Miracle-dz/UniFAR-FTUs huggingface dataset:
Force-Sensing-Based Multi-Platform Robotic Assistance for Vitreoretinal Surgery

ii ACKNOWLEDGEMENTS . v TABLE OF CONTENTS . ix LIST OF TABLES . xii LIST OF FIGURES . xiii Chapter 1 : INTRODUCTION. 1 1.1 Thesis Statement . 1 1.2 Vitreoretinal Surgery . 1 1.2.1 Epiretinal Membrane Peeling . 3 1.2.2 Retinal Vein Cannulation . 3 1.3. Challenges in Vitreoretinal Surgery . 4 1.3. 1 Epiretinal Membrane Peeling . 5 1.3. 2 Retinal Vein Cannulation . 6 1.4 Dissertation Overview . 8 Chapter 2 : RELATED WORK . 10 2.1. Force Sensing . 10 2.2. Robotic Systems for Ophthalmology . 11 2.3. 2 Hand-held Robots . 12 2.3. 3 Cooperatively-Controlled Robots . 13 Chapter 3 : FORCE-SENSING INSTRUMENTS FOR ASSISTED VITREORETINAL SURGERY . 15 3.
Are Magnetic Wind-driving Disks Inherently Unstable?

There have been claims in the literature that accretion disks in which a centrifugally driven wind is the dominant mode of angular momentum transport are inherently unstable. This issue is considered here by applying an equilibrium-curve analysis to the wind-driving, ambipolar diffusion dominated, magnetic-disk model of Wardle and Königl. The equilibrium solution curves for this class of models typically exhibit two distinct branches. It is argued that only one of these branches represents unstable equilibria and that a real disk/wind system likely corresponds to a stable solution.
The Riemann sum method for the design of sum-of-cisoids simulators for Rayleigh fading channels in non-isotropic scattering environments

In this paper, we introduce the Riemann sum method (RSM) as an effective tool for the design of sum-of-cisoids (SOC) simulators for narrowband mobile Rayleigh fading channels under non-isotropic scattering conditions. We show that the RSM results in an excellent approximation of the channel's autocorrelation function (ACF). Furthermore, we compare the performance of the RSM with that of the generalized method of equal areas (GMEA) and L p -norm method (LPNM), which were until now the only methods available for the design of SOC simulators for non-isotropic scattering channels. The obtained results indicate that the RSM is better suited than the GMEA and the LPNM to approximate the channel's ACF, whereas the latter two methods provide better results regarding the emulation of the envelope distribution. Owing to its simplicity and good performance, the RSM can be used to design flexible simulation platforms for the analysis of mobile communication systems operating in non-isotropic scattering environments.
Multi-agent Inverse Reinforcement Learning for Zero-sum Games

In this paper we introduce a Bayesian framework for solving a class of problems termed Multi-agent Inverse Reinforcement Learning (MIRL). Compared to the well-known Inverse Reinforcement Learning (IRL) problem, MIRL is formalized in the context of a stochastic game rather than a Markov decision process (MDP). Games bring two primary challenges: First, the concept of optimality, central to MDPs, loses its meaning and must be replaced with a more general solution concept, such as the Nash equilibrium. Second, the non-uniqueness of equilibria means that in MIRL, in addition to multiple reasonable solutions for a given inversion model, there may be multiple inversion models that are all equally sensible approaches to solving the problem. We establish a theoretical foundation for competitive two-agent MIRL problems and propose a Bayesian optimization algorithm to solve the problem. We focus on the case of two-person zero-sum stochastic games, developing a generative model for the likelihood of unknown rewards of agents given observed game play assuming that the two agents follow a minimax bipolicy. As a numerical illustration, we apply our method in the context of an abstract soccer game. For the soccer game, we investigate relationships between the extent of prior information and the quality of learned rewards. Results suggest that covariance structure is more important than mean value in reward priors.
Rainfall-runoff modeling using Doppler weather radar data for Adyar watershed, India

