Amirkabir University of Technology

About: Amirkabir University of Technology is a education organization based out in Tehran, Iran. It is known for research contribution in the topics: Nonlinear system & Finite element method. The organization has 15254 authors who have published 31165 publications receiving 487551 citations. The organization is also known as: Tehran Polytechnic & Tehran Polytechnic University.

Overview of wearable electronics and smart textiles

Abstract: Protection and esthetics are the two common characteristics typically associated with textiles as clothing. Nevertheless, with the quickly altering needs of today’s consumers, a third characteristic is rising – that of “intelligence” – that is being integrated into fabrics to produce interactive or textiles (or i-textiles). The term electronic textiles, or e-textiles, are used to denote the class of fabric structures that integrate electronic elements with textiles and can sense changes in its environment and respond to it. This new class of wearable electronic systems is being designed to meet new and innovative applications in the military, public safety, healthcare, space exploration, sports, and consumer fitness fields. The goal of this paper is to focus on recent advances in the field of Smart Textiles and pay particular attention to the materials and their manufacturing process. Each technique shows advantages and disadvantages and the aim of this study is to improve the overall usability of...

Photo induced silver on nano titanium dioxide as an enhanced antimicrobial agent for wool

Abstract: In this study an effective nanocomposite antimicrobial agent for wool fabric was introduced. The silver loaded nano TiO(2) as a nanocomposite was prepared through UV irradiation in an ultrasonic bath. The nanocomposite was stabilized on the wool fabric surface by using citric acid as a friendly cross-linking agent. The treated wool fabrics indicated an antimicrobial activity against both Staphylococcus aureus and Escherichia coli bacteria. Increasing the concentration of Ag/TiO(2) nanocomposite led to an improvement in antibacterial activities of the treated fabrics. Also increasing the amount of citric acid improved the adsorption of Ag/TiO(2) on the wool fabric surface leading to enhance antibacterial activity. The EDS spectrum, SEM images, and XRD patterns was studied to confirm the presence of existence of nanocomposite on the fabric surface. The role of both cross-linking agent and nanocomposite concentrations on the results was investigated using response surface methodology (RSM).

Interior-Point Method for Reservoir Operation with Stochastic Inflows

Abstract: A new method is proposed for long-term reservoir operation planning with stochastic inflows. In particular, the problem is formulated as a two-stage stochastic linear program with simple recourse. The stochastic inflows are approximated by multiple inflow scenarios, leading to a very large deterministic model which is hard to solve using conventional optimization methods. This paper presents an efficient interior-point optimization algorithm for solving the resulting deterministic problem. It is also shown how exploiting the problem structure enhances the performance of the algorithm. Application to regulation of the Great Lakes system shows that the proposed approach can handle the stochasticity of the inflows as well as the nonlinearity of the operating conditions in a real-world reservoir system.

A Novel ANFIS-Based Islanding Detection for Inverter-Interfaced Microgrids

Abstract: This paper presents a new islanding detection strategy for low-voltage inverter-interfaced microgrids based on adaptive neuro-fuzzy inference system (ANFIS) The proposed islanding detection method exploits the pattern recognition capability of ANFIS and its nonlinear mapping of relation between inputs The ANFIS monitors seven inputs measured at point of common coupling (PCC), namely root-mean square (RMS) of voltage and current (RMS U and RMS I ), total harmonic distortion (THD) of voltage and current (THD U and THD I ), frequency ( ${f}$ ), and active and reactive powers ( ${P}$ , ${Q}$ ) that are experimentally obtained based on practical measurement in a real-life microgrid The proposed method is composed of passive monitoring of the mentioned inputs It does not influence power quality (PQ) and considerably decreases non detection zones (NDZs) In order to cover as many situations as possible, minimize false tripping and still remain selective; type and number of samples are introduced Here, one of the primary goals is reducing NDZ while keeping PQ in order Based on the sampled frequency and number of samples, we find that the proposed method has less detection time and better accuracy when compared to the reported methods Simulations performed in MATLAB/Simulink software environment and several tests performed based on different active load conditions and multiple distributed generation, prove the effectiveness, authenticity, selectivity, accuracy and precision of the proposed method with allowable impact on PQ according to UL1741 standard

Low-Density Parity-Check Lattices: Construction and Decoding Analysis

Abstract: Low-density parity-check codes (LDPC) can have an impressive performance under iterative decoding algorithms. In this paper we introduce a method to construct high coding gain lattices with low decoding complexity based on LDPC codes. To construct such lattices we apply Construction D', due to Bos, Conway, and Sloane, to a set of parity checks defining a family of nested LDPC codes. For the decoding algorithm, we generalize the application of max-sum algorithm to the Tanner graph of lattices. Bounds on the decoding complexity are derived and our analysis shows that using LDPC codes results in low decoding complexity for the proposed lattices. The progressive edge growth (PEG) algorithm is then extended to construct a class of nested regular LDPC codes which are in turn used to generate low density parity check lattices. Using this approach, a class of two-level lattices is constructed. The performance of this class improves when the dimension increases and is within 3 dB of the Shannon limit for error probabilities of about 10-6. This is while the decoding complexity is still quite manageable even for dimensions of a few thousands