A Multi-Experimental Examination of Analyzing Mouse Cursor Trajectories to Gauge Subject Uncertainty

Providing information online is pervasive in human-computer interactions. While providing information, people may deliberate their responses. However, organizations only receive the end-result of this deliberation and therefore have no contextual information surrounding the response. One type of contextual information includes knowing people’s response uncertainty while providing information. Knowing uncertainty allows organizations to weigh responses, ask follow-up questions, provide assistance, or identify problematic instructions or responses. This paper explores how mouse cursor movements may indicate uncertainty in a human-computer interaction context. Specifically, it hypothesizes how uncertainty on multiple-choice questions influences a mouse-movement statistic called area-under-the-curve (AUC). We report the result of two studies that suggest that AUC is higher when people have moderate uncertainty about an answer than if people have high or low uncertainty. The results suggest a methodology for measuring uncertainty to facilitate multi-method research and to assess data in a pragmatic setting

A Review of Mouse-Tracking Applications in Economic Studies

Since mouse-tracking paradigm came under the spotlight two decades ago, by providing mouse cursor trajectories, it has been applied by behavioral scientists to a variety of topics to help understand real-time psychological state when people are faced with multiple choices. In this article, we provide a comprehensive, documentation of experimental economics studies with mouse-tracking paradigm. Among these studies, some focus on measuring choice uncertainty including subject uncertainty, temporal uncertainty, and probabilistic uncertainty; the rest are concerned with economic games including bargaining games and social dilemma games. Why and how these works employ mouse-tracking technique in their experiments is elaborated in detail. Finally, limitations of mouse-tracking paradigm are discussed, and research opportunities are proposed. Basic know-hows are appended as a general guide for interested readers

Rigor, Relevance, and Practical Significance: A Real-life Journey to Organizational Value

In this essay, we describe a research journey focusing on how to analyze mouse cursor movements, typing fidelity, and data from other human-computer interaction (HCI) devices to better understand the end-user online experience. We begin by defining organizational value and how it relates to other aspects that researchers use to assess academic research quality. We then describe and contrast our research journey by demonstrating key research milestones: from achieving statistical significance to achieving practical significance and, finally, to reaching relevance to practice. We then explain how we crossed the chasm between academic research and technology commercialization (i.e., the last research mile). We conclude by describing the process one can follow to develop an initial prototype—the minimal viable product (MVP)—and how demonstrations with potential customers provides continuous insight and validation for evolving the commercial product capabilities to meet constantly changing and evolving customer and industry needs

Human or AI? Using Digital Behavior to Verify Essay Authorship

Large language models (LLMs) such as OpenAI\u27s GPT-4 have transformed natural language processing with their ability to understand context and generate human-like text. This has led to considerable debate, especially in the education sector, where LLMs can enhance learning but also pose challenges to academic integrity. Detecting AI-generated content (AIGC) is difficult, as existing methods struggle to keep pace with advancements in generation technology. This research proposes a novel approach to AIGC detection in short essays, using digital behavior capture and follow-up questioning to verify text authorship. We executed a controlled experiment as an initial evaluation to test the prototype system. The results obtained show promise in differentiating between user-authored and AI-generated text. The system design and prototype represent valuable contributions for future research in this area. The solution also provides a novel approach to addressing practical challenges posed by LLMs, particularly in maintaining academic integrity in educational settings

3D motion : encoding and perception

The visual system supports perception and inferences about events in a dynamic, three-dimensional (3D) world. While remarkable progress has been made in the study of visual information processing, the existing paradigms for examining visual perception and its relation to neural activity often fail to generalize to perception in the real world which has complex dynamics and 3D spatial structure. This thesis focuses on the case of 3D motion, developing dynamic tasks for studying visual perception and constructing a neural coding framework to relate neural activity to perception in a 3D environment. First, I introduce target-tracking as a psychophysical method and develop an analysis framework based on state space models and the Kalman filter. I demonstrate that target-tracking in conjunction with a Kalman filter analysis framework produce estimates of visual sensitivity that are comparable to those obtained with a traditional forced-choice task and a signal detection theory analysis. Next, I use the target-tracking paradigm in a series of experiments examining 3D motion perception, specifically comparing the perception of frontoparallel motion with the perception of motion-through-depth. I find that continuous tracking of motion-through-depth is selectively impaired due to the relatively small retinal projections resulting from motion-through-depth and the slower processing of binocular disparities. The thesis then turns the neural representation of 3D motion and how that underlies perception. First I introduce a theoretical framework that extends the standard neural coding approach, incorporating the environment-to-retina transformation. Neural coding typically treats the visuals stimulus as a direct proxy for the pattern of stimulation that falls on the retina. Incorporating the environment-to-retina transformation results in a neural representation fundamentally shaped by the projective geometry of the world onto the retina. This model explains substantial anomalies in existing neurophysiological recordings in primate visual cortical neurons during presentations of 3D motion and in psychophysical studies of human perception. In a series of psychophysical experiments, I systematically examine the predictions of the model for human perception by observing how perceptual performance changes as a function of viewing distance and eccentricity. Performance in these experiments suggests a reliance on a neural representation similar to the one described by the model. Taken together, the experimental and theoretical findings reported here advance the understanding of the neural representation and perception of the dynamic 3D world, and adds to the behavioral tools available to vision scientists.Neuroscienc

