An Enhanced Naked Mole Rat Algorithm for Optimal Cross-Layer Solution for Wireless Underground Sensor Networks

Nature-inspired algorithms serve as the backbone of modern computing technology, and over the past three decades, the field has grown enormously. Many applications were solved by such algorithms and are replacing the traditional classical optimization processes. A recent naked mole-rat algorithm (NMRA) was proposed based on the mating patterns of naked mole-rats. This algorithm proved its worth in terms of competitiveness and application to various domains of research. The aim was to propose an algorithm based on NMRA, named enhanced NMRA (ENMRA), by mitigating the problems that this algorithm suffers from: slow convergence, poor exploration, and local optima stagnation. To enhance the exploration capabilities of basic NMRA, grey wolf optimization (GWO)-based search equations were employed. Exploitation was improved using population division methods based on local neighborhood search (LNS) and differential evolution (DE) equations. To avoid the local stagnation problem, a neighborhood search strategy around the best individual was utilized. Such improvements help the new variant to solve highly challenging optimization problems in contrast to existing algorithms. The efficacy of ENMRA was evaluated using CEC 2019 benchmark test suite. The results were statistically analyzed by the Wilcoxon rank-sum test and Friedman rank (f-rank) test. The resulting analysis proved that ENMRA is superior to the competitive algorithms for test functions CEC 2019 with overall effectiveness of 60.33%. Moreover, the real-world optimization problem from underground wireless sensor networks for an efficient cross-layer solution was also used to test the efficiency of ENMRA. The results of comparative study and statistical tests affirmed the efficient performance of the proposed algorithm.

Improvement of Indirect X-ray Detector Performance by Applying Additive Solvent to the Organic Active-Layer

In this paper, we studied how the sensitivity of an indirect X-ray detector was changed by adding the additive solvent DIO to the organic active-layers, such as P3HT:PCBM and PBDB-T:PCBM. The crystallinity and absorbance of the active-layer films were compared with different additive DIO contents. In both active-layers, the highest crystallinity and absorbance were obtained when 3 v% of the DIO was mixed with the active-layer solution. At the same mixing condition of the DIO, the highest sensitivity, of 1.17 mA/Gy · cm2, was obtained for the P3HT:PCBM detector, and the highest sensitivity, 1.87 mA/Gy · cm2, was obtained for the PBDB-T:PCBM detector. Compared to the detector without the DIO, the sensitivities of the detectors with the P3HT:PCBM and PBDB-T:PCBM increased by 18.12% and 20.27%, respectively.

Characterization of Perovskite Solar Cells According to TiO2 Mesoporous Layer Treated with Ti-Diisopropoxide Bis

The power conversion efficiency of perovskite solar cells, which are next-generation photovoltaic cells, has rapidly increased up to 20% through ongoing research and development. Recently, various methods have been employed to increase the active area of the mesoporous layer in perovskite solar cells. In this study, the particle aggregation of the TiO2 was controlled by adding Ti-diisopropoxide bis to the mesoporous layer solution; thus, the contact area between the mesoporous layer and perovskite layer was increased. The amount of Ti-diisopropoxide bis added to the mesoporous layer solution was adjusted to prevent the inhibition of electron transport caused by separation of particles and instability of mesoporous layer. To evaluate the changes in the characteristics of the perovskite solar cells due to the TiO2 particle aggregation in the mesoporous layer, X-ray diffraction and spectrophotometric absorbance, as well as cross-sectional and surface scanning electron microscopy measurement were performed, and the current density–voltage curve, power conversion efficiency and other properties were evaluated under solar simulator. It was found that the mesoporous layer was improved due to its enlarged contact area, and hence, can be expected to improve the efficiency of perovskite solar cells.

A mesh adaptation algorithm using new monitor and estimator function for discontinuous and layered solution

<p style='text-indent:20px;'>In this work a novel mesh adaptation technique is proposed to approximate discontinuous or boundary layer solution of partial differential equations. We introduce new estimator and monitor function to detect solution region containing discontinuity and layered region. Subsequently, this information is utilized along with equi-distribution principle to adapt the mesh locally. Numerical tests for numerous scalar problems are presented. These results clearly demonstrate the robustness of this method and non-oscillatory nature of the computed solutions.</p>

Enhancing the Retailer Gift Card via Blockchain

Though the retailer gift card has been an ultra-practical marketing tactic to attract customers to spend more, it, on the contrary, also places a great number of customers in troublesome situations due to its current limitations. First, dealing with unwanted gift cards is often time-consuming, costly, or even risky due to the frequent occurrences of gift card resale frauds. Worse still, the issuance and redemption of gift cards happen inside the retailer as in a “black-box,” indicating that a compromised retailer can cheat customers (or even third-party auditors) to deny the issuances of some unredeemed gift cards. This paper proposes a practical middle-layer solution based on blockchain to address the fundamental issues of the existing gift card system, with incurring minimal changes to the current infrastructure.