Precipitation is a significant input for hydrologic models; so, it needs to be quantified precisely. The measurement with rain gauges gives the rainfall at a particular location, whereas the radar obtains instantaneous snapshots of electromagnetic backscatter from rain volumes that are then converted into rainfall via algorithms. It has been proved that the radar measurement of areal rainfall can outperform rain gauge network measurements, especially in remote areas where rain gauges are sparse, and remotely sensed satellite rainfall data are too inaccurate. The research focuses on a technique to improve rainfall-runoff modeling based on radar derived rainfall data for Adyar watershed, Chennai, India. A hydrologic model called ‘Hydrologic Engineering Center-Hydrologic Modeling System (HEC-HMS)’ is used for simulating rainfall-runoff processes. CARTOSAT 30 m DEM is used for watershed delineation using HEC-GeoHMS. The Adyar watershed is within 100 km radius circle from the Doppler Weather Radar station, hence it has been chosen as the study area. The cyclonic storm Jal event from 4-8 November, 2010 period is selected for the study. The data for this period are collected from the Statistical Department, and the Cyclone Detection Radar Centre, Chennai, India. The results show that the runoff is over predicted using calibrated Doppler radar data in comparison with the point rainfall from rain gauge stations.
Modeling light scattering at soil surfaces

Structures visible on soil profiles contain transport-relevant information. The ultimate goal of this study is to map regions of similar texture on excavated soil profiles. The shape and especially the connectivity of such structures is a first-order approximation for quantifying the transport domains that can be used to predict flow and transport. With this study, we try to understand the spectral information of soil profile images to quantify the spatial arrangement of such structural features. The first and important step is to produce a texture map of the soil profiles from reflectance measurements. Thus, we evaluate reflectance and transmittance spectra measured on small areas of soil surfaces. Reflectance and transmittance depend on particle size. Measurements and simulations show that the influence of texture on reflectance is measurable but small. In this study, we describe first light scattering by idealized particles. They shall represent natural soil particles. We calculate the light absorption and the directional distribution of the scattered light. Second, we use these properties to describe the radiative transfer of visible light and infrared radiation using a four-flux model. The four-flux model combined with the idealized particle model yields a model with which we can calculate the relation between average particle size and reflectance. To test our radiative transfer model, the reflectance and transmittance of three soil materials were measured. The three soil materials differ in color. Each material was sieved into seven fractions to prepare samples of the same material but different texture. Fitting the complex refractive indexes to the measured spectra indicates that these materials can be differentiated and classified according to their light absorption properties.
IDENTIFICATION OF ARTICULATED IBODY INERTIAS AND COORDINATES DECOUPLED CONTROL OF ROBOTS IN TERMS OF QUASI

In this paper we address two prolblems. One is to find the configuration- independent ,,critical parameter" for the articulated body inertia. We analyze the articulated body inertia matrix which appears in discrete Riccati equation. It depends o:n kinematical parameters of the robot and on the inertial param.eters of each link. Due to the dependence of the articulated body inertia on the kinematic parameters a standard Discrete Fourier Transform (13FT) is proposed to identify these parameters. Several examples show that this technique can be successfully applied to articulated inertia parameters. The remaining part of the paper is devoted to adaptive clontrol algorithms for robots whose dynamics is describsed by making use of quasi-coordinates. Two set point control algorithms are presented and illustrated by simulation results.
Raspberry Pimu: Raspberry Pi Based Inertial Sensor Data Processing System

This paper explains the architectural design and development of an application for the reception, visualization and storage of inertial sensor data provided by an inertial measurement system (IMU). The application is built to run in a Raspberry Pi equipped with a small size screen that allows the visualization of the data and the control of data recording. The IMU is connected to a Raspberry Pi through a serial port (USB-TTY).
A MM-WAVE INTERFEROMETER FOR STUDIES OF THE COSMIC MICROWAVE BACKGROUND ANISOTROPY

