Search results for: Shahab Hasani Nasab
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 41

Search results for: Shahab Hasani Nasab

11 A Coupled Extended-Finite-Discrete Element Method: On the Different Contact Schemes between Continua and Discontinua

Authors: Shervin Khazaeli, Shahab Haj-zamani

Abstract:

Recently, advanced geotechnical engineering problems related to soil movement, particle loss, and modeling of local failure (i.e. discontinua) as well as modeling the in-contact structures (i.e. continua) are of the great interest among researchers. The aim of this research is to meet the requirements with respect to the modeling of the above-mentioned two different domains simultaneously. To this end, a coupled numerical method is introduced based on Discrete Element Method (DEM) and eXtended-Finite Element Method (X-FEM). In the coupled procedure, DEM is employed to capture the interactions and relative movements of soil particles as discontinua, while X-FEM is utilized to model in-contact structures as continua, which may consist of different types of discontinuities. For verification purposes, the new coupled approach is utilized to examine benchmark problems including different contacts between/within continua and discontinua. Results are validated by comparison with those of existing analytical and numerical solutions. This study proves that extended-finite-discrete element method can be used to robustly analyze not only contact problems, but also other types of discontinuities in continua such as (i) crack formations and propagations, (ii) voids and bimaterial interfaces, and (iii) combination of previous cases. In essence, the proposed method can be used vastly in advanced soil-structure interaction problems to investigate the micro and macro behaviour of the surrounding soil and the response of the embedded structure that contains discontinuities.

Keywords: contact problems, discrete element method, extended-finite element method, soil-structure interaction

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10 Zakariya Multaniand and his Role in the Spread of Islam and Suhrawardiyya in the Subcontinent

Authors: Mahdi Momeni

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The arrival of Mysticism to the subcontinent can be generally divided into two periods. The first period, was the Sporadic arrival of Sufis whom were traveling to the subcontinent according to the tradition of disquisition and the second period was; when the Sufi dynasties were sending missionaries and caliphs to guide and promote people from different direction to that land. Among the Sufi dynasty that entered to India in the thirteenth century, two dynasties of Chishti and Suhrawardîya were more successful than other Sufi dynasties. And thus they are very important in the spread of Islam and Mysticism to the subcontinent. Suhrawardiyya dynasty was founded by Sheikh Ziauddin Abu Najib Suhrawardi and was developed and spread by his nephew Sheikh Shahabuddin Suhrawardi Abo hafs Omar. Sheikh Shahabuddin sent many Caliphs and missionaries to India. Among these missionaries were People like Sultan Sakhi Sarwar, Seyyed Noureddin Mobarak Ghaznavi, Sheikh Jalal al-din Tabrizi and Sheikh Zakariya Multani. Since Suhrawardiyya doctrine relies on Asceticism and Sharia, so one of the important elements among Suhrawardiyya missionaries was inviting people to Islam. Accordingly Sheikh Shahab Caliphs had a great role in the spread of Islam and Mysticism in different territories, especially India. Such that it can be pointed out is the the role of Sheikh Baha-ud-din Zakariya Multani, the founder of Suhrawardiyya Dynasty in India. Sheikh Zakaria Multani after working in three areas, establishing monasteries, training managers, having numerous trips to different places, participating to social affairs provided the spread of Islam and Mysticism in subcontinent. This paper studies his role and actions in the subcontinent.

