Sharif Digital Repository

Parkinson's disease is a progressive and severe neurodegenerative disorder in the central nervous system that is common in adults and, to some extent, in young people. One way to control and improve this disease is through rehabilitation, specifically in the form of rehabilitation activities. Due to the difficulty of travelling to and from the clinic, systems have been developed today that, using inertial sensors, provide the possibility of remotely monitoring this type of treatment up to 95%. In this regard, a system named SEPANTA has been developed at the Djavad Mowafaghian Research Center to diagnose and monitor the rehabilitation activities performed by patients with Parkinson's disease.... 

Flameless combustion in combustion technology is an innovative method with low nox production that few years provided it passes. In this paper the effects of various parameters on flameless combustion chamber with separate fuel and air jets, has been modeled numerically with the help of Fluent 6.3 software. Differences between traditional combustion and flameless combustion were determined and the flame structure has been studied in different scenarios. In numerical modeling, approach were used to modeling turbulence and eddy dissipation concept (EDC) approach use to modeling combustion and turbulence interaction effects. A global Two-step reaction mechanism for propane and a global... 

According to increasing computer systems, needs for verification of such systems with respect to desirable properties is critical. Model checking is one of the best methods of verification. Different methods have been proposed for model checking. The most efficient of these methods is automata-theoretic approach. In this approach, formal specification of desirable property, specified by formula in temporal logics, is translated to corresponding automaton. If the system model is expressed as automaton, the problem of model checking is then reduced to a problem of automata-theory. The question is the following. Are all the computations of the corresponding automaton accepted by the automaton... 

Beam diagnostics is an essential constituent of any accelerator. The position information of the electron beam is obtained by a set of Beam Position Monitors (BPMs), which in addition to determining the position, are used to derive information concerning lattice functions and beam dynamics. To design of Button Beam Position Monitor(BPM) for a Synchrotron Light Source, to get beam stabilities on submicron levels, preliminary studies were done to have optimal design. We present an algorithem which caculate all required parameteres for different design of button BPMs. To calculate induced charge and voltage on each button, Poisson's equation has been solved by Green method. For sensivity... 

Arising from the intersection of two modern ideas in logic and mathematics, namely Type Theory - specifically Martin-Löf’s intuitionistic type theory, and Homotopy Theory, Homotopy Type Theory has introduced a novel formalism that formalizes every mathematical object - including constructions, definitions, and proofs - in a specific and fundamentally different way from other interpretive frameworks (such as set theory), bringing forth new results - both philosophically and mathematically. The first goal of this research is to understand the meaning of Homotopy Type Theory as a foundation for mathematics through exploring this new formalism. The second goal of this research is to understand... 

Lab-on-a-chip devices have gained a lot of attention in chemical and biomedical analyses during the past two decades. These devices employ microfluidics basics and fundamentals to combine multifold laboratory processes in one single portable chip. The electric field has been often used in most microfluidics applications for the ease of sample control as well as become easily integrated to other chip components. Instabilities in microflows would occur when two fluids of different electric properties are exposed to an adequately strong electric field. Studying these electrokinetic instabilities is not only important for the fundamental studies but also for practical applications in micromixers... 

Cloud computing is a paradigm for scalable processing infrastructure which combines distributed software concepts, networks and IT management. Virtualization techniques help to increase productivity from resources. Services are adjusted based on service level agreement with a contract between users and service providers for specifying quality service. In this way, the level of customer satisfaction will be improved. Reliable and flexible management of service level agreements is very important for users and providers. This agreement model is used to prevent the payment of the penalty by providers and minimized interaction between users and providers. Migration from the traditional model to a... 

In building construction, a rigid vertical diaphragm is capable of transferring lateral forces from exterior walls, roofs and floors to the ground foundation in a direction parallel to its planes.[1] Refractory elements against lateral forces contain moment frames, shear walls or a combination of them. In this research, shear walls are discussed. Nowadays, in cities having old contexture, some of the buildings should be destructed. Thus, modern buildings should be built. Due to the limitation of adequate space and lack of symmetrical plan, buildings must be built in asymmetrical form. To design the structures with asymmetrical plan, it is necessary to study buildings with presence of... 

In this work, we present AppMoTrack, a novel tracking-by-detection (TBD) ap-proach that effectively balances speed and accuracy. The proposed framework lever-ages Incremental Principal Component Analysis (PCA) to extract robust features from bounding boxes, followed by Fisher Linear Discriminant Analysis (LDA) to refine these features by considering class separability, where each unique target across frames rep-resents a class. A hierarchical cost function is introduced to enhance data association precision. For detections with high confidence scores, a two-stage process is employed: first, a combination of Intersection over Union (IoU) and cosine distance between LDA-transformed PCA... 

