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The purpose of this study was to investigate the effect of strategic uncertainty on the business strategy through price, product, promotion, and location compatibility In Selected companies producing sports equipment. The research method is applied in terms of purpose and collecting data, a descriptive survey based on structural equation modeling. The statistical population of the present study was selected productive sport facilities companies' staff. The data collection tool was a standard questionnaire. To assess the validity of the questionnaire, divergent validity tests and convergent validity was used in Smart Pls software. Also, Cronbach's alpha test was used to determine the reliability of the questionnaire; The research findings indicate that strategic uncertainty has a significant effect on the business strategy through price, product, promotion, and location adjustment (P-value = 0.05). Therefore, companies producing sports equipment can develop their business by using strategic uncertainty of techniques such as price adjustment, product adjustment, promotion adjustment, and location adjustment.

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The present article is an attempt for a comparative reading of Marsiaee Baraye Zhale va Ghatelash By "Abutorab Khosravi", an Iranian contemporary author, and Daroonmaye Khaen va Ghahraman by Jorge Luis Borges, Argentinean author, poet and contemporary scholar, based on the revolutionary theories of Post-modernism, which is one of the most significant theories of the contemporary era. This research, by using comparative method based on the theories of Post-modernism and analyzing the evidence, attempts to prove the hypothesis that the commonality between Daroonmaye Khaen va Ghahraman and Marsiaee Baraye Zhale va Ghatelash that in some cases have got imitating nature is not accidental. This reflects the influence of Daroonmaye Khaen va Ghahraman in creating Marsiaee Baraye Zhale va Ghatelash. Using Post-modern approach, similar plot, same narrative style, and common symbols are some of the features that Marsiaee Baraye Zhale va Ghatelash shares in common with Daroonmaye Khaen va Ghahraman. The main purpose of this essay is investigation and analysis of these common features in order to demonstrate the similarities of these two texts.  

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In today's dynamic environment, having a proper strategy is not enough for companies to be able to adjust themselves with their environments. Companies through choosing a suitable organizational structure can benefit innovation to achieve sustainable competitive advantage. The aim of this study is testing the mediating role of organizational structure (formalization, centralization, complexity) between environmental uncertainty and organizational innovation. The questionnaire was used to collect data with high reliability and Structural Equation Modeling and Partial least squares were used for analyzing data. Data collected from medium and large manufacturing firms in the Mashhad city. The results showed that the theoretical model was good fitted and the relationship between environmental uncertainty and dimensions of Organizational structure (complexity, formalization and centralization) is meaningful. Also the relationship between complexity and formalization with organizational innovation were significant. Organizational formalization and complexity mediated between environmental uncertainty and organizational innovation was meaningful but mediating role of centralization was not meaningful.        

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Uncertainties and risks underpinning environmental complexities have undermined lots of assumptions and delivery methods of large industrial projects and have lessened their efficiency and effectiveness. In the literature, selecting proper project delivery method in complex situations still lacks attention, and existing relevant studies have been also conducted based on “the first order of project management”, in which the degree and extent of uncertainties and environmental complexities are considered normal and prevalent. Based on the recent scientific and managerial paradigms such as “the second order of project management”, it is necessary to fulfil required revisions in existing models and solutions, utilizing a novel comprehension and vision to the environment. The main aim of this article is proposing an appropriate method for industrial projects delivery which are planned and conducted in environmental complex situations (and especially high uncertainties as subsequent of situations). This study shows that usual Design and Build method (EPC/TK) – with maximum transferring of risks to contractor – does not satisfy executing large industrial projects, and it should be improved through correction of basics and application of innovative tools and techniques. Flexibility Increasing, sharing risk among parties, supporting problem solving approach, etc. in delivery method form the basis and ground for proposed Design and Build method in this article. This research has utilized a qualitative research methodology, incorporating the Grounded Theory method (of Glitzer’s emerging design type) to identify uncertainties, risks, and the proposed mechanisms for flexible Design and Build delivery method.