Keywords: islam, sufism, Suhrawardiyya, subcontinent, Multan

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9 Using Genetic Algorithm to Organize Sustainable Urban Landscape in Historical Part of City

Authors: Shahab Mirzaean Mahabadi, Elham Ebrahimi

Abstract:

The urban development process in the historical urban context has predominately witnessed two main approaches: the first is the Preservation and conservation of the urban fabric and its value, and the second approach is urban renewal and redevelopment. The latter is generally supported by political and economic aspirations. These two approaches conflict evidently. The authors go through the history of urban planning in order to review the historical development of the mentioned approaches. In this article, various values which are inherent in the historical fabric of a city are illustrated by emphasizing on cultural identity and activity. In the following, it is tried to find an optimized plan which maximizes economic development and minimizes change in historical-cultural sites simultaneously. In the proposed model, regarding the decision maker’s intention, and the variety of functions, the selected zone is divided into a number of components. For each component, different alternatives can be assigned, namely, renovation, refurbishment, destruction, and change in function. The decision Variable in this model is to choose an alternative for each component. A set of decisions made upon all components results in a plan. A plan developed in this way can be evaluated based on the decision maker’s point of view. That is, interactions between selected alternatives can make a foundation for the assessment of urban context to design a historical-cultural landscape. A genetic algorithm (GA) approach is used to search for optimal future land use within the historical-culture landscape for a sustainable high-growth city.

Keywords: urban sustainability, green city, regeneration, genetic algorithm

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8 CT Medical Images Denoising Based on New Wavelet Thresholding Compared with Curvelet and Contourlet

Authors: Amir Moslemi, Amir movafeghi, Shahab Moradi

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One of the most important challenging factors in medical images is nominated as noise.Image denoising refers to the improvement of a digital medical image that has been infected by Additive White Gaussian Noise (AWGN). The digital medical image or video can be affected by different types of noises. They are impulse noise, Poisson noise and AWGN. Computed tomography (CT) images are subjected to low quality due to the noise. The quality of CT images is dependent on the absorbed dose to patients directly in such a way that increase in absorbed radiation, consequently absorbed dose to patients (ADP), enhances the CT images quality. In this manner, noise reduction techniques on the purpose of images quality enhancement exposing no excess radiation to patients is one the challenging problems for CT images processing. In this work, noise reduction in CT images was performed using two different directional 2 dimensional (2D) transformations; i.e., Curvelet and Contourlet and Discrete wavelet transform(DWT) thresholding methods of BayesShrink and AdaptShrink, compared to each other and we proposed a new threshold in wavelet domain for not only noise reduction but also edge retaining, consequently the proposed method retains the modified coefficients significantly that result in good visual quality. Data evaluations were accomplished by using two criterions; namely, peak signal to noise ratio (PSNR) and Structure similarity (Ssim).

Keywords: computed tomography (CT), noise reduction, curve-let, contour-let, signal to noise peak-peak ratio (PSNR), structure similarity (Ssim), absorbed dose to patient (ADP)

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7 The Effect of Psychosomatic Aspects of Endometriosis on Marital Relationships and Quality of Life: A Review Study

Authors: Farzaneh Askari, Jila Ganji, Sedigheh Hasani Moghadam

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Background and Aim: Endometriosis has been reported as one of the most common chronic gynecological conditions characterized by physical and psychological complications. Given that the impact of this disease on marital relationships and quality of life is multidimensional, the present review study aimed to reflect on the effect of psychosomatic aspects of endometriosis on marital relationships and quality of life. Materials and Methods: A narrative review methodology using keywords determined by the Medical Subject Headings (MeSH) thesaurus was adopted in this study. For this purpose, the databases of ScienceDirect, Scientific Information Database (SID), Google Scholar, and PubMed were searched by means of key terms including endometriosis, marital relationships, physical complications, psychological complications, and quality of life in English and Persian from 2005 to 2020. At the end of the search, 38 articles were retrieved, and ultimately a total number of 16 studies were recruited for this review. Results: A review of the selected articles demonstrated that endometriosis could affect marital relationships and quality of life among couples featuring in three different categories, i.e. “category I: physical health dimension” (chronic pelvic pain, dysmenorrhea, cramps but not period, reduction and loss of fertility), “category II: sexual health dimension” (no sexual intercourse, dyspareunia, lack of sexual satisfaction), and “category III: psychosocial health dimension” (negative self-esteem, low energy, sense of loneliness, depression, social isolation, insufficient sleep, marital distress, divorce and marriage breakdown, inability to work and socialize). Conclusion: In general, it is suggested to pay particular attention to psychosomatic aspects of marital problems in patients affected with endometriosis. Accordingly, implementing educational and counseling strategies to minimize the complications of this disease can provide the grounds for improving marital relationships and maintaining the quality of life in these patients.

