A KELM-Based Ensemble Learning Approach for Exchange Rate Forecasting

In this paper, a KELM-based ensemble learning approach, integrating Granger causality test, grey relational analysis and KELM(Kernel Extreme Learning Machine), is proposed for the exchange rate forecasting. The study uses a set of sixteen macroeconomic variables including, import,export, foreign exchange reserves, etc. Furthermore, the selected variables are ranked and then three of them, which have the highest degrees of relevance with the exchange rate, are filtered out by Granger causality test and the grey relational analysis, to represent the domestic situation. Then, based on the domestic situation, KELM is utilized for medium-term RMB/USD forecasting. The empirical results show that the proposed KELM-based ensemble learning approach outperforms all other benchmark models in different forecasting horizons, which implies that the KELM-based ensemble learning approach is a powerful learning approach for exchange rates forecasting.     

Real-Time Pricing of Smart Grid Based on Piece-Wise Linear Functions

In a power grid system, utility is a measure of the satisfaction of users' electricity consumption; cost is a monetary value of electricity generated by the supplier. The utility and cost functions represent the satisfaction of different users and the supplier. Quadratic utility, logarithmic utility,and quadratic cost functions are widely used in social welfare maximization models of real-time pricing. These functions are not universal; they have to be discussed in detail for individual models. To overcome this problem, a piece-wise linear utility function and a piece-wise linear cost function with general properties are proposed in this paper. By smoothing the piece-wise linear utility and cost functions, a social welfare maximization model can be transformed into a differentiable convex optimization problem. A dual optimization method is used to solve the smoothed model. Through mathematical deduction and numerical simulations, the rationality of the model and the validity of the algorithm are verified as long as the elastic and cost coefficients take appropriate values. Thus, different user types and the supplier can be determined by selecting different elastic and cost coefficients.     

Energy Management System Design and Testing for Smart Buildings Under Uncertain Generation (Wind/Photovoltaic) and Demand

This study provides details of the energy management architecture used in the Goldwind microgrid test bed. A complete mathematical model, including all constraints and objectives, for microgrid operational management is first described using a modified prediction interval scheme. Forecasting results are then achieved every 10 min using the modified fuzzy prediction interval model, which is trained by particle swarm optimization.A scenario set is also generated using an unserved power profile and coverage grades of forecasting to compare the feasibility of the proposed method with that of the deterministic approach. The worst case operating points are achieved by the scenario with the maximum transaction cost. In summary, selection of the maximum transaction operating point from all the scenarios provides a cushion against uncertainties in renewable generation and load demand.     

Robust Adaptive Multi-Switching Synchronization of Multiple Different Orders Unknown Chaotic Systems

Multi-switching synchronization(MSS) of multiple different orders unknown chaotic(UC)systems confines hacking in the digital transmission process. Similarly, the suppression of undesirable chattering increases synchronization performance. This paper proposes a new robust synchronization control(RASC) technique and discusses the MSS of multiple different orders UC systems. This controller accomplishes(i) quick convergence,(ii) reduces the transient oscillations, and(iii) the rate of convergence decreases in the vicinity of the origin that causes the suppression of chattering. Analysis based on the Lyapunov direct method assures this convergence behavior with any positive values of the feedback gains. This work also provides parameters updated law that estimates the true values of unknown parameters. Numerical examples of five UC systems different orders are simulated. The computer based graphical results validate the efficiency and performance of the proposed RASC technique and the synchronization strategy when compare to peer works. In the simulation, the proposed synchronization strategy successfully recovers an encrypted received image on a communication channel.The article suggests some future research problems to extend the use of the proposed work.     

