The results of studies of the functional mechanodynamics of the arteries of the cardiovascular system are presented. Methods of mathematical neural computer modeling, developed by the authors, were reproduced the features of blood flow in statics and dynamics, taking into account the spiral laying of vessels smooth muscle with the transfer of its relief through a thin endothelial membrane lining the inner surface. It is shown that the the nature of the blood flow significantly differs with the both quantitative and qualitative characteristics from the blood flow without regard to the spiral endothelial relief repeating helical laying of smooth shell. The developed methods of neurocomputer modeling allow reconstruct and detect events to recreate the picture of the functioning of living bio tissue. Based on the obtained results and neural networks modeling, a new paradigm for the design of implantable cardiac-gadgets purposed.

Forest fires in Sumatra and Kalimantan resulted in degradation of peatlands significantly. The strong indicator of forest and land fires including in peatland can be identified using hotspots which occurred consecutively in 2 to 5 days. The previous studies have been conducted in mining sequence patterns on hotspot datasets in Sumatra and Kalimantan. However, those studies applied the sequential pattern algorithms on the datasets containing temporal and rough spatial features. This study aims to generate sequence pattern of hotspot datasets using the SPADE algorithm with the improvement of the spatial feature. The study results in 892 1-frequent sequences and 28 2-frequent sequence patterns at the minimum support of 0.02%. A total of 484 hotspots were found from the 28 2-frequents sequence patterns, most of which were occurred in September to November 2014 and 2015. Central Kalimantan, Riau, and South Sumatra are the area where hotspots mostly occurred in 2014 and 2015. The visualization module for hotspot sequences was successfully developed in two iterations using the JavaScript.

Ultrasonic waves are most commonly used to measure the presence of an object and its distance from the source using time of flight concept. These are pulses of sound waves that have frequency range higher than the human hearing range. In this paper, we will discuss the measurement of the tilt angle of a robot with respect to a flat base using ultrasonic waves and time of flight concept [2]. An Arduino platform was used with Atmel328P as the processing microcontroller chipset which will then compute the angle of tilt using the distance calculated from an ultrasonic sound transmitter and a receiver using coordinate geometry and trigonometric functions. A combination of gyroscope and accelerometer is also used to find the true tilt angle of the apparatus and then it is compared with the angle readings obtained from the ultrasonic sensor system. A high response time and low delay is necessary for instantaneous angle measurement. Hence, gyroscope-based angles have been used as a reference to adjust filter parameters to decrease error and noise at every iteration.

The main focuses are to design controlling systems of good disturbance, stability rejection, and small error-tracking. Trajectory tracking of robot manipulators are controlled by several methodologies, but when robot manipulator works with uncertain dynamic models, some limitations of this technique appear. Concerning the control perspective, such uncertainty can be divided into two groups: the unstructured inputs (e.g. disturbance effect) and the structure dynamics (e.g. the changes of parameter). Within a small number of applications, some environments, could be unknown or unstructured, make use of robot manipulators, along with some tools of strong mechanics also can make use of new methods of control to design a controller of nonlinear robust with a reasonable performance. So in this paper we test the effect of disturbance in control the first DOF of PUMA 560 using non model based FO-Fuzzy-PID controller and compared its results with two model based controllers (CTC, ANN). Also we study the effect of change of inertias parameters in the 2 cases Model based control and non- Model based control and then discus which controller give the best results. The main objective of this paper is that the non model based FO-Fuzzy-PID is able to emulate the manipulator dynamic behaviour without the need to have a complex nonlinear mathematical model for the robot.

The main objective of this proposed work is to develop an Embedded System for plant monitoring and watering system using Internet of Things, Raspberry Pi as Processor, and sensors for sensing environmental conditions. In this work, IoT concept is introduced to connect devices through Internet and facilitate information access by the users. The system can obtain accurate perception of Environmental information in agriculture field and then transmit the same to users. The system monitors different parameters like Temperature, Humidity, Soil Moisture and Intensity of light. IR sensor is fixed to check any external object entry into the field, in case of intruder detection buzzer will turn on for few seconds. The Motor fixed in the field operates both manually and automatically depending upon Moisture sensor results in soil. Motor automatically switches between on and off stage of pumping action. Results are observed either in web app and monitor.