Characteristics of Nanostructured Powder Mixture Produced by Ball Milling

Azimi Hossein,Ahmadi Eltefat,Hadavi S.M.Mehdi 한국분말야금학회 2006 한국분말야금학회 학술대회논문집 Vol.2006 No.1

In the present work, the influence of the ball-milling time, milling atmosphere and weight ratio of ball to powder on characteristics of was studied. Results show that, the grain sizes of the and CuO in the ball-milled powder mixture were significantly decreased with increasing the milling time. Those of each oxide ball-milled in Argon and Hexane atmosphere for 30 and 20 hour were about 98 and 84 nm, respectively. After milling of 20 hour in Hexane as PCA, the powder had a homogeneously mixed structure and the average size of powders was determined to about 230nm.

Subnormality and Weighted Composition Operators on L² Spaces

AZIMI, MOHAMMAD REZA Department of Mathematics 2015 Kyungpook mathematical journal Vol.55 No.2

Subnormality of bounded weighted composition operators on $L^2({\Sigma})$ of the form $Wf=uf{\circ}T$, where T is a nonsingular measurable transformation on the underlying space X of a ${\sigma}$-finite measure space (X, ${\Sigma}$, ${\mu}$) and u is a weight function on X; is studied. The standard moment sequence characterizations of subnormality of weighted composition operators are given. It is shown that weighted composition operators are subnormal if and only if $\{J_n(x)\}^{+{\infty}}_{n=0}$ is a moment sequence for almost every $x{{\in}}X$, where $J_n=h_nE_n({\mid}u{\mid}^2){\circ}T^{-n}$, $h_n=d{\mu}{\circ}T^{-n}/d{\mu}$ and $E_n$ is the conditional expectation operator with respect to $T^{-n}{\Sigma}$.

Prioritizing the Components Affecting Patient's Satisfaction with Healthcare Services using Multiple Attribute Decision Making Technique

Azimi, Seyed Ali Ziaee,Makui, Ahmad Korean Institute of Industrial Engineers 2017 Industrial Engineeering & Management Systems Vol.16 No.4

Given the increasing importance of patient's satisfaction with healthcare services in the management planning and decision making, the aim of this study is to identify and prioritize the components affecting patients' satisfaction with healthcare public hospitals using SERVQUAL developed model and Multiple Attribute Decision Making (MADM). This is an applied study in terms of goal and the method and the nature of the study is descriptive survey. Statistical population consisted of all the patients who were admitted in one of the clinics of public hospitals in Tehran and data were collected using SERVQUAL model questionnaire. After the reliability and validity test, SAW and TOPSIS and ELECTRE techniques were used in order to prioritize the components affecting patient's satisfaction and finally, the results of different techniques were combined together using Copeland Method and a ranking of the components was obtained. The results show that the most important components affecting patient's satisfaction with the healthcare services from consumers' perspective including "employing employees with sufficient knowledge and skills," "new facilities of clinic," and "assurance" are of the highest importance and the cost is almost the least importance.

COMPARISON OF METAHEURISTIC ALGORITHMS FOR EXAMINATION TIMETABLING PROBLEM

Azimi, Zhara-Naji 한국전산응용수학회 2004 Journal of applied mathematics & informatics Vol.16 No.1

SA, TS, GA and ACS are four of the main algorithms for solving challenging problems of intelligent systems. In this paper we consider Examination Timetabling Problem that is a common problem for all universities and institutions of higher education. There are many methods to solve this problem, In this paper we use Simulated Annealing, Tabu Search, Genetic Algorithm and Ant Colony System in their basic frameworks for solving this problem and compare results of them with each other.

A Review on the Use of Artificial Intelligence in Spinal Diseases

Azimi Parisa,Yazdanian Taravat,Benzel Edward C.,Aghaei Hossein Nayeb,Azhari Shirzad,Sadeghi Sohrab,Montazeri Ali 대한척추외과학회 2020 Asian Spine Journal Vol.14 No.4

