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In order to develop our understanding of valuation models and so extend this to encompass the important area of performance measurement and its interpretation, it is essential to have a framework which will enable such developments to take place. This paper presents a theoretical model based on a certainty equivalent approach which enables the market risk of individual properties and portfolios to be assessed on an expectations basis. The data requirements for using the model are not onerous and with simple extensions it can be adapted to cope with changes in risk that occur when variations in the lease structure are anticipated. Understanding the influence of systematic or market risk is essential if our understanding of valuation is to improve. Systematic risk is the single most important factor which determines the premium which should be allowed to compensate for risk. This aspect has been largely ignored in the property literature with the result that risk premium figures are frequently assumed to be constant across all sectors and properties. This paper derives a model which attempts to overcome some of these problems. Due to data limitations empirical tests of the model cannot be regarded as conclusive. However, those tests that have been carried out suggest that the model could be used for estimating the required rate of return of both sectors and individual properties. It also has considerable potential in estimating growth expectations for groups of properties and can thus be used in the decision‐making process. Much, however, remains to be done.

In the previous two articles the emphasis was on wet and electrochemical techniques, with particular reference to the potentiostat. The physical examination of corrosion products is of equal importance, especially, for example, in the study of oxidation by dry gases at elevated temperatures where electrochemical studies are not normally feasible. In this article the application of physical techniques to corrosion studies will be discussed.

This paper aims to apply He's homotopy perturbation method (HPM) to obtain solitary solutions for the nonlinear dispersive equations with fractional time derivatives.

The authors choose as an example the nonlinear dispersive and equations with fractional time derivatives to illustrate the validity and the advantages of the proposed method.

The paper extends the application of the HPM to obtain analytic and approximate solutions to the nonlinear dispersive equations with fractional time derivatives.

This paper extends the HPM to the equation with fractional time derivative.

WHEN the temperature of the gas reaches the high level, the molecules begin to break up into atoms or groups of atoms, which after recombination form new and smaller molecules of a simpler structure. For instance, tri‐atomic molecules after having been split form diatomic ones. This process is called the dissociation of gases. The newly‐formed molecules, when colliding, again form molecules of the original gas, so two processes are occurring simultaneously. However, the higher the temperature, the larger the percentage of dissociated molecules.

The study aims to examine the effect of knowledge management strategy (KMS) on knowledge-sharing behavior (KSB) and its subsequent effect on knowledge performance (KP). It also throws light on the mediating role of KM enablers (KMEs) and KSB.

In purview of previous literature, several hypotheses were framed. Structural equation modeling (SEM) using SPSS 20, PROCESS macro and AMOS 20 was used to examine the research hypotheses in a sample of empirical data collected from 350 employees of information technology (IT) service provider firms.

This paper empirically proves the existence of mediation effect of the proposed mediators (KME, KSB) between predictors (KMS, KSB) and outcomes (KSB, KP) in different hypothesized relationships. Result provides empirical evidence toward the positive influence of KMS dimensions (internal-oriented KMS, external-oriented KMS) on KSB and also confirms the influence of KSB on KP.

This study examines the effect of KMS and KSB on KP with reference to the IT sector, thereby limiting generalization to other sectors. Practical and managerial implications have been discussed in the later sections of the study.

This study adds value to the existing KM literature by adjoining the links among knowledge strategy, sharing behavior and performance.

A scheme for conversion from magnetic tape to computer control of an industrial robot has been developed. Programming has been extended from the normal teach capability to operation from a remote hand‐held joystick as well as from the computer console.

FAILURE of panels under static compression, or for that matter under any loads, involves a vast array of problems ranging from properties of material to initial instability and post‐buckling phenomena as occurring in various types of panels. It is not intended here to do justice to all these aspects of the subject but to select a single—but at the same time very important—topic, develop its analysis as fully as possible, and present the results in a readily applicable form. The structure investigated is the single skin stiffened panel under compression and the mode of failure considered, denoted by flexural cum torsional failure, involves predominantly flexure and torsion of the stringer with a wavelength of greater order of magnitude than stringer height and pitch. By torsional deformation of the stringer we understand a rotation of its undistorted cross‐section about a longitudinal axis R in the plane of the plate, the position of which will be selected later on (see FIG. 1b). The panel may, of course, also fail in a local mode of stringer and plate with a short wave‐length of the order of magnitude of stringer height and pitch, but the analysis of this case is not included here (see, however, Argyris and Dunne). Note that a local mode of deformation of a stringer formed by straight walls is commonly defined as a distortion of the cross‐section in which the longitudinal edges where two adjacent walls meet remain straight (see FIG. 1c).

