Primary and widely in use Computed Tomography (CT) dose descriptor is a volumetric CT Dose Index (CTDIv) that is usually measured by a pencil ionization chamber with active length of 100mm and polymethyl methacrylate (PMMA) phantom. CTDIv depends on scan parameters such as mAs, kV, collimation, tube rotation time but is independent of patient’s size and shape. For the purpose of a good estimation of dose received by the patients, American Association of Physicists in Medicine (AAPM) published the conversion factors for both 16 and 32cm (head and body phantoms respectively); through this, users can extract conversion factors according to lateral (LAT) and/or anterior-posterior (AP) sizes and calculate real CTDIv. Since this procedure is time consuming, we designed MATLAB-based software to reduce such calculations. To design the software, GUI toolbar of MATLAB software was used. To test the software, scan parameters of two patients for head and pelvis scan were read from PACS and lateral (LAT) and anterior-posterior (AP) sizes were measured. Finally, SSDEs were calculated for two patients by the software. The software can be measured based on AP and/or LAT measures and/or in special cases (under the age of 18) through patients’ age.

Background and Objective Land surface temperature is a vital indicator for studying environmental changes, hydrological conditions and the energy balance of the earth, which can also be used to monitor the temperature changes of cities. The lack of meteorological stations in most parts of the country, including the study area, has created information limitations in the field of surface temperature data. There are also a large number of non-remote sensing users who need LST maps, and most of them are not familiar enough with LST computing software and inevitably have to spend a lot of time mapping to prepare their maps. This process can be time-consuming even for remote sensing professionals if the number of images is high. The use of valid data for validation that has the least time difference with the satellite passes time is very important in estimating the accuracy of the results. By reviewing internal research similar to the one under study, most internal studies used only meteorological station data to validate the results, the data recording time at these stations is different from the satellite passes time. In this study, due to the large area of the study area and the insufficient number of meteorological stations, in addition to the surface temperature data measured in synoptic stations, the land surface temperature in two ground stations was recorded simultaneously with the satellite. Creating a graphical user interface (GUI) to automatically calculate the surface temperature of Ardabil city with two single-channel and RTE algorithms and use the results to evaluate the temperature changes of land uses Materials and Methods In this study, in order to automatically calculate the land surface temperature of Ardabil city from three types of data: Landsat 5 and 8 satellite images, land surface temperature data recorded at two meteorological stations in the study area and also due to an insufficient number of stations Meteorological data land surface temperature data measured with digital thermometers are also used as the satellite passes. After preparing thermal and multispectral images, first MODTRAN web computing software was used to model the atmospheric transferability and atmospheric coefficients were extracted. Then, to create graphical user interfaces and automatic calculation of LST, land surface temperature with two algorithms single-channel and RTE method with Landsat 5 and Landsat 8 satellite images for two dates: 31/07/2000 and 21/08/2019 in MATLAB software were coded and using these codes, graphical user interfaces were created for each algorithm and finally, an automatic land surface temperature calculator application was produced. Also, the land use map of Ardabil city for both mentioned dates was classified and extracted using a random forest algorithm in the Google Earth engine system environment with 7 classes. This algorithm has a much better performance compared to traditional methods such as maximum likelihood due to its hierarchical structure in selecting each pixel to the appropriate class. To validate surface temperature maps from two types of surface temperature data recorded in two meteorological stations and surface temperature recorded by a digital thermometer that simultaneously passes the satellite in two points of the homogeneous non-urban environment with agricultural use (alfalfa) and Bayer that product It was harvested, used. To evaluate the accuracy of land use maps, using Google Earth, which has a better spatial resolution than the image used, 248 ground control points were obtained from pure pixels of different land uses and used in the validation process. Also, statistical parameters such as error matrix, overall accuracy and kappa coefficient were applied to the output of both land use maps. Results and Discussion Using the codes written in MATLAB software, graphical user interfaces (GUI) were created and then the automatic LST calculator application was produced. The output of the application was surface temperature maps with single channel algorithms and radiation transfer equation (RTE) for 31/07/2000 using thermal image (band 6) of Landsat 5 satellite TM and 21/08 / 2019 was created by the 10 TIRS sensor band of Landsat 8 satellite. After comparing the output maps with the meteorological station and ground station data, the results showed that the single-channel method had the lowest temperature deviations compared to the stations in both years. After preparing LST maps and selecting the optimal algorithm (single channel), land use maps of Ardabil city were prepared using a random forest algorithm in the GEE platform. Statistical evaluations of the classification results showed that for 2000, the highest pixel interference was related to the middle and poor rangeland class, which has a 16-pixel displacement with residential and rainfed agricultural classes. Due to the improved spatial resolution of the Landsat 8 satellite compared to the Landsat 5, followed by better class separation, this pixel displacement in the 2019 user map shows a smaller value. The most common error was related to the aquaculture class, which had a displacement of 10 pixels with rich rangeland and rainfed agriculture classes. Finally, using the LST map and land use map, the temperature changes of the land uses over a period of 19 years were evaluated. By entering the input images and atmospheric parameters in the application, the land surface temperature was calculated with two one-channel algorithms and the RTE method. Evaluation of output maps with meteorological and terrestrial data showed that the single-channel algorithm with a difference of +2. 5 and-2 with stations 1 and 2 for the year 2000 and with a temperature difference of +1. 3, +0. 9,-1 and-0. 9 with stations 1, 2, 3 and 4 in 2019, respectively, had higher accuracy than the RTE method. Also, the results of validation of land use maps showed an overall accuracy of 0. 95 and a kappa coefficient of 0. 94 for 2000 and overall accuracy of 0. 96 and a kappa coefficient of 0. 95 for 2019. Conclusion Assessing the relationship between land surface temperature and land use maps showed that despite the significant physical growth of the urban sector over a period of 19 years, except for residential areas, all land uses in 2019 compared to 2000 with an increase in average surface temperature. It seems that factors such as the expansion of agricultural lands with irrigated cultivation around the urban area up to a radius of 10 km and the entanglement of these farms with the urban sector have a great impact on the temperature adjustment of the urban sector. In 2000, these lands were mainly under cultivation of rain-fed crops, and by solving the water problem (digging deep wells and water transfer projects), they became orchards and irrigated farms such as potatoes. Due to the high water requirement, these products also have high greenery, and this factor has increased the rate of evapotranspiration, followed by cooling of the cultivation area and the urban sector. Among other classes, in both years of water use, the lowest and the use of barren lands had the highest average surface temperature. The generated application can be run on any operating system that supports the exe format, and the user by specifying atmospheric parameters can automatically estimate the LST. This application can also be used in various sectors such as agricultural systems, and climate and water resources management.

