Internationalizing a Master of Design Program in Strategic Foresight and Innovation

This study establishes a framework for a strategic and normative plan for creating a graduate level Master of Design program in the Dubai International Academic City (DIAC) free zone. The program investigated for internationalization is the MDes in Strategic Foresight & Innovation at OCAD University. Drawing from foresight methods, the research is grounded in a contextual understanding of societal, academic and business implications of internationalizing a Canadian graduate level program for the Middle Eastern market. The report makes a number of recommendations for adapting the SFI program for international implementation, and for the design of a manageable and sustainable prototype that leverages hybrid distance education. The objective of launching a sustainable and scalable pilot program in DIAC that grows over time, is to provide graduate level education in strategic thinking and design of innovation, to a broader developing region in much need of quality higher education

Using TurbSim stochastic simulator to improve accuracy of computational modelling of wind in the built environment

Small wind turbines are often sited in more complex environments than in open terrain. These sites include locations near buildings, trees and other obstacles, and in such situations, the wind is normally highly three-dimensional, turbulent, unstable and weak. There is a need to understand the turbulent flow conditions for a small wind turbine in the built environment. This knowledge is crucial for input into the design process of a small wind turbine to accurately predict blade fatigue loads and lifetime and to ensure that it operates safely with a performance that is optimized for the environment. Computational fluid dynamics is a useful method to provide predictions of local wind flow patterns and to investigate turbulent flow conditions at small wind turbine sites, in a manner that requires less time and investment than actual measurements. This article presents the results of combining a computational fluid dynamics package (ANSYS CFX software) with a stochastic simulator (TurbSim) as an approach to investigate the turbulent flow conditions on the rooftop of a building where small wind turbines are sited. The findings of this article suggest that the combination of a computational fluid dynamics package with the TurbSim stochastic simulator is a promising tool to assess turbulent flow conditions for small wind turbines on the roof of buildings. In particular, in the prevailing wind direction, the results show a significant gain in accuracy in using TurbSim to generate wind speed and turbulence kinetic energy profiles for the inlet of the computational fluid dynamics domain rather than using a logarithmic wind-speed profile and a pre-set value of turbulence intensity in the computational fluid dynamics code. The results also show that small wind turbine installers should erect turbines in the middle of the roof of the building and avoid the edges of the roof as well as areas on the roof close to the windward and leeward walls of the building in the prevailing wind direction

The Effect of Social Marketing on Customer Satisfaction with Regard to the Moderating Role of Environmental Approach

The purpose of this study is to investigate the factors affecting customer satisfaction through social marketing features with regard to the moderating role of environmental approach in Organization of Transportation and Traffic of Mashhad Municipality. For this purpose, aspects and parameters related to the research variables were identified by referring to conducted studies and based on these variables, a questionnaire was designed based on of 28 questions whose reliability was confirmed by the elite in the field of management. The study population are all contacts of the organization of transportation and traffic of Mashhad Municipality; the sample size of which is 220 people by using Cochran formula. Also, to test the hypotheses of this research, Pearson correlation coefficient test and multiple regression are used and the results suggest that the environment moderates the correlation between social marketing and customer satisfaction in the Organization of Transportation and Traffic of Mashhad Municipality

A Study of the Essence of Tragedy in Millerian Plays throughout Nietzsche’s Idea of Inevitability

Arthur Miller’s plays give a deep tragic sensation to the readers dealing with tragic life of modern man; in which a normal man who seems to have committed no tragic flaw faces a drastic tragic outcome. In his article Tragedy and Common Man, Miller declares his intent of re-portraying tragedy in the twentieth century: “since the life of man and his challenges has had been the apt subject for tragedy throughout history”. Besides, in his Birth of Tragedy Nietzsche points out that tragedy claims a spreading subject in man’s life which encompasses the whole human generations and drags them to a tragic fate, and this is raised from a deep-seated problem in man’s life. All Millerian heroes are stricken in such a tragic fate. The present study deals with the indispensable problem of this tragic fate which seems to take in the world of Millerian tragedy and calls this factor as “Inevitability”: the unavoidable tragic end, in which the tragic hero is stricken, has no loophole, and finally has to submit the fate. This study tracks the paradigm of this discourse in Arthur Miller’s tragic plays. Finally the article comes to the conclusion that despite all the struggles of the heroes of modern tragedies, their fate is inevitable. The inevitability is the factor Nietzsche point out for the birth of tragedy: the fundamental problem in man’s fate drags him to the unavoidable noose, and it is the reason for the re-birth of tragedy in twentieth century and Arthur Miller’s plays. Key words: Tragedy; Inevitability; Tragic Flaw; Tragic Pity and Fear; Catharsis; Presentimen

