Massive Files Prefetching Model Based on LSTM Neural Network with Cache Transaction Strategy

In distributed storage systems,file access efficiency has an important impact on the real-time nature of information forensics.As a popular approach to improve file accessing efficiency,prefetching model can fetches data before it is needed according to the file access pattern,which can reduce the I/O waiting time and increase the system concurrency.However,prefetching model needs to mine the degree of association between files to ensure the accuracy of prefetching.In the massive small file situation,the sheer volume of files poses a challenge to the efficiency and accuracy of relevance mining.In this paper,we propose a massive files prefetching model based on LSTM neural network with cache transaction strategy to improve file access efficiency.Firstly,we propose a file clustering algorithm based on temporal locality and spatial locality to reduce the computational complexity.Secondly,we propose a definition of cache transaction according to files occurrence in cache instead of time-offset distance based methods to extract file block feature accurately.Lastly,we innovatively propose a file access prediction algorithm based on LSTM neural network which predict the file that have high possibility to be accessed.Experiments show that compared with the traditional LRU and the plain grouping methods,the proposed model notably increase the cache hit rate and effectively reduces the I/O wait time.

A Surfing Concurrence Transaction Model for Key-Value NoSQL Databases

As more and more application systems related to big data were developed, NoSQL (Not Only SQL) database systems are becoming more and more popular. In order to add transaction features for some NoSQL database systems, many scholars have tried different techniques. Unfortunately, there is a lack of research on Redis’s transaction in the existing literatures. This paper proposes a transaction model for key-value NoSQL databases including Redis to make possible allowing users to access data in the ACID (Atomicity, Consistency, Isolation and Durability) way, and this model is vividly called the surfing concurrence transaction model. The architecture, important features and implementation principle are described in detail. The key algorithms also were given in the form of pseudo program code, and the performance also was evaluated. With the proposed model, the transactions of Key-Value NoSQL databases can be performed in a lock free and MVCC (Multi-Version Concurrency Control) free manner. This is the result of further research on the related topic, which fills the gap ignored by relevant scholars in this field to make a little contribution to the further development of NoSQL technology.

Evaluation method for assessing the auxiliary service transaction mechanism in regional power markets

Accurate and seamless auxiliary services in the power market can guarantee smooth and continuous power system operation. China’s new round of power system reform has entered a critical period, and reform implementation requires comprehensive improvements in the maturity of the supporting auxiliary service market. This study reviews the development status and evolution path of the European unified power market and the US regional power market, provides experience for the development of China’s regional power market, then identifies the key influencing factors of auxiliary service trading mechanism design in regional power markets. To analyze the rationality of the auxiliary service trading evaluation index, this paper established an evaluation model for assessing regional power markets. Using combined weight optimization, the gray correlation TOPSIS method was applied to comprehensively evaluate auxiliary service trading in the regional power market. Finally, the application of the proposed evaluation method was briefly analyzed to examine four regional power markets in China and evaluate the effectiveness of current market construction in different regions and provide suggestions for future market construction.

Parallel Binomial American Option Pricing under Proportional Transaction Costs

We present a parallel algorithm that computes the ask and bid prices of an American option when proportional transaction costs apply to trading in the underlying asset. The algorithm computes the prices on recombining binomial trees, and is designed for modern multi-core processors. Although parallel option pricing has been well studied, none of the existing approaches takes transaction costs into consideration. The algorithm that we propose partitions a binomial tree into blocks. In any round of computation a block is further partitioned into regions which are assigned to distinct processors. To minimise load imbalance the assignment of nodes to processors is dynamically adjusted before each new round starts. Synchronisation is required both within a round and between two successive rounds. The parallel speedup of the algorithm is proportional to the number of processors used. The parallel algorithm was implemented in C/C++ via POSIX Threads, and was tested on a machine with 8 processors. In the pricing of an American put option, the parallel speedup against an efficient sequential implementation was 5.26 using 8 processors and 1500 time steps, achieving a parallel efficiency of 65.75%.

