Abstract: Wheelchair users spend long hours in a sitting position, and selecting the right cushion is highly critical in preventing pressure ulcers in that demographic. Pressure Mapping Systems (PMS) are typically used in clinical settings by therapists to identify the sitting profile and pressure points in the sitting area to select the cushion that fits the best for the users. A PMS is a flexible mat composed of arrays of distributed networks of pressure sensors. The output of the PMS systems is a color-coded image that shows the intensity of the pressure concentration. Therapists use the PMS images to compare different cushions fit for each user. This process is highly subjective and requires good visual memory for the best outcome. This paper aims to develop an image processing technique to analyze the images of PMS and provide an objective measure to assess the cushions based on their pressure distribution mappings. In this paper, we first reviewed the skeletal anatomy of the human sitting area and its relation to the PMS image. This knowledge is then used to identify the important features that must be considered in image processing. We then developed an algorithm based on those features to analyze the images and rank them according to their fit to the user's needs.
Abstract: Automatic irrigation systems usually conveniently protect landscape investment. While conventional irrigation systems are known to be inefficient, automated ones have the potential to optimize water usage. In fact, there is a new generation of irrigation systems that are smart in the sense that they monitor the weather, soil conditions, evaporation and plant water use, and automatically adjust the irrigation schedule. In this paper, we present an agent based smart irrigation system. The agents are built using a mix of commercial off the shelf software, including MATLAB, Microsoft Excel and KEPServer Ex5 OPC server, and custom written code. The Irrigation Scheduler Agent uses fuzzy logic to integrate the information that affect the irrigation schedule. In addition, the Multi-Agent system uses Open Platform Connectivity (OPC) technology to share data. OPC technology enables the Irrigation Scheduler Agent to communicate over the Internet, making the system scalable to a municipal or regional agent based water monitoring, management, and optimization system. Finally, this paper presents simulation and pilot installation test result that show the operational effectiveness of our system.
Abstract: Evapotranspiration is one of the most important
components of the hydrological cycle. Evapotranspiration (ETo) is an
important variable in water and energy balances on the earth’s
surface, and knowledge of the distribution of ET is a key factor in
hydrology, climatology, agronomy and ecology studies. Many
researchers have a valid relationship, which is a function of climate
factors, to estimate the potential evapotranspiration presented to the
plant water stress or water loss, prevent. The FAO-Penman method
(PM) had been recommended as a standard method. This method
requires many data and these data are not available in every area of
world. So, other methods should be evaluated for these conditions.
When sufficient or reliable data to solve the PM equation are not
available then Hargreaves equation can be used. The Hargreaves
equation (HG) requires only daily mean, maximum and minimum air
temperature extraterrestrial radiation .In this study, Hargreaves
method (HG) were evaluated in 12 stations in the North West region
of Iran. Results of HG and M.HG methods were compared with
results of PM method. Statistical analysis of this comparison showed
that calibration process has had significant effect on efficiency of
Hargreaves method.
Abstract: In this article, it is considered a class of optimal control
problems constrained by differential and integral constraints are
called canonical form. A modified measure theoretical approach is
introduced to solve this class of optimal control problems.
Abstract: Although so far, many methods for ranking fuzzy numbers
have been discussed broadly, most of them contained some shortcomings,
such as requirement of complicated calculations, inconsistency
with human intuition and indiscrimination. The motivation of
this study is to develop a model for ranking fuzzy numbers based
on the lexicographical ordering which provides decision-makers with
a simple and efficient algorithm to generate an ordering founded on
a precedence. The main emphasis here is put on the ease of use
and reliability. The effectiveness of the proposed method is finally
demonstrated by including a comprehensive comparing different
ranking methods with the present one.