Sharif University of Technology
Scientia Iranica
1026-3098
2345-3605
27
3
2020
06
01
Variance-based features for keyword extraction in Persian and English text documents
1301
1315
EN
Hadi
Veisi
0000-0003-2372-7969
Faculty of New Sciences and Technologies (FNST), University of Tehran, Tehran, Iran
h.veisi@ut.ac.ir
Niloofar
Aflaki
Kish International Campus, University of Tehran, Kish, Iran
n.aflaki@ut.ac.ir
Pouyan
Parsafard
Kish International Campus, University of Tehran, Kish, Iran
pooyanoarsafard@ut.ac.ir
10.24200/sci.2019.50426.1685
This paper address automatic keyword extraction in Persian and English text documents. Generally, for keyword extraction in a text, a weight is assigned to each token and words having higher weights are selected as the keywords. We have proposed four methods for weighting the words and have compared these methods with five previous weighting techniques. The previous methods used in this paper are term frequency (TF), term frequency inverse document frequency (TF-IDF), variance, discriminative feature selection (DFS), and document length normalization based on unit words (LNU). The proposed weighting methods are based on using variance features and include variance to TF-IDF ratio, variance to TF ratio, the intersection of TF and variance, and the intersection of variance and IDF. <br /> For evaluation, the documents are clustered using the extracted keywords as feature vectors, and K-means, expectation maximization (EM), and Ward hierarchical clustering methods. The entropy of the clusters and pre-defined classes of the documents are used as the evaluation metric. For the evaluations, we have collected and labelled Persian documents. Results show that our proposed weighting method, variance to TF ratio, has the best performance for Persian. Also, the best entropy is resulted by variance to TD-IDF ratio for English.
Keyword Extraction,Term Frequency,Variance,Clustering,Persian Text Processing
http://scientiairanica.sharif.edu/article_21440.html
http://scientiairanica.sharif.edu/article_21440_ad197d880148e31b20fe1bc974c16529.pdf
Sharif University of Technology
Scientia Iranica
1026-3098
2345-3605
27
3
2020
06
01
A genetic algorithm-based framework for mining quantitative association rules without specifying minimum support and minimum confidence
1316
1332
EN
Fateme
Moslehi
School of Industrial Engineering, Iran University of Science & Technology, Tehran, Iran
moslehi_fateme@ind.iust.ac.ir
Abdorrahman
Haeri
School of Industrial Engineering, Iran University of Science & Technology, Tehran, Iran
ab.haeri@gmail.com
10.24200/sci.2019.51030.1969
Discovering association rules is a useful and common technique for data mining in which relations and co-dependencies between datasets are shown. One of the most important challenges of data mining is to discover the rules of continuous numerical datasets. Furthermore, another restriction imposed by algorithms in this area is the need to determine the minimum threshold for the support and confidence criteria. In this paper a multi-objective algorithm for mining quantitative association rules is proposed. The procedure is based on the Genetic Algorithm, and there is no need there is no need to determine the extent of the threshold for the support and confidence criteria. By proposing a multi-criteria method, the useful and attractive rules and the most suitable numerical intervals are discovered, without the need to discrete numerical values and the determination of the minimum support threshold and minimum confidence threshold. Different criteria are used to determine appropriate rules. In this algorithm, the selected rules are extracted based on confidence, interestingness, and cosine2. The results obtained from real-world datasets demonstrate the effectiveness of the proposed approach. The algorithm is used to examine three datasets and the results show the performance superiority of the proposed algorithm compared to similar algorithms.