TransJ： An Abstract Independent-Framework for Weaving Crosscutting Concern into Distributed Transactions

Implementing crosscutting concerns for transactions is difficult, even using aspect-oriented programming languages such as AspectJ. Many of these challenges arise because the context of a transaction-related crosscutting concern consists of loosely-coupled abstractions like dynamically-generated identifiers, timestamps, and tentative value sets of distributed resources. Current aspect-oriented programming languages do not provide joinpoints and pointcuts for weaving advice into high-level abstractions or contexts, like transaction contexts. To address these problems, we propose an extension to AspectJ framework, called TransJ, that allows developers to define pointcuts in terms of transaction abstractions and that automatically keeps track of context information for transactions. This paper describes TransJ as an abstract independent framework for weaving crosscutting concerns into high-level runtime abstractions, with which developers can implement transaction-related crosscutting concerns in modular, cohesive and loosely coupled transaction-aware aspects. Finally, this paper presents eight different ways in which TransJ can improve the reuse with preserving the performance of applications requiring transactions. Informally, these hypotheses are that TransJ yields （1） better encapsulation and separation of concern; （2） looser coupling and less scattering; （3） higher cohesion and less tangling; （4） reduces complexity; （5） improves obliviousness; （6） preserves efficiency; （7） improves extensibility; and （8） hastens the productivity. A brief discussion of experiment to test the hypotheses is provided, but the details of the experiment are left for another paper.

An Object-Oriented Transaction Model

In object-oriented database systems(OODBSs),the traditional transaction models are no longer suit- able because of the difference between the object-oriented data model(OODM)and the conventional da- ta models(e.g.relational data model).In this paper,transaction models for advanced databuse applica- tions are reviewed and their shortcomings are analyzed.Exchangeability of operations is proposed in- stead of commuativity and recoverability for using more semantics in transaction management.As a result,an object-oriented transaction model(in short,OOTM)is presented.It is not modeled for some special application,but directly based on object-oriented paradigms.A transaction is regarded as an interpretation of a method.Each transaction(even subtransactions)keeps relative ACID(Atomicity, Consistency,Isolation,Durability )properties,therefore the special problems appearing in OODBSs such as“long transactions”,“visibility of inconsistent database state”can be solved.

Optimal Dividend-Equity Issuance Strategy in a Dual Model with Fixed and Proportional Transaction Costs

In this paper, we consider the problem of optimal dividend payout and equity issuance for a company whose liquid asset is modeled by the dual of classical risk model with diffusion. We assume that there exist both proportional and fixed transaction costs when issuing new equity. Our objective is to maximize the expected cumulative present value of the dividend payout minus the equity issuance until the time of bankruptcy,which is defined as the first time when the company＇s capital reserve falls below zero. The solution to the mixed impulse-singular control problem relies on two auxiliary subproblems： one is the classical dividend problem without equity issuance, and the other one assumes that the company never goes bankrupt by equity issuance.We first provide closed-form expressions of the value functions and the optimal strategies for both auxiliary subproblems. We then identify the solution to the original problem with either of the auxiliary problems. Our results show that the optimal strategy should either allow for bankruptcy or keep the company＇s reserve above zero by issuing new equity, depending on the model＇s parameters. We also present some economic interpretations and sensitivity analysis for our results by theoretical analysis and numerical examples.

Bank transaction data modeling by optimized hybrid machine learning merged with ARIMA

The bank transactions are needed to be modeled to predict the future transactions of the banks based on the previous transactions.In order to achieve efficient modeling of bank data transactions,Deep Belief Network(DBN)and Neural network(NN)classifiers are used in this paper.Initially,the bank transaction data such as transaction count and amount are subjected to feature extraction to extract the statistical features.Now,the extracted data are modeled using the combination of DBN and NN models,where the average modeled output from both the network is considered as the final result.The above procedure is utilized for the two prediction models such as transaction count and transaction amount.Moreover,the transaction count from prediction model 1 is subjected to the Auto-Regressive Integrated Moving Average(ARIMA)model to compute the relationship between the transition count and transition amount.Here,as the main contribution,the number of hidden neurons in both DBN and NN are optimized or tuned accurately using the hybridized optimization models with Lion Algorithm(LA),and Artificial Bee Colony(ABC)named L-ABC model.The average of entire transactional amounts,i.e.the modeled outputs are matched with the actual data to validate the performance of the implemented model.