This paper focuses on the development of a Graphical User Interface (GUI) and Artificial Neural Network (ANN) for the prediction of photovoltaic (PV) power output. PV power is generated based on the time, location, and surrounding climate conditions. Therefore, solar power generation predictions using computational methods are needed since the changing weather, which will impact the output power will not generate according to its rating. The objectives of this research are to predict photovoltaic power output at Universiti Tun Hussein Onn Malaysia (UTHM), develop an ANN configuration that can perform the prediction of solar power generation, and design GUI system that can both perform the calculations of power generation and ANN. In order to test the efficiency and reliability, MATLAB software has been used to develop the GUI and ANN, and the output is compared with the proposed mathematical equations. The real data as input data was obtained from the PV solar panel located at GSEnergy Focus Group fertigation site. The GUI with user-friendly features and ANN have been successfully designed and developed which can perform daily prediction of solar power output. On top of that, the results have shown that the ANN predictions are more precise to the real data than the GUI.

E-learning tools should be developed based on learners' psychology. Many studies have been conducted on the nature of learning and the factors affecting it. One of the psychological issues that should be considered is the user interface in E-learning because the user interface (UI) is the point of interaction between the user and the learner. The user interface influences the possibility of using an application and the ease of learning. If such correlation fails, the training objectives may not be achieved, even if the training content is well chosen and the user is willing to learn. For this reason, the main issues in successful collaboration, which should be considered in designing user interfaces for E-learning and educational applications, are the focus of this study. This research aims to investigate the rules of graphic user interface design for the design of Iranian educational applications. The research method is a descriptive survey, and the data collection methods are library-based and qualitative. One hundred educational applications published in the Google Store, rated between 4 and 5, have been examined in this study. These applications have been reviewed regarding overall design style, fonts, primary colors, icons, and more. Also, a questionnaire was designed to know the importance of each item from the audience's point of view, and it was distributed among 169 people, and its results were analyzed and checked using SPSS. The results showed that successful applications use similar design styles, fonts, colors, and icons, which can be used as a suitable model.

The data acquisition system of the Alvand tokamak is a very old system of 32 channels. The data capacity of each channel is 2 kilobytes, altogether 64 kilobytes, which store the experimental data of selected channels in binary format. The most important deficiency of this system is the use of the CGA graphic adapter resolution of 320240× pixels of 4 bits in-depth. By considering the old graphical user interface, this deficiency has made displaying the experimental data in more detail impossible. Due to the old software used to display the experimental data, updating to an appropriate graphical environment, that can display the data on a typical modern computer at this laboratory, is necessary. For this purpose, a software package was developed to speed up the data analysis of experiments. The core of this package includes 400 lines and the graphical user interface consists of 3000 lines of Matlab code.

