Hunan University of Humanities, Science and Technology

Long W., Cai S., Jiao J., Xu M., Wu T.

Quickly, accurately and reliably extract the parameters of solar photovoltaic (PV) model is very critical to simulate, evaluate and control the PV systems. During the past few years, many analytical, numerical and meta-heuristic algorithms have been suggested to extract the parameters of PV models based on the experimental data. However, extracting the parameters of PV models is still a great challenge. In this paper, a new hybrid algorithm based on grey wolf optimizer and cuckoo search (GWOCS) is developed to extract the parameters of different PV cell models with the experimental data under different operating conditions. In GWOCS, a new opposition learning strategy for the decision layer individuals (i.e., α, β, and δ) is proposed to enhance diversity of GWO. The main advantage of GWOCS is its ability to balance between exploration and exploitation. The performance of GWOCS is firstly tested on 10 complex benchmark functions. Then, the GWOCS is applied to extract the parameters of several solar PV cell models under different operating conditions. The comprehensively experimental results show the GWOCS is a promising candidate approach to extract the parameters of solar PV models.

Mohsin M., Naseem S., Sarfraz M., Azam T.

• Highly CO 2 emission oriented economic sectors contributed to the environmental sustainability destruction. • Energy consumption is a significant source of CO 2 emission. • Environmental Sustainability of Europe and Central Asian Countries can be enhanced by rectifying the considerable sectors of CO 2 emission. • Economic and human activities superiorly increase the pollutants, gases and particles. Environmentalists and scientists are agreed that the rapid growth of the global economy and human activities has become the reason for the environmental deterioration. The typical energy resources like fossil fuels are considered ecological devastation factors. This research investigates the relationship between a sustainable environment and economic growth in the European and Central Asian Countries by using yearly data series from 1971 to 2016. The ARDL approach is used to determine the short and long-run relationship among the selected set of variables. The CO 2 emission represents environmental sustainability while energy consumption, personal remittances, GDP, and FDI are independent variables and archetypal of economic growth. The CO 2 emission is the Granger cause of GDP while energy consumption and FDI Granger cause CO 2 emission. The results confirm long and short-run relationships among variables. Conclusively, a significant negative relationship for the long run and a positive relationship for the short-run between CO 2 emission and GDP authorizes the worsening of environmental sustainability is because of economic growth for a longer term. By analyzing data series and determining their impact on the environment, this research suggested that the adaptation of the green resource is necessary for the individual sector of the economy sooner rather than later to maintain the environment for the living being. This research will be a healthy contribution to the discussion of green growth and help policymakers establish the normative ground for economic sectors to contribute to environmental sustainability.

Long W., Wu T., Xu M., Tang M., Cai S.

Establishing accurate and reliable models based on the measured data for photo-voltaic (PV) modules are significant to design, control and evaluate the PV systems. Although many meta-heuristic algorithms have been proposed in the literature, achieving reliable, accurate and quick parameters identification for PV models is still a challenge. This paper develops a variant of butterfly optimization algorithm (called EABOA) to identify the unknown parameters of PV models. In EABOA, a new position search equation and good-point set are proposed to balance between exploration and exploitation. 12 classical benchmark test problems are firstly selected for verifying the effectiveness of EABOA, and the results indicate that EABOA provides better performance than other selected algorithms. Then, EABOA is applied to identify the unknown parameters of three benchmark test PV models, i.e., single diode (SD), double diode (DD) and PV module models. The comparison results with some other reported parameter identification methods from literature suggest that the proposed EABOA outperforms most approaches in terms of accuracy and reliability. The least SIAE value of EABOA is smaller than other compared algorithms about 56.6%, 5.84%, and 10.2% for SD, DD, and PV module models, respectively. Finally, EABOA is applied to solve parameter identification problem of practical module and obtains the satisfactory results. • An enhanced adaptive butterfly optimization algorithm is proposed. • The proposed algorithm is applied to identify the parameters of PV models. • A dynamical position search equation by introducing a guide factor is designed. • EABOA is an effective technique for parameter identification of PV models.