Data mining,Quantitative Association Rules,Multi-Objective Evolutionary Algorithms,Genetic Algorithm
http://scientiairanica.sharif.edu/article_21432.html
http://scientiairanica.sharif.edu/article_21432_8f2cc4b83db58b59f874fae0d5562fd0.pdf
Sharif University of Technology
Scientia Iranica
1026-3098
2345-3605
27
3
2020
06
01
Constructing automated test oracle for low observable software
1333
1351
EN
Meysam
Valueian
Faculty of Computer Science and Engineering, Shahid Beheshti University, G.C, Tehran, P.O. Box 1983963113, Iran
m.valuyan@mail.sbu.ac.ir
Niousha
Attar
Faculty of Computer Science and Engineering, Shahid Beheshti University, G.C, Tehran, P.O. Box 1983963113, Iran
nio.attar@gmail.com
Hassan
Haghighi
0000-0002-6762-0920
Faculty of Computer Science and Engineering, Shahid Beheshti University, G.C, Tehran, P.O. Box 1983963113, Iran
h_haghighi@sbu.ac.ir
Mojtaba
Vahidi-Asl
0000-0003-4964-992X
Faculty of Computer Science and Engineering, Shahid Beheshti University, G.C, Tehran, P.O. Box 1983963113, Iran
mo_vahidi@sbu.ac.ir
10.24200/sci.2019.51494.2219
Using machine learning techniques for constructing automated test oracles have been successful in recent years. However, existing machine learning based oracles have deficiencies when applied to software systems with low observability, such as embedded software, cyber-physical systems, multimedia software programs, and computer games. This paper proposes a new black box approach to construct automated oracles which can be applied to software systems with low observability. The proposed approach employs an Artificial Neural Network (ANN) algorithm which uses input values as well as corresponding pass/fail outcomes of the program under test, as the training set. To evaluate the performance of the proposed approach, we have conducted extensive experiments on several benchmarks. The results manifest the applicability of the proposed approach to software systems with low observability as well as its higher accuracy in comparison to a well-known machine learning based method.<br /> We have also assessed the effect of different parameters on the accuracy of the proposed approach.
Software testing,Test Oracle,Machine learning,Embedded Software,neural networks
http://scientiairanica.sharif.edu/article_21524.html
http://scientiairanica.sharif.edu/article_21524_06f943a06c6c19a8171e00f781b6ef4e.pdf
Sharif University of Technology
Scientia Iranica
1026-3098
2345-3605
27
3
2020
06
01
Sensitivity analysis of economic variables using neuro-fuzzy approach
1352
1359
EN
Ehsan
Lotfi
0000-0001-6427-0825
Department of Computer Engineering, Torbat-e Jam Branch, Islamic Azad University, Torbat-e Jam, Iran
esilotf@gmail.com
S.
Babrzadeh
Department of Computer Engineering and Information Technology, Payam-e Noor University, Asalooye, Iran
sa.babrzadeh@gmail.com
A.
Khosravi
Center for Intelligence Systems Research, Deakin University, Geelong 3217, Australia
10.24200/sci.2019.5488.1305
Sensitivity analysis (SA) is a vital task for decision making in economic management. In this paper, a novel fuzzy sensitivity analyzer (FSA) is proposed to analyze the sensitivity of economic variables. The proposed FSA algorithm consists of an adaptive neuro-fuzzy inference system (ANFIS) that is adjusted for forecasting economic time series. Based on the output of ANFIS, FSA can determine the importance degree of parameters. In the numerical studies, the proposed method is applied for the sensitivity analysis of oil and gold time series. According to the results, FSA indicates that oil price is highly dependent upon the inflation rate, dollar index and market index while OPEC production level and gold price have less impact. Furthermore, in the gold price modeling, the highest sensitivity is obtained from silver price while demand for gold is more a function of market index and inflation rate. The proposed method can be used in many SA applications.
Fuzzy forecast,economic time series,sensitivity analysis,Soft computing
http://scientiairanica.sharif.edu/article_21402.html
http://scientiairanica.sharif.edu/article_21402_9497845b4a20f771eee97aa1e0a570d7.pdf
Sharif University of Technology
Scientia Iranica
1026-3098
2345-3605
27
3
2020
06
01
Dynamic negawatt demand response resource modeling and prioritizing in power markets
1361
1372
EN
Ali
Abdollahi
a. Department of Economics, Shahid Bahonar University of Kerman, Kerman, Iran.
c. Shakhes Pajouh Research Institute, Isfahan, Iran.
Naser
Pour-Moallem
b. Faculty of Engineering, Imam Khomeini International University of Qazvin, Iran.
c. Shakhes Pajouh Research Institute, Isfahan, Iran.
Amir
Abdollahi
d. Department of Engineering, Shahid Bahonar University, Kerman, Iran.
a.abdollahi@uk.ac.ir
10.24200/sci.2017.4406
In recent years, integrated use of demand- and supply-side resources has been performed by electric utilities, because of its potential attractiveness, both at operation and economic levels. Demand Response Resources (DRRs) can be used as demand side options which are the consequence of implementing Demand Response Programs (DRPs). DRPs comprise the actions taken by end-use customers to reduce their electricity consumption in response to electricity market’s high prices; and/or reliability problems on the electricity network. In this paper, a dynamic economic model of DRPs is derived based upon the concept of flexible elasticity of demand and the customer benefit function. Precise modeling of these virtual negawatt resources helps system operators to investigate the impact of responsive loads on power system studies. This paper also aims to prioritize multifarious DRPs by means of Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and entropy methods. Performance of the proposed model is investigated through numerical studies using a standard IEEE test system.
