Shangping Ren

Shiyi Luo, Mingshuo Liu, Yifeng Yu et al.

In the field of model compression, choosing an appropriate rank for tensor decomposition is pivotal for balancing model compression rate and efficiency. However, this selection, whether done manually or through optimization-based automatic methods, often increases computational complexity. Manual rank selection lacks efficiency and scalability, often requiring extensive trial-and-error, while optimization-based automatic methods significantly increase the computational burden. To address this, we introduce a novel, automatic, and budget-aware rank selection method for efficient model compression, which employs Layer-Wise Imprinting Quantitation (LWIQ). LWIQ quantifies each layer's significance within a neural network by integrating a proxy classifier. This classifier assesses the layer's impact on overall model performance, allowing for a more informed adjustment of tensor rank. Furthermore, our approach includes a scaling factor to cater to varying computational budget constraints. This budget awareness eliminates the need for repetitive rank recalculations for different budget scenarios. Experimental results on the CIFAR-10 dataset show that our LWIQ improved by 63.2% in rank search efficiency, and the accuracy only dropped by 0.86% with 3.2x less model size on the ResNet-56 model as compared to the state-of-the-art proxy-based automatic tensor rank selection method.

Chunhui Guo, Zhicheng Fu, Zhenyu Zhang et al.

Improving the effectiveness and safety of patient care is the ultimate objective for medical cyber-physical systems. Many medical best practice guidelines exist, but most of the existing guidelines in handbooks are difficult for medical staff to remember and apply clinically. Furthermore, although the guidelines have gone through clinical validations, validations by medical professionals alone do not provide guarantees for the safety of medical cyber-physical systems. Hence, formal verification is also needed. The paper presents the formal semantics for a framework that we developed to support the development of verifiably safe medical guidelines. The framework allows computer scientists to work together with medical professionals to transform medical best practice guidelines into executable statechart models, Yakindu in particular, so that medical functionalities and properties can be quickly prototyped and validated. Existing formal verification technologies, UPPAAL timed automata in particular, is integrated into the framework to provide formal verification capabilities to verify safety properties. However, some components used/built into the framework, such as the open-source Yakindu statecharts as well as the transformation rules from statecharts to timed automata, do not have built-in semantics. The ambiguity becomes unavoidable unless formal semantics is defined for the framework, which is what the paper is to present.

Chunhui Guo, Zhicheng Fu, Zhenyu Zhang et al.

Improving effectiveness and safety of patient care is an ultimate objective for medical cyber-physical systems. A recent study shows that the patients' death rate can be reduced by computerizing medical guidelines. Most existing medical guideline models are validated and/or verified based on the assumption that all necessary medical resources needed for a patient care are always available. However, the reality is that some medical resources, such as special medical equipment or medical specialists, can be temporarily unavailable for an individual patient. In such cases, safety properties validated and/or verified in existing medical guideline models without considering medical resource availability may not hold any more. The paper argues that considering medical resource availability is essential in building verifiably correct executable medical guidelines. We present an approach to explicitly and separately model medical resource availability and automatically integrate resource availability models into an existing statechart-based computerized medical guideline model. This approach requires minimal change in existing medical guideline models to take into consideration of medical resource availability in validating and verifying medical guideline models. A simplified stroke scenario is used as a case study to investigate the effectiveness and validity of our approach.

Chunhui Guo, Zhicheng Fu, Zhenyu Zhang et al.

Improving patient care safety is an ultimate objective for medical cyber-physical systems. A recent study shows that the patients' death rate is significantly reduced by computerizing medical best practice guidelines. Recent data also show that some morbidity and mortality in emergency care are directly caused by delayed or interrupted treatment due to lack of medical resources. However, medical guidelines usually do not provide guidance on medical resource demands and how to manage potential unexpected delays in resource availability. If medical resources are temporarily unavailable, safety properties in existing executable medical guideline models may fail which may cause increased risk to patients under care. The paper presents a separately model and jointly verify (SMJV) architecture to separately model medical resource available times and relationships and jointly verify safety properties of existing medical best practice guideline models with resource models being integrated in. The SMJV architecture allows medical staff to effectively manage medical resource demands and unexpected resource availability delays during emergency care. The separated modeling approach also allows different domain professionals to make independent model modifications, facilitates the management of frequent resource availability changes, and enables resource statechart reuse in multiple medical guideline models. A simplified stroke scenario is used as a case study to investigate the effectiveness and validity of the SMJV architecture. The case study indicates that the SMJV architecture is able to identify unsafe properties caused by unexpected resource delays.

Chunhui Guo, Hao Wu, Xiayu Hua et al.

Reliability, longevity, availability, and deadline guarantees are the four most important metrics to measure the QoS of long-running safety-critical real-time applications. Software aging is one of the major factors that impact the safety of long-running real-time applications as the degraded performance and increased failure rate caused by software aging can lead to deadline missing and catastrophic consequences. Software rejuvenation is one of the most commonly used approaches to handle issues caused by software aging. In this paper, we study the optimal time when software rejuvenation shall take place so that the system's reliability, longevity, and availability are maximized, and application delays caused by software rejuvenation is minimized. In particular, we formally analyze the relationships between software rejuvenation frequency and system reliability, longevity, and availability. Based on the theoretic analysis, we develop approaches to maximizing system reliability, longevity, and availability, and use simulation to evaluate the developed approaches. In addition, we design the MIN-DELAY semi-priority-driven scheduling algorithm to minimize application delays caused by rejuvenation processes. The simulation experiments show that the developed semi-priority-driven scheduling algorithm reduces application delays by 9.01% and 14.24% over the earliest deadline first (EDF) and least release time (LRT) scheduling algorithms, respectively.

Chunhui Guo, Zhicheng Fu, Zhenyu Zhang et al.

Improving patient care safety is an ultimate objective for medical cyber-physical systems. A recent study shows that the patients' death rate can be significantly reduced by computerizing medical best practice guidelines. To facilitate the development of computerized medical best practice guidelines, statecharts are often used as a modeling tool because of their high resemblances to disease and treatment models and their capabilities to provide rapid prototyping and simulation for clinical validations. However, some implementations of statecharts, such as Yakindu statecharts, are priority-based and have synchronous execution semantics which makes it difficult to model certain functionalities that are essential in modeling medical guidelines, such as two-way communications and configurable execution orders. Rather than introducing new statechart elements or changing the statechart implementation's underline semantics, we use existing basic statechart elements to design model patterns for the commonly occurring issues. In particular, we show the design of model patterns for two-way communications and configurable execution orders and formally prove the correctness of these model patterns. We further use a simplified airway laser surgery scenario as a case study to demonstrate how the developed model patterns address the two-way communication and configurable execution order issues and their impact on validation and verification of medical safety properties.