The small angular scale, or high `, component of the Cosmic Microwave Background anisotropy spectrum contains cosmological information about the early universe. In particular, the angular power spectrum above ` ∼ 600 should be damped due to photon diffusion between hot and cold regions and due to averaging along the line of sight. Fluctuations and damping at these scales have already been discovered at 30 GHz. At these frequencies, however, contamination from point sources can interfere with interpretation of these results. This work describes the design, construction, and performance of a 150 GHz, four-element interferometer built specifically to probe ` > 1000 at frequencies where minimum point source contamination is expected. A new microwave channelizer and fully digital correlator are discussed in detail, and the performance during the first season of observation at a high Chilean site is examined. Advisor: Professor Lyman Page Jr.
Place recognition for mobile robot in changing environments

This thesis is concerned with the problem of place recognition for a mobile robot using an omnidirectional camera as its sole sensor modality. The problems we are faced with range from orientation estimation to loop closure detection, in the absence of any prior knowledge of position. In order to resolve the challenging issues encountered by any appearancebased place recognition system specifically, perceptual aliasing and variability we first develop a quadtree-based image comparison method. In contrast to most existing methods, this method does not involve the computationally expensive step of feature or keypoint detection and description, which utilises the spatial structure property of an image to provide robustness against dynamic changes in scenes. Our algorithm is experimentally evaluated on one public dataset, and two datasets collected by ourselves in different environments, thereby demonstrating its effectiveness in handling perceptual aliasing and environment variability. For many tasks in mobile robotics, it is crucial accurately to determine the orientation of the robot, relying on a single vision sensor. For this purpose, we propose an evaluation methodology that focuses on the ability of different image-based algorithms to establish the heading of the robot when capturing two images. Critical analysis of performance is also provided. In addition, a quadtree-based loop closure detection method is proposed, with the intention of increasing the number of correctly-recognized revisited locations (high recall) at low false positives (high precision). The loop closure detection is performed by pairwise image comparison. The performance of the proposed method is evaluated using our collected dataset, which contains highly aliased images and drastic perceptual changes. The experimental results show that our method can achieve a high recall at 100% precision, and outperform other related algorithms in term of closeness to ground truth.
A New Form of Boussinesq Equation with Improved Linear Dispersion Characteristics

It has been shown that Boussinesq type equations, which include the lowest order effects of nonlinearity and frequency dispersion, can provide an accurate description of wave evolution in coastal regions. But different linear dispersion characteristics of the equation can be obtained by different integrating method. In this paper, a new form of the Boussinesq equation is derived by use of two different layer horizontal velocity variables instead of the commonly used depth-averaged velocity or an arbitrary layer velocity. This significantly improves the linear dispersion properties of the Boussinesq equation and enables it to be applied to a wider range of water depth.
Image restoration algorithms based on singular value decomposition of 3-D optical sectioning microscopy

The paper discusses the basic theory of optical sectioning microscopy, and also analyzes the ill posed problem caused by the degradation in fluorescence images resulting from the singularity of point spread function circular matrix of the microscope system. By applying the singular value decomposition, the bigger eigenvalues are selected and the ill posed problem is solved. With the fast Fourier transform, this problem is transformed from space to frequency domain, which simplifies the computation process. Finally, a good result is achieved.
Efficient color histogram indexing

In image retrieval based on color, the weighted distance between color histograms of two images, represented as a quadratic form, may be defined as a match measure. However, this distance measure is computationally expensive (naively O(N/sup 2/) and at best O(N) in the number N of histogram bins) and it operates on high dimensional features (O(N)). We propose the use of low-dimensional, simple to compute distance measures between the color distributions, and show that these are lower bounds on the histogram distance measure. Results on color histogram matching in large image databases show that pre-filtering with the simpler distance measures leads to significantly less time complexity because the quadratic histogram distance is now computed on a smaller set of images. The low-dimensional distance measure can also be used for indexing into the database. <<ETX>>
Development of General Rules for Matching Multi-scale Area Objects

