Design and implementation of a prototype active infrared sensor controlled automatic sliding door for mitigation of coronavirus disease 2019 (COVID-19)

The door is an essential part of any structure that provides access and security of lives and properties. The manual operation of a door could be cumbersome and laborious when the traffic volume is high. Also, it has been observed that doors could serve as a medium of spreading the deadly coronavirus disease 2019 (COVID-19) infection. Therefore, a prototype automatic sliding door that plays a crucial role in curbing the spread of this infectious diseases has been designed and implemented in this paper. The design of the prototype sliding door is in two parts namely; the structural part and the automation part. The structural design of the door was achieved using the Microsoft Visio 2016 while the design of the automation system was achieved using express printed circuit board. The implementation of the structural part was achieved using 1 inch particle board while the implementation of the automation system was based on the components like the active infrared sensor, resistors (10 kΩ), capacitor (1000 µF), transistors (TIP41 Q8, BC548 Q7), LED indicators, press button switch, pulley system, drive belt, stepper motor (IP65), and ATMEGA 8 microcontroller. The result of the tests carried out on the door showed that the prototype automatic sliding door was characterized by average opening time, closing time, delay time, and optimal sensing range of 3.10 s, 3.05 s, 5.72 s, and 23.5 cm, respectively. It can therefore be concluded from this work that the prototype automatic sliding door is effective in overriding the manual operation of the door

Patient-specific RF safety assessment in MRI: Progress in creating surface-based human head and shoulder models

The interaction of electromagnetic (EM) fields with the human body during magnetic resonance imaging (MRI) is complex and subject specific. MRI radiofrequency (RF) coil performance and safety assessment typically includes numerical EM simulations with a set of human body models. The dimensions of mesh elements used for discretization of the EM simulation domain must be adequate for correct representation of the MRI coil elements, different types of human tissue, and wires and electrodes of additional devices. Examples of such devices include those used during electroencephalography, transcranial magnetic stimulation, and transcranial direct current stimulation, which record complementary information or manipulate brain states during MRI measurement. The electrical contact within and between tissues, as well as between an electrode and the skin, must also be preserved. These requirements can be fulfilled with anatomically correct surface-based human models and EM solvers based on unstructured meshes. Here, we report (i) our workflow used to generate the surface meshes of a head and torso model from the segmented AustinMan dataset, (ii) head and torso model mesh optimization for three-dimensional EM simulation in ANSYS HFSS, and (iii) several case studies of MRI RF coil performance and safety assessment

Design of a Transceive Coil Array for Parallel Imaging at 9.4T

The main goal of this thesis is to design and develop a transmit/receive (transceive) coil array for small animal imaging at 9.4T. The goal is achieved by following basic RF design principles with a methodical construction approach and demonstrating viable applications. As operational frequencies increase linearly with higher static fields, the wavelength approaches the size of the sample being imaged. The resulting standing wave mode deteriorates image homogeneity. Fortunately, with multi-channel coil arrays, the produced Bi field can be tailored to produce a homogeneous excitation in the region of interest, thus overcoming the so called dielectric resonance effect. We examined a solution to achieve a higher level of Bx homogeneity and we compared the improvement of RF wavelength effects reduction against the results obtained with a similar-sized conventional birdcage coil. An additional benefit of this design lies in the fact that the use of multiple receiving coil elements is necessary for the implementation of fast imaging acquisition techniques such as parallel imaging. This is possible because the distinct element sensitivities are used to reconstruct conventional images from undersampled (or accelerated) data. The greatest advantage of parallel imaging is thus the reduction of total acquisition time. In functional MRI (fMRI), single-shot EPI is one of the standard imaging technique. Unfortunately, EPI suffers from significant limitations, precisely because all of the data is acquired following a single RF excitation. As a result EPI images can manifest artifacts and blurring due to susceptibility mismatch, off-resonance effects and reduced signal at the edges of k-space. Fortunately, parallel imaging can be used to decrease such unwanted effects by reducing the total k-space data acquired. Presented in this thesis is the logical progression of the construction of a transceive coil from surface coil fundamentals to high field applications such as field focusing and parallel imaging techniques

A hybrid cavity and parallel-plate PEEC method for analysis of complex power net area fills, and a tool development for peak distortion analysis

