Algorithms on determining the correlation laws between ultrasonic images and quality of spot welds.

Conventional quality control devices for spot welding cannot perform on-line inspection and provide feedback to the welding control system. In this way, the traditional quality control systems are similar to statistical welding parameters monitoring systems. It is imperative to combine the idea of on-line quality inspection with closed-loop feedback control in a robust control system. However, there is no single acoustic method to date capable of manipulating real-time control and on-line quality inspection, concurrently, since specific procedures (e.g. scanning time and adjustment time) need to be adopted by traditional acoustic microscopes to retrieve proper information, and these procedures tend to disable the real-time and on-line capability of acoustic microscopy. With recent hardware improvements, the novel portable acoustic device is able to reduce the scanning time to real-time fashion without losing any significant data. On the other hand, the adjustment time of the portable acoustic device can be reduced noticeably by employing intelligent control software instead of human operators. This new hardware-software configuration will be an ideal approach to the on-line, real-time nondestructive inspection of spot welds. The primary goal of this research is to develop an intelligent system to accomplish the on-line, real-time nondestructive inspection for spot welds. The following objectives were fulfilled to reach the final goal. (1) Classification of the acoustic images of spot welds. (2) Quantification of acoustic information as parameters. (3) The study of the influence of each parameter on the strength of spot welds. (4) Identification of important and significant parameters. (5) Integration of these parameters into the knowledge base of the software. The system developed can be an on-line advisor that is capable of providing critical information about the quality of spot welds during the process. Furthermore, this system is able to render warning signals to the process control unit to prevent further mistakes.Dept. of Industrial and Manufacturing Systems Engineering. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis1999 .L33. Source: Dissertation Abstracts International, Volume: 66-02, Section: B, page: 1132. Advisers: Roman Maev; Michael Wang. Thesis (Ph.D.)--University of Windsor (Canada), 1999

Melatonin Therapy Prevents Programmed Hypertension and Nitric Oxide Deficiency in Offspring Exposed to Maternal Caloric Restriction

Nitric oxide (NO) deficiency is involved in the development of hypertension, a condition that can originate early in life. We examined whether NO deficiency contributed to programmed hypertension in offspring from mothers with calorie-restricted diets and whether melatonin therapy prevented this process. We examined 3-month-old male rat offspring from four maternal groups: untreated controls, 50% calorie-restricted (CR) rats, controls treated with melatonin (0.01% in drinking water), and CR rats treated with melatonin (CR + M). The effect of melatonin on nephrogenesis was analyzed using next-generation sequencing. The CR group developed hypertension associated with elevated plasma asymmetric dimethylarginine (ADMA, a nitric oxide synthase inhibitor), decreased L-arginine, decreased L-arginine-to-ADMA ratio (AAR), and decreased renal NO production. Maternal melatonin treatment prevented these effects. Melatonin prevented CR-induced renin and prorenin receptor expression. Renal angiotensin-converting enzyme 2 protein levels in the M and CR + M groups were also significantly increased by melatonin therapy. Maternal melatonin therapy had long-term epigenetic effects on global gene expression in the kidneys of offspring. Conclusively, we attributed these protective effects of melatonin on CR-induced programmed hypertension to the reduction of plasma ADMA, restoration of plasma AAR, increase of renal NO level, alteration of renin-angiotensin system, and epigenetic changes in numerous genes

Model Extraction Attack against Self-supervised Speech Models

Self-supervised learning (SSL) speech models generate meaningful representations of given clips and achieve incredible performance across various downstream tasks. Model extraction attack (MEA) often refers to an adversary stealing the functionality of the victim model with only query access. In this work, we study the MEA problem against SSL speech model with a small number of queries. We propose a two-stage framework to extract the model. In the first stage, SSL is conducted on the large-scale unlabeled corpus to pre-train a small speech model. Secondly, we actively sample a small portion of clips from the unlabeled corpus and query the target model with these clips to acquire their representations as labels for the small model's second-stage training. Experiment results show that our sampling methods can effectively extract the target model without knowing any information about its model architecture

