About: Yazd University is a education organization based out in Yazd, Iran. It is known for research contribution in the topics: Fuzzy logic & Cyclic voltammetry. The organization has 4291 authors who have published 7409 publications receiving 82273 citations. The organization is also known as: Yazd University.
Topics: Fuzzy logic, Cyclic voltammetry, Catalysis, Differential pulse voltammetry, Nonlinear system
Papers published on a yearly basis
••01 Jul 2010
TL;DR: A possible fusion of fuzzy sets and rough sets is proposed to obtain a hybrid model called rough soft sets, based on a Pawlak approximation space, and a concept called soft–rough fuzzy sets is initiated, which extends Dubois and Prade's rough fuzzy sets.
Abstract: Theories of fuzzy sets and rough sets are powerful mathematical tools for modelling various types of uncertainty. Dubois and Prade investigated the problem of combining fuzzy sets with rough sets. Soft set theory was proposed by Molodtsov as a general framework for reasoning about vague concepts. The present paper is devoted to a possible fusion of these distinct but closely related soft computing approaches. Based on a Pawlak approximation space, the approximation of a soft set is proposed to obtain a hybrid model called rough soft sets. Alternatively, a soft set instead of an equivalence relation can be used to granulate the universe. This leads to a deviation of Pawlak approximation space called a soft approximation space, in which soft rough approximations and soft rough sets can be introduced accordingly. Furthermore, we also consider approximation of a fuzzy set in a soft approximation space, and initiate a concept called soft---rough fuzzy sets, which extends Dubois and Prade's rough fuzzy sets. Further research will be needed to establish whether the notions put forth in this paper may lead to a fruitful theory.
TL;DR: In this article, a chronologically collected and reviewed the extensive global solar radiation models available in the literature and to classify them into four categories, i.e., sunshine-based, cloudbased, temperature-based and other meteorological parameter-based models, based on the employed meteorological parameters as model input.
Abstract: Solar radiation is a primary driver for many physical, chemical, and biological processes on the earth’s surface. Solar energy engineers, architects, agriculturists, hydrologists, etc. often require a reasonably accurate knowledge of the availability of the solar resource for their relevant applications at their local. In solar applications, one of the most important parameters needed is the long-term average daily global irradiation. For regions where no actual measured values are available, a common practice is to estimate average daily global solar radiation using appropriate empirical correlations based on the measured relevant data at those locations. These correlations estimate the values of global solar radiation for a region of interest from more readily available meteorological, climatological, and geographical parameters. The main objective of this study is to chronologically collect and review the extensive global solar radiation models available in the literature and to classify them into four categories, i.e., sunshine-based, cloud-based, temperature-based, and other meteorological parameter-based models, based on the employed meteorological parameters as model input. Furthermore, in order to evaluate the accuracy and applicability of the models reported in this paper for computing the monthly average daily global solar radiation on a horizontal surface, the geographical and meteorological data of Yazd city, Iran was used. The developed models were then evaluated and compared on the basis of statistical error indices and the most accurate model was chosen in each category. Results revealed that all the proposed correlations have a good estimation of the monthly average daily global solar radiation on a horizontal surface in Yazd city, however, the El-Metwally sunshine-based model predicts the monthly averaged global solar radiation with a higher accuracy.
TL;DR: In this paper, semi-supervised feature selection methods are fully investigated and two taxonomies of these methods are presented based on two different perspectives which represent the hierarchical structure of semi- supervised feature Selection methods.
