Sharif Digital Repository

Literature on the informal economy can mainly be divided into two different contrasting theories. According to the dual labor market theory (DLM), which considers the informal economy as a spare sector providing jobs for formally unemployed resources, unpleasant economic situations force people to act informally. Legalists, on the other hand, blame government interventions such as minimum wages or price control policies for pushing rent-seeking firms toward the shadows. This study using an Error-correction Multi-Indicators Multi-Causes (EMIMIC) model, a systematic method consisting of structural and measurement equations, shows that these two theories are complementary rather than... 

One crucial part of an image registration algorithm is utilization of an appropriate similarity metric. For common similarity metrics such as CC or MI, it is assumed that the intensities of image pixels are independent from each other and stationary. Accepting these assumptions, one will have difficulty doing image registration in the presence of spatially varying intensity distortion. In Myronenko et al. [5] a solution based on minimization of residual complexity is introduced to solve this problem. In this work, the weakness of RC method is investigated for more complex spatially varying intensity distortions and a modification of this method is presented to improve its performance in such... 

Radiopacity is sometimes an essential characteristic of biomaterials that can help clinicians perform follow-ups during pre- and post-interventional radiological imaging. Due to their chemical composition and structure, most bioceramics are inherently radiopaque but can still be doped/mixed with radiopacifiers to increase their visualization during or after medical procedures. The radiopacifiers are frequently heavy elements of the periodic table, such as Bi, Zr, Sr, Ba, Ta, Zn, Y, etc., or their relevant compounds that can confer enhanced radiopacity. Radiopaque bioceramics are also intriguing additives for biopolymers and hybrids, which are extensively researched and developed nowadays for... 

Dental professionals are in a unique position to promote smoking cessation among their patients. We evaluated the effects of a brief counselling intervention by a dentist on patients' attitude towards the role of dentists in tobacco cessation programmes. In a semi-experimental study in Tehran, Islamic Republic of Iran, 70 eligible smokers were selected and randomly assigned to intervention and control groups. The initial attitudes of the patients regarding tobacco cessation counselling services provided by the dentist were determined using a validated questionnaire. The intervention group received a brief chair-side counselling by a dentist based on the 5 A's approach, while no intervention... 

Content-based image retrieval (CBIR) makes use of image features, such as color, texture or shape, to index images with minimal human intervention. Content-based image retrieval can be used to locate medical images in large databases. In this paper, the fundamentals of the key components of content-based image retrieval systems are introduced first to give an overview of this area. Then, a case study which describes the methodology of a CBIR system for retrieving human brain magnetic resonance images, is presented. The proposed method is based on Adaptive Neuro-fuzzy Inference System (ANFIS) learning and could classify an image as normal and tumoral. This research uses the knowledge of CBIR... 

The role of context for better decision-making has been a topic of significant research effort over the years. Context-aware systems are able to adapt their operations to the current context without explicit user intervention and thus aim at increasing usability and effectiveness by taking environmental context into account. These systems exploit information about the context of use, such as the location, tasks and preferences of the user, in order to adapt their behavior in response to change operating environments and user requirements. Pervasive computing sketches a pleasant vision for future computing environments that computing power is present anywhere anytime. Utilizing context,... 

Background: A few clinical trials have examined the effect of treatment interventions on postural control in patients with chronic low back pain, all of which have exclusively evaluated postural stability using traditional linear measures of postural sway. However, postural control improvement cannot be determined by exclusively relying on linear measurements, because these parameters provide no information on underlying motor control mechanisms. Objective: This study aimed to compare the effect of using lumbosacral orthoses (LSO) together with routine physical therapy, compared to routine physical therapy alone on postural control, using nonlinear analysis techniques. Methods: Forty-four... 

We study the problem of experiment design to learn causal structures from interventional data. We consider an active learning setting in which the experimenter decides to intervene on one of the variables in the system in each step and uses the results of the intervention to recover further causal relationships among the variables. The goal is to fully identify the causal structures with minimum number of interventions. We present the first deep reinforcement learning based solution for the problem of experiment design. In the proposed method, we embed input graphs to vectors using a graph neural network and feed them to another neural network which outputs a variable for performing... 

Content-based image retrieval (CBIR) has turned into an important and active potential research field with the advance of multimedia and imaging technology. It makes use of image features, such as color, texture and shape, to index images with minimal human intervention. A CBIR system can be used to locate medical images in large databases. In this paper we propose a CBIR system which describes the methodology for retrieving digital human brain magnetic resonance images (MRI) based on textural features and the Adaptive neuro-fuzzy inference system (ANFIS) learning to retrieve similar images from database in two categories: normal and tumoral. A fuzzy classifier has been used, because of the...