Customers’ benefit function,Dynamic demand response,Entropy method,Load economic model,TOPSIS
http://scientiairanica.sharif.edu/article_4406.html
http://scientiairanica.sharif.edu/article_4406_964296cc8a2629c26cd96996bc28768c.pdf
Sharif University of Technology
Scientia Iranica
1026-3098
2345-3605
27
3
2020
06
01
Demand response as a complement for wind energy from the viewpoint of system well-being
1373
1383
EN
M. N.
Hassanzadeh
Department of Electrical and Computer Engineering, Islamic Azad University, Science and Research Branch, Tehran, P.O. Box: 1477893855, Iran
M.
Fotuhi-Firuzabad
Center of Excellence in Power System Control and Management, Department of Electrical Engineering, Sharif University of
Technology, Tehran, P.O. Box 11155-8639, Iran
fotuht@sharif.edu
A.
Safdarian
Center of Excellence in Power System Control and Management, Department of Electrical Engineering, Sharif University of
Technology, Tehran, P.O. Box 11155-8639, Iran
Soodabeh
Soleymani
Department of Electrical and Computer Engineering, Islamic Azad University, Science and Research Branch, Tehran, P.O. Box: 1477893855, Iran
10.24200/sci.2018.20605
The risk imposed by the stochastic nature of wind energy sources has always been a major barrier despite their proliferation in power systems. To further penetrate these sources, this paper draws upon dynamic prices, which realize demand response potentials along with decimating the risk involved. To do so, a model is first established to study the impacts of activating demand response, on the risk index in a system with a high penetration of wind resources. Then, the model is used to estimate the extra wind capacity that can be hosted by the system such that the risk remains within the acceptable range. The well-being indices are calculated via sequential Monte Carlo simulation approach and Fuzzy theory. The demand response with dynamic prices is modeled by self and cross elasticity coefficients of different load sectors. The performance and applicability of the proposed model are verified through simulations on the IEEE Reliability Test System. (IEEE-RTS).
Demand side management,Dynamic Pricing,elasticity coefficient,wind energy sources,well-being analysis
http://scientiairanica.sharif.edu/article_20605.html
http://scientiairanica.sharif.edu/article_20605_8f95802f6aa55fd85f16cacd439ce2a2.pdf
Sharif University of Technology
Scientia Iranica
1026-3098
2345-3605
27
3
2020
06
01
Analytic solution of a system of linear distributed order differential equations in the Reimann-Liouville sense
1384
1397
EN
Hamed
Taghavian
Department of Electrical Engineering Sharif University of Technology, Tehran, Iran
Mohammad Saleh
Tavazoei
Department of Electrical Engineering Sharif University of Technology, Tehran, Iran
10.24200/sci.2018.20335
In this paper, solution of a system of linear differential equations of distributed order in the Riemann-Liouville sense is analytically obtained. The distributed order relaxation equation is a special case of the system investigated in this paper. The solution of the mentioned system is introduced on the basis of a function which can be considered as the distributed order generalization of the matrix Mittag-Leffler functions. It is shown that this generalized function in two special cases of the weight function can be expressed in terms of the multivariate Mittag-Leffler functions and the Wright functions.
