Welcome to Macro IoT Solution & Engineering Services, where innovation meets excellence in electrical project. Explore how our IoT solutions revolutionize the industry.
3D-Printed Super-Wideband Spidron Fractal Cube Antenna with Laminated Copper:
In this paper, a 3D-printed super-wideband (SWB) Spydron fractal cube antenna is proposed. The Spidron fractal configuration is utilized as a self-complementary structure on each face of a 3D frame to attain SWB characteristics. The antenna is excited through a tapered microstrip balun for both mode transforming and impedance matching.
A prototype of the proposed antenna, including the 3D frame fabricated with the help of a 3D printer and Spidron fractal patches made of copper tape, is experimentally verified. The measured−10 dB reflection ratio bandwidth is 34:1 (0.44–15.38 GHz). The peak gain varies from 3.42 to 9.29 dBi within the operating frequency bandwidth. The measured radiation patterns are nearly omnidirectional at all operating frequency bands.
A 3D-printed SWB Spidron fractal cube antenna is designed using 3D printing technology. To ensure the SWB characteristics, a self-complementary structure constructed using a Spidron fractal configuration is implemented on each face of a 3D frame, with the conductor part created using copper tape. The proposed antenna is excited by a tapered microstrip balun.
The measured−10 dB reflection ratio bandwidth is 34.9:1 (0.44–15.38 GHz). The measured peak gain ranges from 3.42 to 9.29 dBi within the operating frequency band. In addition, the radiation patterns are nearly omnidirectional at every operating frequency. Therefore, the proposed antenna can be feasibly applied in areas which require SWB characteristics.
Project: Electrical Projects, Embedded Projects, Microcontroller Projects, Power Electronics Projects, Security Projects
Coordinated Control Strategies for a Permanent Magnet Synchronous Generator based Wind Energy Conversion System:
In this paper, a novel coordinated hybrid maximum power point tracking (MPPT)-pitch angle based on a radial basis function network (RBFN) is proposed for a variable speed variable pitch wind turbine. The proposed controller is used to maximize output power when the wind speed is low and optimize the power when the wind speed is high. The proposed controller provides robustness to the nonlinear characteristic of wind speed. It uses wind speed, generator speed, and generator power as input variables and utilizes the duty cycle and the reference pitch angle as the output control variables.
The duty cycle is used to control the converter so as to maximize the power output and the reference pitch angle is used to control the generator speed in order to control the generator output power in the above rated wind speed region. The effectiveness of the proposed controller was verified using MATLAB/Simulink software. In this paper, a novel coordinated hybrid maximum power point tracking (MPPT)-pitch angle based on a radial basis function network (RBFN) is proposed for a variable speed variable pitch wind turbine.
The proposed controller is used to maximize output power when the wind speed is low and optimize the power when the wind speed is high. The proposed controller provides robustness to the nonlinear characteristic of wind speed. It uses wind speed, generator speed, and generator power as input variables and utilizes the duty cycle and the reference pitch angle as the output control variables.
The duty cycle is used to control the converter so as to maximize the power output and the reference pitch angle is used to control the generator speed in order to control the generator output power in the above rated wind speed region. The effectiveness of the proposed controller was verified using MATLAB/Simulink software.
A novel coordinated hybrid MPPT-Pitch angle control strategy employing RBFN based ANN technique for PMSG based WECS was proposed to enhance the overall efficiency of wind power generation in all operating regions. The proposed controller tracks the maximum power when the wind speed is below the rated wind speed and limits the output power in the high wind speed region. To develop the controller, a highly non-linear wind speed input was considered.
The wind speed, generator speed, and generated power were selected as the control input variables. The duty cycle and pitch command to the blade were considered as the controlled output variables. The selection of which output variable to be activated is based on the wind speed. In the low wind speed region, the duty cycle is generated to control the power electronics converter thus obtaining maximum available power from the wind speed. When the wind speed exceeds the rated wind velocity, the blade tends to change its angle in order to limit the output power.
