With the increasing contribution of aquaculture to seafood supply, the interactions between fisheries and aquaculture are expected to become even more important. So this paper has investigated SEASONALity price INTEGRATION for farmed and wild fishes in Fars province. The analysis draws on monthly price data from March 2007 to March 2013 for four species of fish, including Shir, Ghobad, Sangsar and Ghezelalla and applies SEASONAL unit root and INTEGRATION approaches. The results show that almost SEASONAL unit roots have bilateral causality and farmed and wild fishes markets are integrated. Therefor policy making in each market will effect on price behavior in the other markets.

The SEASONAL behavior of agricultural prices is generally a main feature of the market. In recent decades, there has been significant interest for MODELing non-adjusted SEASONAL time series and this issue was seen as an important field in econometrics. Therefore, this study aims to analyze SEASONAL behavior of egg market in north-west provinces, using quarterly retail prices for the period from 1381 to 89. The EGHL-type SEASONAL coINTEGRATION test and SEASONAL error correction MODEL (SECM) were applied. Results confirmed the existence of SEASONAL behavior at all frequencies. There were evidences of some cointegrating relationships at the long run frequencies between five egg price pairs of West Azerbaijan-East Azerbaijan, Ardabil-Zanjan, Zanjan-Ardabil provinces and in the annual frequencies between Ardabil-East Azerbaijan and Kordestan-Zanjan provinces. According to the estimated adjusted speeds parameters in SECM, the egg prices adjust to equilibrium after a shock. According to the results of price SEASONAL coINTEGRATION between regions, it is recommended that the egg price stabilization policy in a province be made in coordination with other province.

This study tries to MODEL the SEASONAL behavior of GDP in different economic sectors (agriculture, services, oil) using periodic autoregressive (PAR) and SEASONAL INTEGRATION (SI) MODELs during 1998: 3-2010: 6. According to the results, the GDP of agricultural sector has a regular and periodic behavior, therefore employing the periodic autoregressive MODEL for GDP behavior of this sector can be very effective. Results of the Hylleberg et al (1990) SEASONAL unit root test showed SEASONAL behavior in service sector, so the data became stationary using appropriate filters and then the appropriate SEASONAL INTEGRATION MODEL was estimated. The oil sector showed no SEASONAL behavior, and autoregressive integrated moving average (ARIMA) MODEL is applied to MODEL the GDP of this sector. Finally, the fitted MODELs utilized to forecast the next two years production in economic sectors. So, due to the different nature of the various economic sectors, studying the sectors independently is recommended.

The goal of this article is to proposing a conceptual MODEL explaining the Information Systems INTEGRATION. In this paper, passing the concept of Intra-Organizational Information Systems INTEGRATION, we emphasis on the concept of Inter-Organizational INTEGRATION. The problem is what the Information Systems INTEGRATION is, and which problems the organizations face. The method using in this research is a four step method proposed according to the system thinking and related theories in this domain. Due to the fact that, emphasizing on the Inter-Organizational Information Systems, at the first step we draw an expanded conceptual MODEL of the Organizational Informatics Doman between the two organizations. After that, this MODEL expands within the network of organizations. This MODEL has a lot of applications. For example, using this MODEL, we can provide a list of the important and required managerial and technical issues for the successful implementation of INTEGRATION projects, which these expensive projects and programs will fail without this notification. Moreover, aggregating cognitive propositions extracting from this MODEL, we are able to achieve an initial theory regarding Information Systems INTEGRATION.

1. Introduction: In the present paper, the ability of the Artificial Neural Network (ANN) and combined wavelet-neural network (WANN) MODEL were investigated for multistep MODELing of hydroclimatic processes with the least input. For this purpose, the ANN MODEL and then the WANN MODEL were used to predict one to twelve steps in advance. Finally, the efficiencies of all MODELs were examined using the evaluation criteria, and all MODELs were compared with each other. . .

By studying the efficient market theory, the new financial management has confirmed the existence of calendar anomalies such as daily transaction effect, special monthly effect, holiday effect, etc as well as non calendar anomalies like initial public offering stock effect, neglected firm stock effect, political cycle effect, etc and acknowledges them as anomalies of the efficient market theory. In fact, the recognition and existence or non existence tests of these anomalies is a new subject within the investment arena in recent years and several studies have been carried out in this regard by using different experiments specially time series and regression MODEL with dummy variables, which are much observable in developed as well as emerging markets. By scrutinizing calendar and non calendar effects as well as full description of the efficient market theory anomalies, a sample of these effects known as "The effect of special months on Tehran Stock Exchange (TSE) is studied and the produced results of the study is used to test the efficiency of TSE.