Analytic solution,distributed order differential equation,Reimann-Liouville fractional derivative,Mittag-Leffler function,relaxation process
http://scientiairanica.sharif.edu/article_20335.html
http://scientiairanica.sharif.edu/article_20335_9c3fff9bfa849d410a81a373581c7bfb.pdf
Sharif University of Technology
Scientia Iranica
1026-3098
2345-3605
27
3
2020
06
01
The variable step-size wavelet transform-domain LMS adaptive filter algorithm
1398
1412
EN
Mohammad
Shams Esfand Abadi
Faculty of Electrical Engineering, Shahid Rajaee Teacher Training
University, P.O.Box: 16785-163, Tehran, Iran
mshams@srttu.edu
Hamid
Mesgarani
Faculty of Science, Shahid Rajaee Teacher Training University, P.O.Box: 16785-163, Tehran, Iran
Seyed Mahmoud
Khademiyan
Faculty of Science, Shahid Rajaee Teacher Training University, P.O.Box: 16785-163, Tehran, Iran
10.24200/sci.2018.20827
In this paper, the wavelet transform domain least mean squares (WTDLMS) adaptive algorithm with variable<br />step-size (VSS) is established. The step-size changes according to the largest decrease in mean square deviation. To keep the computational complexity low, the Haar wavelet transform (HWT) is utilized as a transform. In addition, the mean square performance analysis of the VSS-WTDLMS is studied in the stationary and nonstationary environments and the theoretical relations for transient and steady-state performances are established. The simulation results show that the proposed VSS-WTDLMS has faster convergence rate and lower misadjustment than conventional WTDLMS. The theoretical relations are also verified by presenting various experimental results.
Wavelet transform domain LMS (WTDLMS),variable step-size,mean square performance,stationary,nonstationary
http://scientiairanica.sharif.edu/article_20827.html
http://scientiairanica.sharif.edu/article_20827_d900e001682eea503ec20ebcb752db84.pdf
Sharif University of Technology
Scientia Iranica
1026-3098
2345-3605
27
3
2020
06
01
Medium-term planning of vehicle-to-grid aggregators for providing frequency regulation service
1413
1423
EN
Mohammad Hossein
Sarparandeh
Department of Electrical Engineering, Sharif University of Technology, Tehran, Iran
Mostafa
Kazemi
Faculty of Electrical Engineering, University of Shahreza, Shahreza, Iran
mkazemi@shahreza.ac.ir
Mehdi
Ehsan
Department of Electrical Engineering, Sharif University of Technology, Tehran, Iran
10.24200/sci.2018.20612
Utilization of electric vehicles’ battery to provide frequency regulation service in electricity markets is a technically feasible and economically attractive idea. The role of aggregators as a middleman between electric vehicle owners and the frequency regulation market has been discussed in literature. However, the economic interaction between the aggregator and the vehicle owners on division of interests is still a missing point. In this paper, a new pricing model for aggregators of electric vehicles is proposed in a way, that not only maximizes its profit, but also the vehicle owners have sufficient incentives to take part in the offered Vehicle-to-Grid program. In our proposed model, the aggregator takes into account the depreciation cost of electric vehicle batteries and the cost of net energy transaction between the electric vehicles and the grid, and considers these items in settling accounts with vehicle owners. The proposed model has been implemented on PJM frequency regulation market and the results are discussed in the paper.
Electric Vehicles,Frequency Regulation,Pricing,Vehicle-to-Grid (V2G),Aggregator
http://scientiairanica.sharif.edu/article_20612.html
http://scientiairanica.sharif.edu/article_20612_0fd9ad57e57011f66e39d2ae206ab5eb.pdf
Sharif University of Technology
Scientia Iranica
1026-3098
2345-3605
27
3
2020
06
01
Recognizing involuntary actions from 3D skeleton data using body states
1424
1436
EN
Mozhgan
Mokari
https://orcid.org/0000-0002-1707-7907
Department of Electrical Engineering, Sharif University
of Technology, Tehran, Iran
Hoda
Mohammadzade
0000-0002-9852-5088
Department of Electrical Engineering, Sharif University
of Technology, Tehran, Iran
hoda@sharif.edu
Benyamin
Ghojogh
0000-0002-9617-291X
Department of Electrical Engineering, Sharif University
of Technology, Tehran, Iran
ghojogh_benyamin@ee.sharif.edu
10.24200/sci.2018.20446
Human action recognition has been one of the most active fields of research in computer vision over the last years. Two dimensional action recognition methods are facing serious challenges such as occlusion and missing the third dimension of data. Development of depth sensors has made it feasible to track positions of human body joints over time. This paper proposes a novel method for action recognition which uses<br />temporal 3D skeletal Kinect data. This method introduces the definition of body states and then every action is modeled as a sequence of these states. The learning stage uses Fisher Linear Discriminant Analysis (LDA) to construct discriminant feature space for discriminating the body states. Moreover, this paper suggests the use of the Mahalonobis distance as an appropriate distance metric for the classification of the states of involuntary actions. Hidden Markov Model (HMM) is then used to model the temporal transition between the body states in each action. According to the results, this method significantly outperforms other popular methods, with recognition (recall) rate of 88.64% for eight different actions and up to 96.18% for classifying the class of all fall actions versus normal actions.
