神经网络算法在股指预测中的应用

GMDH是一种具有自组织特征的数据处理方法,适用于非线性系统的建模,股指是一种重要的金融数据,具有混沌特性。该文将相空间重构引入了GMDH神经网络的建模中,并将之应用于道琼斯等股指的预测。同BP神经网络方法及一阶局域预测法相比,GMDH获得了更好的预测效果。

Prediction of the Helix/Sheet Content of Proteins from Their Primary Sequences by Neural Network Method

The amino acid composition and the biased auto-correlation function are considered as features, BP neural network algorithm is used to synthesize these features. The prediction accuracy of this method is verified by using the independent non-homologous protein database. It is shown that the average absolute errors for resubstitution test are 0.070 and 0.068 with the standard deviations 0.049 and 0.047 for the prediction of the content of α-helix and β-sheet respectively. For cross-validation test, the average absolute errors are 0.075 and 0.070 with the standard deviations 0.050 and 0.049 for the prediction of the content of α-helix and β-sheet respectively. Compared with the other methods currently available, the BP neural network method combined with the amino acid composition and the biased auto-correlation function features can effectively improve the prediction accuracy.

Exact Solutions of VNE: A Survey

Network virtualization is an enabling technology of running multiple virtual networks on a shared substrate network. It aims to deal with the ossification of current network architecture. As a crucial component of network virtualization, virtual network embedding(VNE) can efficiently and effectively allocates the substrate resource to proposed virtual network requests. According to the optimization strategy, VNE approaches can be classified into three categories: exact, heuristic and meta-heuristic solution. The VNE exact solution is the foundation of its corresponding heuristic and meta-heuristic solutions. This paper presents a survey of existing typical VNE exact solutions, and open problems for the future research of VNE exact solutions are proposed.

SPEECH EMOTION RECOGNITION USING MODIFIED QUADRATIC DISCRIMINATION FUNCTION

Quadratic Discrimination Function （QDF） is commonly used in speech emotion recognition, which proceeds on the premise that the input data is normal distribution. In this paper, we propose a transformation to normalize the emotional features, emotion recognition. Features based on prosody then derivate a Modified QDF （MQDF） to speech and voice quality are extracted and Principal Component Analysis Neural Network （PCANN） is used to reduce dimension of the feature vectors. The results show that voice quality features are effective supplement for recognition, and the method in this paper could improve the recognition ratio effectively.

Simulation of Morphologies and Mechanical Properties of A/B Polymer Blend Film

The effects of blend composition and micro-phase structure on the mechanical behavior of A/B polymer blend film are studied by coupling the Monte Carlo(MC) simulation of morphology with the lattice spring model(LSM) of micro mechanics of materials.The MC method with bond length fluctuation and cavity diffusion algorithm on cubic lattice is adopted to simulate the micro-phase structure of A/B polymer blend.The information of morphology and structure is then inputted to the LSM composed of a three-dimensional network of springs to obtain the mechanical properties of polymer blend film.Simulated results show that the mechanical response is mainly affected by the density and the composition of polymer blend film through the morphology transition.When a force is applied on the outer boundary of polymer blend film,the vicinity of the inner cavities experiences higher stresses and strains responsible for the onset of crack propagation and the premature failure of the entire system.

The retromer component SNX6 interacts with dynactin p150Glued and mediates endosome-to-TGN transport

The retromer is a protein complex that mediates retrograde transport of transmembrane cargoes from endosomes to the trans-Golgi network （TGN）. It is comprised of a cargo-selection subcomplex of Vps26, Vps29 and Vps35 and a membrane-binding coat subcomplex of sorting nexins （SNXs）. Previous studies identified SNX1/2 as one of the components of the SNX subcomplex, and SNX5/6 as candidates for the second SNX. How the retromer-associated cargoes are recognized and transported by molecular motors are largely unknown. In this study, we found that one of SNX1/2＇s dimerization partners, SNX6, interacts with the p150Gued subunit of the dynein/dynactin motor complex. We present evidence that SNX6 is a component of the retromer, and that recruitment of the motor complex to the membrane-associated retromer requires the SNX6-pl50Gued interaction. Disruption of the SNX6-pl50Glued interaction causes failure in formation and detachment of the tubulovesicular sorting structures from endosomes and results in block of CI-MPR retrieval from endosomes to the TGN. These observations indicate that in addition to SNX1/2, SNX6 in association with the dynein/dynactin complex drives the formation and movement of tubular retrograde intermediates.

