This study presents the kinematic analysis of a four-degree freedom medical robotic arm using the Matlab and the robotic-tool, the arm was designed using a solid work program, As well as details of the control of the real design of this arm using Arduino Mega 2560, The specialist enters the position to be reached by the automatic arm (injection position), Or moving the arm to any position by entering the values of the corners of the joints, In this search, we have moved the arm to the selected position Without injecting into the muscle which need another study and a medical sensor determines the amount of needle entry in the muscle, According to criteria determined by the specialist and can be added to the designed interface.

BLDC motors are used in various industries due to their efficiency, reliability and controllability. Among these applications, electric and hybrid vehicles, robotics and automation systems, residential electronics, aerospace industries, medical equipment, wind turbines and solar systems can be mentioned. In many of these applications, dynamic motor speed control is needed. In this paper, due to the importance of the subject, at first, by applying the PLECS software and using the PWM method along with the PID controller, the simulation of the dynamic speed control of the BLDC motor with dynamic speed references is performed, and then, the experimental implementation of the BLDC motor drive using Arduino Mega microcontroller board, in the conditions of dynamic changes of speed references, is accomplished and the corresponding results are presented. Labview software is used to display and record speed data on the computer. The simulation and experimental results show that the BLDC motor has good efficiency in tracking the dynamic speed references up to the dynamic frequency of 0.3 Hz.

Today Mega-university, Mega-school, and Mega-teachers by using of educational technology can be concerned to people who are interested to medical education. Mega-schools increase the quality of education in medical sciences by creating collaborative, educational, and therapeutic content along with gamified exercises on a completely independent platform, consisting of students, professors, and university administrators.

The IoT monitoring system for stingless bee colonies aims to provide real-time information about temperature, humidity, and hive weight in response to the issue of colony collapse disorder (CCD) caused by human intervention in beekeeping. It also aims to improve the current monitoring methods for the bees more effectively and efficiently. The monitoring system features a water-cooling control system to maintain an optimal temperature for Tetragonula Biroi (Stingless Bees). The system also includes a user dashboard for remote monitoring and alerts the beekeeper when it is time to harvest. It’s primarily built around the ESP8266-MOD microcontroller, with an Arduino Mega 2560 R3 for the water valve control system. Data were collected from a DHT22 sensor for temperature and humidity, and load cells connected to an HX711 amplifier for hive weight. The system was tested by comparing samples from the system and actual measuring instruments using MAPE for two months, and it demonstrated 98.74% and 97.89% accuracy for surrounding temperature and humidity, respectively. An accuracy of 95.92% for the weight scale and 93% for the water valve control system was also obtained. Hives equipped with the IoT system gained 3.414% more weight than those without it, indicating that the project succeeded in achieving its objectives.

Microfluidics has many applications in modern sciences such as medicine and biomedical engineering. There are usually two ways of injecting fluids; using pressure regulations in fluid flow lines and using syringe pumps, which using syringe pumps is the most common way. Today, a lot of research has been done in this field, but a limited number of them have focused on active control of the droplet size. In this research, a microchannel was first fabricated using photolithography. To inject fluids into the channels, a syringe pump is designed and built using a DC motor with suitable speed and torque and the L298N module. The fluids used in this research are double distilled water as a discrete phase and oil as a continuous phase. An Arduino Mega 2560 board has also been used as the processor to automatically control this system. The droplet diameter is calculated using a digital microscope and its image processing with a high-speed algorithm. The sliding mode control algorithm has been used to control the droplet size due to the nonlinearity of the system behavior as well as the disturbances. The obtained results for three different diameters i.e. 82, 90, and 100 µm, show the accurate performance of the sliding mode controller.