Keywords: Endometriosis, marital relationships, psychosomatic complications, quality of life

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6 Performance Study of Neodymium Extraction by Carbon Nanotubes Assisted Emulsion Liquid Membrane Using Response Surface Methodology

Authors: Payman Davoodi-Nasab, Ahmad Rahbar-Kelishami, Jaber Safdari, Hossein Abolghasemi

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The high purity rare earth elements (REEs) have been vastly used in the field of chemical engineering, metallurgy, nuclear energy, optical, magnetic, luminescence and laser materials, superconductors, ceramics, alloys, catalysts, and etc. Neodymium is one of the most abundant rare earths. By development of a neodymium–iron–boron (Nd–Fe–B) permanent magnet, the importance of neodymium has dramatically increased. Solvent extraction processes have many operational limitations such as large inventory of extractants, loss of solvent due to the organic solubility in aqueous solutions, volatilization of diluents, etc. One of the promising methods of liquid membrane processes is emulsion liquid membrane (ELM) which offers an alternative method to the solvent extraction processes. In this work, a study on Nd extraction through multi-walled carbon nanotubes (MWCNTs) assisted ELM using response surface methodology (RSM) has been performed. The ELM composed of diisooctylphosphinic acid (CYANEX 272) as carrier, MWCNTs as nanoparticles, Span-85 (sorbitan triooleate) as surfactant, kerosene as organic diluent and nitric acid as internal phase. The effects of important operating variables namely, surfactant concentration, MWCNTs concentration, and treatment ratio were investigated. Results were optimized using a central composite design (CCD) and a regression model for extraction percentage was developed. The 3D response surfaces of Nd(III) extraction efficiency were achieved and significance of three important variables and their interactions on the Nd extraction efficiency were found out. Results indicated that introducing the MWCNTs to the ELM process led to increasing the Nd extraction due to higher stability of membrane and mass transfer enhancement. MWCNTs concentration of 407 ppm, Span-85 concentration of 2.1 (%v/v) and treatment ratio of 10 were achieved as the optimum conditions. At the optimum condition, the extraction of Nd(III) reached the maximum of 99.03%.

Keywords: emulsion liquid membrane, extraction of neodymium, multi-walled carbon nanotubes, response surface method

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5 Covid-19 Frontliners Survey: Assessing Complications and Quality of Life in Health Care Workers in District Swat, Khyber Pakhtunkhwa, Pakistan

Authors: Mohsin Shahab, Shagufta Rehmat, Faisal F. Khan

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Background: The global COVID-19 pandemic has generated health problems worldwide. Health care workers are the front-line warriors against the pandemic. The aim of this study was to find out the prevalence of COVID-19 (7th May 2021 to 3rd August 2021) amongst Health Care Workers (HCWs) and to assess the complications associated with it and its effects on their quality of life. Material and Method: The study was conducted in healthcare facilities which serve as pandemic hospitals in district Swat. A total of 140 healthcare workers, who were employed in the COVID-19 health care facilities, including the department of Pulmonology, Intensive Care Unit (ICU), and COVID-19 wards. Participants were tested for COVIID-19 using RT PCR test. A Case Report Form (CRF) for conditions during and post COVID-19 was filled to assess the complications and quality of life of health care workers. Results: A total of 140 Health Care Workers were studied, out of which 40% were doctors, 22% nursing staff, 17% paramedic staff, 9% cleaning staff, lab technologist 6%, 2% operation theater staff, administration staff, and pharmacist. The respondents were also investigated for pre-existing illness prior to SARS-CoV-2 infection, hypertension was the most prevalent, followed by chronic heart diseases and neurological disorders. Fever was the most common symptom, recorded 76.42% in the participants, while 55.71% of participants had dry cough, 55% had a sore throat, following by chest pain 43.56%. Reinfection rate was 10%, with chest pain being recorded in 85.71%. Post disease complication analysis showed that 47.14% of the participants were diagnosed with a new diagnosis after the COVID-19 recovery. Pulmonological diseases were recorded the most as a new diagnosis in, followed by gastrointestinal and psychological problems. Conclusions: The results of the study illustrates how COVID-19 has affected the overall health and quality of life of HCWs in District Swat of Khyber Pakhtunkhwa, Pakistan.