Thus, by using the proposed hybrid control strategy, the output power is maximized with an efficiency of 98.1% compared to 97.3% achieved using an individual MPPT control strategy and 96% using an individual control strategy in below rated wind speed; generator power can be optimized and regulated it the rated value of 3 kW in high wind speed regions.
The proposed controller is a suitable alternative for the re-powering of small scale WECS, many of which have been installed in developing countries.
Project: Electrical Projects, MATLAB Projects, Power Electronics Projects, Security Projects, Sensor Projects
Self-Learning Embedded System for Object Identification in Intelligent Infrastructure Sensors:
The emergence of new horizons in the field of travel assistant management leads to the development of cutting-edge systems focused on improving the existing ones. Moreover, new opportunities are being also presented since systems trend to be more reliable and autonomous. In this paper, a self-learning embedded system for object identification based on adaptive-cooperative dynamic approaches is presented for intelligent sensor’s infrastructures.
The proposed system is able to detect and identify moving objects using a dynamic decision tree. Consequently, it combines machine learning algorithms and cooperative strategies in order to make the system more adaptive to changing environments. Therefore, the proposed system may be very useful for many applications like shadow tolls since several types of vehicles may be distinguished, parking optimization systems, improved traffic conditions systems, etc.
Future Work in Electrical Project:
Taking into account the current simulation results, several conclusions are obtained considering different parts of the proposed scheme. On the one hand, for the decision tree algorithm, it is necessary to select the pruning threshold properly in order to optimize the “unknown” area. A low pruning threshold wastes a lot of space in the features space whereas a high pruning threshold degenerates the learning which causes the extinction of some classes.
The optimization of the pruning threshold is mandatory due to the fact that learning capabilities increase when the “unknown” area is optimized. Something similar occurs with clustering threshold. The selection of an adequate threshold affects largely the number and the definition of new objects that the system is able to detect. A low clustering threshold implies the detection of too many objects that in fact belong to the same category.
The Hepatitis C Virus Nonstructural Protein 2 (NS2): An Up-and-Coming Antiviral Drug Target:
Infection with Hepatitis C Virus (HCV) continues to be a major global health problem. To overcome the limitations of current therapies using interferon-α in combination with ribavirin, there is a need to develop drugs that specifically block viral proteins. Highly efficient protease and polymerase inhibitors are currently undergoing clinical testing and will become available in the next few years.
However, with resistance mutations emerging quickly, additional enzymatic activities or functions of HCV have to be targeted by novel compounds. One candidate molecule is the nonstructural protein 2 (NS2), which contains a proteolytic activity that is essential for viral RNA replication. In addition, NS2 is crucial for the assembly of progeny virions and modulates various cellular processes that interfere with viral replication. This review describes the functions of NS2 in the life cycle of HCV and highlights potential antiviral strategies involving NS2.
With almost half of the individuals infected with genotype 1 HCV not responding to the current treatment with interferon-α and ribavirin, novel highly efficient therapies are sorely needed. A new generation of HCV-specific compounds, most of which target either the NS3 protease or the NS5B RNA-dependent RNA polymerase, is expected to become available soon. However, viral escape mutants that lead to resistance against these drugs have already emerged.
For an efficient and sustainable therapy against HCV infection, a strategy targeting multiple enzymatic activities or other functions of the viral proteins has the best chance for success. Recent advances in elucidating the structure and function of NS2 emphasized on the crucial role of this protein in the HCV life cycle. Therefore, NS2 is an excellent candidate molecule to develop additional antiviral therapies against HCV infection.
- Electrical Projects,
- Microcontroller Projects,
- Microprocessor Projects,
- Security Projects,
- Sensor Projects,
- Telecommunications Projects, Wireless Projects
In conclusion, Macro IoT Solution & Engineering Services delivers unparalleled expertise in electrical projects. Experience the future of innovation and efficiency with our cutting-edge solutions. Trust us to power your success.