Introduction: Yardangs due to intensive wind erosion are exclusive landforms on the earth's desert and possibly occur on Mars and Venus. The recent advances in the remote sensing technique and easily available of high resolution satellite data e.g. QuickBird provide useful information of remote area. Hence the Mega-yardangs with tens meter high and hundred meters long are easily identifiable on satellite images and their global distribution and properties can be mapped.The Lut desert (Dasht-e Lut) in the south east of Iran is described as the “thermal pole of the Earth” (Mildrexler et al., 2006). With an area of about 80, 000 square km it is regarded to the hottest and the driest desert in the world (Alavi Panah et al., 2007; Gabriel, 1938; Mildrexler et al., 2006).Yardangs are streamlined forms up to 150 km long and 75 m in height resulting from a number of formative processes, including wind abrasion, deflation, fluvial incision, desiccation cracks, slumping, weathering and mass movement (Goudie, 2007; McCauley et al., 1977; Ward and Greeley, 1984). A limited number of morphometric investigations have been done on yardangs. Goudie (2007) identified Mega-yardangs in hyper-arid environments with total rainfall less than 50 mm including central Asia, the Lut desert in Iran, northern Saudi Arabia, Bahrain, the Libyan Desert in Egypt, the central Sahara, the Namib desert, the high Andes and Peruvian desert. According to Goudie, these features develop in a wide range of rock types e.g. sandstones, ignimbrites, limestones and basement rocks by a relatively unimodal wind direction.Materials and Methods: In this study 3 arc second DEM of version 3.0 SRTM data (~90 m) with geographic projection acquired was used. That was re-projected to UTM grid with WGS 84 Datum.We used 90 m DEM produced from version 3 SRTM 3 arc second data and the SOM algorithm for identification of yardangs in the western part of Lut desert. Self-Organizing Map (SOM) is an unsupervised and nonparametric artificial neural network algorithm that clusters high dimensional input vectors into low dimensional (usually two dimensional) output map which preserve topology of the input data. In geomorphic studies of landscapes, the first and second order derivatives of DEM are the basic components for morphometric analysis (Evans, 1972). The second order derivatives of DEM are affected by geomorphological processes (Evans, 1972; Wood, 1996 b). To calculate the morphometric features, a local window is passed over the SRTM DEM and the change in gradient of a central point in relation to its neighbors is derived by a bivariate quadratic function. Wood (1996 a) defined a set of criteria to classify DEMs into morphometric classes. Yardang identification and analysis in the study area was performed using the parameters proposed by Wood (1996 a). A local window of 5x5 is passed over the DEM and slope, cross- sectional curvature, maximum and minimum curvatures are derived by fitting a bivariate quadratic approximation surface. The derived morphometric parameters were used as an input to SOM.Frequency histograms and average quantization error of the results are compared. Two dimensional plots of mean values of morphometric parameters (feature space), oblique views of map units draped over the DEM, Landsat ETM+ data and high resolution Quick Bird images were used to study the Mega yardangs in other places than Iran.Results and Discussion: Learning of the SOM was performed with four morphometric parameters as the inputs and a two-dimensional output of 10 neurons. The map with initial radius of 3, final neighborhood radius of 0.01 and 1000 iterations shows the best performance for yardang identification. The output map units from SOM are just numbers and need to be analyzed and interpreted. Studying the spatial relationship between different map units along with their morphometric parameters using feature space analysis allowed us to interpret and label them corresponding to morphometric features e.g. yardangs. Major morphometric features (corridor, planar and yardang) are identified in two-dimensional feature space plots of mean values of maximum curvature (x-axis) and minimum one (y-axis). The analysis of the results and corresponding satellite images shows the effectiveness of the method to identify the overall pattern of the morphometric features in the Lut desert. It is clear that the pattern of yardangs and their corridors running from NNW to SSE direction is parallel to the prevailing wind known as “wind of 120 days or Bad-i-sad-o-bist rooz-e Systan.Conclusion: The results show that digital terrain analysis methods applied on SRTM in the proposed way in this study could extract morphotectonic features from SRTM along Dehshir fault and they contributed to the tectonic interpretation of the study area. According to the evidences extracted from SRTM along Dehshir fault, for example: fault traces, deflected and beheaded drainages, pattern of network drainages, erosion surfaces of uplifted and back erosion of drainages because of the location (situated in quaternary landforms), they are neotectonic evidences for activity of Dehshir fault during quaternary. Our results reveal that the morphometric analysis and feature space analysis of the first and second order derivatives of DEM such as slope, cross-sectional curvature, maximum curvature and minimum curvature led to the description of SOM outputs as yardangs, corridors and planar. Slope allows distinguishing among morphometric features in sub levels.The optimal self organizing map with suitable learning parameters should be selected for feature identification. The lowest average quantization error of 0.1040 was achieved with an initial radius of 3, a final neighborhood radius of 0.01 and 1000 iterations. Result of this method revealed that from the total 6481 km2 coverage of the study area, about 2035 km2 (34%) are classified as yardang while corridors, in total cover 2732 km2 (43%)