Abstract: Feature selection is a significant task in data mining and machine learning applications which eliminates irrelevant and redundant features and improves learning performance. In many real-world applications, collecting labeled data is difficult, while abundant unlabeled data are easily accessible. This motivates researchers to develop semi-supervised feature selection methods which use both labeled and unlabeled data to evaluate feature relevance. However, till-to-date, there is no comprehensive survey covering the semi-supervised feature selection methods. In this paper, semi-supervised feature selection methods are fully investigated and two taxonomies of these methods are presented based on two different perspectives which represent the hierarchical structure of semi-supervised feature selection methods. The first perspective is based on the basic taxonomy of feature selection methods and the second one is based on the taxonomy of semi-supervised learning methods. This survey can be helpful for a researcher to obtain a deep background in semi-supervised feature selection methods and choose a proper semi-supervised feature selection method based on the hierarchical structure of them. A comprehensive survey on semi-supervised feature selection methods is presented.Two categories of these methods are presented from two different perspectives.The hierarchical structure of semi-supervised feature selection methods is given.Advantage and disadvantage of the survey methods are presented.Future research directions are presented.
TL;DR: This review first gives an introduction into the topic of screen-printed electrodes for biosensing and is subdivided into sections (a) on DNA sensors, (b) on aptasensors, (c) on immunosensor, (d) on enzymatic biosensors.
Abstract: Screen-printing is one of the most promising approaches towards simple, rapid and inexpensive production of biosensors. Disposable biosensors based on screen printed electrodes (SPEs) including microelectrodes and modified electrodes have led to new possibilities in the detection and quantitation of biomolecules, pesticides, antigens, DNA, microorganisms and enzymes. SPE-based sensors are in tune with the growing need for performing rapid and accurate in-situ analyses and for the development of portable devices. This review (with 226 refs.) first gives an introduction into the topic and then is subdivided into sections (a) on DNA sensors (including methods for the detection of hybridization and damage), (b) on aptasensors (for thrombin, OTA, immunoglobulins and cancer biomarkers), (c) on immunosensors (for microorganisms, immunoglobulins, toxins, hormones, lactoferrin and biomarkers), (d) on enzymatic biosensors (for glucose, hydrogen peroxide, various pharmaceuticals, neurotransmitters, amino acids, NADH, enzyme based sensors).
TL;DR: An overview of the epidemic disease caused by SARS-CoV-2 called coronavirus disease-19, which has become a serious concern in the medical community, based on the current evidence is provided.
Abstract: In December 2019, a novel coronavirus, named Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) or (2019-nCoV) with unknown origin spread in Hubei province of China. The epidemic disease caused by SARS-CoV-2 called coronavirus disease-19 (COVID-19). The presence of COVID-19 was manifested by several symptoms, ranging from asymptomatic/mild symptoms to severe illness and death. The viral infection expanded internationally and WHO announced a Public Health Emergency of International Concern. To quickly diagnose and control such a highly infectious disease, suspicious individuals were isolated and diagnostic/treatment procedures were developed through patients’ epidemiological and clinical data. Early in the COVID-19 outbreak, WHO invited hundreds of researchers from around the world to develop a rapid quality diagnosis, treatment and vaccines, but so far no specific antiviral treatment or vaccine has been approved by the FDA. At present, COVID-19 is managed by available antiviral drugs to improve the symptoms, and in severe cases, supportive care including oxygen and mechanical ventilation is used for infected patients. However, due to the worldwide spread of the virus, COVID-19 has become a serious concern in the medical community. According to the current data of WHO, the number of infected and dead cases has increased to 8,708,008 and 461,715, respectively (Dec 2019 –June 2020). Given the high mortality rate and economic damage to various communities to date, great efforts must be made to produce successful drugs and vaccines against 2019-nCoV infection. For this reason, first of all, the characteristics of the virus, its pathogenicity, and its infectious pathways must be well known. Thus, the main purpose of this review is to provide an overview of this epidemic disease based on the current evidence.
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|S. Paktinat Mehdiabadi||68||167||14207|
|Amir H. Mohammadi||62||698||16044|
|Mohammad Hossein Ahmadi||60||477||11659|
|Mohammad Ali Zolfigol||56||765||14878|
|Mohammad Hadi Dehghani||43||320||6324|
|Simon De Visscher||39||75||4558|
|Hamid R. Zare||33||156||3654|
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