A multicriteria methodology for equity selection using financial analysis

In this article we present a multiple criteria methodology for supporting decisions that concern the selection of equities, on the basis of financial analysis. The ELECTRE Tri outranking classification method is employed for selecting the attractive equities, through the evaluation of the overall corporate performance of the corresponding firms. The crucial importance issue of the industry/sectoral accounting particularities was strongly taken into account. An elaborate review of coherent research studies is also provided. Finally, the validity of the proposed methodology is tested through a large scale application on the Athens Stock Exchange.     

An integrated multicriteria decision-making methodology for outsourcing management

In this study, an outsourcer evaluation and management system is developed for a textile company by use of fuzzy goal programming (FGP). At first phase of the methodology, evaluation criteria for the outsourcers and the objectives of the company are determined. The existing outsourcers of the company are evaluated by PROMETHEE. At the second phase, the FGP model developed selects the most appropriate outsourcers suitable to be strategic partners with the company and simultaneously allocates the quantities to be ordered to them. In the end, the results achieved are compared with the current situation of the company. The results indicated that scientific methodology for outsourcer management system is very beneficial for the company.Scope and purposeThe purchasing activities of a company constitute a very important part in the overall operation of the company. The quality and the delivery capabilities of any manufacturing firm depend heavily on the performance of its suppliers. When companies outsource a significant part of their business and become more dependent on outsourcers, the quality and delivery performance of the company depends totally on its outsourcers. The consequences of poor decision making become more severe. It is therefore too important for an outsourcing type manufacturer to evaluate, manage and select their suppliers. This research proposes an outsourcer evaluation and management system on scientific basis. The procedure developed is made up of two phases. The first one is the evaluation of outsourcers in terms of the decision maker's objectives. This phase is followed by FGP modeling phase which provides the decision maker the list of suitable outsourcers.     

A general methodology of partitioning and mapping for given regulararrays

A methodology for partitioning and mapping of arbitrary uniform recurrence equations (UREs) expressed as computation graphs onto a given regular array is proposed. Deriving and based on a set of canonical dependencies together with two models of space projection, we give a general method of parallelization. The method has significant advantages in mapping an arbitrary computation graph onto a given processor array while preserving high efficiency in both communication and computation     

Neural network approach for multicriteria solid transportation problem

In this paper, we propose neural network approach for multicriteria solid transportation problems(STP). First we suggest a neural network architecture to solve single-objective STP according to augmented Lagrange multiplier method. Due to the massive computing unit-neurons and parallel mechanism of neural network approach can solve the large scale problem efficiently and optimal solution can be got. Then we transform the original multicriteria problem into a single objective problem by global criteria method and adopt the neural network approach to solve it. By this way we can get the satisfactory solution of the original problem. The procedure and efficiency of this approach are shown with numerical simulations.     

A partitioning methodology that optimizes the communication cost for reconfigurable computing systems

This paper focuses on the design process for reconfigurable architecture. Our contribution focuses on introducing a new temporal partitioning algorithm. Our algorithm is based on typical mathematic flow to solve the temporal partitioning problem. This algorithm optimizes the transfer of data required between design partitions and the reconfiguration overhead. Results show that our algorithm considerably decreases the communication cost and the latency compared with other well known algorithms.     

A modelling methodology for natural dam-river network systems

An approach for modelling a natural dam-river network system is proposed in this paper. Generally, the relationships among the variables of a natural dam-river network system are complex and difficult to describe. In this paper, some simple relationships among the water levels measured at a limited number of points of the network system are presented in such a way that a simple model is achieved. The model is identified and validated with the real time operational data. An example is given and the result shows the feasibility of the modelling methodology. It is believed that the proposed approach can be used in the operation of natural dam-river or river network systems.     

Surviving network partitioning

Applications implemented as distributed systems must withstand network partitioning faults, which split the system into two or more components. Though processes in the same component can communicate with each other, they cannot communicate with processes in other components. If processes continue to operate in the disconnected components, they might perform incompatible operations and make the application data inconsistent. A real-world business cannot stop operating if the network partitions. The authors have developed a strategy that permits processing to continue in all components of a partitioned network. The processes in the disconnected components generate and queue fulfilment transactions that record the actions taken while the network is partitioned. When communication is restored and the components remerge, the fulfilment transactions are dequeued and processed to obtain a consistent state of the application data. Fulfilment transactions allow continued operations, require little additional infrastructure, incur little additional overhead, and are programmed just like other types of transactions     

Acute leukemia diagnosis aid using multicriteria fuzzy assignment methodology

We recently developed a new multicriteria classification method called PROAFTN to help medical diagnosis. The aim of this paper is to present the application of the proposed method for the diagnosis of acute leukemia (AL). The implementation of PROAFTN was carried out on cytological data of 108 cases of AL, using the classification rules of French, American and British hematologists, and was then applied on an independent test set of 83 cases of AL. Forty-seven features, obtained by examining patients' bone-marrow smears with light microscope, defined each case. In order to determine the percentage of correct classifications for each subtype of AL, we compared our results with the clinical diagnosis given previously by the hematologist. 96.4% of the cases were correctly classified by the program, suggesting that the method yields good results in terms of discrimination between AL subtypes.     