Artificial neural networks (ANNs) have been used in a wide variety of real-world applications and it emerges as a promising field across various branches of medicine. This review aims to identify the role of ANNs in spinal diseases. Literature were searched from electronic databases of Scopus and Medline from 1993 to 2020 with English publications reported on the application of ANNs in spinal diseases. The search strategy was set as the combinations of the following keywords: “artificial neural networks,” “spine,” “back pain,” “prognosis,” “grading,” “classification,” “prediction,” “segmentation,” “biomechanics,” “deep learning,” and “imaging.” The main findings of the included studies were summarized, with an emphasis on the recent advances in spinal diseases and its application in the diagnostic and prognostic procedures. According to the search strategy, a set of 3,653 articles were retrieved from Medline and Scopus databases. After careful evaluation of the abstracts, the full texts of 89 eligible papers were further examined, of which 79 articles satisfied the inclusion criteria of this review. Our review indicates several applications of ANNs in the management of spinal diseases including (1) diagnosis and assessment of spinal disease progression in the patients with low back pain, perioperative complications, and readmission rate following spine surgery; (2) enhancement of the clinically relevant information extracted from radiographic images to predict Pfirrmann grades, Modic changes, and spinal stenosis grades on magnetic resonance images automatically; (3) prediction of outcomes in lumbar spinal stenosis, lumbar disc herniation and patient-reported outcomes in lumbar fusion surgery, and preoperative planning and intraoperative assistance; and (4) its application in the biomechanical assessment of spinal diseases. The evidence suggests that ANNs can be successfully used for optimizing the diagnosis, prognosis and outcome prediction in spinal diseases. Therefore, incorporation of ANNs into spine clinical practice may improve clinical decision making.

Time - and Concentration - Dependent Effects of Resveratrol on miR 15a and miR16-1 Expression and Apoptosis in the CCRF-CEM Acute Lymphoblastic Leukemia Cell Line

Azimi, Ako,Hagh, Majid Farshdousti,Talebi, Mehdi,Yousefi, Bahman,feizi, Abbas Ali Hossein pour,Baradaran, Behzad,Movassaghpour, Ali Akbar,Shamsasenjan, Karim,Khanzedeh, Taghi,Ghaderi, Abdol Hasan,Heyd Asian Pacific Journal of Cancer Prevention 2015 Asian Pacific journal of cancer prevention Vol.16 No.15

Background: Chemotherapy is one of the common approaches in treatment of cancers, especially leukemia. However, drug resistance phenomena reduce the likelihood of treatment success. Resveratrol is a herbal compound which through complicated processes makes some selected cells sensitive to treatment and induction of apoptosis. In the present study, the effects of resveratrol on the expression of miR 15a and miR16-1 and apoptosis in the CCRF-CEM cell line were investigated. Materials and Methods: The CCRF-CEM cell line was cultured under standard conditions and changes in miR 15a and miR 16-1 expression were analyzed by real time-PCR technique, with attention to reveratrol dose and time dependence. Also, apoptosis is evaluated by flow cytometry using annexin V and PI. Results: CCRF-CEM cells underwent dose-dependent apoptotic cell death in response to resveratrol. MiR 15a and miR 16-1 expression was up-regulated after 24 and 48 hours resveratrol treatment (p<0.05). Conclusions: The results of our study indicate that resveratrol induces apoptosis in a time and dose-dependent manner in CCRF-CEM cells. Also, increased expression level of miR 16-1 and miR 15a by means of resveratrol in CCRF-CEM cells might have a role in apoptosis induction and predisposition. According to our results resveratrol can be regarded as a dietary supplement to improve efficacy of anti-leukemia therapies.

Using Acoustic Liner for Fan Noise Reduction in Modern Turbofan Engines

Azimi, Mohammadreza,Ommi, Fathollah,Alashti, Naghmeh Jamshidi The Korean Society for Aeronautical and Space Scie 2014 International Journal of Aeronautical and Space Sc Vol.15 No.1

With the increase in global air travel, aircraft noise has become a major public issue. In modern aircraft engines, only a small proportion of the air that passes through the whole engine actually goes through the core of the engine, the rest passes around it down the bypass duct. A successful method of reducing noise further, even in ultra-high bypass ratio engines, is to absorb the sound created within the engine. Acoustically absorbent material or acoustic liners have desirable acoustic attenuation properties and thus are commonly used to reduce noise in jet engines. The liners typically are placed upstream and downstream of the rotors (fans) to absorb sound before it propagates out of the inlet and exhaust ducts. Noise attenuation can be dramatically improved by increasing the area over which a noise reducing material is applied and by placing the material closer to the noise source. In this paper we will briefly discuss acoustic liner applications in modern turbofan engines.

