An Algorithmic Framework for Efficient Large-Scale Circuit Simulation Using Exponential Integrators

We propose an efficient algorithmic framework for time domain circuit simulation using exponential integrator. This work addresses several critical issues exposed by previous matrix exponential based circuit simulation research, and makes it capable of simulating stiff nonlinear circuit system at a large scale. In this framework, the system's nonlinearity is treated with exponential Rosenbrock-Euler formulation. The matrix exponential and vector product is computed using invert Krylov subspace method. Our proposed method has several distinguished advantages over conventional formulations (e.g., the well-known backward Euler with Newton-Raphson method). The matrix factorization is performed only for the conductance/resistance matrix G, without being performed for the combinations of the capacitance/inductance matrix C and matrix G, which are used in traditional implicit formulations. Furthermore, due to the explicit nature of our formulation, we do not need to repeat LU decompositions when adjusting the length of time steps for error controls. Our algorithm is better suited to solving tightly coupled post-layout circuits in the pursuit for full-chip simulation. Our experimental results validate the advantages of our framework.Comment: 6 pages; ACM/IEEE DAC 201

Multi-Label Zero-Shot Learning with Structured Knowledge Graphs

In this paper, we propose a novel deep learning architecture for multi-label zero-shot learning (ML-ZSL), which is able to predict multiple unseen class labels for each input instance. Inspired by the way humans utilize semantic knowledge between objects of interests, we propose a framework that incorporates knowledge graphs for describing the relationships between multiple labels. Our model learns an information propagation mechanism from the semantic label space, which can be applied to model the interdependencies between seen and unseen class labels. With such investigation of structured knowledge graphs for visual reasoning, we show that our model can be applied for solving multi-label classification and ML-ZSL tasks. Compared to state-of-the-art approaches, comparable or improved performances can be achieved by our method.Comment: CVPR 201

Pilots’ visual scan pattern and situation awareness in flight operations

Introduction: Situation awareness (SA) is considered an essential prerequisite for safe flying. If the impact of visual scanning patterns on a pilot’s situation awareness could be identified in flight operations, then eye-tracking tools could be integrated with flight simulators to improve training efficiency. Method: Participating in this research were 18 qualified, mission-ready fighter pilots. The equipment included high-fidelity and fixed-base type flight simulators and mobile head-mounted eye-tracking devices to record a subject’s eye movements and SA while performing air-to-surface tasks. Results: There were significant differences in pilots’ percentage of fixation in three operating phases: preparation (M = 46.09, SD = 14.79), aiming (M = 24.24, SD = 11.03), and release and break-away (M = 33.98, SD = 14.46). Also, there were significant differences in pilots’ pupil sizes, which were largest in the aiming phase (M = 27,621, SD = 6390.8), followed by release and break-away (M = 27,173, SD = 5830.46), then preparation (M = 25,710, SD = 6078.79), which was the smallest. Furthermore, pilots with better SA performance showed lower perceived workload (M = 30.60, SD = 17.86), and pilots with poor SA performance showed higher perceived workload (M = 60.77, SD = 12.72). Pilots’ percentage of fixation and average fixation duration among five different areas of interest showed significant differences as well. Discussion: Eye-tracking devices can aid in capturing pilots’ visual scan patterns and SA performance, unlike traditional flight simulators. Therefore, integrating eye-tracking devices into the simulator may be a useful method for promoting SA training in flight operations, and can provide in-depth understanding of the mechanism of visual scan patterns and information processing to improve training effectiveness in aviation

Promoting consumers’ online brand attention: The study of spatiotemporal analysis in regional apples

With the application and promotion of agricultural products e-commerce, it is of great significance to increase the popularity of brand recognition to promote the market value of agricultural products. Online attention is an important form of regional brand awareness of agricultural products on the Internet. Taking the apple industry as an example, this paper uses 6 years of data from the Baidu search index to analyze the spatiotemporal characteristics of apple brands in China. The study has demonstrated a way to analyze online brand attention and its relationship with regional brands. Further studies are to be made in more detailed attributes associated with the forming of attention to enhance the online brand attention and promote agricultural products

Best Practices in Managing Social Media for Business

The mixed results of social media impacting on businesses have motivated this research to understand the best practices affecting the brand equity of a company utilizing the social media in business. Literature review of relevant theories is conducted. The industry publications of companies doing well in social media are analyzed to distill the best practices implemented in their social media strategies. Multiple case studies are proposed to determine how these best practices explain the desired business outcome in brand equity. The social media strategy concepts, media richness theory and Hagel III and Armstrong’s framework of virtual member development are suggested in guiding our data collection, analysis and interpretation. This research in progress is expected to contribute to the existing knowledge by providing a prescriptive framework of best practices in utilizing Facebook social network, and integrating and extending existing theories to explain the use of social media for developing brand equity

Pilots’ visual scan pattern and attention distribution during the pursuit of a dynamic target

Introduction: The current research is investigating pilots’ visual scan patterns in order to assess attention distribution during air-to-air manoeuvers. Method: A total of thirty qualified mission-ready fighter pilots participated in this research. Eye movement data were collected by a portable head-mounted eye-tracking device, combined with a jet fighter simulator. To complete the task, pilots have to search for, pursue, and lock-on a moving target whilst performing air-to-air tasks. Results: There were significant differences in pilots’ saccade duration (msec) in three operating phases including searching (M=241, SD=332), pursuing (M=311, SD=392), and lock-on (M=191, SD=226). Also, there were significant differences in pilots’ pupil sizes (pixel2) of which lock-on phase was the largest (M=27237, SD=6457), followed by pursuing (M=26232, SD=6070), then searching (M=25858, SD=6137). Furthermore, there were significant differences between expert and novice pilots on the percentage of fixation on the HUD, time spent looking outside the cockpit, and the performance of situational awareness (SA). Discussion: Experienced pilots have better SA performance and paid more attention to the HUD but focused less outside the cockpit when compared with novice pilots. Furthermore, pilots with better SA performance exhibited a smaller pupil size during the operational phase of lock-on whilst pursuing a dynamic target. Understanding pilots’ visual scan patterns and attention distribution are beneficial to the design of interface displays in the cockpit and in developing human factors training syllabi to improve safety of flight operations