中国公募基金择时方法比较与择时能力研究

文章首先通过数据模拟的方法比较了文献中存在的四种针对公募基金择时能力的方法,研究认为基于日度数据的TM模型与HM模型对于公募基金择时有着较高的判断准确性。然后基于2003—2020年中国股票型与混合型共计3175只基金的数据,并对其择时能力进行评估,发现有部分基金存在显著的择时能力。在使用bootstrap调整了标准误差后,依然发现部分基金有着显著的择时能力。同时文章还发现高择时能力的基金横截面上能吸引更多的资金流入。而且如果使用择时能力指标,可以在较长时间窗口内筛选出表现更好的基金资产组合。

论电视剧艺术学的研究方法

作为一门独立的、新兴的学科，电视剧艺术学需要科学的研究方法。本文从研究电视剧艺术的本性展开，联系电视剧艺术作品，参照西方的文学艺术研究方法，重点阐述了电视剧艺术学研究中的两个重要命题：一、电视剧艺术学方法论的科学本体内涵；二、电视剧艺术研究方法择定的指导原则。

古诗词鉴赏择项探微

古诗词鉴赏是高考必考的内容。由于用来做考题的诗词一般是考生不曾读过的,或者是似曾相识却又没有怎么留意的。

不一样的选择

周丽丽，1996年高考，文科国选政治，考分在本科线以上，但最后放弃本科，进入上海旅游高等专科学校导游系，现在旅行社从事出境游方面工作。

选好金融工具 规避汇率风险

本文针对汇率改革后青海省涉外企业对规避汇率风险的各类金融工具了解甚少的现状,就目前涉外企业可以选择的五种主要的金融避险工具及其适用范围和使用方法进行了介绍和分析,协助企业适应汇率改革,提高企业生存和盈利能力。

一类高维映射不变圈的计算

在一类高维映射中实现了由Iooss等人提出的映射不变圈的算法.首先分析了不变圈的分岔条件,然后通过Fredholm择一方法分析了在计算不变圈过程中出现的一类方程解的存在性,再根据不变圈上映射到自身的不变性,通过分析振幅各阶项的系数,最终在一高维映射中实现了不变圈的计算.

Method and standard for selecting elite nut trees of Korean pine

The fruit-bearing quantities of nut Korean pines (Pinus Koraiensis) of natural stands in Changbai Mountain, Xiaoxing'an Mountain, and Wanda Mountain and of artificial forest in Hegang area of Heilongjiang Province were investigated and measured by seed collection of singletree during 1988–1998. In order to evaluate the elite nut tree of fructification, the characteristics of fructification of Korena pine, including, the fruit-bearing quantity, output of seed, quantity of cone, cone size, seed size, the ratio of null seed by solid seed, seed percentage of cone, rate of the cones infested with pest, and fruit-bearing index, etc., were analyzed with the variance analysis, multiple comparison and stepwise regression to obtain the contribution ratio of each fruit-bearing factor to fruit-bearing quantity. The multiple correlation factors and the partial correlation factors for fruit-bearing quantities of Korean pine were determined for different geographical areas, and the cone length, thousand-grain-weight, and the seed percentage of cone were considered as important indices for selection of elite trees. The method of modified weighted coefficients was adopted to select the elite nut trees of Korean pine. Standards for selecting elite nut trees from the natural stands and artificial forest of Korean pine were established. This study could provde selection method and standard of elite nut trees for setting up seed orchard of Korean Pine.

Conceptual design of oil palm fibre reinforced polymer hybrid composite automotive crash box using integrated approach

A hybrid conceptual design approach was introduced in this study to develop a conceptual design of oil palm polymer composite automotive crash box(ACB). A combination of theory of inventive problem solving(TRIZ), morphological charts and biomimetics was applied where the foremost requirements in terms of the material characteristics, function specifications, force identification, root cause analysis, geometry profile and design selection criteria were considered. The strategy was to use creations of nature to inspire five innovative conceptual designs of the ACB structure and the AHP method was applied to perform the pairwise analysis of selecting the best ACB conceptual design. A new conceptual design for a composite ACB was conceived bearing in mind the properties of natural fibre, unlike those of conventional materials such as steel alloys and aluminium alloys. The design with the highest ranking(26.6 %) was chosen as the final conceptual design, which was the one with a honeycomb structure for the outermost profile, reinforced with a spider web structure inside the part, supported by fibre foam structure extracted from the woodpecker sponge tissue at the centre to maximize the energy absorption capability. The new design could solve the problem of bending collapse which is a major cause of failure to absorb maximum impact energy for ACB during collision. However, the final conceptual design will still need several modifications for production and assembly purposes, which will be completed in a further study.

