Sharif Digital Repository

Predictive mutation testing (PMT) is a technique to predict whether a mutant is killed, using machine learning approaches. Researchers have proposed various methods for PMT over the years. However, the impact of unreached mutants on PMT is not fully addressed. A mutant is unreached if the statement on which the mutant is generated is not executed by any test cases. We aim at showing that unreached mutants can inflate PMT results. Moreover, we propose an alternative approach to PMT, suggesting a different interpretation for PMT. To this end, we replicated the previous PMT research. We empirically evaluated the suggested approach on 654 Java projects provided by prior literature. Our results... 

Predictive mutation testing (PMT) is a technique to predict whether a mutant is killed, using machine learning approaches. Researchers have proposed various methods for PMT over the years. However, the impact of unreached mutants on PMT is not fully addressed. A mutant is unreached if the statement on which the mutant is generated is not executed by any test cases. We aim at showing that unreached mutants can inflate PMT results. Moreover, we propose an alternative approach to PMT, suggesting a different interpretation for PMT. To this end, we replicated the previous PMT research. We empirically evaluated the suggested approach on 654 Java projects provided by prior literature. Our results... 

This paper presents a two layer texture modeling method to recognize architectural distortion in mammograms. We propose a method that models a Gaussian mixture on the Curvelet coefficients and the outputs of Spiculated Lesion Filters. The Curvelet transform and the Spiculated Lesion Filters have been applied to extract textural features of mammograms in literature. However the key difference between this study and the previous ones is that in our approach, a Gaussian mixture models the textural features extracted by the Curvelet transform and the Spiculated Lesion Filters. The results of the current study are shown in the form of accuracy and the area under the receiver operating... 

In this paper, the disadvantages of using the Hough transform as a detector have been considered in a search radar. To illustrate the effect of these disadvantages on the performance of the detector, its performance has been compared with the optimum detectors. To do this, the Average Likelihood Ratio detector has been extracted for detecting a target line with a known normal parameter pair in the search environment. Then, the performance of this detector has been compared with the Hough detector by extracting their Receiver Operation Characteristics. The results of this comparison, which has been done through simulations, show that the Average Likelihood Ratio detector has a better... 

Due to the important role that distribution systems play in quality of power delivered to the customers, there has always been a great deal of interest in investigating different methods of efficiency enhancement for these networks. Two of these methods are Feeder Reconfiguration (FR) and Capacitor Allocation (CA); both have been widely employed to reduce losses and improve several other operational characteristics in electrical power distribution systems. As in FR process the topology of the network changes, it is necessary to change some previous settings; for instance: the capacity of capacitor banks in service in each bus, after each reconfiguration process. This is due to the fact that... 

In this paper, the disadvantages of using the Hough transform as a detector have been considered in a search radar. To illustrate the effect of these disadvantages on the performance of the detector, its performance has been compared with the optimum detectors. To do this, the Generalized Likelihood Ratio detector has been extracted for detecting a target line with unknown normal parameter pair in the search environment. Then, the performance of this detector has been compared with the Hough detector by extracting their Receiver Operation Characteristics. The results of this comparison, which has been done through simulations, show that the Generalized Likelihood Ratio detector has a better... 

Ornamental stone sawability is important in predicting the prime cost of production and planning of the stone quarries and factories. Ornamental stone sawability with two standard methods, wire and circular sawing, is dependent on many parameters including; the stone that be sawn and machine characteristics and saw operating characteristic. The investigation of these parameters and the determination of the optimum working conditions for sawing machines in the stone industry is significant for establishing the most suitable and economic usage of the sawing method in the future. Up to now, various attempts have been made to determine these parameters. In this review paper, the important... 

This paper proposes a centralized optimization-based home energy management (HEM) scheme in a macro energy hub structure. An energy hub management system manages the aggregated load of a group of residential micro energy hubs to minimize the total load deviation. The operational characteristics of the household appliances and the threshold energy cost of the customers are incorporated in the propounded method to provide the customers' comfort. Numerical studies show the effectiveness of the proposed method performance  

Normal human breathing exhibits complex variability in both respiratory rhythm and volume. Analyzing such nonlinear fluctuations may provide clinically relevant information in patients with complex illnesses such as asthma. We compared the cycle-by-cycle fluctuations of inter-breath interval (IBI) and lung volume (LV) among healthy volunteers and patients with various types of asthma. Continuous respiratory datasets were collected from forty agematched men including 10 healthy volunteers, 10 patients with controlled atopic asthma, 10 patients with uncontrolled atopic asthma, and 10 patients with uncontrolled non-atopic asthma during 60 min spontaneous breathing. Complexity of breathing... 

Liver-shape analysis and quantification is still an open research subject. Quantitative assessment of the liver is of clinical importance in various procedures such as diagnosis, treatment planning, and monitoring. Liver-shape classification is of clinical importance for corresponding intra-subject and inter-subject studies. In this research, we propose a novel technique for the liver-shape classification based on Spherical Harmonics (SH) coefficients. The proposed liver-shape classification algorithm consists of the following steps: (a) Preprocessing, including mesh generation and simplification, point-set matching, and surface to template alignment; (b) Liver-shape parameterization,... 