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Demographic parameters such as intrinsic rate of increase estimates are of main interest in a wide range of ecological researches. Two widely used uncertainty estimate techniques are bootstrap and jackknife methods. Bootstrap estimates are time-consuming processes that are impossible to use without a computer program. Unfortunately few programs, if any, have been developed for this task. In this study a guideline was offered to prepare a program in Microsoft Excel environment to carry out time-consuming calculations of reproductive life table data in a minute or two by repeatedly pressing a shortcut key. 
 

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Land use/cover change map production is one of the basic needs for environmental monitoring and management. Since the change maps are usually used in planning and decision-making, certainty and reliability of these maps can be very important in many applications. Unfortunately in many studies only probability values as obtained from MLC approach have been used for uncertainty estimation. Here a new approach has been developed which is based on the probability information as well as spatial parameters including distance, neighborhood, extent and the type of change. In this study, two Landsat TM images of Isfahan urban area provided in 1990 and 1998 have been co-registered using first order polynomial and nearest neighbor resampling approach. The registered images have been then classified to ten different land use/land cover classes using Maximum Likelihood Classification algorithm. Probabilistic measures generated by the MLC have been used for modeling uncertainty. Using different spatial analysis functions for modeling the change of agricultural areas to residential areas, the relevant spatial parameters have been extracted. Based on logistic regression approach, probabilistic parameters and spatial parameters have been integrated to generate a layer, which shows uncertainty of change of agricultural areas to residential areas. The Relative Operating Characteristics (ROC) index has been used for validation of the model and it has been estimated to be 0.9944, which is an indicative of very good model fitting. As a final conclusion, development of this model is suggested for quantitative evaluation of uncertainty in change detection.

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In restructured power systems and in a wholesale power market, a distribution company as a market player intends to maximize its profit by utilizing its options. Hence determining an optimal energy acquisition strategy for a distribution company is vital, for attaining to this goal. However an important challenge for determining these strategies is forecasting other competitors and Generation companies' strategies and competitors' incomplete information must be considered as uncertainties in the problem. In this paper, an energy acquisition model for a distribution company with considering distributed generations, interruptible loads and information's uncertainties in a day-ahead electricity market has been presented. In the proposed method, distribution company energy acquisition strategy has been modeled as a two-level multi-objective optimization problem and has been solved by using nonlinear complementarities and L-P metric methods and then, the uncertainties in the competitors' information, has been applied to the model by using Monte Carlo method. An 8-bus system is employed to illustrate the proposed model and algorithm.

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This paper focuses on the issue of decision making in context of uncertainty and in particular on decision making in innovation and knowledge-based Firms. Decision making in uncertain conditions has many complications that make it difficult to rely solely on analyzes and common models in decision making. Meanwhile, the need to consider alternative methods, especially in the real environment of decision making, is felt. In this research, with a descriptive approach, the model of this type of decision is specifically defined in knowledge-based firms with a quantitative method and structural equation modeling. Statistical analyses were performed on 320 researcher-made questionnaires containing 77 items. Smart PLS software was used for modeling. The obtained model shows that time and information categories play a significant role in creating uncertainty. This uncertainty ultimately leads to the decision-makers' reliance on intuitive decision-making. Underlying conditions and interventions include environmental turbulence, rivals, market changes, technological changes, changes in environments, experiences, education, curiosity, and patterns of mental patterns effect on intuitive decisions that themselves include improvements in speed and accuracy of decision making, creativity, satisfaction and performance of the company.