Zhou J.T., Zhang L., Fang Z., Du J., Peng X., Xiao Y.

Recent video anomaly detection methods focus on reconstructing or predicting frames. Under this umbrella, the long-standing inter-class data-imbalance problem resorts to the imbalance between foreground and stationary background objects in video anomaly detection and this has been less investigated by existing solutions. Naively optimizing the reconstructing loss yields a biased optimization towards background reconstruction rather than the objects of interest in the foreground. To solve this, we proposed a simple yet effective solution, termed attention-driven loss to alleviate the foreground-background imbalance problem in anomaly detection. Specifically, we compute a single mask map that summarizes the frame evolution of moving foreground regions and suppresses the background in the training video clips. After that, we construct an attention map through the combination of the mask map and background to give different weights to the foreground and background region respectively. The proposed attention-driven loss is independent of backbone networks and can be easily augmented in most existing anomaly detection models. Augmented with attention-driven loss, the model is able to achieve AUC 86.0% on Avenue, 83.9% on Ped1, 96% on Ped2 datasets. Extensive experimental results and ablation studies further validate the effectiveness of our model.

Ding C., Liu C., Casana R., Cavalcante A.

We obtain an exact Kerr-like black hole solution by solving the corresponding gravitational field equations in Einstein-bumblebee gravity model where Lorentz symmetry is spontaneously broken once a vector field acquires a vacuum expectation value. Results are presented for the purely radial Lorentz symmetry breaking. In order to study the effects of this breaking, we consider the black hole shadow and find that the radial of the unstable spherical orbit on the equatorial plane $$r_c$$ decreases with the Lorentz breaking constant $$\ell >0$$, and increases with $$\ell <0$$. These shifts are similar to those of Einstein-aether black hole. The effect of the LV parameter on the black hole shadow is that it accelerates the appearance of shadow distortion, and could be detected by the new generation of gravitational antennas.

Long W., Wu T., Jiao J., Tang M., Xu M.

Whale optimization algorithm (WOA) is a relatively new meta-heuristic optimization algorithm which mimics the hunting behavior of humpback whales. This paper presents a modified version of WOA, called RLWOA, for solving high-dimensional optimization problems. The proposed RLWOA adopts a modified conversion parameter update rule that relies on Logistic model to balance between diversity and convergence during the search process, and a new refraction-learning strategy based on the principle of refraction of light is proposed to help the population jump out of a local optimum. The experiments on a set of benchmark test functions with various features, i.e., 12 widely used benchmark functions with 100, 1000, and 10000 dimensions, two practical engineering design problems, and parameter estimation problem of photovoltaic model. The comparisons demonstrate that the proposed RLWOA shows better or at least competitive performance against the standard WOA, WOA variants and other state-of-the-art meta-heuristic algorithms for solving high-dimensional numerical optimization, practical engineering design optimization, and photovoltaic model parameter estimation problems.

Jamil K., Liu D., Gul R.F., Hussain Z., Mohsin M., Qin G., Khan F.U.

The study aims to compare CO2 emissions, renewable energy, trade openness, gross domestic product (GDP), financial development (FD), and remittance in selected G-20 countries. The study carried out fully modified ordinary least square (FMOLS) and dynamic ordinary least square (DOLS) models for estimation covering annual data from the year 1990–2019. LM tests detected the cross-section dependency while stationarity of the variables was checked through Levin-Lin-Chu and Im-Pesaran-Shin tests along with Hansen's Covariate-Augmented Dickey Fuller (CADF) test in the presence of cross-section dependency. The panel unit root tests reported that all variables became stationary after converting them into the first difference. The Panel Cointegration and Wester-Lund test examined the existence of long-run equilibrium nexus among selected variables in the context of G-20 countries. The study's findings show that there is a significant and negative relationship between renewable energy and CO2 emissions. It was proven in two models that the economic growth of selected G-20 countries has a positive relationship with CO2 emissions. Furthermore, findings indicate that the coefficient of financial development is positive and significantly impacts CO2 emissions. The remittances have a significant positive effect on CO2 emissions, while trade openness has an insignificant impact on CO2 emissions in both models. This research will enlighten policymakers, researchers, governments, and environmentalists toward attaining a sustainable environment by wisely consuming remittances and renewable energy resources.

