Connecting border collision with saddle-node bifurcation in switched dynamical systems

Author name used in this publication: Chi K. Tse2005-2006 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe

Bioimpedance Sensing and Ablation Needles for Image-Guided Therapy

Sensing and ablation needles and catheter instruments combined with multimodal imaging, navigation and AI-assisted diagnosis have been increasingly utilised by interventional radiologists for image-guided therapy, emerging as an innovative tool for both diagnosis and treatment. This paper reviews the significant advancements in the field over the past decade, focusing on the development and refinement of both bioimpedance sensing needles and thermal ablation needles. Bioimpedance sensing needles differentiate pathological tissues by measuring impedance variations in biological tissues, offering a less invasive diagnostic approach. Thermal ablation needles, on the other hand, employ Radio Frequency (RF) techniques or Electrolytic Ablation (EA) to effectively target and treat lesions. This review covers the evolution of these needles, including advancements in materials, novel sensor technologies, impedance analysis methods, ablation catheter powering techniques, and needle design. It also provides insights into the needle structure, fabrication methods, and testing outcomes of these advanced sensing and ablation needles. Additionally, the paper presents an analysis of bioimpedance data across various pathological tissues and discusses innovative impedance analysis methodologies. The review concludes by presenting the current challenges in the field and discussing directions for future research, thereby providing an overview of the state-of-the-art in electronic technology for medical diagnosis and treatment needles

Resonant critical coupling of surface lattice resonances with fluorescent absorptive thin film

Surface lattice resonance supported on nanoparticle arrays is a promising candidate in enhancing fluorescent effects in both absorption and emission. The optical enhancement provided by surface lattice resonance is primarily through the light confinement beyond the diffraction limit, where the nanoparticle arrays can enhance light-matter interaction for increased absorption as well as providing more local density of states for enhanced spontaneous emission. In this work, we optimize the in-coupling efficiency to the fluorescent molecules by finding the conditions to maximize the absorption, also known as the critical coupling condition. We studied the transmission characteristics and the fluorescent emission of a $TiO_2$ nanoparticle array embedded in an index-matching layer with fluorescent dye at various concentrations. A modified coupled-mode theory that describes the nanoparticle array was then derived and verified by numerical simulations. With the analytical model, we analyzed the experimental measurements and discovered the condition to critically couple light into the fluorescent dye, which is demonstrated as the strongest emission. This study presents a useful guide for designing efficient energy transfer from excitation beam to the emitters, which maximizes the external conversion efficiency.Comment: 26 pages, 10 figure

Towards the Application of Classification Techniques to Test and Identify Faults in Multimedia Systems

The advances in computer and graphic technologies have led to the popular use of multimedia for information exchange. However, multimedia systems are difficult to test. A major reason is that these systems generally exhibit fuzziness in their temporal behaviors. The fuzziness may be caused by the existence of non-deterministic factors in their runtime environments, such as system load and network traffic. It complicates the analysis of test results. The problem is aggravated when a test involves the synchronization of different multimedia streams as well as variations in system loading.\ud \ud In this paper, we conduct an empirical study on the testing and fault-identification of multimedia systems by treating the issue as a classification problem. Typical classification techniques, including Bayesian networks, k-nearest neighbor, and neural networks, are experimented with the use of X-Smiles, an open sourced multimedia authoring tool supporting the Synchronized Multimedia Integration Language (SMIL). From these experiments, we make a few interesting observations and give plausible explanations based on the geometrical properties of the test results

Rate- and State-Dependent Friction Law and Statistical Properties of Earthquakes

In order to clarify how the statistical properties of earthquakes depend on the constitutive law characterizing the stick-slip dynamics, we make an extensive numerical simulation of the one-dimensional spring-block model with the rate- and state-dependent friction law. Both the magnitude distribution and the recurrence-time distribution are studied with varying the constitutive parameters characterizing the model. While a continuous spectrum of seismic events from smaller to larger magnitudes is obtained, earthquakes described by this model turn out to possess pronounced ``characteristic'' features.Comment: Minor revisions are made in the text and in the figures. Accepted for publication in Europhys. Letter

Veni Vidi Dixi: Reliable Wireless Communication with Depth Images

The upcoming industrial revolution requires deployment of critical wireless sensor networks for automation and monitoring purposes. However, the reliability of the wireless communication is rendered unpredictable by mobile elements in the communication environment such as humans or mobile robots which lead to dynamically changing radio environments. Changes in the wireless channel can be monitored with frequent pilot transmission. However, that would stress the battery life of sensors. In this work a new wireless channel estimation technique, Veni Vidi Dixi, VVD, is proposed. VVD leverages the redundant information in depth images obtained from the surveillance cameras in the communication environment and utilizes Convolutional Neural Networks CNNs to map the depth images of the communication environment to complex wireless channel estimations. VVD increases the wireless communication reliability without the need for frequent pilot transmission and with no additional complexity on the receiver. The proposed method is tested by conducting measurements in an indoor environment with a single mobile human. Up to authors best knowledge our work is the first to obtain complex wireless channel estimation from only depth images without any pilot transmission. The collected wireless trace, depth images and codes are publicly available.Comment: Accepted for publication in CoNext 2019 with reproducibility badges. The measurements and the processing codes are available at https://gitlab.lrz.de/lkn_measurements/vvd_measurements for your evaluatio

Utility of CD123 immunohistochemistry in differentiating lupus erythematosus from cutaneous T cell lymphoma

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/149293/1/his13817_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/149293/2/his13817.pd