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The purpose of this study is to explain the ability of the simulation methodology to consider uncertainty of the multi criteria decisions making. The rank order of decision alternatives depends on two types of uncertainty:(1) uncertainty associated with the decision making judgment regarding each element of decision matrix described by distribution function, and (2) uncertainty regarding the future characteristics of the decision making environment described by a set of scenarios. Scenario is description of the decision making environment into some separate situations . Researchers concentrate on this type of uncertainty less than other types. Both types of uncertainty are capable to opposite the rank of alternatives and decline the certainty of decision maker to the rank order of alternatives. In The present research, a simulation approach for handling both types of related uncertainty was described. The final conclusions showed that when uncertainty associated with the decision making judgment regarding each element of decision matrix increases, the probability of rank reversion and rank uncertainty increases too. Under these situations, the final ranking of the alternatives is probabilistic.

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Time and uncertainty play a crucial role in the strategic planning process [1]. Many industries have collapsed or been knocked out of the competition due to unforeseen able changes in the environment and their forecast about the future failed. Organizations are faced with unpredictable changes in new technologies, products and market places and their planned strategies are not able to respond to such a dynamic and changeable environment. These sorts of pressures are increasing in future because of the rapid developments of technology, economics and community. Needless to say, the future is not predictable but it is noteworthy that organizations can prepare themselves to face such changes and this readiness results in competitive advantages. The more the uncertainties, the more considerable the competitive advantages of organizations devised robust and stable strategies against uncertainty will be. This paper aims at introducing a method that enables organizations to draw up robust strategies in uncertain situations and leads to formulation of strategies to immunize them against environment changes. The method put forth in this paper has combined 'scenario planning method' and 'fuzzy inference system' with traditional strategic planning by adopting a novel and creative approach. Using the values of uncertain factors in the external environment, this method designs some probable forthcoming scenarios of the organization and then based on fuzzy information defined by experts for fuzzy inference systems, defines a robust strategy to deal with the designed scenarios. This method assists a manager and an organizational strategic planner in their evaluations of future environment and provides them with deep understanding of their planned strategies to keep their competitive advantages in the unstable and unsettled future.

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Hyper inflation rates impose direct and indirect costs upon society. It has undesirable consequences that are caused by inflation uncertainty. In this regard, the following questions are raised: How do inflation rate and its uncertainty affect economic growth? Does the structural breakpoint affect relationship between inflation and growth rate? In this study the above questions are examined for the Iran's economy in period 1974-2007. For this purpose the regressive model is applied. In this model, growth rate of GDP depends on inflation rate, growth rate of the money supply, growth rate of the real gross fixed capital formation and inflation uncertainty. For the measuring inflation uncertainty Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model is used. Based on data analysis, structural break point occurs at inflation rate equal to 20 percent. Results show that the impact of inflation rate on economic growth is significantly negative but it minimizes at the rate of less than 20 percent and increases at the rate of more than 20 percent. Moreover, inflation uncertainty has significant and negative effect on growth.

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This paper addresses robust state estimation problem for Genetic Regulatory Networks (GRNs). A delay-dependent robust                          filter is designed for a realistic nonlinear stochastic model of GRN. The model provided is the most complete model used in the literature so far, in the sense that delays are time-varying, parameter uncertainties (time-varying and norm-bounded) are considered, stochastic noises appear at the state equations as well as the measurement equations. Besides, stochastic noise and disturbance are considered simultaneously in this model. Using a proper Lyapunov-Krasovskii functional based on delay decomposition approach, sufficient conditions for the existence of the filter are derived in terms of linear matrix inequality (LMI). These conditions ensure robust asymptotic mean square stability of the filtering error dynamics with a prescribed  disturbance attenuation level. By use of delay decomposition approach and using a lemma containing a stochastic integral inequality, the obtained conditions are delay-dependent and have less conservativeness. The filter parameters are determined then, as the solution of another LMI. A simulation study is also given to show the effectiveness of the proposed filter design procedure.