Human action recognition,involuntary action recognition,Fisher,Linear Discriminant Analysis (LDA),kinect,3D skeleton data,hidden markov model (HMM)
http://scientiairanica.sharif.edu/article_20446.html
http://scientiairanica.sharif.edu/article_20446_ea35f6f03838aa88195865faf3aa793b.pdf
Sharif University of Technology
Scientia Iranica
1026-3098
2345-3605
27
3
2020
06
01
A holistic day-ahead distributed energy management approach: Equilibrium selection for customers' game
1437
1449
EN
A.
Shojaei Berjouei
Electrical and Computer Department, Isfahan University of Technology, Isfahan, Iran
M.
Moallem
Electrical and Computer Department, Isfahan University of Technology, Isfahan, Iran
M. H.
Manshaei
Electrical and Computer Department, Isfahan University of Technology, Isfahan, Iran
10.24200/sci.2018.20825
n this paper, a new holistic distributed day-ahead energy management approach with desired equilibrium selection capability in a smart distribution grid is proposed. The interaction between customers and the distribution company is modeled as a single-leader multiple-follower Stackelberg game. The interaction among customers is modeled as a non-cooperative generalized Nash game because they meet a common constraint. Customers hold the average of the aggregate load in the appropriate domain to reshape it and improve the Load Factor. The strategy of the distribution company is day-ahead energy pricing obtained through maximizing its profit which is formulated as a stochastic conditional value at risk optimization to consider the uncertainty of the price of electricity in the wholesale market. Customers’ strategies are based on hourly consumption of deferrable loads and scheduled charge/discharge rates of energy storage devices in response to price. It is proved that the generalized Nash game has multiple equilibria; hence, the distributed proximal Tikhonov regularization algorithm is proposed here to achieve the desired equilibrium. The simulation results validate the performance of the proposed algorithm with 31.46% increase in the Load Factor besides 45.89 % and 14.23 % reduction in the maximum aggregate demand and aggregate billing cost, respectively.
smart grid,energy management,generalized Nash game,load factor,proximal Tikhonov regularization algorithm
http://scientiairanica.sharif.edu/article_20825.html
http://scientiairanica.sharif.edu/article_20825_37c05e95194eae276c00a16f206f0499.pdf
Sharif University of Technology
Scientia Iranica
1026-3098
2345-3605
27
3
2020
06
01
A Modified Variant of Grey Wolf Optimizer
1450
1466
EN
Narinder
Singh
Department of Mathematics, Punjabi University, Patiala-147002, Punjab, India
narindersinghgoria@ymail.com
10.24200/sci.2018.50122.1523
The original version of Grey Wolf Optimization (GWO) algorithm has small number of disadvantages of low solving accuracy, bad local searching ability and slow convergence rate. In order to overcome these disadvantages of Grey Wolf Optimizer, a new version of Grey Wolf Optimizer algorithm has been proposed by modifying the encircling behavior and position update equations of Grey Wolf Optimization Algorithm. The accuracy and convergence performance of modified variant is tested on several well known classical further more like sine dataset and cantilever beam design functions. For verification, the results are compared with some of the most powerful well known algorithms i.e. Particle Swarm Optimization, Grey Wolf Optimizer and Mean Grey Wolf Optimization. The experimental solutions demonstrate that the modified variant is able to provide very competitive solutions in terms of improved minimum objective function value, maximum objective function value, mean, standard deviation and convergence rate.
