Introduction In the field of management, the statistics and performance of the deputies and functions of the organization are always of great importance, which requires instant access to the latest status of the System under coverage and minimal forecast of the future situation, to provide quality services Also improve. All of this justifies the existence of an intelligent Statistical System with decision-making capabilities. Methods In this study, we try to create an integrated web-based System in order to electronicize the processes of defining and recording Statistical information along with the aggregation of scattered data in the System and finally extract reliable knowledge from this data using modern artificial intelligence methods. In order to make decisions in the fields of health, treatment, medical education as well as health management. The intelligent management System of North Khorasan University of Medical Sciences has been designed and implemented under the web with the technique of making Webserver software & Learning & data mining in three phases for 48 months in PHP language and MySQL database. Results For this study, the Statistical turnover structure of the university was classified into 1058 units. By classification based on the decision tree algorithm and reviewing the records of reports submitted to organizations at the same level and above, we reached 269833 units of data, 376 data types and 3885 data content. In the proposed method, the time cost of data transfer is less than one minute per item, and the required human resources due to the addition of multiple control sensors is 2640 people-hours per year, and significant time and financial savings were made. Conclusions According to the findings, it seems necessary to create a mechanized System for distribution, collection, control, analysis and reporting of Statistical indicators that can have high accuracy and time and financial savings.

In Iran, pressurized irrigation Systems cover a large area of agricultural land, but water use efficiency remains low because farmers tend to do deficit (over) - irrigation due to their lack of knowledge of crop water requirements. To address this issue, irrigation Systems can be automated, and it is important to estimate crop water requirements accurately. This can be done based on soil moisture deficit or meteorological data. The water required can then be applied using a volume meter or by determining irrigation time based on the sprinkler flow rate. The study aimed to compare crop water requirement estimates based on soil moisture deficit and meteorological data, as well as the amount of water applied using volume and time-based methods.The study was conducted in the research farm of Razi University, Kermanshah, Iran, on a sprinkler irrigation System equipped with pressure and flow measuring devices, pressure switches, and electrical valves. The field was under corn cultivation, and four types of irrigation management were evaluated, which included a combination of two methods of determining crop water requirement (soil moisture deficiency and meteorological data) and two methods of irrigation application (time or volume). The four treatments were soil moisture - time (MT), soil moisture - volume (MV), weather - time (WT), and weather - volume (WV). The crop water requirement was calculated using the Penman-Monteith formula based on daily weather data. Soil moisture was measured at different depths one day before irrigation, and the soil moisture deficit was calculated to determine the crop water requirement based on soil moisture. The irrigation volume for each sprinkler in the irrigation cycle was calculated using equations that written in the paper.In the volumetric-based method (treatments WV and MV), the volume of water applied was measured using a water meter with a precision of 0.1 liters, and irrigation was stopped after passing the required volume of water. In the time-based method (treatments WT and MT), the irrigation time was calculated by dividing the irrigation volume by the average flow rate of the sprinklers (3 liters per second), and irrigation was stopped after the calculated duration. The actual sprinkler flow rate was calculated based on the volume of applied water and irrigation time in each treatment and irrigation round. Crop yield was measured at the time of harvest in the studied treatments and a control treatment managed by the Faculty of Agriculture. The irrigation treatments were not applied in the first month of the growth period due to field limitations.The results show that the crop water requirement calculated based on meteorological data at the beginning and end of the growing period was more than the method based on soil moisture. In total, the amount of crop water requirement calculated based on soil moisture was 8% more than the meteorological-based method. The volume of applied water in treatments of MT and WT was 14 and 8% more than in MV and WV treatments, respectively.The actual flow rate of sprinklers was different from the design flow rate due to irrigation situations in other parts of the farm. The average discharge of sprinklers (12 irrigation events) in WT, MT, WV, and MV treatments was 2.79, 3.03, 3.27, and 3.12 l/s, respectively. The irrigation time in volume and time-based methods also showed a significant difference. The irrigation time in MT and MV treatments was 10 and 18% longer than in WT and WV treatments, respectively. The study found that due to the non-uniformity of sprinkler discharge, applying irrigation by volume method is better than the time-based method. The results suggest that the MV treatment, which determined the amount of irrigation based on soil moisture deficit and applied it using a volumetric method, is a suitable option for automating sprinkler irrigation Systems in the studied region.

Objectives: Today, many hardware and software products, including office Automation software, and web-based websites are used by employees, including professors and employees of different departments in offices. Websites are considered one of the main competitive advantages in any organization. This study aims to investigate the usability of the Integrated Research Automation System (SYAT): A Heuristic Evaluation. Methods: The present study was a descriptive-cross-sectional study with a heuristic evaluation performed on the integrated research System software (SYAT) by 3 evaluators. They then evaluated the intensity of each of the ten options and scored from 0 to 4. After each problem was classified as one of the 10 branches of Nielsen's evaluation by the evaluators, similar problems were eliminated and the average scores and the severity of the deterioration of the problems were calculated. Results: A total of 92 usability problems were identified in evaluating the usability of the web-based software (System) using the components provided by Nielsen. The majority of the issues were related to the detection instead of reminder with 16 problems (17. 32%). The lowest number of problems was related to both compatibilities between the System and the real world, and the clarity of the System status with 6 cases (6. 52%). Conclusion: The usability assessment method is inexpensive and simple and the problems caused by websites and applications can be evaluated as feedback to improve them. The more accurate the needs of SYAT System users are, the more effective the System will be and the more satisfied the users will be.

In this paper the output port of an industrial Automation System which includes Data Registers, Digital to Analog Converters, Decoders and Buffers is integrated using CMOS Technology. The designed circuits have been simulated in SPICE using 1.5 micrometer CMOS Technology. The designed output port is eight bits, with -5 V power supply, which is capable of handling data with a frequency of 5 :MHz with a power consumption of 29.3 mw. The fractional Temperature coefficient of the current reference is very low and in the rage of 333 PPM/oC. The settling time for the full scale input is about 700 nsec.s and the output voltage swing is from zero to 4.3 volts.