An Optimal Portfolio Model with Transaction Cost

In this paper, a convex programming model for portfolio select with trans- action costs was present, we proved the existence condition of optimal solution, and gave a simple example to the optimal solution.

Portfolio Optimization Model with Transaction Costs

The purpose of the article is to formulate, under the ∞ risk measure, a model of portfolio selection with transaction costs and then investigate the optimal strategy within the proposed. The characterization of a optimal strategy and the efficient algorithm for finding the optimal strategy are given.

Analysis of Specialized Production of Transaction Services Based on Essential Services Quantity

The specialized production of e-commerce transaction systems is an important research topic, which is of great significance for evaluating the development level and forecasting the development direction of e-commerce. However, there is a certain disparity between the current mainstream research model and reality, which leads to a deviated result. This paper puts forward a definition of ＂transaction efficiency＂ based on essential transaction services and establishes a model of the middleman＇s specialized production decision of transaction services. The research result shows that （1） transaction efficiency plays an important role in improving the middleman＇s specialized production level, （2） only when the transaction efficiency is higher than a certain threshold will the distribution middleman appear, and （3） the degree of economic specialization, price of commodities and transaction services, and other associated factors also affect the evolution of e-commerce transaction systems.

Ensuring consistency of Web services transaction

Composite Web services provide promising prospects for conducting cross-organizational Web service transactions. Such transactions generally require longer processing time and manipulate financially critical data. To efficiently manage these Web services transactions, isolation is commonly relaxed, but inconsistency will be caused by concurrently executing isolation-relaxing transactions. This article proposes an extension to the WS-Business Activity Protocol, which ensures the consistent executions of isolation-relaxing Web service transactions, and which is based on transaction dependency graphs distributed over multiple nodes. Furthermore, this article presents several algorithms implementing the protocol, and introduces the implement of a prototype system.

CVaR-hedging and its applications to equity-linked life insurance contracts with transaction costs

This paper analyzes Conditional Value-at-Risk(CVaR)based partial hedging and its applications on equity-linked life insurance contracts in a Jump-Diffusion market model with transaction costs.A nonlinear partial differential equation(PDE)that an option value process inclusive of transaction costs should satisfy is provided.In particular,the closed-form expression of a European call option price is given.Meanwhile,the CVaR-based partial hedging strategy for a call option is derived explicitly.Both the CVaR hedging price and the weights of the hedging portfolio are based on an adjusted volatility.We obtain estimated values of expected total hedging errors and total transaction costs by a simulation method.Furthermore,our results are implemented to derive target clients’survival probabilities and age of equity-linked life insurance contracts.

Optimal dividend and capital injection problem with a random time horizon and a ruin penalty in the dual model

In the dual risk model, we consider the optimal dividend and capital injection problem, which involves a random time horizon and a ruin penalty. Both fixed and proportional costs from the transactions of capital injection are considered. The objective is to maximize the total value of the expected discounted dividends, and the penalized discounted both capital injections and ruin penalty during the horizon, which is described by the minimum of the time of ruin and an exponential random variable. The explicit solutions for optimal strategy and value function are obtained, when the income jumps follow a hyper-exponential distribution.Besides, some numerical examples are presented to illustrate our results.

Reactive Power and FACTS Cost Models’ Impact on Nodal Pricing in Hybrid Electricity Markets

In a competitive environment reactive power management is an essential service provided by independent system operator taking into account the voltage security and transmission losses. The system operator adopts a transparent and non-dis-criminatory procedure to procure the reactive power supply for optimal deployment in the system. Since generators’ are the main source of reactive power generation and the cost of the reactive power should be considered for their noticeable impact on both real and reactive power marginal prices. In this paper, a method based on marginal cost theory is presented for locational marginal prices calculation for real and reactive power considering different reactive power cost models of generators’ reactive support. With the presence of FACTS controllers in the system for more flexible operation, their impact on nodal prices can not be ignored for wheeling cost determination and has also to be considered taking their cost function into account. The results have been obtained for hybrid electricity market model and results have also been computed for pool model for comparison. Mixed Integer Non-linear programming (MINLP) approach has been formulated for solving the complex problem with MATLAB and GAMS interfacing. The proposed approach has been tested on IEEE 24-bus Reliability Test System (RTS).