Keywords: SARS-CoV-2, COVID-19, HCW's, symptoms, questionnaire, post COVID-19

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4 Therapeutic Challenges in Treatment of Adults Bacterial Meningitis Cases

Authors: Sadie Namani, Lindita Ajazaj, Arjeta Zogaj, Vera Berisha, Bahrije Halili, Luljeta Hasani, Ajete Aliu

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Background: The outcome of bacterial meningitis is strongly related to the resistance of bacterial pathogens to the initial antimicrobial therapy. The objective of the study was to analyze the initial antimicrobial therapy, the resistance of meningeal pathogens and the outcome of adults bacterial meningitis cases. Materials/methods: This prospective study enrolled 46 adults older than 16 years of age, treated for bacterial meningitis during the years 2009 and 2010 at the infectious diseases clinic in Prishtinë. Patients are categorized into specific age groups: > 16-26 years of age (10 patients), > 26-60 years of age (25 patients) and > 60 years of age (11 patients). All p-values < 0.05 were considered statistically significant. Data were analyzed using Stata 7.1 and SPSS 13. Results: During the two year study period 46 patients (28 males) were treated for bacterial meningitis. 33 patients (72%) had a confirmed bacterial etiology; 13 meningococci, 11 pneumococci, 7 gram-negative bacilli (Ps. aeruginosa 2, Proteus sp. 2, Acinetobacter sp. 2 and Klebsiella sp. 1 case) and 2 staphylococci isolates were found. Neurological complications developed in 17 patients (37%) and the overall mortality rate was 13% (6 deaths). Neurological complications observed were: cerebral abscess (7/46; 15.2%), cerebral edema (4/46; 8.7%); haemiparesis (3/46; 6.5%); recurrent seizures (2/46; 4.3%), and single cases of thrombosis sinus cavernosus, facial nerve palsy and decerebration (1/46; 2.1%). The most common meningeal pathogens were meningococcus in the youngest age group, gram negative-bacilli in second age group and pneumococcus in eldery age group. Initial single-agent antibiotic therapy (ceftriaxone) was used in 17 patients (37%): in 60% of patients in the youngest age group and in 44% of cases in the second age group. 29 patients (63%) were treated with initial dual-agent antibiotic therapy; ceftriaxone in combination with vancomycin or ampicillin. Ceftriaxone and ampicillin were the most commonly used antibiotics for the initial empirical therapy in adults > 50 years of age. All adults > 60 years of age were treated with the initial dual-agent antibiotic therapy as in this age group was recorded the highest mortality rate (M=27%) and adverse outcome (64%). Resistance of pathogens to antimicrobics was recorded in cases caused by gram-negative bacilli and was associated with greater risk for developing neurological complications (p=0.09). None of the gram-negative bacilli were resistant to carbapenems; all were resistant to ampicillin while 5/7 isolates were resistant to cefalosporins. Resistance of meningococci and pneumococci to beta-lactams was not recorded. There were no statistical differences in the occurrence of neurological complications (p > 0.05), resistance of meningeal pathogens to antimicrobics (p > 0.05) and the inital antimicrobial therapy (one vs. two antibiotics) concerning group-ages in adults. Conclusions: The initial antibiotic therapy with ceftriaxone alone or in combination with vancomycin or ampicillin did not cover cases caused by gram-negative bacilli.

