Search

Z-number that proposed by Zadeh is an effective tool to describe the information with uncertainty in decision-making problems. However, most of the researches on Z-numbers employed linguistic cardinalities with uniformly distributed scales. In fact, unbalance situation is much common in terms of the psychology of experts. In this paper, we propose a new computational method based on Probabilistic Linguistic Z-number with Unbalanced semantics(UPLZ), which can represent the linguistic evaluations of experts precisely combined with individual risk appetite. A new score function of UPLZs is provided based on hesitant degree and linguistic scale function to reduce the computational complexity. Afterward, a linear programming is constructed to determine weights of criteria by considering cross entropy maximization. The robust decision result can be obtained by applying MULTIMOORA method since it is specific with peculiarities of three subordinate models. Finally, a case study concerning medicine selection for the patients with mild symptoms of the COVID-19 is provided to illustrate the feasibility and effectiveness of the proposed method. The advantages of it are highlighted by sensitivity analysis and comparative analysis with two outstanding multi-criteria decision-making methods.

Relay assisted communication helps to extend the transmission coverage area. In more realistic scenarios, the available relays are untrusted, which try to decode the confidential signals during their main relaying function. Thus, these untrusted relays are regarded as potential eavesdroppers, and the confidential signals are vulnerable. A positive secrecy rate can be achieved at the physical layer without any cryptography, in particular, the mutual interference achieved from two-way relaying network can be used to secure the confidential signals against eavesdroppers attack. In this paper, the relay selection of two-way untrusted relays network is presented, and a directed beamforming is aligned to zero force the transmission at all other non-selected relays. Particularly, we propose a selection scheme based on max–min criterion, which requires an exhaustive search. Then, the lower bound (LB) of the secrecy rate is introduced to minimize the complexity of the selection criterion. The closed forms of the secure outage probability (SOP) for the max–min LB scheme is formulated and compared with other schemes. The simulations results validate the proposed analytical forms, and the performance of max–min LB scheme appears to be quite close to that of the max–min scheme with limited complexity. [ABSTRACT FROM AUTHOR]

Distributed controlled coarse-grained reconfigurable arrays (CGRAs) enable efficient execution of irregular control flows by reconciling divergence in the processing elements (PEs). To further improve performance by better exploiting spatial parallelism, the triggered instruction architecture (TIA) eliminates the program counter and branch instructions by converting control flows into predicate dependencies as triggers. However, pipeline stalls, which occur in pipelines composed of both intra and inter-PEs, remain a major obstacle to the overall performance. In fact, the stalls in distributed controlled CGRAs pose a unique problem that is difficult to resolve by previous techniques. This work presents a triggered-issuance and triggered-execution (TITE) paradigm in which the issuance and execution of instructions are separately triggered to further relax the predicate dependencies in TIA. In this paradigm, instructions are paired as dual instructions to eliminate stalls caused by control divergence. Tags that identify the data transmitted between PEs are forwarded for acceleration. As a result, pipeline stalls of both intra- and inter-PEs can be significantly minimized. Experiments show that TITE improves performance by 21 percent, energy efficiency by 17 percent, and area efficiency by 12 percent compared with a baseline TIA. [ABSTRACT FROM AUTHOR]

In this paper, a joint beamforming alignment and suboptimal power allocation (Sub-OPA) for a two-way untrusted relay network is presented. Considering the link between users is established via only an untrusted relay because of either the shadowing fading or long distance between users, we utilize a destination-assisted-jamming (DAJ) technique to improve the security performance. In each time slot, a user transmits confidential signals and the other emits jamming signals simultaneously to prevent the untrusted relay from intercepting the confidential signals. First, we design a novel beamforming to align the confidential signal to the subspace corresponding to the confidential transmission channel and direct the cooperative jamming signal toward untrusted relay. Then, an iterative algorithm is presented to generate the Sub-OPA of each user for the transmission of confidential and cooperative jamming signal. The correctness and efficiency of the proposed beamforming scheme and the Sub-OPA are validated by numerical simulations and the results are compared via MatLab optimization toolbox. Moreover, the simulations show the iterative algorithm is converged after the fourth iteration at lower signal-to-noise ratios (SNRs) and rapidly converged with allocating more power to the confidential signals at higher SNRs. [ABSTRACT FROM PUBLISHER]

Goal: Dermoscopy images often suffer from blur and uneven illumination distortions that occur during acquisition, which can adversely influence consequent automatic image analysis results on potential lesion objects. The purpose of this paper is to deploy an algorithm that can automatically assess the quality of dermoscopy images. Such an algorithm could be used to direct image recapture or correction. Methods: We describe an application-driven no-reference image quality assessment (IQA) model for dermoscopy images affected by possibly multiple distortions. For this purpose, we created a multiple distortion dataset of dermoscopy images impaired by varying degrees of blur and uneven illumination. The basis of this model is two single distortion IQA metrics that are sensitive to blur and uneven illumination, respectively. The outputs of these two metrics are combined to predict the quality of multiply distorted dermoscopy images using a fuzzy neural network. Unlike traditional IQA algorithms, which use human subjective score as ground truth, here ground truth is driven by the application, and generated according to the degree of influence of the distortions on lesion analysis. Results: The experimental results reveal that the proposed model delivers accurate and stable quality prediction results for dermoscopy images impaired by multiple distortions. Conclusion: The proposed model is effective for quality assessment of multiple distorted dermoscopy images. Significance: An application-driven concept for IQA is introduced, and at the same time, a solution framework for the IQA of multiple distortions is proposed. [ABSTRACT FROM AUTHOR]