In this paper fully centralized, hierarchical decentralized, and fully decentralized multisensor structures of Kalman filter are introduced and compared with together and with one sensor structure of Kalman filter. Decentralized structures are obtained through parallelism in centralized Kalman filter and give high processing speed. Fully decentralized structure requires no central processor and each processor estimates system's states. Therefore, the system is very resilient to loss of one or more of its processors and its survivability and robustness are increased. Decentralized algorithms are modified so that t-he computation complexity is reduced with keeping the same accuracy. Simulation results 'for time-variant system illustrate clearly that despite of reducing the computation complexity, the accuracy of the estimation is remained the same. Also, multisensory structures have high accuracy of estimation in comparison to one sensor structure.

These days, the most important areas of research in many different applications, with different tools, are focused on how to get awareness. One of the serious applications is the awareness of the behavior and activities of patients. The importance is due to the need of ubiquitous medical care for individuals. That the doctor knows the patient's physical condition, sometimes is very important. Of course, there are other important applications for this information. There are a variety of methods and tools for measurement, gathering, and analysis of the physical behaviors and activities’ information. One of the most successful tools for this aim are ubiquitous intelligent electronic devices, specifically smartphones, and smart watches. There are many sensors in these devices, some of which can be used to understand the activities of daily living. As an output result, these sensors produce many raw data. Thus, it is needed to process these information and recognize the individual behavior of the output of this processing. In this paper, the basic components of the analysis phase for this process have been proposed. Simulations validate the benefits and superiority of this method.

Introduction: The oceans cover about 70% of the earth's surface and contain the most water on Earth, as well as important marine ecosystems. In generally, global waters are classified into two types of water (the first case and the second case). In waters of the first type, such as the waters of the open ocean, phytoplankton dominate the inherent optical properties of water. However Case-2 waters, like coastal waters, are complex waters that are affected by a variety of active light compounds such as phytoplankton, colored dissolved organic matter and Total suspended matter. Coastal wetlands are considered as the Case-2 water. These types of areas are dynamic environments that are threatened by the entry of pollutants and because the wetlands have a calm environment and away from open sea waves, they are exposed to the accumulation of natural and human pollution. As a result, the identification and monitoring of coastal and marine pollution is essential to minimize their destructive effects on human health and the environment and economic damage to coastal communities. Phytoplankton are floating or scattered single-celled algae that travel primarily through water waves. Chlorophyll-a considered as an indicator of the abundance of phytoplankton and biomass in oceanic, coastal and lake waters. Field and laboratory methods are difficult and time consuming and weak for spatial and temporal observations. In contrast to the weakness of field methods, remote sensing methods can provide the spatial perspective needed to gather information on ocean and coastal water surface on a regional and global scale. The purpose of this study was to compare and evaluate atmospheric correction methods (high atmospheric radiation and high atmospheric reflectance) on the algorithm for estimating the concentration of chlorophyll A based on blue and green bands (OC2) in Landsat-8 and Sentinel-2 data, evaluating the results using Field data and finally the time series mapping of chlorophyll-a concentration. Materials & Methods: In this study, Landsat 8, Sentinel 2 satellite time series data and field data collected from the study area were used. First, the satellite images used in ENVI 5. 3. 1 software were converted to Surface Reflectance and Top of Atmosphere Reflectance. Then, MATLAB 2018a software was used for image processing and coding. to estimate the chlorophyll-A concentration, the bio-optical algorithm OC2 was used, which in fact uses a nonlinear relationship to link between field data and satellite data. In order to evaluate the results two statistical parameters R2 and RMSE were used. Results & Discussion: Based on the analysis of field data, the concentration of chlorophyll-A in all sampled stations was less than 1 mg/m3. Water in the Surface Reflectance and Top of Atmosphere Reflectance Sentinel 2 and Landsat 8 data had a relatively similar spectral signature at wavelengths, due to the similarity in the spectral signature of water on the satellites used, covering the same spectral range in the Landsat 8 and Sentinel 2 satellites systems. The OC2 algorithm had amounts R2 (0. 91 and 0. 64) and RMSE (0. 13 and 0. 33) in Landsat 8 and Sentinel 2 Surface Reflectance data, respectively, while Landsat 8 and Sentinel 2 Top of Atmosphere Reflectance data had amounts R2 (0. 12 and 0. 53) and RMSE (0. 45 and 0. 51), respectively. The time series of chlorophyll-A concentration estimated using surface reflectance data (Landsat 8) corresponds to the natural conditions of the region, However, the time series of chlorophyll-a concentrations using the surface reflectance data (Sentinel 2) during the seasons estimated the chlorophyll concentration to be uniformly and downward. The reason for this poor performance in the Sentinel 2 is the lack of sufficient field data for calibration. Conclusion: In this study, we tried to evaluate and compare the reflectance algorithms (Landsat 8 and Sentinel 2) in the OC2 algorithm. Preliminary results indicate that the type of satellite data used (surface reflectance and Top Atmosphere reflectance) is of great importance for entering the OC2 bio-optical algorithm because the satellite image to enter the OC2 algorithm must be surface reflectance data and atmospheric correction that In fact, these algorithms are sensitive to high-atmosphere reflectance data. In general, the results showed that 10 field data is enough to calibrate with Landsat 8 data, but for Sentinel 2 data, more than 10 numbers field data must be calibrated to obtain a good result.

Introduction: There are increasing advances in science. Medical science must move with this growing trend. Therefore, it is necessary to change the content and setup of medical education curriculum especially basic sciences courses. This study aimed to review literatures about Integration in medical curriculum and to present concepts, importance, types and stages of Integration in medical science.Methods: In this review article, Google Scholar, Pub Med, books and journals were search using following key words: curriculum planning, medical education, and Integration. Search was limited to published literature during 2000-2011. Fifty articles were obtained through this search strategy. Finally, 31 articles and book reviews were selected and reviewed.Results: Concepts, importance, types, stages, and effectiveness were extracted from selected literature.Generally, Integration means creating a whole or combining separate systems into an integrated system.There are two main types of Integration (horizontal and vertical Integration) in medical education.Integrated learning through learning environment is more emphasized in clinical courses. Harden offers eleven stages to turn a subject-based education to an integrated curriculum Conclusion: Integration is an important strategy and complex concept in medical education. The most appropriate step in Integration for a medical school depends on some factors such as existing program, teachers' experience and attitude, medical school and the overall goals of curriculum. Integration of basic and clinical sciences based on body organs lead to increased learning. It is necessary to know that matching and arranging information about an organ is not necessarily equal to the Integration for learners. Integration by learners and faculty members is different.

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in recent years, urban planners and designers look at public art-the art that exists in public domain - as an opportunity for creating vibrant and meaningful environments in many big and small cities in all over the world. Although public art as an integrated art in urban spaces that happens in streets, urban parks, public buildings, house estates and anywhere people live, work and take their leisure is not a new concept, urban planners and designers and everyone who makes policies for cities should consider it as a powerful item in city that can cause gradation in urban physical, social, behavioral, economic and cultural context. Also we should consider that public art depends on a certain interaction with the public, based on some shared postulates. This article tries to clarify the definitions, limitations and boundaries of public art and its influences on public space.