Digital Rights Management：Model,Technology and Application

with rapid achievement of current information technology and computing ability and applications,much more digital content such as films,cartoons,design drawings,office documents and software source codes are produced in daily work,however to protect the content being copying,shared or deliberately stolen by inside or outside,digital rights management(DRM) became more and more important for digital content protection.In this paper,we studied various DRM model,technology and application,and first proposed DRM Security Infrastructure(DSI),in which we defined encryption,hash,signature algorithm,watermarking algorithms,authentication,usage control,trusted counter,conditional trace,secure payment,and based on the DSI we then proposed a whole classification approach and architecture of all kinds of DRMs,in which we proposed 6 typical classes of copyrights and content protection DRMs architecture:(1) Software-oriented DRM,(2) e Book-oriented DRM,(3) Video-oriented DRM,(4) Image-Oriented DRM(5) Unstructured data oriented DRM,(6) Text-oriented DRM.Based on the above DSI,we then proposed a dynamic DRM model selection method for various DRM application,which can be adapted dynamically for different technology of different applications,which can provide awhole solution for variant DRM development in a rapid and customized mode.The proposed DRM method,technology and application in this paper provided a common,flexible and extendable solution for variant DRM scenes,and can support rapid and customized development.Moreover,we proposed an opinion that the future life will enter into a new era that the content usage and consumption will not again adopt DRM technology rather than with law,liberty and morality.

A Heterogeneous Information Fusion Deep Reinforcement Learning for Intelligent Frequency Selection of HF Communication

The high-frequency(HF) communication is one of essential communication methods for military and emergency application. However, the selection of communication frequency channel is always a difficult problem as the crowded spectrum, the time-varying channels, and the malicious intelligent jamming. The existing frequency hopping, automatic link establishment and some new anti-jamming technologies can not completely solve the above problems. In this article, we adopt deep reinforcement learning to solve this intractable challenge. First, the combination of the spectrum state and the channel gain state is defined as the complex environmental state, and the Markov characteristic of defined state is analyzed and proved. Then, considering that the spectrum state and channel gain state are heterogeneous information, a new deep Q network(DQN) framework is designed, which contains multiple sub-networks to process different kinds of information. Finally, aiming to improve the learning speed and efficiency, the optimization targets of corresponding sub-networks are reasonably designed, and a heterogeneous information fusion deep reinforcement learning(HIF-DRL) algorithm is designed for the specific frequency selection. Simulation results show that the proposed algorithm performs well in channel prediction, jamming avoidance and frequency channel selection.

Diffusion Monte Carlo Study of Bond Dissociation Energies for BH2, B（OH）2, BCl2, and BCI

On basis of bond dissociation energies （BDEs） for BH2, B（OH）2, BCl2, and BCl, the diffusion Monte Carlo （DMC） method is applied to explore the BDEs of HB-H, HOB-OH, ClB-Cl, and B-Cl. The effect of the choice of orbitals, as well as the backflow transformation, is studied. The Slater-Jastrow DMC algorithm gives BDEs of 359.1±0.12 kJ/mol for HB-H, 410.5±0.50 kJ/mol for HOB-OH, 357.8±1.46 kJ/mol for ClB-Cl, and 504.5±0.96 kJ/mol for B-Cl using B3PW91 orbitals and similar BDEs when B3LYP orbitals are used. DMC with backflow corrections （BF-DMC） gives a HB-H BDE of 369.9±0.12 kJ/mol which is close to one of the available experimental value （375.8 kJ/mol）. In the case of HOB-OH BDE, the BF-DMC calculation is 446.04-1.84 k J/mol that is closer to the experimental BDE. The BF-DMC BDE for ClB-Cl is 343.2±2.34 kJ/mol and the BF-DMC B-Cl BDE is 523.3±0.33 kJ/mol, which are close to the experimental BDEs, 341.9 and 530.0 kJ/mol, respectively.