Methylene Blue for Treatment of Hospitalized COVID-19 Patients, Randomized, Controlled, Open-Label Clinical Trial, Phase 3

Funding: This work was supported by a grant from Mashhad University of Medical Sciences (Grant number: 990096, 990845). Acknowledgements: The authors gratefully acknowledge the nurses in Iamm Reza Hospital, Shariati Hospital, Hasheminejad Hospital for their excellent cooperation.Peer reviewedPublisher PD

Sensing of Alzheimer’s Disease and Multiple Sclerosis Using Nano-Bio Interfaces

It is well understood that patients with different diseases may have a variety of specific proteins (e.g., type, amount, and configuration) in their plasmas. When nanoparticles (NPs) are exposed to these plasmas, the resulting coronas may incorporate some of the disease-specific proteins. Using gold (Au) NPs with different surface properties and corona composition, we have developed a technology for the discrimination and detection of two neurodegenerative diseases, Alzheimer's disease (AD) and multiple sclerosis (MS). Applying a variety of techniques, including UV-visible spectra, colorimetric response analyses and liquid chromatography-tandem mass spectrometry, we found the corona-NP complexes, obtained from different human serums, had distinct protein composition, including some specific proteins that are known as AD and MS biomarkers. The colorimetric responses, analyzed by chemometrics and statistical methods, demonstrate promising capabilities of the technology to unambiguously identify and discriminate AD and MS. The developed colorimetric technology might enable a simple, inexpensive and rapid detection/discrimination of neurodegenerative diseases. KEYWORDS: Alzheimer’s disease; colorimetric technology; disease-specific protein corona; gold nanoparticles; multiple sclerosi

Investigation on quality of hydroxyapatite adhesion on investment casting mould

Quality of Hydroxyapatite adhesion on investment casting mould was investigated in this project. Investment casting is a new method for HAp coating onto the metals. First stage of applying this method is making appropriate investment casting mould. Appropriate investment casting mould should have specific properties such as: sufficient strength, proper shape for obtaining sound casting, and the must important one, enough amount of HAp should adhered onto the inner layer of investment casting mould to defuse into the metal during casting for desirable coating. For this purpose appropriate methods used to stick sufficient amount of Hydroxyapatite onto inner layer of ceramic investment casting mould to prepare it for metal coating by casting. therefore 3 different HAp-water mixture viscosities: 5, 7.5 and 10 seconds, were applied to find out which of them was support enough amount of Hydroxyapatite after dewaxing and firing. Dewaxing in three different temperatures 100°, 200° and 300° C applied as well to investigate the effect of the dewaxing temperature on the quality of HAp adhesion on to the moulds. Finally after gathering the results of dewaxing; moulds that have the desirable properties were fired at 600° C to study the effect of firing process on the quality of hydroxyapatite adhesion on moulds. After all XRD, EDAX tests and 3D microscope supervision were done to find out the results. By considering these tests 5 seconds viscosity of HAp-water mixture and 300°C dewaxing temperature had the desirable properties for making sufficient investment casting moulds for metal coating