Anticipatory network models of multicriteria decision-making processes

In this article, we will investigate the properties of a compromise solution selection method based on modelling the consequences of a decision as factors influencing the decision making in subsequent problems. Specifically, we assume that the constraints and preference structures in the (k?+?1)st multicriteria optimisation problem depend on the values of criteria in the k-th problem. To make a decision in the initial problem, the decision maker should take into account the anticipated outcomes of each linked future decision problem. This model can be extended to a network of linked decision problems, such that causal relations are defined between the time-ordered nodes. Multiple edges starting from a decision node correspond to different future scenarios of consequences at this node. In addition, we will define the relation of anticipatory feedback, assuming that some decision makers take into account the anticipated future consequences of their decisions described by a network of optimisers ? a class of information processing units introduced in this article. Both relations (causal and anticipatory) form a feedback information model, which makes possible a selection of compromise solutions taking into account the anticipated consequences. We provide constructive algorithms to solve discrete multicriteria decision problems that admit the above preference information structure. An illustrative example is presented in Section 4. Various applications of the above model, including the construction of technology foresight scenarios, are discussed in the final section of this article.     

A Methodology for Mapping and Partitioning Arbitrary N-Dimensional Nested Loops into 2-Dimensional VLSI Arrays

A new methodology is proposed for mapping and partitioning arbitrary n-dimensional nested loop algorithms into 2-dimensional fixed size systolic arrays.Since planar VLSI arrays are easy to implement,our approach has good feasibility and applicability.In the transformation process of an algorithm,we take into account not only data dependencies imposed by the original algorithm but also space dependencies dictated by the algorithm ransformation,Thus,any VLSI algorithm generated by our methodology has optimal parallel execution time and yet remains space-time conflict free.Moreover,a theory of the least complete set of interconnection matrices is proposed to reduce the computational complexity for finding all possible space transformations for a given algorithm.     

A data clustering algorithm for stratified data partitioning in artificial neural network

The statistical properties of training, validation and test data play an important role in assuring optimal performance in artificial neural networks (ANNs). Researchers have proposed optimized data partitioning (ODP) and stratified data partitioning (SDP) methods to partition of input data into training, validation and test datasets. ODP methods based on genetic algorithm (GA) are computationally expensive as the random search space can be in the power of twenty or more for an average sized dataset. For SDP methods, clustering algorithms such as self organizing map (SOM) and fuzzy clustering (FC) are used to form strata. It is assumed that data points in any individual stratum are in close statistical agreement. Reported clustering algorithms are designed to form natural clusters. In the case of large multivariate datasets, some of these natural clusters can be big enough such that the furthest data vectors are statistically far away from the mean. Further, these algorithms are computationally expensive as well. We propose a custom design clustering algorithm (CDCA) to overcome these shortcomings. Comparisons are made using three benchmark case studies, one each from classification, function approximation and prediction domains. The proposed CDCA data partitioning method is evaluated in comparison with SOM, FC and GA based data partitioning methods. It is found that the CDCA data partitioning method not only perform well but also reduces the average CPU time.     

A real-time QoE methodology for AMR codec voice in mobile network

This paper studies a general strategy to predict voice Quality of Experience （QoE） for various mobile networks. Particularly, based on data-mining for Adaptive Multi-Rate （AMR） codec voice, a novel QoE assessment methodology is proposed. The proposed algorithm consists of two parts. The first part is devoted to assessing speech quality of fixed rate codec mode （CM） of AMR while in the other one a adaptive rate CM is designed. Measuring basic network parameters that have much impact on speech quality, QoE can be monitored in rei time for operators. Meanwhile, based on the measurement data sets from real mobile network, the QoE prediction strategy can be implemented and QoE assessment model for AMR codec voice is trained and tested. Finally, the numerical results suggest that the correlation coefficient between predicted values and true values is greater than 90~0 and root mean squared error is less than 0.5 for fixed and adaptive rate CM.     

A methodology for developing deadlock-free dynamic network reconfiguration processes. Part II

For pt.I see ibid., vol.16, no.5, p.412-427 (2005). Dynamic network reconfiguration is defined as the process of changing from one routing function to another while the network remains up and running. The main challenge is in avoiding deadlock anomalies while keeping restrictions on packet injection and forwarding minimal. Current approaches either require virtual channels in the network or they work only for a limited set of routing algorithms and/or fault patterns. In this paper, we present a methodology for devising deadlock free and dynamic transitions between old and new routing functions that is consistent with newly proposed theory [J. Duato et al., (2005)]. The methodology is independent of topology, can be applied to any deadlock-free routing function, and puts no restrictions on the routing function changes that can be supported. Furthermore, it does not require any virtual channels to guarantee deadlock freedom. This research is motivated by current trends toward using increasingly larger Internet and transaction processing servers based on clusters of PCs that have very high availability and dependability requirements, as well as other local, system, and storage area network-based computing systems.     