Combination of Ecoprofile and Least-cost Model for Eco-network Planning

The protecting requirements and functional connectivity of species in isolated habitat patches are crucial factors of eco-network planning.This study aimed to improve the method of eco-network planning for species conservation.Ecoprofiling was used to group the species by similar behavior types,namely,choice of ecosystem,area requirement,and short distance dispersal abilities.A least-cost model was used to simulate the optimal corridor location to maintain functional connectivity.A combination of ecoprofile and least-cost model was hired to develop an eco-network that promoted species conservation.A case study was also conducted in Beijing,China.In addition to the required ecosystem,habitat area is an important parameter for habitat extraction.Habitat area can remove noise habitat patches because of lacking area.Short-distance dispersal can be used to identify corridor requirements and avoid unnecessary building requirements.Species with various dispersal abilities exhibit significant differences in terms of corridor length and location requirement.Habitat isolation is the main threat for weakly mobile species,and habitat loss is the major risk of mobile species protection.Different species groups also exhibit distinct landscape pattern demands for an eco-network,and the eco-network planning based on specific species can not protect other species.We proposed that a combination of ecoprofile and least-cost model improved the efficiency of species conservation by eco-network planning.

Study on the network delay of periodic information in the NCS based on EPA

The network delay of the periodic messages transmission in the network control system （NCS） based on Ethemet for plant automation （EPA） is analyzed from the theoretical and experimental perspective in this paper. The composition and the characteristics of the network delay of EPA periodic messages transmission in a subnet is studied through analyzing the information transmission regularity and EPA deterministic scheduling mechanism. On this basis, the queuing delay at communication schedule management entity （EPA _ CSME） that is the most important component of network delay is analyzed, during which the formulas for the queuing delay of periodic messages and other real time parameters are proposed. Furthermore, an experiment is developed to test each component of network delay of periodic messages transmission in a EPA subnet. According to the experimental and the theoretical analysis, the conclusion is drawn that the delay during which the periodic messages wait for the periodic messages transmission time slice is the main factor that causes considerable network delay, and improvement method is presented.

Forecasting available parking space with largest Lyapunov exponents method

The techniques to forecast available parking space(APS) are indispensable components for parking guidance systems(PGS). According to the data collected in Newcastle upon Tyne, England, the changing characteristics of APS were studied. Thereafter, aiming to build up a multi-step APS forecasting model that provides richer information than a conventional one-step model, the largest Lyapunov exponents(largest LEs) method was introduced into PGS. By experimental tests conducted using the same dataset, its prediction performance was compared with traditional wavelet neural network(WNN) method in both one-step and multi-step processes. Based on the results, a new multi-step forecasting model called WNN-LE method was proposed, where WNN, which enjoys a more accurate performance along with a better learning ability in short-term forecasting, was applied in the early forecast steps while the Lyapunov exponent prediction method in the latter steps precisely reflect the chaotic feature in latter forecast period. The MSE of APS forecasting for one hour time period can be reduced from 83.1 to 27.1(in a parking building with 492 berths) by using largest LEs method instead of WNN and further reduced to 19.0 by conducted the new method.

Online Edutainment Videos Recontextualizing and Reconceptualizing Expert Discourse in a Participatory Web-culture

The online world is becoming more and more edutainment, where learning, getting informed and entertained seem to be part of one and the same activity. As a result of this current fascination, people are drawn increasingly towards a new genre, i.e. free online 20-minute long lectures that borrow from film and storytelling techniques, that are offering an engaging series of speeches and even courses in many different scientific subjects. Though English as a lingua franca is still the dominant language of the internet, as a result of a growing new trend, namely crowdsourcing translation, knowledge dissemination is further enhanced and is now reaching further into many different cultures, allowing even the so-called minor languages to regain dignity and circulate, by engaging native speakers from different cultural backgrounds. This paper offers an overview on the phenomenon of online edutainment considering the role played by collaborative users who not only enjoy but also create and translate content. In addition, a case study focused on TED Talks allows a more in depth analysis of the new genre and the increasing need for subtitling scripts.

Research on the oral teaching of university network English in promoting students＇ creative thinking abilities

Many authors probe into the models of promoting college students＇ creative thinking abilities from their own perspectives, among which there are innovative works. However, whether we can improve the above abilities of college students in the oral teaching of university network English still remains blank in the study. Based on the deconstruction of the creative thinking abilities of the students, we should build the components of this capacity from four aspects.