Modern ASICs and FPGAs are becoming more and more dense, which is causing an increasing demand of the current draw from the power distribution network (PDN). And one of the main design objectives of a power distribution network is to reduce the voltage noise ripple below a specified allowable limit. Although the target impedance is a commonly used criterion in most PDN designs, it may not be efficient because it\u27s usually rather pessimistic. Herein a time domain voltage ripple decomposition approach is proposed to avoid overdesign as well as provide design guidance to PI engineers. Based on a physics-based circuit model for PDN and a switching current generator including both high frequency switching and low frequency power gating, the total voltage ripple can be divided into several components. Each component will have a one-to-one correspondence to the real PDN geometry. Thus design curves can also be derived, which can guide PI engineers when making design decisions. Peak distortion analysis (PDA) is commonly used to find the worst-case eye diagram and data pattern. Compared to traditional long transient simulations, PDA can significantly reduce the computation time by only taking into consideration the worst case. Generally PDA is based on a superposition technique with a single bit response (SBR), which requires the system to be linear time invariant (LTI) or can be well approximated as an LTI system. SBR is no longer applicable for systems which have different rising and falling edge responses due to asymmetric I/O design or mismatches between pull-up and pull-down drivers. Also sometimes the nonlinearity can extend beyond the edge transitions which can result from the voltage noise on the power distribution network (PDN). Herein PDA based on the superposition of multiple edge responses (MER) is proposed to account for a non-LTI system as well as asymmetric rising and falling edges --Abstract, page iii

Sketch interpretation using multiscale stochastic models of temporal patterns

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2006.Includes bibliographical references (p. 102-114).Sketching is a natural mode of interaction used in a variety of settings. For example, people sketch during early design and brainstorming sessions to guide the thought process; when we communicate certain ideas, we use sketching as an additional modality to convey ideas that can not be put in words. The emergence of hardware such as PDAs and Tablet PCs has enabled capturing freehand sketches, enabling the routine use of sketching as an additional human-computer interaction modality. But despite the availability of pen based information capture hardware, relatively little effort has been put into developing software capable of understanding and reasoning about sketches. To date, most approaches to sketch recognition have treated sketches as images (i.e., static finished products) and have applied vision algorithms for recognition. However, unlike images, sketches are produced incrementally and interactively, one stroke at a time and their processing should take advantage of this. This thesis explores ways of doing sketch recognition by extracting as much information as possible from temporal patterns that appear during sketching.(cont.) We present a sketch recognition framework based on hierarchical statistical models of temporal patterns. We show that in certain domains, stroke orderings used in the course of drawing individual objects contain temporal patterns that can aid recognition. We build on this work to show how sketch recognition systems can use knowledge of both common stroke orderings and common object orderings. We describe a statistical framework based on Dynamic Bayesian Networks that can learn temporal models of object-level and stroke-level patterns for recognition. Our framework supports multi-object strokes, multi-stroke objects, and allows interspersed drawing of objects - relaxing the assumption that objects are drawn one at a time. Our system also supports real-valued feature representations using a numerically stable recognition algorithm. We present recognition results for hand-drawn electronic circuit diagrams. The results show that modeling temporal patterns at multiple scales provides a significant increase in correct recognition rates, with no added computational penalties.by Tevfik Metin Sezgin.Ph.D

Accurate modeling techniques for power delivery

“Power delivery is essential in electronic systems to provide reliable power from voltage sources to load devices. Driven by the ambitious user demands and technology evolutions, the power delivery design is posed serious challenges. In this work, we focus on modeling two types of power delivery paths: the power distribution network (PDN) and the wireless power transfer (WPT) system. For the modeling of PDN, a novel pattern-based analytical method is proposed for PCB-level PDN impedance calculations, which constructs an equivalent circuit with one-to-one correspondences to the PCB’s physical structure. A practical modeling methodology is also introduced to optimize the PDN design. In addition, a topology-based behavior model is developed for the current-mode voltage regulator module (VRM). This model includes all the critical components in the power stage, the voltage control loop, and the current control loop of a VRM device. A novel method is also proposed to unify the modeling of the continuous and discontinuous conduction modes for transient load responses. Cascading the proposed VRM model with the PCB-level PDN model enables a combined PDN analysis, which is much needed for modern PDN designs. For the modeling of WPT system, a system-level model is developed for both efficiency and power loss of all the blocks in WPT systems. A rectifier characterization method is also proposed to obtain the accurate load impedance. This model is capable of deriving the power capabilities for both the fundamental and higher order harmonics. Based on the system model, a practical design methodology is introduced to simultaneously optimize multiple system parameters, which greatly accelerates the design process”--Abstract, page iv