Brushless doubly fed induction generator (BDFIG) has substantial benefits, which make it an attractive alternative as a wind turbine generator. However, it suffers from lower efficiency and larger dimensions in comparison to DFIG. Hence, optimizing the BDFIG structure is necessary for enhancing its situation commercially. In previous studies, a simple model has been used in BDFIG design procedure that is insufficiently accurate. Furthermore, magnetic saturation and iron loss are not considered because of difficulties in determination of flux density distributions. The aim of this paper is to establish an accurate yet computationally fast model suitable for BDFIG design studies. The proposed... 

Despite the significant research efforts devoted to the microgrid and smart grid areas, numerous problems related to real world implementations still remain unsolved. The present special issue was announced with the objective of addressing and disseminating state-of-the-art R&D results on microgrids to bring together researchers from both academia and industry with the goal of fostering interactions among stakeholders. In response, 190 two-page extended abstracts were received and considered for the first round of reviews. Authors of about 60 selected abstracts were then invited to submit the full papers in the second round and out of them 27 high-quality manuscripts were ultimately approved... 

In this extended summary, our aim is analyzing functional magnetic resonance imaging (fMRI) data by independent component analysis (ICA) in order to find regions of brain which were activated by neural activity in human brain. We employ the minimum description length (MDL) criterion to reduce the dimension of the data and estimate the number of components, which makes ICA work more efficiently. We also use a simple oscillating index method to select automatically the components of interest. MDL and oscillating index criteria have not already been used in applying ICA for analyzing fMRI data. In order to investigate the advantage of using MDL and oscillating index, we perform some experiments... 

In distribution systems, feeder reconfiguration (FR) can lead to loss reduction, reliability improvement and some other economic savings. These advantages can be intensified by proper control and switching of Capacitor Banks (CBs). In this paper, using Ant Colony Optimization (ACO) technique, a novel method is proposed for simultaneous dynamic scheduling of FR and CB switching in the presence of DG units having uncertain and variant generations over time. This method is applicable to both smart and classic distribution systems. While for the latter, state estimation method should be used to estimate the loads at different buses by employing a limited number of measurements. The objective of... 

Contrast induced nephropathy (CIN) has been reported to be the third foremost cause of acute renal failure. Metabolomics is a robust technique that has been used to identify potential biomarkers for the prediction of renal damage. We aim to analyze the serum and urine metabolites changes, before and after using contrast for coronary angiography, to determine if metabolomics can predict early development of CIN. 66 patients undergoing elective coronary angiography were eligible for enrollment. Urine and serum samples were collected prior to administration of CM and 72 h post procedure and analyzed by nuclear magnetic resonance. The significant differential metabolites between patients who... 

The artificial neural network (ANN) is a sort of machine learning method which has been used in determination of risk of human disorders. In the current investigation, we have created an ANN and trained it based on the genetic data of 401 multiple sclerosis (MS) patients and 390 healthy subjects. Single nucleotide polymorphisms (SNPs) within ANRIL (rs1333045, rs1333048, rs4977574 and rs10757278), EVI5 (rs6680578, rs10735781 and rs11810217), ACE (rs4359 and rs1799752), MALAT1 (rs619586 and rs3200401), GAS5 (rs2067079 and rs6790), H19 (rs2839698 and rs217727), NINJ2 (rs11833579 and rs3809263), GRM7 (rs6782011 and rs779867), VLA4 (rs1143676), CBLB (rs12487066) and VEGFA (rs3025039 and... 

Background: Convolutional neural networks (CNN) have enabled significant progress in speech recognition, image classification, automotive software engineering, and neuroscience. This impressive progress is largely due to a combination of algorithmic breakthroughs, computation resource improvements, and access to a large amount of data. Method: In this paper, we focus on the automated detection of autism spectrum disorder (ASD) using CNN with a brain imaging dataset. We detected ASD patients using most common resting-state functional magnetic resonance imaging (fMRI) data from a multi-site dataset named the Autism Brain Imaging Exchange (ABIDE). The proposed approach was able to classify ASD... 

This article proposes a compressed-domain signal processing (CSP) multiple-input multiple-output (MIMO) radar, a MIMO radar approach that achieves substantial sample complexity reduction by exploiting the idea of CSP. CSP MIMO radar involves two levels of data compression followed by target detection at the compressed domain. First, compressive sensing is applied at the receive antennas, followed by a Capon beamformer, which is designed to suppress clutter. Exploiting the sparse nature of the beamformer output, a second compression is applied to the filtered data. Target detection is subsequently conducted by formulating and solving a hypothesis testing problem at each grid point of the... 

Periodontitis is a common oral disorder leading to tooth loss in both developed and developing regions of the world. This multifactorial condition is related to the abnormal activity of several molecular pathways, among them are oxytocin-related pathways. In this study, we enrolled 26 patients and 28 controls and assessed the expression of four oxytocin-related genes, namely, FOS, ITPR, RCAN1, and RGS2, in circulation and affected tissues of enrolled individuals using real-time PCR. Expression of FOS was downregulated in total periodontitis tissues compared with total control tissues [ratio of mean expression (RME) = 0.23, P-value = 0.03]. Expression of FOS was also lower in total blood...