Segregation between the parietal memory network and the default mode network： effects of spatial smoothing and model order in ICA

Abstract A brain network consisting of two key parietal nodes, the precuneus and the posterior cingulate cortex, has emerged from recent fMRI studies. Though it is anatomically adjacent to and spatially overlaps with the default mode network （DMN）, its function has been associated with memory processing, and it has been referred to as the parietal memory network （PMN）. Independent component analysis （ICA） is the most common data-driven method used to extract PMN and DMN simultaneously. However, the effects of data preprocessing and parameter determi- nation in ICA on PMN-DMN segregation are completely unknown. Here, we employ three typical algorithms of group ICA to assess how spatial smoothing and model order influence the degree of PMN-DMN segregation. Our findings indicate that PMN and DMN can only be stably separated using a combination of low-level spatial smoothing and high model order across the three ICA algorithms. We thus argue for more considerations on parametric settings for interpreting DMN data.

GMP-quadruplex-based hydrogels stabilized by lanthanide ions

This work describes the gelation behaviors and properties of a biological molecule, guanosine 5′-monophosphate disodium salt(GMP), in the presence of trivalent lanthanide ions. Hydrogels composed of GMP-quadruplexes were prepared by adjusting p H,through which the protonation of phosphate group was controlled to tune the interactions between lanthanide ions and GMP.Within the p H region of 2–6, the electrostatic interaction between lanthanide ions and phosphate group is hindered and the cation-dipole interaction acts as the main driving force for the formation of G-quadruplexes. All the hydrogels were found consisting of three-dimensional network of the intertwining one-dimensional nanofibers formed by the stacking G-quartets induced by lanthanide ions. A significant fluorescence enhancement of thioflavin T(Th T), a fluorescent molecule, was found to be triggered by the G-quadruplex structures, for which the rotation of chromophoric groups on Th T molecules were prohibited due to the implant into the G-quadruplex structures.

Oscillatory Dynamics and Oscillation Death in Complex Networks Consisting of Both Excitatory and Inhibitory Nodes

Zn neural networks, both excitatory and inhibitory cells play important roles in determining the functions of systems. Various dynamical networks have been proposed as artificial neural networks to study the properties of biological systems where the influences of excitatory nodes have been extensively investigated while those of inhibitory nodes have been studied much less. In this paper, we consider a model of oscillatory networks of excitable Boolean maps consisting of both excitatory and inhibitory nodes, focusing on the roles of inhibitory nodes. We find that inhibitory nodes in sparse networks （smM1 average connection degree） play decisive roles in weakening oscillations, and oscillation death occurs after continual weakening of oscillation for sufficiently high inhibitory node density. In the sharp contrast, increasing inhibitory nodes in dense networks may result in the increase of oscillation amplitude and sudden oscillation death at much lower inhibitory node density and the nearly highest excitation activities. Mechanism under these peculiar behaviors of dense networks is explained by the competition of the duplex effects of inhibitory nodes.

Novel degradable polymer networks containing acetal components

A novel copolymer network with acetal structure was prepared using bis[4-(vinyloxy)butyl](4-methyl-1,3-phenylene)biscarbamate(BECT)as the crosslinking agent.Firstly,a tri-copolymer of maleic anhydride(MAn),n-butyl vinyl ether(BVE)and 4-hydroxybutyl vinyl ether(HBVE)was synthesized via free-radical polymerization with 2,2′-azobisisobutyronitrile as the initiator.The tri-copolymer consisted of two sorts of alternating units,MAn-alt-BVE and MAn-alt-HBVE.The linear copolymer Poly((MAn-alt-BVE)-co-(MAn-alt-HBVE))with pending hydroxyl groups was then combined with BECT in the presence of pyridinium p-toluenesulfonate,generating a copolymer network comprising acetal components in the crosslinking segment. This polymer network exhibited degradation in acid conditions.

Weighted Scaling in Non-growth Random Networks

We propose a weighted model to explain the self-organizing formation of scale-free phenomenon in nongrowth random networks. In this model, we use multiple-edges to represent the connections between vertices and define the weight of a multiple-edge as the total weights of all single-edges within it and the strength of a vertex as the sum of weights for those multiple-edges attached to it. The network evolves according to a vertex strength preferential selection mechanism. During the evolution process, the network always holds its totM number of vertices and its total number of single-edges constantly. We show analytically and numerically that a network will form steady scale-free distributions with our model. The results show that a weighted non-growth random network can evolve into scMe-free state. It is interesting that the network also obtains the character of an exponential edge weight distribution. Namely, coexistence of scale-free distribution and exponential distribution emerges.