The Electron Paramagnetic Resonance(EPR) is a retrospective and accurate dosimetry method to measure irradiated-induced radical population in the matter for determination the induced dose in the matter. The dose uncertainties will be about 1 percent. in the first stage of the present research, the response of EPR system to a reference sample has been measured. Then, responses due to the other samples has been compared with it and the secondary sample dose has been calculated. The reference sample usually is alanine. Unlike the perturbation theory forecast,the EPR signal intensity response to dose for alanine is not linear. In this thesis, first, the alanine samples (with pellet form) have... 

Action recognition has a lot of applications in everyday human life. In the past, the researchers concentrated on using RGB frames, but since the advent of 3-dimensional sensors such as Kinect, 3D action recognition drew researchers' attention. Kinect can extract the joints of the body in action as time series. One of the main challenges of action recognition is that different individuals perform an action with various styles and speeds. Hence, the conventional methods such as calculating Euclidean distance seem inappropriate for this task. One solution is to use the techniques such as DTW, which aims to temporal aligning of the sequences. The DTW is not a metric distance; hence, in this... 

Nowadays, due to environmental problems, electric cars are becoming more and more popular. The main drawback of these cars is due to the large volume, weight, and price of the battery and its long charging time. Charging the battery at short intervals or even in moving, can help to use a smaller battery and reduce battery problems. Therefore, the dynamic wireless power transmission technology that provides power without having to stop the car to recharge its batteries can revolutionize the electric car industry. The ever-expanding advance of power electronics and wireless power transmission technologies has made it possible to transfer power to moving electric cars. Barriers to this industry... 

Object tracking is one of the first, most basic and among the topics of interest in the field of computer vision. Nowadays, with the availability of high-quality and inexpensive video cameras and the expansion of neural networks, there has been a great interest in automatic video analysis using object tracking algorithms. However, many of the existing object tracking algorithms do frame-by-frame tracking using videos with high frame rates, which is not suitable for all locations that use surveillance cameras, because due to existing hardware limitations, the recorded videos are either kept for a limited period of time or are forcibly stored with low frame rates, which leads to the loss of a... 

Recent approaches in the field of semantic image segmentation rely on deep networks that are trained by pixel-level labels. This level of labeling requires a lot of time for the labeler person; because these networks require large training datasets to achieve optimal accuracy and the lack of data at the labeled pixel level causes a significant drop in their performance. In order to overcome this problem, weakly supervised segmentation approaches have been proposed. In these approaches, weaker labels such as image-level labels, bounding boxes, scribbles, etc. have been introduced to train the networks.In this thesis, a method for segmentation of kidney and kidney tumor in CT scan images based... 

Pedestrian detection has been a significant area of interest both independently and as part of the object detection task. Classical algorithms always struggle with common environmental changes due to their simplistic approach to semantic feature extraction. In contrast, deep convolutional networks develop simple features through multiple layers, resulting in more reliable detections. Convolutional neural networks have demonstrated superior performance compared to classical algorithms, and they mostly run in real time thanks to graphic cards. However, speeding them up can reduce operational costs. This thesis focuses on static scenes and utilizes background information to make the detection... 

This thesis suggests a practical system designed for the implementation of vision-based virtual assistants, aligning with the identified needs in the research background. Distinguishing itself from current literature, this study thoroughly explores and delineates the computing hierarchy while also suggesting the appropriate software architecture customized for the effective utilization of virtual assistants. Focusing on the most common application in vision-based virtual assistants—object detection and tracking—the research introduces an efficient multi-object tracking method using the tracking-by-detection paradigm. Notably, the proposed tracker stands out for its minimal computational... 

The human action recognition is one of the most important concepts of computer vision in recent decades. Most of the two dimensional methods in this field are facing serious challenges such as occlusion and missing the third dimension of data. Development of depth sensors has made easy access to tracking people and 3D positions of human body joints. This Thesis proposes a new method of action recognition that utilizes the position of joints obtained by Kinect sensor. The learning stage uses Fisher Linear Discriminant Analysis (LDA) to construct discriminant feature space. Two types of distances, i.e., Euclidean and Mahalanobis, are used for recognizing the states. Also, Hidden Markov Model... 

The non-stationary nature of brain activity signals and their many inter-subject differences have created many challenges in the practical applications of emotion recognition based on electroencephalogram (EEG) signals, such as brain-computer interfaces. In such a way, the use of traditional classifiers in classifying these signals leads to a significant decrease in accuracy when applying the classifier to a new subject. Domain Adaptation methods seem to be an effective way to solve this problem by minimizing the difference between the EEG signals of different subjects. But in the basic techniques for domain adaptation, looking at all subjects' data in the same look causes the loss of a part...