Sequential Extraction of Aluminum and Iron from Acidic Soils by Chemical Selective Dissolution Methods

Potassium chloride, Na-pyrophosphate, CuCl2, NH4-oxalate, dithionite-citrate-bicarbonate (DCB) and Na-citrate solutions were employed to extract aluminum (Al) and iron (Fe) sequentially and separately from 15 acidic soils located at the Mangshan Mountains, Hunan Province, China. Many evidences showed that separate pyrophosphate extracted mainly KCI-extractable Al, organo-Al complexes and some inorganic Al compounds, whereas separate CuCl2 extracted KCl-extractable Al and some organo-Al complexes. CuCl2 extracted much less amounts of Al than pyrophosphate did from the soils. Separate oxalate did not extract all KCl-Pyrophosphate- CuCl2 -oxalate sequentially extractable Al and Fe. Also, separate DCB did not extract all KCl- pyrophosphate- CuCl2 -oxalate- DCB sequentially extractable Al. The forms of Al extracted by oxalate and DCB from the soils were majorly noncrystalline. The interlayered materials of 1.4-nm intergrade minerals of the soils were attributed mainly to hydroxy Al polymers.

TWO-STAGE SENTENCE SELECTION APPROACH FOR MULTI-DOCUMENT SUMMARIZATION

Compared with the traditional method of adding sentences to get summary in multi-document summarization,a two-stage sentence selection approach based on deleting sentences in acandidate sentence set to generate summary is proposed,which has two stages,the acquisition of acandidate sentence set and the optimum selection of sentence.At the first stage,the candidate sentenceset is obtained by redundancy-based sentence selection approach.At the second stage,optimum se-lection of sentences is proposed to delete sentences in the candidate sentence set according to itscontribution to the whole set until getting the appointed summary length.With a test corpus,theROUGE value of summaries gotten by the proposed approach proves its validity,compared with thetraditional method of sentence selection.The influence of the token chosen in the two-stage sentenceselection approach on the quality of the generated summaries is analyzed.

Optimization model of unascertained measurement for underground mining method selection and its application

An optimization model of underground mining method selection was established on the basis of the unascertained measurement theory.Considering the geologic conditions,technology,economy and safety production,ten main factors influencing the selection of mining method were taken into account,and the comprehensive evaluation index system of mining method selection was constructed.The unascertained evaluation indices corresponding to the selected factors for the actual situation were solved both qualitatively and quantitatively.New measurement standards were constructed.Then,the unascertained measurement function of each evaluation index was established.The index weights of the factors were calculated by entropy theory,and credible degree recognition criteria were established according to the unascertained measurement theory.The results of mining method evaluation were obtained using the credible degree criteria,thus the best underground mining method was determined.Furthermore,this model was employed for the comprehensive evaluation and selection of the chosen standard mining methods in Xinli Gold Mine in Sanshandao of China.The results show that the relative superiority degrees of mining methods can be calculated using the unascertained measurement optimization model,so the optimal method can be easily determined.Meanwhile,the proposed method can take into account large amount of uncertain information in mining method selection,which can provide an effective way for selecting the optimal underground mining method.

Optimum mining method selection using fuzzy analytical hierarchy process–Qapiliq salt mine,Iran

Mining method selection is the first and the most critical problem in mine design and depends on some parameters such as geotechnical and geological features and economic and geographic factors. In this paper, the factors affecting mining method selection are determined. These factors include shape, thick- ness, depth, slope, RMR and RSS of the orebody, RMR and RSS of the hanging wall and footwall. Then, the priorities of these factors are calculated. In order to calculate the priorities of factors and select the best mining method for Qapiliq salt mine, Iran, based on these priorities, fuzzy analytical hierarchy process （AHP） technique is used. For this purpose, a questionnaire was prepared and was given to the associated experts. Finally, after a comparison carried out based on the effective factors, between the four mining methods including area mining, room and pillar, cut and fill and stope and pillar methods, the stope and nillar mining method was selected as the most suitable method to this mine.