Admittance Method for Estimating Local Field Potentials Generated in a Multi-Scale Neuron Model of the Hippocampus

Significant progress has been made toward model-based prediction of neral tissue activation in response to extracellular electrical stimulation, but challenges remain in the accurate and efficient estimation of distributed local field potentials (LFP). Analytical methods of estimating electric fields are a first-order approximation that may be suitable for model validation, but they are computationally expensive and cannot accurately capture boundary conditions in heterogeneous tissue. While there are many appropriate numerical methods of solving electric fields in neural tissue models, there isn\u27t an established standard for mesh geometry nor a well-known rule for handling any mismatch in spatial resolution. Moreover, the challenge of misalignment between current sources and mesh nodes in a finite-element or resistor-network method volume conduction model needs to be further investigated. Therefore, using a previously published and validated multi-scale model of the hippocampus, the authors have formulated an algorithm for LFP estimation, and by extension, bidirectional communication between discretized and numerically solved volume conduction models and biologically detailed neural circuit models constructed in NEURON. Development of this algorithm required that we assess meshes of (i) unstructured tetrahedral and grid-based hexahedral geometries as well as (ii) differing approaches for managing the spatial misalignment of current sources and mesh nodes. The resulting algorithm is validated through the comparison of Admittance Method predicted evoked potentials with analytically estimated LFPs. Establishing this method is a critical step toward closed-loop integration of volume conductor and NEURON models that could lead to substantial improvement of the predictive power of multi-scale stimulation models of cortical tissue. These models may be used to deepen our understanding of hippocampal pathologies and the identification of efficacious electroceutical treatments

Analysis and mitigation of parallel-plate noise for high-isolation applications

Achieving highs levels of isolation between different functionalities in a PCB can be challenging. One of the major issues is that vertically adjacent planes or area fills in a PCB can form a parallel-plate waveguide with no cutoff frequency and serve as an efficient coupling mechanism between interconnects. Due to the finite size of the conductors, reflections off the edges of these parallel-plate cavities can result in the formation of standing-wave patterns with very high field strengths, resulting in high coupling at certain frequencies. This noise coupling mechanism can be suppressed by connecting the parallel plates together with an adequate amount of vias. However, adjacent power and ground conductors can not be conductively connected together because they are at different DC potentials. As a result, there is no way to eliminate the existence of parallel-plate noise in a power/ground cavity. A fundamental understanding of this problem is needed to determine how it can be mitigated. The first part of the thesis develops a qualitative understanding of the underlying physics of how noise is coupled to the parallel plates from a variety of interconnects and how the noise can spread throughout the design. This discussion is then expanded to more complex geometries that are representative of what could occur in actual designs. Test vehicles are created to study the noise coupling to various interconnects from noise injected into the power distribution network by an amplifier. Parameters affecting the transfer of noise from an amplifier to the power distribution network, such as the addition of capacitors, are then explored. An expression to predict the noise coupling using S-parameter measurements of the PCB and the amplifier is developed. It is demonstrated that results from full-wave electromagnetic simulation can be used to predict the amount of noise coupling before PCB fabrication. General design recommendations are then presented to improve design robustness to the parallel-plate noise --Abstract, page iii

OBJECT TRACKING

„Object tracking‟ is an important task within the field of computer vision. The prevention of theft, the focusing of light to the actor or model automatically during theatre, award show, and concerts, then the law enforcement operation such as search and rescue, prison yard security and helicopter chases. It is needed for simple object tracking designed for simple technique to keep low cost and limited processing power. This project is to develop simple object tracking by using infrared signal. The technique that can be implemented is by allowing the object to be tracked through transmitted infrared. Tracker detects infrared signal and more pointer (spotlight) towards object and the position is the feedback to control system which actuated by means of stepper motor. The adjustment can be in different elements using control system such as P, PI, PD and PID controller. This project successfully can detect the object maximum up to 3.2m