Strategy Selection for Product Service Systems Using Case-based Reasoning

A product service system integrates products and services in order to lower environmental impact. It can achieve good eco-efficiency and has received increase in the last decade. This study focuses on strategy selection for product service system design. Case-based reasoning is utilized to provide suggestions for finding an appropriate strategy. To build a case database, successful PSS cases from the literature and websites were collected and formulated. Twelve indices under three categories were analyzed and selected to describe cases. A lot of successful PSS cases and their information were collected. Forty seven cases were used in this study because of the completeness of information. The analytic hierarchic process is used to find the relative weights of the factors that relate to the selection of customers. These weights are used in calculating the similarity in the case-based reasoning process. The successful strategy of the most similar case is extracted and recommended for PSS strategy determination. More than 90% of tested cases obtained an appropriate strategy from the most similar case. Finally, two new products are introduced to find the best strategy for product service system design and development using the proposed case-based reasoning system

Improving Axial Resolution of Optical Resolution Photoacoustic Microscopy with Advanced Frequency Domain Eigenspace Based Minimum Variance Beamforming Method

Optical resolution photoacoustic microscopy (OR-PAM) leverages optical focusing and acoustic detection for microscopic optical absorption imaging. Intrinsically it owns high optical lateral resolution and poor acoustic axial resolution. Such anisometric resolution hinders good 3-D visualization; thus 2-D maximum amplitude projection images are commonly presented in the literature. Since its axial resolution is limited by the bandwidth of acoustic detectors, ultrahigh frequency, and wideband detectors with Wiener deconvolution have been proposed to address this issue. Nonetheless, they also introduce other issues such as severe high-frequency attenuation and limited imaging depth. In this work, we view axial resolution improvement as an axial signal reconstruction problem, and the axial resolution degradation is caused by axial sidelobe interference. We propose an advanced frequency-domain eigenspace-based minimum variance (F-EIBMV) beamforming technique to suppress axial sidelobe interference and noises. This method can simultaneously enhance the axial resolution and contrast of OR-PAM. For a 25-MHz OR-PAM system, the full-width at half-maximum of an axial point spread function decreased significantly from 69.3 $\mu$m to 16.89 $\mu$m, indicating a significant improvement in axial resolution

Copy-Paste Image Augmentation with Poisson Image Editing for Ultrasound Instance Segmentation Learning

Deep learning has shown great success in high-level image analysis problems; yet its efficacy relies on the quality and diversity of the training data. In this work, we introduce a copypaste image augmentation for ultrasound images. The Poisson image editing technique is used to generate realistic and seamless boundary transitions around the pasted image. Results showed that the proposed image augmentation technique improves training performance in terms of higher objective metrics and more stable training results

Computer and biological experiments: Modeling, estimation, and uncertainty quantification

Statistical experimental analysis is an indispensable tool in engineering, science, bio-medicine, and technology innovation. There are generally two types of experiments: computer and physical experiments. Computer experiments are simulations using complex mathematical models and numerical tools, while physical experiments are actual experiments performed in a laboratory or observed in the field. Analyzing these experiments helps us understand real-world phenomena and motivates interesting statistical questions and challenges. This thesis presents new methodologies for applications in computer experiments and biomedical studies. In Chapters 1 and 2, we show that the concept of using transformation for improving the additivity of a target function is beneficial in computer experiments and big data modeling. In Chapter 3, motivated by a biological experiment, we propose a new method for quantifying uncertainty in biology studies. Chapter 4 addresses the problem of identifying an optimal computer simulator for the observed physical experiments.Ph.D

Identifiability of the Simplex Volume Minimization Criterion for Blind Hyperspectral Unmixing: The No Pure-Pixel Case

In blind hyperspectral unmixing (HU), the pure-pixel assumption is well-known to be powerful in enabling simple and effective blind HU solutions. However, the pure-pixel assumption is not always satisfied in an exact sense, especially for scenarios where pixels are heavily mixed. In the no pure-pixel case, a good blind HU approach to consider is the minimum volume enclosing simplex (MVES). Empirical experience has suggested that MVES algorithms can perform well without pure pixels, although it was not totally clear why this is true from a theoretical viewpoint. This paper aims to address the latter issue. We develop an analysis framework wherein the perfect endmember identifiability of MVES is studied under the noiseless case. We prove that MVES is indeed robust against lack of pure pixels, as long as the pixels do not get too heavily mixed and too asymmetrically spread. The theoretical results are verified by numerical simulations

Lymphangiomatous macroglossia associated with extensive cervicomediastinal cystic hygromas

AbstractChildren with lymphangiomatous macroglossia often have difficulty eating and talking, and their airways may be compromised because of bleeding and infection, especially when extensive cervicomediastinal cystic hygromas are present. We report a case of lymphangiomatous macroglossia associated with extensive cystic hygromas in the cervicomediastinal region. The 3-year-old girl was treated with anterior wedge reduction of the tongue, needle aspiration of the cervicomediastinal cystic hygromas, and systemic steroids and antibiotics. The extensive cystic cervicomediastinal hygromas spontaneously regressed, and further surgery was not needed until 4 years later. Surprisingly, subtotal or partial lymphatic malformation removal improved the complicated lymphatic malformation

Novel CMOS RFIC Layout Generation with Concurrent Device Placement and Fixed-Length Microstrip Routing

With advancing process technologies and booming IoT markets, millimeter-wave CMOS RFICs have been widely developed in re- cent years. Since the performance of CMOS RFICs is very sensi- tive to the precision of the layout, precise placement of devices and precisely matched microstrip lengths to given values have been a labor-intensive and time-consuming task, and thus become a major bottleneck for time to market. This paper introduces a progressive integer-linear-programming-based method to gener- ate high-quality RFIC layouts satisfying very stringent routing requirements of microstrip lines, including spacing/non-crossing rules, precise length, and bend number minimization, within a given layout area. The resulting RFIC layouts excel in both per- formance and area with much fewer bends compared with the simulation-tuning based manual layout, while the layout gener- ation time is significantly reduced from weeks to half an hour.Comment: ACM/IEEE Design Automation Conference (DAC), 201