Object matching plays a key role in data integration and updating between multi-scale maps.It is implemented based on the similarity of geometry,topology and semantic between multi-scale objects.There are six matching modes between area objects from larger-scale to smaller-scale maps,namely 1∶0,1∶1,0∶1,1∶M,N∶1 and N∶M.Therefore,taking residential data as example,a common geometric matching method is proposed for multi-scale vector area objects.This method constructs candidate matching set by taking all larger-scale area objects into account,which have an intersection with the minimum bounding rectangle(MBR) of a smaller-scale area object.By analyzing the characteristics of all matching modes,the corresponding rules are made to identify six matching modes mentioned above from each other.The experimental results show that these rules work properly.
LAMBDA METHOD FOR RIGID BODY ATTITUDE DETERMINATION BASED ON GPS

The rigid body's attitude determination is discussed using two baselines based on GPS; baseline vector coordinates are calculated with GPS carrier phase interference, and integer ambiguities are calculated with LAMBDA method. CPU time figure shows that this method calculates integer ambiguities quickly and correctly, which has good application value for real time attitude determination systems.
A Controllable Untethered Vehicle Driven by Electrically Actuated Liquid Metal Droplets

Liquid metal is an interesting metallic material with many unique properties that can be applied in many applications. Liquid metal droplets can be activated by an external electrical field in aqueous environments, which has led to the development of novel actuators. However, a study on the development and control of liquid metal actuating robots is still absent, which hinders their further applications. In this paper, we report the development of a novel controllable untethered vehicle driven by electrically actuated liquid metal droplets in a sodium hydroxide solution. The simplified dynamic model of the vehicle in sodium hydroxide solution was developed. The vehicle's performance, including translational and rotating locomotion with various speeds, was experimentally evaluated. The vehicle driven by liquid metal droplets possesses many advantages such as working silently, almost wear-free motion, and low power consumed, which has great potential to be applied in liquid metal enabled robotics and automation process such as laboratory automation.
Utility Enhancement of Deficient Relational Recordset Anonymization

Increase in the use of digital platforms generate a very huge amount of user data which on processing reveals more valuable information about users while mining or it may also reveal some future events. Privacy preserving data mining (PPDM) is the current developing area of research that precisely ensures a certain level of privacy by increasing the utility of information. Data Anonymization is a PPDM technique that protects sensitive information in the recordset with high confidence. Anonymizing recordsets that consists of null values habitually referred as deficient recordsets, suffer from serious information loss owing to null value contamination. This would be arisen because of the null values present in the original recordset. In this paper, we proposed an enhanced ARX framework to anonymize the deficient recordsets through a higher level of privacy and utility. We explore the characteristics of null value contamination on generalization, driven by these characteristics, we formulate an Enhanced ARX Anonymization(K, Rn )Anonymity Model to preserve data utility on deficient recordsets. The results obtained by executing our framework over the real world dataset proved to be optimized in providing better tradeoff between utility and privacy for deficient recordsets in Cell oriented Anonymization (CoA), Attribute oriented Anonymization (AoA) and Record oriented Anonymization (RoA) than the existing procedures.
Analysis of Large Graph Partitioning and Frequent Subgraph Mining on Graph Data