This study aims to examine the value of the call option contract in hedging the risks in the supply chain. The decentralized supply chain without call option contract is first studied as the criterion model for evaluations. This paper addresses several questions: What will be the optimal manufacturer’s production quantity, retailer’s ordering and pricing policies in the presence of random demand and random yield by applying the downconversion approach? How will the call option contract influence the optimal decisions for the members of the supply chain? Can the risk from randomness be divided among the members in the supply chain through the call option contract?

This paper considers a two-level decentralized supply chain under random yield and random demand in which the manufacturer takes advantage of the downconversion approach with two scenarios, with and without option contract. To the best of the authors’ knowledge, no article or study uses the downconversion approach in a supply chain regarding random yield and random demand. Furthermore, the paper considers pricing with option contract in the supply chain, which makes this article stands out significantly from other articles in the literature.

This study shows that the downconversion approach would reduce the risk caused by the random yield, which appears to be the appropriate method for the environmental goal of the supply chains. Moreover, adopting a call option contract can increase flexibility and mitigate risks, resulting in more expected members’ profits.

To simplify the model, the authors assume one manufacturer and one retailer, so extending the model to consider multiple retailers instead of one retailer and inventory sharing between them would be interesting. Considering the option and exercise prices as decision variables would be important future research topics. Put option and bidirectional option contracts could be investigated in the future. Another extension is modeling asymmetry of information in supply chain.

This paper provides managerial insights on dealing with both demand and yield risks in a manufacturer–retailer supply chain. The manufacturer has a random yield production and produces two types of vertical products: low-end and high-end. To reduce waste caused by the random yield, the manufacturer uses a downconversion approach in which low-end products are made by converting the defective high-end products. The manufacturer purchased a shortage of high-end products from the secondary market (i.e. emergency sourcing). High-end products are sold through the retailer, and low-end products are sold directly by the manufacturer. The customer demand for high-end products in the end market is random and depends on the selling price, and the customer demand for the low-end products in the secondary market is independent and random. The retailer contracts the manufacturer with the call option to obtain high-end products to meet a random demand; in fact, by using the call option contract, the authors try to balance the risks between two members. Two scenarios of with and without call option contract are proposed. After the high-end product demand is observed, the retailer would exercise the option order quantity in the call option contract scenario and then place an instant order with the manufacturer if necessary. In each scenario, the manufacturer and the retailer make their decisions simultaneously (static game) to determine the retailer’s optimal ordering and pricing policies and the optimal production quantity of the manufacturer (Nash equilibrium) by maximizing their expected profits. Finally, the impact of the model parameters on the supply chain is expressed through numerical examples. The numerical analysis shows that the call option contract provides greater profit than the wholesale price contract.

A variety of phenomena such as world wide web, social or business networks, interactions are modelled by various kinds of networks (such as the scale free or preferential attachment networks). However, due to the model‐specific requirements one may want to rewire the network to optimize the communication among the various nodes while not overloading the number of channels (i.e. preserving the number of edges). The purpose of this paper is to present a formal framework for this problem and to examine a family of local search strategies to cope with it.

This is mostly theoretical work. The authors use rigorous mathematical framework to set‐up the model and then we prove some interesting theorems about it which pertain to various local search algorithms that work by rerouting the network.

This paper proves that in cases when every pair of nodes is sampled with non‐zero probability then the algorithm is ergodic in the sense that it samples every possible network on the specified set of nodes and having a specified number of edges with nonzero probability. Incidentally, the ergodicity result led to the construction of a class of algorithms for sampling graphs with a specified number of edges over a specified set of nodes uniformly at random and opened some other challenging and important questions for future considerations.

The measure‐theoretic framework presented in the current paper is original and rather general. It allows one to obtain new points of view on the problem.

This study aims to promote the anti-disturbance and tracking accuracy of optoelectronic stabilized platforms, which ensure that optical detectors accurately track targets and acquire high-quality images.

An improved active disturbance rejection control (ADRC) strategy based on model-assisted double extended state observers (MDESOs) is proposed in this paper. First, by establishing an auxiliary model, the total disturbances are separated into two parts: inner and external disturbances. Then, MDESOs are designed to estimate the two parts by separately using two parallel ESOs, by which the controlled plant is adjusted to the ideal pure integral series. Simultaneously, combined with the nonlinear state error feedback, an overall control strategy is established.

Compared with the conventional ADRC and proportional derivative, the improved ADRC (IADRC) has stronger robustness and adaptability and effectively reduces the requirements for model accuracy and the gain of the ESO. The error of the auxiliary model is tolerated to exceed 50%, and the parameter values of the MDESOs are reduced by 90%.

The total disturbance rejection rate of the proposed strategy is only 3.11% under multiple disturbances, which indicates that the IADRC strategy significantly promotes anti-disturbance performance.