CFVS: Coarse-to-Fine Visual Servoing for 6-DoF Object-Agnostic Peg-In-Hole Assembly

Robotic peg-in-hole assembly remains a challenging task due to its high accuracy demand. Previous work tends to simplify the problem by restricting the degree of freedom of the end-effector, or limiting the distance between the target and the initial pose position, which prevents them from being deployed in real-world manufacturing. Thus, we present a Coarse-to-Fine Visual Servoing (CFVS) peg-in-hole method, achieving 6-DoF end-effector motion control based on 3D visual feedback. CFVS can handle arbitrary tilt angles and large initial alignment errors through a fast pose estimation before refinement. Furthermore, by introducing a confidence map to ignore the irrelevant contour of objects, CFVS is robust against noise and can deal with various targets beyond training data. Extensive experiments show CFVS outperforms state-of-the-art methods and obtains 100%, 91%, and 82% average success rates in 3-DoF, 4-DoF, and 6-DoF peg-in-hole, respectively

D2ADA: Dynamic Density-aware Active Domain Adaptation for Semantic Segmentation

In the field of domain adaptation, a trade-off exists between the model performance and the number of target domain annotations. Active learning, maximizing model performance with few informative labeled data, comes in handy for such a scenario. In this work, we present D2ADA, a general active domain adaptation framework for semantic segmentation. To adapt the model to the target domain with minimum queried labels, we propose acquiring labels of the samples with high probability density in the target domain yet with low probability density in the source domain, complementary to the existing source domain labeled data. To further facilitate labeling efficiency, we design a dynamic scheduling policy to adjust the labeling budgets between domain exploration and model uncertainty over time. Extensive experiments show that our method outperforms existing active learning and domain adaptation baselines on two benchmarks, GTA5 -> Cityscapes and SYNTHIA -> Cityscapes. With less than 5% target domain annotations, our method reaches comparable results with that of full supervision.Comment: 14 pages, 5 figure

The different molecular forms of urine neutrophil gelatinase-associated lipocalin present in dogs with urinary diseases

Neutrophil gelatinase-associated lipocalin (NGAL) is a useful biomarker for the early prediction of renal diseases. NGAL may exist as monomer, dimer and/or NGAL/MMP-9 complex forms in humans. In this study, the existence of various forms of NGAL in urine (uNGAL) was determined and whether these forms are related to the different urinary diseases found in dogs is further discussed

Body-as-Subject in the Four-Hand Illusion

In a recent study (Chen et al., 2018), we conducted a series of experiments that induced the “four-hand illusion”: using a head-mounted display (HMD), the participant adopted the experimenter's first-person perspective (1PP) as if it was his/her own 1PP. The participant saw four hands via the HMD: the experimenter's two hands from the adopted 1PP and the subject's own two hands from the adopted third-person perspective (3PP). In the active four-hand condition, the participant tapped his/her index fingers, imitated by the experimenter. Once all four hands acted synchronously and received synchronous tactile stimulations at the same time, many participants felt as if they owned two more hands. In this paper, we argue that there is a philosophical implication of this novel illusion. According to Merleau-Ponty (1945/1962) and Legrand (2010), one can experience one's own body or body-part either as-object or as-subject but cannot experience it as both simultaneously, i.e., these two experiences are mutually exclusive. Call this view the Experiential Exclusion Thesis. We contend that a key component of the four-hand illusion—the subjective experience of the 1PP-hands that involved both “kinesthetic sense of movement” and “visual sense of movement” (the movement that the participant sees via the HMD)—provides an important counter-example against this thesis. We argue that it is possible for a healthy subject to experience the same body-part both as-subject and as-object simultaneously. Our goal is not to annihilate the distinction between body-as-object and body-as-subject, but to show that it is not as rigid as suggested by the phenomenologists