Graph mining has attracted much attention due to explosive growth in generating graph databases. The graph database is one type of database that consists of either a single large graph or a number of relatively small graphs. Some applications that produce graph database are biological networks, semantic web and behavioural modelling. Frequent subgraph mining is playing an essential role in data mining, with an objective of extracting knowledge in the form of repeated structures. Many efficient subgraph mining algorithms have been discovered in the last two decades, yet most do not scale to the type of data, the so-called “Large-Scale Graph Data”. Many problems are so large or complex that it is impractical or impossible to solve them on a single computer, especially with given limited memory. Scalable parallel computing algorithms holds the key role for solving the problem in this context. Various algorithms and parallel frameworks have been discussed for graph partitioning, frequent subgraph mining based on apriori and pattern growth approaches, and large-scale graph processing techniques. The central objective of this paper is to initiate research and development of identifying frequent subgraph mining and strategies for graph data centres in such a way that brings it parallel frameworks for achieving memory scalability, partitioning, load balancing, granularity, and technical enhancement for future generations. Keywords: graph partitioning; frequent subgraph mining; apriori; pattern growth; parallel framework.
ROI Coding Research Based on Residual Image

Unlike MAXSHIFT algorithm of JPEG2000,by combining coding and embedded zerotree wavelet(EZW),a novel regions of interest(ROI) algorithm based on residue image called RZ was presented in this paper.The RZ algorithm is based on integer wavelet transform(IWT). The residue image of ROI based on high compressionm ratio EZW is coded by embedded zerotree coding based on integer square quantization threshold.The entropy coding was given to the residue data and the result was transmitted after original coding data.This algorithm can realize the lossless or near lossless ROI coding.The experiment results demonstrate RZ algorithm realizes ROI coding of low complication based on EZW framework and is applied to image transmission based on net.
Design of a cheap compact low-pass filter with wide stopband

In these work, a cheap and compact Low-Pass filter (LPF) with wide stopband is designed using modified hair-pin resonator. The first transmission zero is obtained from the transfer function (TF) analysis of the hair-pin resonator. Further, open stubs are added to widen the stopband. An approximate LC equivalent circuit of the proposed structure is derived and the response is in accord with simulated result. A prototype of the proposed LPF is fabricated on FR4 substrate. The proposed LPF has -3 dB cut-off frequency at 1.1 GHz with wide stopband ranging from 1.6 GHz to 11.5 GHz. The size occupied by the proposed LPF is 15.8 mm x 14.3 mm. In the passband region, the insertion loss is -0.3 dB and return loss is better than -25 dB. The proposed LPF is measured and there is a good agreement between the simulated and measured results.
Fuzzy clustering hierarchy arithmetic based on residual energy prediction for WSN

In order to reduce the energy consumption and prolong the network lifetime of Wireless Sensor Networks(WSNs), a fuzzy clustering hierarchy arithmetic based on residual energy prediction for WSNs is proposed. The new algorithm estimates required energy consumption that the candidate nodes forward their data packets to base station according to the distance between nodes and the base station and the number of neighbors, and then obtains the expected residual energy of nodes. Cluster-heads are elected on the basis of the competition radius that can be computed through fuzzy theory based on the consideration of the original energy and the remaining energy of the candidate nodes, to build clusters of uneven size. Simulation experiments show that compared with other routing algorithms, this arithmetic can better optimize the structure of the cluster, balance energy consumption, and prolong the life cycle of the network.
Projected fringe profilometry for profile measurement of high reflective surface

An improved non-contact optical measuring method,projected fringe profilometry,is proposed to realize the 3-D structure measurement of high reflective surfaces.The reflection characteristics of high reflective surfaces and their effects on phase computation are analyzed,and it is pointed out that the failure reason of the traditional projected fringe profilometry is the mismatch of the range of reflection intensity with the dynamic range of the measuring camera.Then,the techniques of lightdark fringe projection,multi-exposure time image acquisition and image synthesis are introduced to match the measuring range of intensity of camera with the range of reflection intensity.The feasibility and useable range of the method are analyzed.Finally,the processes of fringe projection and image acquisition in the improved profilometry are given.Experimental results indicate that the improved profilometry is able to handle the problems of fringe image saturation and dark images.Moreover,it has obtained 3-D data cloud more than 99.6%,and solve the problem of loss of 3-D data.In conclusions,the improved methodcan measure the 3-D profiles of high reflective surfaces with non-contact methods.