particle swarm optimization (PSO),Grey Wolf Optimization (GWO),Mean Grey Wolf Optimization and Meta-heuristics
http://scientiairanica.sharif.edu/article_20638.html
http://scientiairanica.sharif.edu/article_20638_c20d05ec25f35993037f2b119fd7ef3c.pdf
Sharif University of Technology
Scientia Iranica
1026-3098
2345-3605
27
3
2020
06
01
A comparative study of economic load dispatch using sine cosine algorithm
1467
1480
EN
Nitish
Patel
Department of Electrical Engineering, Institute of Technology, Nirma University, SG Highway, Gota Ahmedabad - 382481, India
16meee18@nirmauni.ac.in
Kuntal
Bhattacharjee
0000-0001-6934-6702
Department of Electrical Engineering, Institute of Technology, Nirma University, SG Highway, Gota Ahmedabad - 382481, India
kuntal.bhattacharjee@nirmauni.ac.in
10.24200/sci.2018.50635.1796
Economic Load Dispatch (ELD) is an important part of cost minimization procedure in power system operation. Different derivative and probabilistic methods are used to solve ELD problems. This paper proposes a powerful Sine Cosine Algorithm (SCA) to explain the ELD issue including equality and inequality restrictions. The main aim of ELD is to satisfy the entire electric load at minimum cost. The SCA is a population based probabilistic method which guides its search agents that are randomly placed in the search space, towards an optimal point using their fitness function and also keeps a track of the best solution achieved by each search agent. SCA is being used to solve the ELD problem with their high exploration and local optima escaping technique. This algorithm confirms that the promising areas of the search space are exploited to have a smooth transition from exploration to exploitation using sine and cosine functions. Simulation results prove that the proposed algorithm surpasses other existing optimization techniques in terms quality of solution obtained and computational efficiency. The final results also prove the robustness of the SCA.
Economic Load Dispatch,optimization,Prohibited operating zone,Sine Cosine Algorithm,Valve-point loading
http://scientiairanica.sharif.edu/article_21064.html
http://scientiairanica.sharif.edu/article_21064_bb49b2ca551b3d6cfacabacf8d7b3add.pdf
Sharif University of Technology
Scientia Iranica
1026-3098
2345-3605
27
3
2020
06
01
Voltage and reactive power control in a distribution network considering optimal network configuration and voltage security constraints
1481
1493
EN
Gholamreza
Memarzadeh
Department of Electrical Engineering, Shahid Bahonar University of Kerman,
Postal code: 7616914111, Kerman, Iran
Saeid
Esmaeili
Department of Electrical Engineering, Shahid Bahonar University of Kerman, Postal code: 7616914111, Kerman, Iran
s_esmaeili@uk.ac.ir
10.24200/sci.2018.20565
In order to reduce energy losses and improve voltage stability index in distribution system, two different approaches have been proposed and employed including voltage and reactive power control (volt/var control) and distribution network reconfiguration. In the present paper, volt/var control and network reconfiguration in distribution system considering voltage security constraints is modelled as a multi-objective optimization problem. Total electrical energy losses, voltages deviations and voltage stability have been considered as objectives. Also, a new method for distribution network reconfiguration has been utilized for implementation of these two problems simultaneously. In this way, the two problems can be solved in less time. In addition, different nature of loads in each bus is considered in network load modelling. Non-dominated sorting genetic algorithm-II is used to solve this problem. Finally, the effectiveness of the proposed method is evaluated by implementation on the IEEE 33-bus system and a real 77-bus distribution system.
Voltage and reactive power control,Distribution network reconfiguration,Distribution system,Voltage security constraints,Non-dominated sorting genetic algorithm-II (NSGA-II)
http://scientiairanica.sharif.edu/article_20565.html
http://scientiairanica.sharif.edu/article_20565_61d490de51602ac31df9f23a04d21f78.pdf
Sharif University of Technology
Scientia Iranica
1026-3098
2345-3605
27
3
2020
06
01
Modified quasi-Y-source converter for increasing boost factor
1494
1505
EN
F.
Zohrabi
Department of Electronics and Electrical Engineering, Shiraz University of Technology, Shiraz, Iran
E.
Abiri
Department of Electronics and Electrical Engineering, Shiraz University of Technology, Shiraz, Iran
A.
Rajaei
Department of Electronics and Electrical Engineering, Shiraz University of Technology, Shiraz, Iran
A.