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Exoskeleton robot has attracted attention of many researchers because it realizes an old aspiration to attain a machine which is worn by man and maximizes his might via its powerful actuators. Thorough coordination between robot movements and that of user constitutes the greatest complexity of exoskeleton technology. Investigations showed that impedance control (IC) is suitable for this application but the present forms of IC are mostly dedicated to industrial robots which have significant differences with exoskeleton. In this article a versatile form of IC for the mentioned application is developed. Besides, according to perpetual uncertainties in load and measured force signals, for the first time an adaptive method for IC of exoskeleton robot is implemented. Simulating operation of robot in tracking user's walking motion while carrying a load of 50 (Kg) and with uncertainties in load and measured forces, proves efficiency of the proposed control method. Tracking error during simulation is almost zero and torques needed at interfaces are immaterial.

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A robust delayed plant-input mapping methodology is proposed to control of industrial plants through wireless communication networks. In this way, firstly a robust classic controller is designed for original continuous-time system according to a predefined uncertainty bound. Then compensation of the destabilizing effects of a constant delay is then concerned. For this purpose, a digital controller is designed using D-K iteration method. Finally this algorithm is modified to overcome the wireless network effects, e.g. random network delay, packet loss and packet disordering. Simulation studies on two benchmark industrial problems demonstrate the effectiveness of the proposed method for uncertain plants.

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Information systems decisions are of the main concerns of managers. Existence of uncertainties and different objectives and attributes influence the quality of decisions. Environmental uncertainties can challenge the quality of IS investment decisions. Investment decisions, made without any respect to environmental changes, will loose their effectiveness as time passes. IS investment decisions require attention to different attributes such as return on investment, strategic competitiveness and user satisfaction. Multi-attribute decision making (MADM) approaches can play an important role to make investment decisions. This study aims to integrate scenario planning (as a tool to meet environmental uncertainties), Axiomatic Design (MADM approach) and Fuzzy Delphi method (experts opinions acquiring and consensus tool) as a Hybrid Model to propose a new methodology to make IS investment decisions about the outsourcing or insourcing of the development of the information systems. A case study in IS investment has been done. The case is about the selection of an ERP system in Iranian National Oil Company (NOC).

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Since the breakdown of the Bretton Woods system of fixed exchange rates, both real and nominal exchange rates have fluctuated widely. Empirical findings indicate significant impact of exchange rate uncertainty on macroeconomic variables such as output, trade, and investment. This article investigates the impact of the real exchange rate uncertainty on total factor productivity (TFP) in agriculture sector of Iran during the period of 1974-2007. The uncertainty of real exchange rate is defined as the conditional variances obtained from Exponential Generalized Auto-Regressive Conditional Heteroscedasticity (EGARCH) model. The econometric estimation using Auto-Regressive Distributed Lag (ARDL) approach shows that the real exchange rate uncertainty has a significant and negative effect on TFP in Iran's agriculture sector in long- and short term. According to the results, in order to reduce the real exchange rate uncertainty, it is recommended that the appropriate policies should be made by policymakers to lessen the difference between nominal and real exchange rates.  

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Measurement of wave velocity in materials is very important.It has applications in ultrasonic thickness gauging as well as estimating the elastic constants of materials. In this paper, it is intended to improve the accuracy of wave velocity measurements by signal processing techniques. For this purpose, the SAGE algorithm, which is a model-based estimation technique, is implemented. Using SAGE, the overlapping echoes are separated and consequently the time-delay between these echoes is estimated more accurately. The signal processing scheme reduces the adverse effects of noise too. To demonstrate the effectiveness of the proposed technique, an AISI 4140 steel block with four steps of thicknesses 10, 15, 20, and 25 mm was tested by the immersion ultrasonic testing technique. The time-delaybetween echoes obtained from each step was measured fifty times and by averaging these measurements, the actual time-delay and its uncertainty were estimated. The thickness of the block at each step was also measured by a micrometer. Using the time-delay and thickness data, the wave velocity and its uncertainty were estimated for each of the four thicknesses. The results shows that this technique can reduce the uncertainty of wave velocity measurements significantly.