Embodied Conversational Agents (EGAs) are life-like computer generated characters that interact with human users in face-to-face multi-modal conversations. ECA systems are generally complex and difficult for individua...
详细信息
Wireless communications and modern machine learning techniques have jointly been applied in the recent development of vehicle health monitoring (VHM) systems. The performance of rail vehicles running on railway tracks...
详细信息
ISBN:
(纸本)9781601320728
Wireless communications and modern machine learning techniques have jointly been applied in the recent development of vehicle health monitoring (VHM) systems. The performance of rail vehicles running on railway tracks is governed by the dynamic behaviors of railway bogies especially in the cases of lateral instability and track irregularities. In this study we have proposed a system to monitor the vertical displacements of railway wagons attached to a moving locomotive. The system uses a classical linear regression machine learning technique with real wagon body acceleration data to predict vertical displacements of vehicle body motion. The system is then able to generate precautionary signals and system status which can be used by the locomotive driver for necessary actions. This VHM system provides forward-looking decisions on track maintenance that can reduce maintenance costs and inspection requirements of railway systems.
Advances in modern machine learning techniques has encouraged interest in the development of vehicle health monitoring (VHM) systems. These techniques are useful for the reduction of maintenance and inspection require...
详细信息
ISBN:
(纸本)1601320620
Advances in modern machine learning techniques has encouraged interest in the development of vehicle health monitoring (VHM) systems. These techniques are useful for the reduction of maintenance and inspection requirements of railway systems. The performance of rail vehicles running on a track is limited by the lateral instability and track irregularities of a railway wagon. In this study, a forecasting model has developed to investigate vertical acceleration behavior of railway wagons attached to a moving locomotive using different regression algorithms. Front and rear vertical acceleration conditions have predicted using ten popular learning algorithms. Different types of models can be built using a uniform platform to evaluate their performances. This study was conducted using ten different regression algorithms with five different datasets. Finally best suitable algorithm to predict vertical acceleration of railway wagons have suggested based on performance metrics of the algorithms that includes: correlation coefficient, root mean square (RMS) error and computational complexity.
There are race conditions in concurrent programs if the accesses to a sharing resource are not properly *** the races can cause the program to behave in unexpected ways,detecting them is an important aspect of debuggi...
There are race conditions in concurrent programs if the accesses to a sharing resource are not properly *** the races can cause the program to behave in unexpected ways,detecting them is an important aspect of debugging and program *** approaches have been used to detect race conditions,but there still is no effective formal model to visualize the race conditions and program *** this paper,we present a formal graph,named Race Condition Graph（RCG）,to represent race conditions in concurrent *** characteristics of RCG are presented and the potential RCG（PRCG） as well as the data structure is ***,a dining philosopher program is used as a case study.
In the design process of a reconfigurable accelerator employing in an embedded system, multitude parameters may result in remarkable complexity and a large design space. Design space exploration as an alternative to t...
详细信息
This paper proposes a novel framework of incorporating protein-protein interactions (PPI) ontology knowledge into PPI extraction from biomedical literature in order to address the emerging challenges of deep natural l...
详细信息
This paper proposes a novel framework of incorporating protein-protein interactions (PPI) ontology knowledge into PPI extraction from biomedical literature in order to address the emerging challenges of deep natural language understanding. It is built upon the existing work on relation extraction using the hidden vector state (HVS) model. The HVS model belongs to the category of statistical learning methods. It can be trained directly from un-annotated data in a constrained way whilst at the same time being able to capture the underlying named entity relationships. However, it is difficult to incorporate background knowledge or non-local information into the HVS model. This paper proposes to represent the HVS model as a conditionally trained undirected graphical model in which non-local features derived from PPI ontology through inference would be easily incorporated. The seamless fusion of ontology inference with statistical learning produces a new paradigm to information extraction.
We describe the design and implementation of an automated system for the calibration, validation, and failure-mode analysis of thermocouple/voltage modules from an automotive data-acquisition system. The automated sys...
详细信息
ISBN:
(纸本)9780980326727
We describe the design and implementation of an automated system for the calibration, validation, and failure-mode analysis of thermocouple/voltage modules from an automotive data-acquisition system. The automated system calibrates, tests, and analyzes sixteen thermocouple/voltage signal-conditioning cards, with a combined total of 320 data channels, over the data-acquisition system's operating range from -40C through +75C. The automated system collects initial measurements to document on-arrival performance, calibrates each channel, collects final measurements to verify each channel's post-calibration operation, tests each channel's dynamic response over temperature gradients, and then analyzes results and produces reports, all within a period of fifteen hours. The system automatically identifies channels that fail calibration and flags them for repair, often identifying specigfic circuit components that have failed.
The availability of low-powered and cheap microprocessors' radio frequency integrated circuits and the development of new wireless communication techniques' make the wireless sensor networks (WSN) one of today...
详细信息
In a recent paper, Ferraris, Lee and Lifschitz conjectured that the concept of a stable model of a first-order formula can be used to treat some answer set programming expressions as abbreviations. We follow up on tha...
详细信息
暂无评论