Using rough set theory to improve content based image retrieval system

Each image in a Content Based Image Retrieval (CBIR) system is represented by its features such as colour, texture and shape. These three groups of features are stored in the feature vector. Therefore, each image managed by the CBIR system is associated with one or more feature vectors. As a result, the storage space required for feature vectors is proportional to the amount of images in the database. In addition, when comparing the similarities among images, the CBIR needs to compare these feature vectors. Nonetheless, researchers are still facing problems when working with a huge image database. Much time is needed when comparing huge feature vectors, as a large amount of memory is required to run the CBIR system. Due to this problem, feature reduction and selection techniques are employed to alleviate the storage and time requirements of large feature vectors. There are many feature reduction techniques, including linear projection techniques such as Principal Component Analysis (PCA), Linear Discriminate Analysis (LDA) and metric embedding techniques (both linear and non-linear). However, these methods have limitations in the CBIR system and cannot improve CBIR performance (retrieval accuracy) and reduce semantic gap efficiently. Therefore, we need a feature selection method that can deal with image features efficiently and has the ability to deal with uncertainties. This research proposes an improved approach to select significant features from the huge image feature vector. The concept behind this research is that it is possible to extract image feature relational patterns in an image feature vector database. After which, these relational patterns are used to generate rules and improve the retrieval results for a CBIR system. In addition, this research proposes a CBIR system utilising the Rough Set instead of deterministic and crisp methods. In this research, Rough Set rules are evaluated with noisy images. Also, in order to have a more accurate classifier in the CBIR system, the classifier is proposed to be based on the Rough Set and Support Vector Machine (SVM) in this research. The significance of this research is firstly, proposing an improved pre-processing phase to solve CBIR problems. Secondly, proposing an integrated framework of using Rough Set with one-versus-one (1-v-1) Support Vector Machine and Rough Set with one-versus-all (1-v-r) Support Vector Machine classifiers in CBIR systems. The Rough Set theory, as a feature selection method in this pre-processing phase, could solve huge amounts of image features problems by narrowing the search space. Also, this theory could deal with vague and incomplete areas by its upper and lower approximations and solve the incomplete and vague areas in image descriptions. As such, the accuracy of the CBIR system can be improved. This proposed approach also gives the confidence and deviation of the estimation (that traditional methods cannot provide before) when compared with historical systems. Finally, the semantic gap problem can be reduced by the Fuzzy Rough Set semantic rules. The performance of the proposed CBIR system is assessed using 2000 images from the Corel image dataset. The images were divided into 10 semantic groups, as well as a number of features. They were then compared to other techniques such as Gain Ratio, Genetic Algorithm, Information Gain, Isomap, Kernel PCA, OneR, Principal Component Analysis (PCA) and Relief-F. The results from the experiment conducted in this thesis show that the proposed feature selections and classifiers will improve the semantic performance results in the proposed CBIR systems. Retrieval accuracy results for Fuzzy Rough feature selection is 91.06% for Normal images, and the results are 90.31%, 91.28% and 90.42% with Gaussian Noise, Salt & Pepper Noise and Poisson Noise respectively. Moreover, comparing the Rough Set with 1-v-1 SVM and the Rough Set with 1-v-r SVM classifiers to other classifiers (Decision Tree (C5.0), K-nearest neighbour, neural network, and Support Vector Machine) show that the retrieval accuracy has increased to 91.4% for Rough Set 1-v-r SVM and 92% for Rough Set 1-v-1 SVM

Utilising fuzzy rough set based on mutual information decreasing method for feature reduction in an image retrieval system

Content-Based Image Retrieval (CBIR) system has become a focus of research in the area of image processing and machine vision. General CBIR system automatically index and retrieve images with visual features such as colour, texture and shape. However, current research found that there is a significant gap between visual features and semantic features used by humans to describe images. In order to bridge the semantic gap, some researchers have proposed methods for managing and decreasing image features, and extract useful features from a feature vector. This paper presents an image retrieval system utilising fuzzy rough set based on mutual information decreasing method and the Support Vector Machine (SVM) classifier. The system has training and testing phases. In order to reduce the semantic gap, the propose retrieval system used relevance feedback to improve the retrieval performance. This paper also compared the proposed method with other traditional retrieval systems that use PCA, kernel PCA, Isomap and MVU for their feature reduction method. Experiments are carried out using a standard Corel dataset to test the accuracy and robustness of the proposed system. The experiment results show the propose method can retrieve images more efficiently than the traditional methods. The use of fuzzy rough set based on mutual information decreasing method, SVM and relevance feedback ensures that the propose image retrieval system produces results which are highly relevant to the content of an image query

Content based image retrieval system with a combination of rough set and support vector machine

In this paper, a classifier based on a combination of Rough Set and 1-v-1 (one-versus-one) Support Vector Machine for Content Based Image Retrieval system is presented. Some problems of 1-v-1 Support Vector Machine can be reduced using Rough Set. With Rough Set, a 1-v-1 Support Vector Machine can provide good results when dealing with incomplete and uncertain data and features. In addition, boundary region in Rough Set can reduce the error rate. Storage requirements are reduced when compared to the conventional 1-v-1 Support Vector Machine. This classifier has better semantic interpretation of the classification process. We compare our Content Based Image Retrieval system with other image retrieval systems that uses neural network, K-nearest neighbour and Support Vector Machine as the classifier in their methodology. Experiments are carried out using a standard Corel dataset to test the accuracy and robustness of the proposed system. The experiment results show the proposed method can retrieve images more efficiently than other methods in comparison