22 Result(s)
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Chapter
Structural Relationship Preservation in Volume Rendering
This paper presents structural relationship preservation as a technique for improving efficiency of volume rendering-based 3D data analysis. In the presented approach, a map** between data and renderings is ...
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Chapter and Conference Paper
An Effective Feature Selection Method for Text Categorization
Feature selection is an efficient strategy to reduce the dimensionality of data and removing the noise in text categorization. However, most feature selection methods aim to remove non-informative features bas...
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Chapter and Conference Paper
Facilitating Collaboration with Laser Projector-Based Spatial Augmented Reality in Industrial Applications
Spatial Augmented Reality (SAR) superimposes computer generated virtual objects directly on physical objects’ surfaces. This enables user to interact with real world objects in a natural manner. This chapter i...
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Chapter and Conference Paper
Dynamic Workload Adjustments in Human-Machine Systems Based on GSR Features
Workload is found to be a critical factor driving human behavior in human-machine interactions in modern complex high-risk domains. This paper presents a dynamic workload adjustment feedback loop with a dynami...
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Chapter and Conference Paper
Effects of Uncertainty and Cognitive Load on User Trust in Predictive Decision Making
Rapid increase of data in different fields has been resulting in wide applications of Machine Learning (ML) based intelligent systems in predictive decision making scenarios. Unfortunately, these systems appe...
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Chapter and Conference Paper
The Effect of Temperature on Mechanical Properties of Polypropylene
The significant diversity exists among the mechanical properties of PP polymers in range from high temperature to low temperature. With the increasing application of PP polymers in the automobile industry, the...
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Chapter and Conference Paper
The Effect of Extensometers on the Mechanical Properties of the Polypropylene Under Uniaxial Tensile Loading
The elastic modulus and yield strain of polypropylene were obtained by the tensile test at different temperature. Compare the physical performance parameters which were obtained with or without using the exten...
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Chapter
Water Pipe Failure Prediction: A Machine Learning Approach Enhanced By Domain Knowledge
Drinking water pipe and waste water pipe networks are valuable urban infrastructure assets that are responsible for reliable water resource distributions and waste water collection. However, due to fast growin...
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Chapter
2D Transparency Space—Bring Domain Users and Machine Learning Experts Together
Machine Learning (ML) is currently facing prolonged challenges with the user acceptance of delivered solutions as well as seeing system misuse, disuse, or even failure. These fundamental challenges can be attr...
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Chapter
Revealing User Confidence in Machine Learning-Based Decision Making
This chapter demonstrates the link between human cognition states and Machine Learning (ML) with a multimodal interface. A framework of informed decision making called DecisionMind is proposed to show how human’s...
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Chapter
Do I Trust a Machine? Differences in User Trust Based on System Performance
Trust plays an important role in various user-facing systems and applications. It is particularly important in the context of decision support systems, where the system’s output serves as one of the inputs for...
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Chapter and Conference Paper
Multitask Learning for Sparse Failure Prediction
Sparsity is a problem which occurs inherently in many real-world datasets. Sparsity induces an imbalance in data, which has an adverse effect on machine learning and hence reducing the predictability. Previous...
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Chapter and Conference Paper
A Complex Attacks Recognition Method in Wireless Intrusion Detection System
During recent years, the challenge faced by wireless network security is getting severe with the rapid development of internet. However, due to the defects of wireless communication protocol and difference amo...
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Chapter and Conference Paper
Physiological Indicators for User Trust in Machine Learning with Influence Enhanced Fact-Checking
Trustworthy Machine Learning (ML) is one of significant challenges of “black-box” ML for its wide impact on practical applications. This paper investigates the effects of presentation of influence of training ...
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Chapter
Towards Explainability for AI Fairness
AI explainability is becoming indispensable to allow users to gain insights into the AI system’s decision-making process. Meanwhile, fairness is another rising concern that algorithmic predictions may be misal...
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Chapter and Conference Paper
Are Graph Neural Network Explainers Robust to Graph Noises?
With the rapid deployment of graph neural networks (GNNs) based techniques in a wide range of applications such as link prediction, community detection, and node classification, the explainability of GNNs beco...
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Chapter and Conference Paper
Does a Compromise on Fairness Exist in Using AI Models?
Artificial Intelligence (AI) has been increasingly used to assist decision making in different domains. Multiple parties are usually affected by decisions in decision making, e.g. decision-maker and people aff...
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Chapter
Towards Humanity-in-the-Loop in AI Lifecycle
Human needs are important aspects for the humanity. Artificial intelligence (AI) has the strong capacity to meet and promote various levels of human needs ranging from basics needs such as food and water needs...
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Chapter and Conference Paper
A Hip Active Lower Limb Support Exoskeleton for Load Bearing Sit-To-Stand Transfer
Sit-to-stand (STS) transfer is a basic and important motion function in daily living. Most currently-existing studies focus on movement assistance for patients who lost mobility or have impaired their muscle s...
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Chapter and Conference Paper
QoE and Reliability-Aware Task Scheduling for Multi-user Mobile-Edge Computing
Mobile-edge computing (MEC) has become a popular research topic from both academia and industry since it can alleviate the computation and power limitations of mobile devices by offloading computation-intensiv...