Robust Multi Objective H₂/H<SUB>∞</SUB> Control of MIMO Nonlinear Uncertain systems via T-S Fuzzy Model

Vahid Azimi,Peyman Akhlaghi,Mohammad Hossein Kazemi 제어로봇시스템학회 2011 제어로봇시스템학회 국제학술대회 논문집 Vol.2011 No.10

This paper describes robust H₂/H∞ multi-objective state feedback controller for nonlinear uncertain systems. To apply the H₂/H∞ multi-objective state feedback method, the nonlinear dynamics is represented by a T-S fuzzy model. First, uncertain parameters and Quantification of uncertainty on physical parameters is defined by affine parameter-dependent systems method. Next, the Takagi and Sugeno"s fuzzy linear model is utilized to approximate uncertain nonlinear systems. Then, some states (error of tracking) are augmented to the system in order to improve tracking control. Finally, based on fuzzy linear model with augmented state, a H₂/H∞ multi-objective state feedback controller is developed to achieve the robustness design of nonlinear uncertain systems. LMI (Linear Matrix Inequality) method and PDC (Parallel Distributed Compensation) are used to design the controller for the whole system. The results show that the proposed method can effectively meet the performance requirements like robustness, disturbance rejection and tracking for the 3-phase permanent magnet synchronous motor (PMSM).

Dynamic Failure Investigation in Ultrafi ne Grained AA2219: Mechanical and Microstructural Analysis

Amin Azimi,Gbadebo Moses Owolabi,Nikhil Kumar,Grant Warner 대한금속·재료학회 2019 METALS AND MATERIALS International Vol.25 No.4

In this study, the high strain rate behavior of ultrafi ne grained (UFG) AA2219 alloy processed via multi axial forging atcryogenic temperature was investigated. Room temperature forged sample was used as a reference to determine the eff ectsof signifi cant grain size refi nement on the dynamic response of the materials. The initial microstructure characterizationindicated that severe plastic deformation in the cryogenically process alloy resulted in its grain size reduction to ~ 270 nmand the second phase breakage to fi ner particles. The results of the dynamic impact tests show that the strain hardening andthermal softening are substantially less signifi cant in the UFG materials, whereas the maximum fl ow stress and the strain ratesensitivity increased. Furthermore, the grain size reduction led to the absorption of higher portion of the deformation energyand an increase in the toughness of the fabricated UFG material when compared to the conventionally forged samples. Thisimprovement is approximately 56% at a strain rate of 4000 s −1 obtained via the grain structure refi nement. Microstructureanalysis of the post-deformed samples revealed two fully transformed adiabatic shear bands (ASBs) in the coarser grainedmaterial due to intense localized strain and thermal instability during the impact tests which caused the pushing off of thesecond phases and cracks formation inside the ASBs. However, low-intensity deformed ASBs and a notable enhancementin crack initiation strength were observed by morphology and fi nal confi guration of the post-deformed UFG samples. Inaddition, no considerable hardness variations were experienced in the impacted UFG material due to the saturation of grainsize during the cryogenically forging process. In contrary to the UFG alloys, signifi cant hardness increase was observed inthe deformed coarse grained material which was associated with softening in the adjacent regions providing a zone proneto cracks initiation.

Statistical and Machine Learning-Based FHB Detection in Durum Wheat

Nasrin Azimi,Omid Sofalian,Mahdi Davari,Ali Asghari,Naser Zare 한국육종학회 2020 Plant Breeding and Biotechnology Vol.8 No.3

Pathogens are the major causes of wheat crop yield losses, including the fungus Fusarium graminearum, an agent of Fusarium Head Blight (FHB). A better understanding of the relationship between plant morphological and biochemical traits and resistance to FHB can be effective in implementing a successful breeding program. This study investigated the relationship between FHB resistance as well as the morphological and biochemical traits in 20 durum wheat lines. Both morphological and biochemical traits were investigated using statistical tools. Therefore, analyses of variance, mean, as well as the correlation between the traits were considered. In addition, for the morphological traits, cluster analyses were performed to identify similar genotypes in control and infected conditions. Furthermore, machine learning (ML) classification techniques, including Support Vector Machine (SVM), were proposed to detect the infected plants using morphological traits. The results show a great promise for the application of data-driven ML-based methods in plant breeding and disease detection.