower tangential forces, force ratio, and specific energy than those in dry grinding. The simulation outcomes exhibit that the relative deviation of simulated and experimental forces is in the range of 1-15%. The increase in feed rate considerably reduces grinding temperature, while enhancement of DOC elevates the heat generation in the cutting zone

Applying Conflict Management Styles to Resolve Task Conflict and Enhance Team Innovation

Task conflicts among group members have a significant impact on team creativity, so it is critical to identify which conflict resolution styles should be used. This paper aims to examine how various conflict management styles influence team creativity via task conflict. The empirical research was conducted using the Structural Equation Model (SEM) for a sample of 257 employees working for Vietnamese organizations. The results show that dominating style increases task conflict while combining and obliging styles reduce it. To take advantage of the creativity-related benefits associated with task conflict, team leaders should develop an open atmosphere that encourages participants' integrating styles, rather than dominating styles. The negative influence of obliging style reflects Vietnamese culture's high collectivism. The study provides various approaches for task conflict management and also highlights the role of controlling task conflicts in enhancing team innovation. It implies that employees will be able to work better as a team in practice if conflict management strategies are used in a flexible manner. It helps them to build a good connection and successfully implement new ideas. Further research should extend the conclusion of this analysis in various contexts to generalize the findings. Doi: 10.28991/esj-2021-01303 Full Text: PD

Flat Seeking Bayesian Neural Networks

Bayesian Neural Networks (BNNs) provide a probabilistic interpretation for deep learning models by imposing a prior distribution over model parameters and inferring a posterior distribution based on observed data. The model sampled from the posterior distribution can be used for providing ensemble predictions and quantifying prediction uncertainty. It is well-known that deep learning models with lower sharpness have better generalization ability. However, existing posterior inferences are not aware of sharpness/flatness in terms of formulation, possibly leading to high sharpness for the models sampled from them. In this paper, we develop theories, the Bayesian setting, and the variational inference approach for the sharpness-aware posterior. Specifically, the models sampled from our sharpness-aware posterior, and the optimal approximate posterior estimating this sharpness-aware posterior, have better flatness, hence possibly possessing higher generalization ability. We conduct experiments by leveraging the sharpness-aware posterior with state-of-the-art Bayesian Neural Networks, showing that the flat-seeking counterparts outperform their baselines in all metrics of interest.Comment: Accepted at NeurIPS 202

Optimal generation for wind-thermal power plant systems with multiple fuel sources

In this paper, the combined wind and thermal power plant systems are operated optimally to reduce the total fossil fuel cost (TFFC) of all thermal power plants and supply enough power energy to loads. The objective of reducing TFFC is implemented by using antlion algorithm (ALA), particle swarm optimization (PSO) and Cuckoo search algorithm (CSA). The best method is then determined based on the obtained TFFC from the three methods as dealing with two study cases. Two systems with eleven units including one wind power plant (WPP) and ten thermal power plants are optimally operated. The two systems have the same characteristic of MFSs but the valve loading effects (VLEs) on thermal power plants are only considered in the second system. The comparisons of TFFC from the two systems indicate that CSA is more powerful than ALA and PSO. Furthermore, CSA is also superior to the two methods in terms of faster search process. Consequently, CSA is a powerful method for the problem of optimal generation for wind-thermal power plant systems with consideration of MFSs from thermal power plants