Keywords: adults, bacterial meningitis, outcomes, therapy

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3 Urban Planning Patterns after (COVID-19): An Assessment toward Resiliency

Authors: Mohammed AL-Hasani

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The Pandemic COVID-19 altered the daily habits and affected the functional performance of the cities after this crisis leaving remarkable impacts on many metropolises worldwide. It is so obvious that having more densification in the city leads to more threats altering this main approach that was called for achieving sustainable development. The main goal to achieve resiliency in the cities, especially in forcing risks, is to deal with a planning system that is able to resist, absorb, accommodate and recover from the impacts that had been affected. Many Cities in London, Wuhan, New York, and others worldwide carried different planning approaches and varied in reaction to safeguard the impacts of the pandemic. The cities globally varied from the radiant pattern predicted by Le Corbusier, or having multi urban centers more like the approach of Frank Lloyd Wright’s Broadacre City, or having linear growth or gridiron expansion that was common by Doxiadis, compact pattern, and many other hygiene patterns. These urban patterns shape the spatial distribution and Identify both open and natural spaces with gentrified and gentrifying areas. This crisis paid attention to reassess many planning approaches and examine the existing urban patterns focusing more on the aim of continuity and resiliency in managing the crises within the rapid transformation and the power of market forces. According to that, this paper hypothesized that those urban planning patterns determine the method of reaction in assuring quarantine for the inhabitance and the performance of public services and need to be updated through carrying out an innovative urban management system and adopt further resilience patterns in prospective urban planning approaches. This paper investigates the adaptivity and resiliency of variant urban planning patterns regarding selected cities worldwide that affected by COVID-19 and their role in applying certain management strategies in controlling the pandemic spread, finding out the main potentials that should be included in prospective planning approaches. The examination encompasses the spatial arrangement, blocks definition, plots arrangement, and urban space typologies. This paper aims to investigate the urban patterns to deliberate also the debate between densification as one of the more sustainable planning approaches and disaggregation tendency that was followed after the pandemic by restructuring and managing its application according to the assessment of the spatial distribution and urban patterns. The biggest long-term threat to dense cities proves the need to shift to online working and telecommuting, creating a mixture between using cyber and urban spaces to remobilize the city. Reassessing spatial design and growth, open spaces, urban population density, and public awareness are the main solutions that should be carried out to face the outbreak in our current cities that should be managed from global to tertiary levels and could develop criteria for designing the prospective cities

Keywords: COVID-19, densification, resiliency, urban patterns

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2 Colored Image Classification Using Quantum Convolutional Neural Networks Approach

Authors: Farina Riaz, Shahab Abdulla, Srinjoy Ganguly, Hajime Suzuki, Ravinesh C. Deo, Susan Hopkins

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Recently, quantum machine learning has received significant attention. For various types of data, including text and images, numerous quantum machine learning (QML) models have been created and are being tested. Images are exceedingly complex data components that demand more processing power. Despite being mature, classical machine learning still has difficulties with big data applications. Furthermore, quantum technology has revolutionized how machine learning is thought of, by employing quantum features to address optimization issues. Since quantum hardware is currently extremely noisy, it is not practicable to run machine learning algorithms on it without risking the production of inaccurate results. To discover the advantages of quantum versus classical approaches, this research has concentrated on colored image data. Deep learning classification models are currently being created on Quantum platforms, but they are still in a very early stage. Black and white benchmark image datasets like MNIST and Fashion MINIST have been used in recent research. MNIST and CIFAR-10 were compared for binary classification, but the comparison showed that MNIST performed more accurately than colored CIFAR-10. This research will evaluate the performance of the QML algorithm on the colored benchmark dataset CIFAR-10 to advance QML's real-time applicability. However, deep learning classification models have not been developed to compare colored images like Quantum Convolutional Neural Network (QCNN) to determine how much it is better to classical. Only a few models, such as quantum variational circuits, take colored images. The methodology adopted in this research is a hybrid approach by using penny lane as a simulator. To process the 10 classes of CIFAR-10, the image data has been translated into grey scale and the 28 × 28-pixel image containing 10,000 test and 50,000 training images were used. The objective of this work is to determine how much the quantum approach can outperform a classical approach for a comprehensive dataset of color images. After pre-processing 50,000 images from a classical computer, the QCNN model adopted a hybrid method and encoded the images into a quantum simulator for feature extraction using quantum gate rotations. The measurements were carried out on the classical computer after the rotations were applied. According to the results, we note that the QCNN approach is ~12% more effective than the traditional classical CNN approaches and it is possible that applying data augmentation may increase the accuracy. This study has demonstrated that quantum machine and deep learning models can be relatively superior to the classical machine learning approaches in terms of their processing speed and accuracy when used to perform classification on colored classes.