Nabinezhad
Department of Electronics and Electrical Engineering, Shiraz University of Technology, Shiraz, Iran
10.24200/sci.2018.20788
<strong>In this paper, a new topology of quasi-Y-source impedance network is presented. This converter utilizes the change of winding factor and shoot through state in order to improve the gain of network. The proposed impedance network employs less turn ratio compared to quasi-Y-source and Y-source network to achieve high voltage gain. The continuous input current of the proposed converter is an advantage particularly for the applications related to the renewable energy sources such as Fuel Cell (FC) and photovoltaic (PV) systems. Furthermore, there is a dc-current-blocking capacitors in the proposed network, which helps to avoid the saturation of the coupled inductor. Operation principles of the converter are discussed and the steady state relations as well as voltage gain and voltage stress across the dc-blocking capacitors are derived. Proposed converter is compared to the conventional quasi-Y-source network, to show the advantages of the converter. Several simulations are done and the results are shown to indicate the performance of the proposed network. In this paper, an experimental </strong><strong>prototype of a converter is presented. To prove the validity and consistency of the proposed network, several tests are carried out.</strong><strong>This plan, can have a negative gain, similar to </strong><strong>the quasi-Y-source network.</strong>
impedance source network,quasi-Y-source converter,renewable energy resource
http://scientiairanica.sharif.edu/article_20788.html
http://scientiairanica.sharif.edu/article_20788_d88323c1bad9e9ef0b8c3981b5a5cb14.pdf
Sharif University of Technology
Scientia Iranica
1026-3098
2345-3605
27
3
2020
06
01
Combination of Marx generator and capacitor diode voltage multiplier for pulsed power applications
1506
1514
EN
Mohammad
Kebriaei
Faculty of Electrical and Computer Engineering, University of Kashan, Ghotb-e-Ravandi Blv., Kashan, Iran
kebriaei@gmail.com
Abolfazl
Halvaei Niasar
0000-0003-4265-5120
Faculty of Electrical and Computer Engineering, University of Kashan, Ghotb-e-Ravandi Blv., Kashan, Iran
halvaei@kashanu.ac.ir
Abbas
Ketabi
Faculty of Electrical and Computer Engineering, University of Kashan, Ghotb-e-Ravandi Blv., Kashan, Iran
aketabi@kashanu.ac.ir
10.24200/sci.2018.20689
<strong>Recently, the pulsed power and pulsed electric field systems used in various industries and these systems have found wide applications. For this reason, using the pulsed power generators that in addition to responding to the needs of the user, are providing the advantages of compactness, high flexibility, high repetition rate and cost efficiency is inevitable. In this paper a hybrid solid state pulsed power generator is introduced that is modular and very flexible. This converter which is a combination of Marx and capacitor diode voltage multiplier, is capable of producing high voltage pulses with varying amplitudes at different frequencies. This proposed converter due to having high reliability, low cost, low weight, and structure’s simplicity can cover a wide area of applications. In this paper after introducing the proposed topology, its analytical design is described and its verification is proved by the simulation results in MATLABSIMULINK and by presenting the measurement results taken from the experimental prototype in low voltages.</strong><br />
pulsed power system,pulsed electric field,Marx generator,capacitor diode voltage multiplier
http://scientiairanica.sharif.edu/article_20689.html
http://scientiairanica.sharif.edu/article_20689_2d4d83771c5fae656c64db6237b9f1f7.pdf
Sharif University of Technology
Scientia Iranica
1026-3098
2345-3605
27
3
2020
06
01
A new aspect of transition between line and continuous spectrum and its relation to seismic in influence on structures
1515
1524
EN
Ranko
Babić
Department of Electrical and Computing Engineering, Faculty of Technical Sciences, University of Pristina, Knjaza Milosa Street, No. 7, P.O. Box 38220, Kosovska Mitrovica, Serbia
Lidija
Babić
Department of Civil Engineering, Faculty of Technical Sciences, University of Pristina, Knjaza Milosa Street, No. 7, P.O. Box 38220, Kosovska Mitrovica, Serbia
Branimir
Jakšić
Department of Electrical and Computing Engineering, Faculty of Technical Sciences, University of Pristina, Knjaza Milosa Street, No. 7, P.O. Box 38220, Kosovska Mitrovica, Serbia
10.24200/sci.2018.20326
We considered a new view on transition process from periodic to aperiodic signals, in time and spectral domains, pointing out how the concept of infinity is involved. It contributes to better understanding of the nature of both spectral descriptions, and conditions of their practical use, particularly in unusual cases. There we highlight the invariance in spectrum convergence by introducing some numerical parameters which exactly describe such process. Their behaviour is numerically examined to detail. Also, we considered the opposite transition, from aperiodic to periodic, to clarify the meaning of spectral line. To suggest applicability of our analysis we used an actual seismic signal. By extracting the most prominent waveform part, regarding influence on structures, we formed a periodic signal which line spectrum can clearly show possible resonance with vibrating tones of structures.
Line spectrum,Fourier analysis,Spectrum invariance,Seismic signal,Structure dynamics
http://scientiairanica.sharif.edu/article_20326.html
http://scientiairanica.sharif.edu/article_20326_3f53694c34dfadb390d9ca1f33906639.pdf