Effect of twine thickness on size-selectivity of driftnet for the yellow croaker Larimichthys polyactis in southwestern Sea of Korea

In order to determine the effect of twine thickness on the size-selectivity of the driftnet used for the yellow croaker, size-selectivity tests were conducted with three different twine thicknesses(monofi lament diameters of 0.279 mm(number's method; No. 3), 0.321 mm(No. 4), and 0.360 mm(No. 5)) of driftnets for the yellow croaker in the seas around Chooja-do, Jeju Islands. The selectivity curve was estimated by using Kitahara's method. In order to determine the physical properties of the twine used in the experimental fi shing nets, we measured the breaking load, elongation, and stiffness under both dry and wet conditions. In terms of physical properties, the thinnest twine(No. 3) had the strongest breaking strength per unit cross-sectional area, along with good elongation and excellent fl exibility. The thickest twine(No. 5) had the lowest fl exibility. In terms of selectivity, the net of No. 3 twine showed the broadest selection range and, thus, a relatively low selectivity compared with the other nets, while the less fl exible net of No. 5 twine showed the narrowest selectivity range and high selectivity. In addition, it was found that a thicker twine resulted in a smaller haul of small fi sh. Therefore, it can be inferred that the thickness of the twine affects the size of the catch and selectivity, and thus the size composition of the catch as well.

Optimal measurement configurations for kinematic calibration of six-DOF serial robot

An optimal measurement pose number searching method was designed to improve the pose selection method.Several optimal robot measurement configurations were added to an initial pre-selected optimal configuration set to establish a new configuration set for robot calibration one by one.The root mean squares (RMS) of the errors of each end-effector poses after being calibrated by these configuration sets were calculated.The optimal number of the configuration set corresponding to the least RMS of pose error was then obtained.Calibration based on those poses selected by this algorithm can get higher end-effector accuracy,meanwhile consumes less time.An optimal pose set including optimal 25 measurement configurations is found during the simulation.Tracking errors after calibration by using these poses are 1.54,1.61 and 0.86 mm,and better than those before calibration which are 7.79,7.62 and 8.29 mm,even better than those calibrated by the random method which are 2.22,2.35 and 1.69 mm in directions X,Y and Z,respectively.

A Novel Efficient Method for Synthesis of β-Organoseleno Substituted Allyl Sulfoxides

Hydroselenation of 1, 2-allenyl sulfoxides give 2-organoseleno substituted allyl sulfoxides in high yields and the reaction is absolute regioselective.

A purely data driven method for European option valuation

An alternative option pricing method is proposed based on a random walk market model. The minimal entropy martingale measure which adopts no arbitrage opportunity in the market, is deduced for this market model and is used as the pricing measure to evaluate European call options by a Monte Carlo simulation method. The proposed method is a purely data driven valuation method without any distributional assumption about the price process of underlying asset. The performance of the proposed method is compared with the canonical valuation method and the historical volatility-based Black-Scholes method in an artificial Black-Scholes world. The simulation results show that the proposed method has merits, and is valuable to financial engineering.

Network Selection Based on Context-Awareness Services

In this paper,we propose a systemic architecture of network selection based on context-awareness services,which gathers contextual information that includes such network information,user information and local information.This network selection strategy considers the Quality of Service(QoS) and user preferences.Also,it perceives contexts such as speed,coverage percentage and location,etc.,and it eventually performs network selection decision making and network execution based on multiple factors.From the perspective of network decision,it presents two network selection algorithms,namely the fuzzy mathematics evaluation method and multiple attribute decision making using the TOPSIS evaluation method.System simulations suggest that network selection based on the mathematics evaluation method is much faster than the TOPSIS evaluation method.However,the TOPSIS evaluation method is practically more efficient.The network selection method based on context-awareness provides an effective and flexible network vertical handover strategy,and ensures a good accuracy and efficiency.