Keywords: CIFAR-10, quantum convolutional neural networks, quantum deep learning, quantum machine learning

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1 Effective Emergency Response and Disaster Prevention: A Decision Support System for Urban Critical Infrastructure Management

Authors: M. Shahab Uddin, Pennung Warnitchai

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Currently more than half of the world’s populations are living in cities, and the number and sizes of cities are growing faster than ever. Cities rely on the effective functioning of complex and interdependent critical infrastructures networks to provide public services, enhance the quality of life, and save the community from hazards and disasters. In contrast, complex connectivity and interdependency among the urban critical infrastructures bring management challenges and make the urban system prone to the domino effect. Unplanned rapid growth, increased connectivity, and interdependency among the infrastructures, resource scarcity, and many other socio-political factors are affecting the typical state of an urban system and making it susceptible to numerous sorts of diversion. In addition to internal vulnerabilities, urban systems are consistently facing external threats from natural and manmade hazards. Cities are not just complex, interdependent system, but also makeup hubs of the economy, politics, culture, education, etc. For survival and sustainability, complex urban systems in the current world need to manage their vulnerabilities and hazardous incidents more wisely and more interactively. Coordinated management in such systems makes for huge potential when it comes to absorbing negative effects in case some of its components were to function improperly. On the other hand, ineffective management during a similar situation of overall disorder from hazards devastation may make the system more fragile and push the system to an ultimate collapse. Following the quantum, the current research hypothesizes that a hazardous event starts its journey as an emergency, and the system’s internal vulnerability and response capacity determine its destination. Connectivity and interdependency among the urban critical infrastructures during this stage may transform its vulnerabilities into dynamic damaging force. An emergency may turn into a disaster in the absence of effective management; similarly, mismanagement or lack of management may lead the situation towards a catastrophe. Situation awareness and factual decision-making is the key to win a battle. The current research proposed a contextual decision support system for an urban critical infrastructure system while integrating three different models: 1) Damage cascade model which demonstrates damage propagation among the infrastructures through their connectivity and interdependency, 2) Restoration model, a dynamic restoration process of individual infrastructure, which is based on facility damage state and overall disruptions in surrounding support environment, and 3) Optimization model that ensures optimized utilization and distribution of available resources in and among the facilities. All three models are tightly connected, mutually interdependent, and together can assess the situation and forecast the dynamic outputs of every input. Moreover, this integrated model will hold disaster managers and decision makers responsible when it comes to checking all the alternative decision before any implementation, and support to produce maximum possible outputs from the available limited inputs. This proposed model will not only support to reduce the extent of damage cascade but will ensure priority restoration and optimize resource utilization through adaptive and collaborative management. Complex systems predictably fail but in unpredictable ways. System understanding, situation awareness, and factual decisions may significantly help urban system to survive and sustain.

Keywords: disaster prevention, decision support system, emergency response, urban critical infrastructure system

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