This paper presents a Graphical User Interface (GUI) and simulator, which is designed for a cable suspended robot (ICaSbot), in Lab VIEW environment. This interface is designed to be used for training users in a virtual environment and also controlling the cable robot in an on-line manner. The proposed GUI consists of kinematics, dynamics and on-line control sections. All the mentioned sections are involved in the simulator of the robot employed to display the motion of the end-effector in a virtual environment. Using the proposed GUI, the user is able to exert the desired commands and study the end-effector motion and all of its kinematics and kinetics output in a virtual environment. Afterward, this motion can be applied to the real robot in the part called "hardware control", while six different control methodologies can be selected. The controlling commands, such as driving the motors and monitoring the actual data received from the sensors, can be managed in this part of the GUI. The efficiency and applicability of the designed GUI are proved by conducting some ISO and experimental tests on the cable robot of IUST, called ICaSbot, and comparing the results with simulation, including repeatability and accuracy tests and tracking a predefined trajectory.

Structural health monitoring (SHM) plays a critical role in preventing bridge failures by enabling the assessment of a bridge's current condition under various loading scenarios. However, the complex interplay of numerous dependent and independent structural parameters makes it challenging to accurately estimate a bridge's health. To address this challenge, we present the Integrated Bridge Health Monitoring Toolbox (IBHMT). The IBHMT is a user-friendly toolbox that streamlines the SHM process for concrete bridges. It leverages existing operational methods, such as visual inspection, static and dynamic testing, and non-destructive testing, in three distinct phases. Each phase builds upon the previous one, allowing users to progress from basic health assessments to a comprehensive understanding of the bridge's physical parameters. Phase 1: Initial Assessment - This phase focuses on a preliminary evaluation using visual inspection techniques. Users record observations of damage and assign severity levels to specific locations on the bridge. IBHMT utilizes this information and a structural analysis engine (e.g., CSiBridge) to perform basic calculations and assess the overall health status. The toolbox then suggests areas for further investigation based on the initial findings. Phase 2: Rapid Assessment - Building upon the initial assessment, Phase 2 incorporates data from rapid assessment methods to create a more refined analytical model. This model is then used for a more comprehensive structural analysis, providing valuable insights into the bridge's behavior under different loading conditions. Phase 3: Model Updating - The final phase utilizes data from Non-Destructive Testing (NDT) techniques to further refine the structural model. This refined model allows for advanced structural analysis, enabling engineers to assess the bridge's long-term performance and remaining service life with greater confidence. The IBHMT integrates a user-friendly Graphical User Interface (GUI) developed using MATLAB. This GUI facilitates data entry for each phase and performs automated data processing and analysis. Users can easily enter information related to visual observations, rapid assessment tests, and NDT results. The toolbox then presents clear and concise results, eliminating the need for expertise in complex software tools. This user-centric design empowers engineers and bridge inspectors to efficiently navigate the SHM process. The IBHMT offers several advantages for bridge owners, infrastructure managers, and decision-makers. It provides a structured and integrated SHM approach, streamlining the process from basic inspections to advanced model updating. This valuable information enables proactive maintenance strategies, ultimately extending the lifespan of concrete bridges and reducing the risk of costly repairs or service disruptions. The user-friendly interface allows even those new to SHM practices to get started, while subsequent phases cater to more detailed analyses. This flexibility addresses the varying needs and resource constraints within the infrastructure management domain. In conclusion, the IBHMT presents a comprehensive and user-friendly solution for bridge health monitoring. By integrating existing methods and employing sophisticated data processing techniques, the toolbox empowers engineers to gain valuable insights into the structural health of bridges. This information is crucial for ensuring the safety and functionality of bridges, ultimately contributing to a more resilient transportation infrastructure network.

Background: Independent Component Analysis (ICA) is the most common and standard technique used in functional neuroscience data analysis. Objective: In this study, two of the significant functional brain techniques are introduced as a model for neuroscience data analysis. Material and Methods: In this experimental and analytical study, Electroencephalography (EEG) signal and functional Magnetic Resonance Imaging (fMRI) were analyzed and managed by the developed tool. The introduced package combines Independent Component Analysis (ICA) to recognize significant dimensions of the data in neuroscience. This study combines EEG and fMRI in the same package for analysis and comparison results. Results: The findings of this study indicated the performance of the ICA, which can be dealt with the presented easy-to-use and learn intuitive toolbox. The user can deal with EEG and fMRI data in the same module. Thus, all outputs were analyzed and compared at the same time,the users can then import the neurofunctional datasets easily and select the desired portions of the functional biosignal for further processing using the ICA method. Conclusion: A new toolbox and functional graphical user interface, running in cross-platform MATLAB, was presented and applied to biomedical engineering research centers.

This paper discusses the development of a new GA for layout design. The GA was already designed and reported. However the implementation used in the earlier work was rudimentary and cumbersome, having no suitable Graphical User Interface, GUI. This paper discusses the intricacies of the algorithm and the GA operators used in previous work. It also reports on implementation of a new GA operator which was not included in earlier reports. The software was then used to conduct a series of experimentations to establish the best configuration of the operators for better results. The paper is also demonstrating a comparison of the new GA results and results from the literature. In addition the results show the solution of two new problems by various methods from the author’s own layout developments in industry. The results demonstrate that in most cases the new GA is superior to the existing methods. In particular the speed of the new GA is achieving a reasonable solution is significantly low.