Open access Mega journals represent an increasingly important part of the scholarly communications. The current research aims to introduce eight international Mega journals and to investigate their performance in a five-year time span (2012-2016). The current study is an applied research in terms of objectives while it is a descriptive study in terms of data analysis and conducted using scientometric indicators. Research population comprised of 195011 articles published in eight Mega journals during 2012-2016 and indexed by the Web of Science. Data was collected using three products of the Clarivate Analytics, namely Web of Science, Journal Citation Reports as well as InCites. Data analysis was conducted using Microsoft Excel. Results of the study showed 101% growth in 2016 compared to 2012 with regard to publications in eight studied Mega journals. A total of 195011 articles have been published in eight Mega journals during 2012-2016. Considering article processing fees of each journal, we can assume that roughly 300 million USD has been charged by eight Mega journals. Papers published in Mega journals were found to have higher citation impact compared with the average of the Web of Science database. Results revealed that two Mega journals, namely PLoS One and Scientific Reports, were accountable for 91. 6% of total publications and 96. 1% of total citations. The highest share of publications in eight Mega journals was found to be in the following research categories: Biochemistry & Molecular Biology, Multidisciplinary Sciences, Neurosciences, Oncology and Immunology. Moreover, the US, China, the UK, Germany and Japan had the highest number of publications in eight studied Mega journals. Reputable publishers have identified a market demand for publication of scholarly output and are offering their services using open access Mega journals. The Mega journal market seems likely to keep increasing in the future.

Background: People with severe disabilities, especially spinal cord injury (SCI), encounter many difficulties in communicating with computer systems, because their problem is generally not addressed in computer programs. Objectives: With the advent of technology and the move toward Internet of Things (IoT), a new technique has been developed by combining an eye tracking system with IoT to create a platform for the use of SCI patients. Methods: Eye tracking methods include invasive, non-invasive and semi-invasive techniques. A non-invasive method in which the eye movement is traceable in visible or infrared light is used in this research. An algorithm is designed and developed that allows an IoT-based connection providing higher speed and precision compared with previous algorithms. Therefore, this technique is novel in application of eye tracking for issuing control commands in an IoT-based smart home by individuals with SCI or other physical disabilities. The totalcommandreceipt, confirmation, and execution time in this system is less than 10 seconds. The optical conditions in this research were 5 ~ 300 lux and 2 ~ 6 lux in invisible and infrared light processing, respectively. It produced 97% correct responses with the help of statistical weighted averaging and elimination of bad data. This system uses the Arduino Mega 2560 board in IoT part, and MATLAB software in feature-based face detection processing. Results: This methodology improved the quality and accuracy of gaze tracking due to the following reasons: enhanced image clarity, use of two-eye processing, and use of statistical weighted averaging, as well as the use of both visible/infrared lights to reduce the sensitivity to the ambient light. This system has the advantage of having no sensitivity to age, gender, hairstyle, beard, mustache, and veil, and the possibility of producing output for several devices. Conclusions: The proposed system is reliable for designing a smart home for SCI patients.