This paper presents a vibration suppression control design of cantilever beam using two piezoelectric patches. One patch was used as an actuator element, while the other was used as a sensor. The controller design was designed via the balance realization reduction method to elect the reduced order model that is most controllable and observable. the sliding mode observer was designed to estimate six states from the reduced order model but three states are only used in the control law. Estimating a number of states larger than that used is in order to increase the estimation accuracy. Moreover, the state estimation error is proved bounded. An optimal LQR controller is designed then using the estimated states with the sliding mode observer, to suppress the vibration of a smart cantilever beam via the piezoelectric elements. The control spillover problem was avoided, by deriving an avoidance condition, to ensure the asymptotic stability for the proposed vibration control design. The numerical simulations were achieved to test the vibration attenuation ability of the proposed optimal control. For 15 mm initial tip displacement, the piezoelectric actuator found able to reduce the tip displacement to about 0.1 mm after 4s, while it was 1.5 mm in the open loop case. The current experimental results showed a good performance of the proposed LQR control law and the sliding mode observer, as well a good agreement with theoretical results.
Medical image segmentation is one of the most actively studied fields in the past few decades, as the development of modern imaging modalities such as magnetic resonance imaging (MRI) and computed tomography (CT), physicians and technicians nowadays have to process the increasing number and size of medical images. Therefore, efficient and accurate computational segmentation algorithms become necessary to extract the desired information from these large data sets. Moreover, sophisticated segmentation algorithms can help the physicians delineate better the anatomical structures presented in the input images, enhance the accuracy of medical diagnosis and facilitate the best treatment planning. Many of the proposed algorithms could perform w
... Show MoreThe main objective of this work is to propose a new routing protocol for wireless sensor network employed to serve IoT systems. The routing protocol has to adapt with different requirements in order to enhance the performance of IoT applications. The link quality, node depth and energy are used as metrics to make routing decisions. Comparison with other protocols is essential to show the improvements achieved by this work, thus protocols designed to serve the same purpose such as AODV, REL and LABILE are chosen to compare the proposed routing protocol with. To add integrative and holistic, some of important features are added and tested such as actuating and mobility. These features are greatly required by some of IoT applications and im
... Show MoreA .technology analysis image using crops agricultural of grading and sorting the test to conducted was experiment The device coupling the of sensor a with camera a and 75 * 75 * 50 dimensions with shape cube studio made-factory locally the study to studio the in taken were photos and ,)blue-green - red (lighting triple with equipped was studio The .used were neural artificial and technology processing image using maturity and quality ,damage of fruits the of characteristics external value the quality 0.92062, of was value regression the damage predict to used was network neural artificial The .network the using scheme regression a of means by 0.98654 of was regression the of maturity and 0.97981 of was regression the of .algorithm Marr
... Show MoreNurse scheduling problem is one of combinatorial optimization problems and it is one of NP-Hard problems which is difficult to be solved as optimal solution. In this paper, we had created an proposed algorithm which it is hybrid simulated annealing algorithm to solve nurse scheduling problem, developed the simulated annealing algorithm and Genetic algorithm. We can note that the proposed algorithm (Hybrid simulated Annealing Algorithm(GS-h)) is the best method among other methods which it is used in this paper because it satisfied minimum average of the total cost and maximum number of Solved , Best and Optimal problems. So we can note that the ratios of the optimal solution are 77% for the proposed algorithm(GS-h), 28.75% for Si
... Show MoreAttack stream cipher system , using cipher text only , depends on the characteristics of plain teKt language and the randomness of the key , that used in encryption , without having detailed k.nuwh:dgt:: uf cipher algorithm by benefiting from the balance between O's and I' in the key to reduce the probability of key space.
Background: Laser urinary stone lithotripsy is an established endourological modality. Ho:YAG(2100nm) laser have broadened the indications for ureteroscopic stone managements to include larger stone sizes throughout the whole urinary tract.
Purpose: To evaluate the effectiveness and safety of Holmium: YAG(2100nm) laser lithotripsy with a semirigid uretero scope for urinary stone calculi in a prospective cohort of 17 patients.
Patients and Methods: Holmium: YAG(2100nm) laser lithotripsy was performed with a semirigid ureteroscope in 17 patients from September 2016 to December 2016. Calculi were located in the lower ureter in 9 patients (52.9%), the midure
... Show MoreThe paper presents a neural synchronization into intensive study in order to address challenges preventing from adopting it as an alternative key exchange algorithm. The results obtained from the implementation of neural synchronization with this proposed system address two challenges: namely the verification of establishing the synchronization between the two neural networks, and the public initiation of the input vector for each party. Solutions are presented and mathematical model is developed and presented, and as this proposed system focuses on stream cipher; a system of LFSRs (linear feedback shift registers) has been used with a balanced memory to generate the key. The initializations of these LFSRs are neural weights after achiev
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