Effect of Graphene Nanoplatelets addition on mechanical properties of pure aluminum using a semi-powder method

In recent years, graphene has attracted considerable research interest in all fields of science due to its unique properties. Its excellent mechanical properties lead it to be used in nano-composites for strength enhancement. This paper reports an Aluminum–Graphene Nanoplatelets(Al/GNPs)composite using a semi-powder method followed by hot extrusion. The effect of GNP nano-particle integration on tensile, compressive and hardness response of Al is investigated in this paper. It is demonstrated that 0.3 wt% Graphene Nanoplatelets distributed homogeneously in the matrix aluminum act as an effective reinforcing filler to prevent deformation. Compared to monolithic aluminum(in tension), Al–0.3 wt% GNPs composite exhibited higher 0.2% yield strength(+14.7%), ultimate tensile strength(+11.1%) and lower failure strain( -40.6%). Surprisingly, compared to monolithic Al(in compression), Al–0.3 wt% GNPs composite exhibited same 0.2% compressive yield strength and lower ultimate compression strength(- 7.8%),and lower failure strain(- 20.2%). The Al–0.3 wt% GNPs composite exhibited higher Vickers hardness compared to monolithic aluminum(+11.8%).Scanning electron microscopy(SEM), Energy-Dispersive X-ray Spectroscopy(EDS) and X-ray diffraction(XRD) were used to investigate the surface morphology, elemental percentage composition, and phase analysis, respectively.     

Template/surfactant free and UV light irradiation assisted fabrication of Mn-Co oxides composite nanorings: Structure and synthesis mechanism

A facile, green, cost effective, and template or surfactant free strategy via a two-step route i.e. UV irradiation followed by dissolution-growth for the controlled synthesis of Mn-Co composite nanorings at room temperature was proposed. The nanorings structures and the process were systematically studied via TEM, HRTEM, EDX and XRD. Bir-MnO_2 nanosheets first formed through the direct photolysis of KMnO_4 under UV light irradiation. This was followed by a dissolution-growth process via the dissolution of Bir-MnO_2 nanosheets by the generated H~+ from the redox reaction between the added Co(NO_3)_2 and residual KMnO_4, as well as the accompanied formation of CoOOH, and Mn-Co composite nanorings. It was found that a balance between the dissolution and growth rate was needed. Suitable pH, KMnO_4 presence and the starting nanosheets like Bir-MnO_2 were the key factors for the formation of nanorings. The obtained Mn-Co nanorings/TiO_2 showed enhanced efficiency for the catalytic oxidation of HCHO. Based on the above understandings, it is believed that the developed dissolution-growth method can be adopted for the designing and preparation of other Mn-Co composite nanostructures which can be further applied for environmental pollution remediation.     

Spider mites (Acari: Tetranychidae) of Saudi Arabia: two new species,new records and a key to all known species

A total of 18 spider mite species belonging to 10 genera of the family Tetranychidae (Acari: Prostigmata) are reported from different provinces of Saudi Arabia (SA). Among these, two new species, Sonotetranychus madinahensis sp. nov. and Tetranychus salicornicus sp. nov., belonging to the subfamily Tetranychinae are described and illustrated. Also, five genera and 11 species are new to the mite fauna of SA. The distribution and host data of all recorded species in the current study are provided. A key to all spider mite species of SA is provided as well as a key to the species of the armenychus species group of the genus Tetranychus Dufour, based on males.

www.zoobank.org/urn:lsid:zoobank.org:pub:C41BB3ED-99D5-4DCF-B557-09526FA7D56B     

Identification of an S5n allele in Oryza rufipogon Griff. and its effect on embryo sac fertility

Oryza rufipogon exhibits abundant genetic diversity and contains many elite genes. In this work, a total of 441 accessions of O. rufipogon were genetically examined using the functional marker S5n, revealing that 18 accessions carried the S5n allele with a heterozygous genotype (S5nS5i/j). Of these accessions, 14 were from Guangdong Province, 2 from Guangxi Zhuang Autonomous Region, 1 from Hainan Province and 1 from Jiangxi Province. Further sequence analysis spanning both sides of the deletion in S5n allel...