Zheng H., Wu D., Wang Y., Liu X., Gao P., Liu W., Wen J., Rebrov E.V.

A new approach was proposed for the preparation of metal–organic framework/metal oxide composites in one step using only metal salts. Here, crystalline rhombohedral dodecahedron ZIF-8, hollow ZnO microsphere, and ZIF-8/ZnO composites were obtained in different one-pot solvothermal processes where the growth toward individual ZIF-8 and ZnO phases and toward ZIF-8/ZnO composites was controlled by adjusting the ratio of metal salts to 2-methylimidazole. Subsequently, a series of derived (C and/or N)-doped ZnO nanoparticles was obtained by a two-step calcination process. The absorption kinetics and photocatalytic activity in methyl orange degradation under visible light were investigated. ZIF-8-derived ZnO could maintain their original morphology and displayed excellent photocatalytic activity 10 times higher than that of the original ZIF-8.

Ji C., Huang Z., Tian X., He H., Wen J., Peng Y.

A series of red emitting phosphors Mg3Y2-xGe3O12:xSm3+ (0≤x ≤ 0.06) were successfully synthesized. Samples Mg3Y2-xGe3O12:Sm3+ exhibited a cubic structure pertaining to the Ia-3d (230) space group and the particle sizes range from 1 μm to 5 μm. The optical properties displayed that the optimum doping concentration of Sm3+ is 4%. The phosphor Mg3Y1.96Ge3O12:0.04Sm3+ not only exhibited a broad band gap of 5.54 eV but also showed a high color purity of 97.6%. In addition, the strongest emission intensity located at 566 nm belonged to the 4G5/2 → 6H5/2 transition when excited at 405 nm. Thermal quenching test revealed that the sample Mg3Y1.96Ge3O12:0.04Sm3+ are excellent powders with splendid thermal stability, in which only 3.6% of the PL intensity is quenched at 473 K in comparison with that of 298 K. As a result, the W-LEDs based on Mg3Y1.96Ge3O12:0.04Sm3+ yielded a high Ra of 91.1, a low CCT of 4881 K, and CIE coordinates of (0.3476, 0.3466) in a 20 mA driven current. This research work provided important guidance for the synthesis of Sm3+ doped red component with excellent luminesce properties and high thermal stability characteristics used in W-LEDs.

Naseem S., Mohsin M., Zia-UR-Rehman M., Baig S.A., Sarfraz M.

The multi-dimensional pollutions in the earth zone due to the degradation of the environmental levels have been emerging as an urgent issue in the developing economies. The BRICS group of countries holds a unique position in the emerging economies, playing a leading role in reinforcing political power globally and domestically. This study examines the annual time series over the period of 1971–2017 for Brazil, India, China, and South Africa, and 1990–2017 for Russia, to explore the relationship between environmental quality and economic growth in correspondence with the Environmental Kuznets Curve (EKC) hypothesis as well as the Decoupling Index (DI). The presence of an EKC strongly supports any of the individualistic environmental determinants effected in the long run by Autoregressive Distributed Lag (ARDL), building linkage with the approach of the co-integration and the DI, which brings about economic growth as well as CO2 emission and environmental degradation simultaneously. A short-run relationship and presence of the EKC hypothesis are observed in Brazil, Russia, and India with 92%, while China’s (55%) and South Africa’s (79%) have a slower speed of adjustment to long-run equilibrium. This study concludes that economic expansion and environmental degradation are interrelated in the long run. Environment degradation (CO2 emission) can be eradicated by continuous economic growth, management of energy demands and energy crises, implementation of environmentally sustainable policies, application of green technologies for the use of natural resources, and controllability of urban population growth with immediate and effective actions.