A multi-class queuing network analysis methodology for improving hospital emergency department performance

This paper derives an open queuing network model of an emergency department (ED) design intended to increase the capacity of an ED to treat patients. The methodology captures hospital-specific differences in patient acuity mix, arrival patterns and volumes, and efficiencies of processes in a single common computational model. A spreadsheet implementation of the resulting queuing equations is used by managers, in real time, to size ED areas using waiting time and overflow probability as quality of service targets. Non-homogeneous arrival patterns, non-exponential service time distributions, and multiple patient types are all incorporated. The methodology has been applied to a fleet of hospitals for validation. Results from one of them are used to demonstrate the methodology.     

A formal methodology for integral security design and verification of network protocols

In this work we propose a methodology for incorporating the verification of the security properties of network protocols as a fundamental component of their design. This methodology can be separated in two main parts: context and requirements analysis along with its informal verification; and formal representation of protocols and the corresponding procedural verification. Although the procedural verification phase does not require any specific tool or approach, automated tools for model checking and/or theorem proving offer a good trade-off between effort and results. In general, any security protocol design methodology should be an iterative process addressing in each step critical contexts of increasing complexity as result of the considered protocol goals and the underlying threats. The effort required for detecting flaws is proportional to the complexity of the critical context under evaluation, and thus our methodology avoids wasting valuable system resources by analyzing simple flaws in the first stages of the design process. In this work we provide a methodology in coherence with the step-by-step goals definition and threat analysis using informal and formal procedures, being our main concern to highlight the adequacy of such a methodology for promoting trust in the accordingly implemented communication protocols. Our proposal is illustrated by its application to three communication protocols: MANA III, WEP's Shared Key Authentication and CHAT-SRP.     

CSMA/CD with network partitioning

One of the local area network medium access control standards created by the Institute of Electrical and Electronic Engineers in IEEE Project 802 is the carrier sense multiple access with collision detection (CSMA/CD. These studies show that control. Numerous studies have been reported in the literature on the performance of CSMA/CD. These studies show that CSMA/CD performs well under light network load but not well at heavy load. To improve the performance of CSMA/CD under heavy load, a new concept called network partitioning is presented. Network partitioning allows the network to be partitioned into segments when under heavy load. Partition stations then act as bridges between the segments. The impact of network partitioning on network performance was tested using a simulation model of an Ethernet local area network (an implementation of the CSMA/CD medium access control). The simulation results show that network partitioning can significantly improve the performance of CSMA/CD under heavy load.     

基于边分割的社交网络敏感边保护技术

用户间的敏感关系是社交网络中用户的重要隐私信息。为了解决社交网络中用户间敏感关系泄露问题,提出一种边分割算法。首先,将已删除敏感边的简单匿名社交网络的非敏感边分割成多条子边;然后,将原非敏感边携带的信息分配到子边上,使得每条子边只携带原非敏感边的部分信息,从而生成具有隐私能力的匿名社交网络。理论分析和仿真实验结果表明,相比cluster-edge和cluster-based with constraints算法,边分割算法在保证数据具有较高可用性的情况下能更大限度降低敏感关系泄露的概率,泄露概率分别降低了约30%和20%,因此所提算法能够有效解决社交网络中敏感关系泄露问题。     

A multicriteria approach for risks assessment in ERP maintenance

Enterprise resource planning (ERP) systems cannot remain static after their implementation, they need maintenance. ERP maintenance is a key process required by the rapidly changing business environment and the usual software maintenance needs. However, these projects are highly complex and risky. So, the risks management associated with ERP maintenance projects is crucial to attain a satisfactory performance. Unfortunately, ERP maintenance risks have not been studied in depth. For this reason, this paper presents a general risks taxonomy. It gathers together the risks affecting the performance of ERP maintenance. Moreover, the authors use the analytic hierarchy process (AHP) methodology to analyze the risks factors identified. It helps managers, vendors, consultants, auditors, users and IT staff to manage ERP maintenance better. Results suggest that the most critical stage in ERP maintenance is the first phase, which receives, identifies, classifies and ranks the software modification. The most important hazards in ERP maintenance are the cooperation and commitment of ERP users and managers.     

A multicriteria ant colony algorithm for generating music playlists

In this paper we address the problem of music playlist generation based on the user-personalized specification of context information. We propose a generic semantic multicriteria ant colony algorithm capable of dealing with domain-specific problems by the use of ontologies. It also employs any associated metadata defined in the search space to feed its solution-building process and considers any restrictions the user may have specified. An example is given of the use of the algorithm for the problem of automatic generation of music playlists, some experimental results are presented and the behavior of the approach is explained in different situations.