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The work presented in this paper describes an intelligent scheduling software framework that utilizes domain-specific heuristics. The customizability of the framework and heuristics allows the software to develop a valid schedule that reflects each domain's specific preferences and constraints. Four distinct examples of this are presented in the areas of prototype vehicle testing, pharmaceutical packaging,...
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A non-linear, yet simple, multiplicative human-control model is developed by studying the statistical properties of human subjects' motor response to a visual input; statistical analysis of the magnitude of the steering angle, from subjects performing a tracking task with a steering wheel, shows that the data is consistent with a log-normal distribution. Thus the possibility of modelling human-control...
This paper identifies a small, essential set of static software code metrics linked to the software product quality characteristics of reliability and maintainability and to the most commonly identified sources of technical debt. A plug-in is created for the Understand code visualization and static analysis tool that calculates and aggregates the metrics. The plug-in produces a high-level interactive...
The purpose of this industrial brief is to introduce an information system named Inventorum, which implements the idea of open innovation. Its aim is to increase cooperation between business and academia and in this way boost economic competitiveness. The system recommends innovations, projects, experts, partners, and conferences to the users based on their profiles. Information is served in three...
Background. Stability and growth in life insurance market is an important economic indicator. Therefore, yearly coverage lapse-rate estimates are one of the key statistics that actuarial analysts need to characterize and manage the insurance business. Aim. We aim to present machine learning based approach applied to a real data set covering a decade long customer history of an international financial...
With the growing number of automated welding systems present throughout manufacturing, achieving high precision is naturally a key objective. The alignment of weld tip to weld seam, particularly in very long welds (such as in pipes), is a technical challenge in which computer vision has much to offer. This paper introduces a real-time methodology for weld-seam tracking. The key challenge associated...
Automated mental workload measurement is particularly important in safety-critical settings, such as in nuclear plants, aviation, air traffic control, shipping, and transportation, to name a few. As an example, recent statistics have suggested that 90% of the accidents in the transport industry are due to human factors. In this paper, we explore the potential of off-the-shelf wearable technologies...
This paper describes a human-in-the-loop evaluation of a power plant Human-Machine Interface (HMI), that was designed using a User-Centered Design approach. General Electric (GE) developed ActivePoint∗ HMI (AP HMI) to increase plant operator efficiency and awareness. UCD was applied as a design process along with existing industry design guidelines and other design approaches. The goal of the evaluation...
Wearable devices such as prosthetics, exoskeleton, robotic manipulator, orthosis are necessary for training rehabilitation process for disabled people. They require a compact size, a light weight and a safe interact between people and equipment. This paper proposes a design and analysis of a new gear-driven compliant torsional spring for rehabilitation device of an upper limb. The device consists...
Estimation distribution algorithms (EDAs) have been widely used in single objective optimization problems. In this paper EDAs are combined with differential mutation (DM) to find Pareto optimal front for multi-objective optimization problems (MOPs). First, a modified extreme elitism selection method is used to choose some promising solutions as the parent solution. This selection represents some leading...
In this paper, we present a method to estimate abstract parameters of high definition (HD) maps from sensor data. Parameters we estimate include the distance from ego-vehicle to road boundary, orientation of the ego-vehicle with respect to lanes, number of lanes, and street type. Our method is realized as a Convolutional Neural Network (CNN) that takes pre-processed sensor information in the form...
Argument Component Boundary Detection (ACBD) is an important sub-task in argumentation mining; it aims at identifying the word sequences that constitute argument components, and is usually considered as the first sub-task in the argumentation mining pipeline. Existing ACBD methods heavily depend on task-specific knowledge, and require considerable human efforts on feature-engineering. To tackle these...
Object Tracking is an important task in Computer Vision, which has gained increasing attention from academia to industry. In this paper, we propose a real-time tracking system based on weak segmentation. Different from general tracking by detection systems, we do not classify objects into car, cat or bike, instead we just classify the image into object area and non-object area. Many tracking systems...
In recent years, network representation learning (NRL) has been increasingly applied into web data analysis, such as video, image and text. Most of NRL methods can widely pursue nodes classification, community detection and link prediction tasks. Due to the nodes in these kinds of networks mostly contain the common attributes and share the same neighbors, we identify them as homogeneous networks,...
In this paper, we study the link-oriented tasks in signed network, i.e., labeling link signs and predicting new links. Usually, prior arts directly focus on the link signs, while their intrinsic structural regularities have been largely ignored. Furthermore, these techniques suffer the sensitiveness to the high dimension and sparsity of networks. To deal with these tasks, with verifying the effect...
The purpose of this study is to clarify the applicability of data-driven approach in accounting area. As the first stage, focusing on the model comparison, this paper shows the effectiveness of model selection with data mining technique for the development of earnings prediction model based on financial statement data. In accounting area, researchers have not considered the characteristic of financial...
Argumentation mining aims at automatically extracting the premises-claim discourse structures in natural language texts. There is a great demand for argumentation corpora for customer reviews. However, due to the controversial nature of the argumentation annotation task, there exist very few large-scale argumentation corpora for customer reviews. In this work, we novelly use the crowdsourcing technique...
Independent mobility is important for the self-esteem and well-being of people with mobility impairments. For people with severe disabilities, there is a body of research investigating how best to share control of motion between a person with disabilities and a "smart wheelchair". Traditionally in "shared control", the control law is a linear combination of the human's intended...
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