Stock Trading via Feedback Control： Stochastic Model Predictive or Genetic？

We seek a discussion about the most suitable feedback control structure for stock trading under the consideration of proportional transaction costs. Suitability refers to robustness and performance capability. Both are tested by considering different one-step ahead prediction qualities, including the ideal case （perfect price-ahead prediction）, correct prediction of the direction of change in daily stock prices and the worst-case （wrong price rate sign-prediction at all sampling intervals）. Feedback control structures are partitioned into two general classes： stochastic model predictive control （SMPC） and genetic. For the former class, three controllers are discussed, whereby it is distinguished between two Markowitz- and one dynamic hedging-inspired SMPC formulation. For the latter class, five trading algorithms are disucssed, whereby it is distinguished between two different moving average （MA） based strategies, two trading range （TR） based strategies, and one strategy based on historical optimal （HistOpt） trajectories. This paper also gives a preliminary discussion about how modified dynamic hedging-inspired SMPC formulations may serve as alternatives to Markowitz portfolio optimization. The combinations of all of the eight controllers with five different one-step ahead prediction methods are backtested for daily trading of the 30 components of the German stock market index DAX for the time period between November 27, 2015 and November 25, 2016.

Primary Study of Power-Exchanging Trans- action Model Among Price-Varied Power Plants in Practical Conditions

At present, electricity price to grid of domestic power plants is priced by the national administration based on the policy of "one power plant with one electricity price to grid," which is difficult to realize real bidding for access to grid in practice in a short term. This paper presents one kind of power-exchanging transaction model among price-varied power plants, which will be beneficial to price-varied power plants without any loss of profits of them and guarantee state-owned assets profits in minimum loss with no promotion of average price limit by power plants. Under ideal conditions, the computation results showed the sufficiency and necessity of power-exchanging transaction and maximum similarity with the requirements of optimized resources disposition in economics. The presented model is shown to be full of practicability and has been used in some part of power market.

Research on Contractual Model Selection of Farmers' Cooperatives——A Case Study of Production and Marketing Cooperative of Sweet Pomegranate in Mengzi,Yunnan

In the perspective of new institutional economics,we regard farmers' cooperatives as a "contractual set" integrating a series of long-term contractual relations,and transform the selection problem of organization forms into selection problem of contractual model within organization.By the theoretical framework of Transaction Cost Economics,we analyze the formation mechanism and determinant factors of contractual model of different farmers' cooperatives and conduct case study on Production and Marketing Cooperative of Sweet Pomegranate in Mengzi,Yunnan.The results show that selecting contractual forms of cooperatives is the result of weighing many factors;new organization model or contractual arrangement is complementary to the former system arrangement;the selection of cooperatives model is an important factor impacting cooperation efficiency and stability of organization.One organization model with efficiency not only hinges on the transaction characteristic of organization,but also considers the compatibility with exterior transaction environment.In the process of selecting contractual model,we should conform to objective evolving law,but not be in thrall to a certain given form.

我国数据要素市场治理的模式、现状与对策

要推动数据要素市场高质量发展,首先需要构建科学高效的市场治理机制。本文对数据要素市场治理素现状进行了梳理,提出市场化治理、垂直型治理和关系型治理等三种治理模式,并比较其特点,分析其现状与瓶颈。在此基础上,本文指出我国需要同时采用多种治理模式,形成以市场化治理为主、垂直型治理为辅、关系型治理作为重要补充的数据要素市场治理格局,并就三种治理模式的进一步完善提出了对策建议。

基于Logit模型的技术供需交易影响因素分析

将技术供方和专利视为整体,将供需双方是否通过某专利交易视为被解释变量,系统研究技术特征、组织实力和供需方多维邻近关系等对技术交易的影响。基于Logit模型对燃料电池领域专利数据实证研究发现:(1)考虑三维特征建立Logit模型,对交易形成预测的精度高达83.3%;(2)技术特征、组织实力特征、多维邻近特征对技术交易均有显著正向影响;(3)多维邻近特征对技术交易的促进程度远高于其他维度特征,供需双方信任是交易形成的关键因素。最后,从建立高质量技术供需数据库、技术交易信任体系、技术交易网络及交易推荐机制等方面提出对策思考。