Search results for: Siavash Heydarzadeh
5 A 1.8 V RF CMOS Active Inductor with 0.18 um CMOS Technology
Authors: Siavash Heydarzadeh, Massoud Dousti
Abstract:
A active inductor in CMOS techonology with a supply voltage of 1.8V is presented. The value of the inductance L can be in the range from 0.12nH to 0.25nH in high frequency(HF). The proposed active inductor is designed in TSMC 0.18-um CMOS technology. The power dissipation of this inductor can retain constant at all operating frequency bands and consume around 20mW from 1.8V power supply. Inductors designed by integrated circuit occupy much smaller area, for this reason,attracted researchers attention for more than decade. In this design we used Advanced Designed System (ADS) for simulating cicuit.
Keywords: CMOS active inductor , 0.18um CMOS technology , ADS
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 33344 Implemented 5-bit 125-MS/s Successive Approximation Register ADC on FPGA
Authors: S. Heydarzadeh, A. Kadivarian, P. Torkzadeh
Abstract:
Implemented 5-bit 125-MS/s successive approximation register (SAR) analog to digital converter (ADC) on FPGA is presented in this paper.The design and modeling of a high performance SAR analog to digital converter are based on monotonic capacitor switching procedure algorithm .Spartan 3 FPGA is chosen for implementing SAR analog to digital converter algorithm. SAR VHDL program writes in Xilinx and modelsim uses for showing results.Keywords: Analog to digital converter, Successive approximation, Capacitor switching algorithm, FPGA
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 43663 Development of a Nano-Alumina-Zirconia Composite Catalyst as an Active Thin Film in Biodiesel Production
Authors: N. Marzban, J. K. Heydarzadeh M. Pourmohammadbagher, M. H. Hatami, A. Samia
Abstract:
A nano-alumina-zirconia composite catalyst was synthesized by a simple aqueous sol-gel method using AlCl3.6H2O and ZrCl4 as precursors. Thermal decomposition of the precursor and subsequent formation of γ-Al2O3 and t-Zr were investigated by thermal analysis. XRD analysis showed that γ-Al2O3 and t-ZrO2 phases were formed at 700 °C. FT-IR analysis also indicated that the phase transition to γ-Al2O3 occurred in corroboration with X-ray studies. TEM analysis of the calcined powder revealed that spherical particles were in the range of 8-12 nm. The nano-alumina-zirconia composite particles were mesoporous and uniformly distributed in their crystalline phase. In order to measure the catalytic activity, esteriļ¬cation reaction was carried out. Biodiesel, as a renewable fuel, was formed in a continuous packed column reactor. Free fatty acid (FFA) was esterified with ethanol in a heterogeneous catalytic reactor. It was found that the synthesized γ-Al2O3/ZrO2 composite had the potential to be used as a heterogeneous base catalyst for biodiesel production processes.Keywords: Nano-alumina-zirconia, composite catalyst, thin film, biodiesel.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17482 Design of a Permanent Magnet Synchronous Machine for the Hybrid Electric Vehicle
Authors: Arash Hassanpour Isfahani, Siavash Sadeghi
Abstract:
Permanent magnet synchronous machines are known as a good candidate for hybrid electric vehicles due to their unique merits. However they have two major drawbacks i.e. high cost and small speed range. In this paper an optimal design of a permanent magnet machine is presented. A reduction of permanent magnet material for a constant torque and an extension in speed and torque ranges are chosen as the optimization aims. For this purpose the analytical model of the permanent magnet synchronous machine is derived and the appropriate design algorithm is devised. The genetic algorithm is then employed to optimize some machine specifications. Finally the finite element method is used to validate the designed machine.Keywords: Design, Finite Element, Hybrid electric vehicle, Optimization, Permanent magnet synchronous machine.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 41131 Mining Implicit Knowledge to Predict Political Risk by Providing Novel Framework with Using Bayesian Network
Authors: Siavash Asadi Ghajarloo
Abstract:
Nowadays predicting political risk level of country has become a critical issue for investors who intend to achieve accurate information concerning stability of the business environments. Since, most of the times investors are layman and nonprofessional IT personnel; this paper aims to propose a framework named GECR in order to help nonexpert persons to discover political risk stability across time based on the political news and events. To achieve this goal, the Bayesian Networks approach was utilized for 186 political news of Pakistan as sample dataset. Bayesian Networks as an artificial intelligence approach has been employed in presented framework, since this is a powerful technique that can be applied to model uncertain domains. The results showed that our framework along with Bayesian Networks as decision support tool, predicted the political risk level with a high degree of accuracy.Keywords: Bayesian Networks, Data mining, GECRframework, Predicting political risk.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2173