Closed-loop prosthetic hand : understanding sensorimotor and multisensory integration under uncertainty.

To make sense of our unpredictable world, humans use sensory information streaming through billions of peripheral neurons. Uncertainty and ambiguity plague each sensory stream, yet remarkably our perception of the world is seamless, robust and often optimal in the sense of minimising perceptual variability. Moreover, humans have a remarkable capacity for dexterous manipulation. Initiation of precise motor actions under uncertainty requires awareness of not only the statistics of our environment but also the reliability of our sensory and motor apparatus. What happens when our sensory and motor systems are disrupted? Upper-limb amputees tted with a state-of-the-art prostheses must learn to both control and make sense of their robotic replacement limb. Tactile feedback is not a standard feature of these open-loop limbs, fundamentally limiting the degree of rehabilitation. This thesis introduces a modular closed-loop upper-limb prosthesis, a modified Touch Bionics ilimb hand with a custom-built linear vibrotactile feedback array. To understand the utility of the feedback system in the presence of multisensory and sensorimotor influences, three fundamental open questions were addressed: (i) What are the mechanisms by which subjects compute sensory uncertainty? (ii) Do subjects integrate an artificial modality with visual feedback as a function of sensory uncertainty? (iii) What are the influences of open-loop and closed-loop uncertainty on prosthesis control? To optimally handle uncertainty in the environment people must acquire estimates of the mean and uncertainty of sensory cues over time. A novel visual tracking experiment was developed in order to explore the processes by which people acquire these statistical estimators. Subjects were required to simultaneously report their evolving estimate of the mean and uncertainty of visual stimuli over time. This revealed that subjects could accumulate noisy evidence over the course of a trial to form an optimal continuous estimate of the mean, hindered only by natural kinematic constraints. Although subjects had explicit access to a measure of their continuous objective uncertainty, acquired from sensory information available within a trial, this was limited by a conservative margin for error. In the Bayesian framework, sensory evidence (from multiple sensory cues) and prior beliefs (knowledge of the statistics of sensory cues) are combined to form a posterior estimate of the state of the world. Multiple studies have revealed that humans behave as optimal Bayesian observers when making binary decisions in forced-choice tasks. In this thesis these results were extended to a continuous spatial localisation task. Subjects could rapidly accumulate evidence presented via vibrotactile feedback (an artificial modality ), and integrate it with visual feedback. The weight attributed to each sensory modality was chosen so as to minimise the overall objective uncertainty. Since subjects were able to combine multiple sources of sensory information with respect to their sensory uncertainties, it was hypothesised that vibrotactile feedback would benefit prosthesis wearers in the presence of either sensory or motor uncertainty. The closed-loop prosthesis served as a novel manipulandum to examine the role of feed-forward and feed-back mechanisms for prosthesis control, known to be required for successful object manipulation in healthy humans. Subjects formed economical grasps in idealised (noise-free) conditions and this was maintained even when visual, tactile and both sources of feedback were removed. However, when uncertainty was introduced into the hand controller, performance degraded significantly in the absence of visual or tactile feedback. These results reveal the complementary nature of feed-forward and feed-back processes in simulated prosthesis wearers, and highlight the importance of tactile feedback for control of a prosthesis

Automated Productivity Models for Earthmoving Operations

Earthmoving operations have significant importance, particularly for civil infrastructure projects. The performance of these operations should be monitored regularly to support timely recognition of undesirable productivity variances. Although productivity assessment occupies high importance in earthmoving operations, it does not provide sufficient information to assist project managers in taking the necessary actions in a timely manner. Assessment only is not capable of identifying problems encountered in these operations and their causes. Many studies recognized conditions and related factors that influence productivity of earthmoving operations. These conditions are mainly project-specific and vary from one project to another. Most of reported work in the literature focused on assessment rather than analysis of productivity. This study presents three integrated models that automate productivity measurement and analysis processes with capabilities to detect different adverse conditions that influence the productivity of earthmoving operations. The models exploit innovations in wireless and remote sensing technologies to provide project managers, contractors, and decision makers with a near-real-time automated productivity measurement and analysis. The developed models account for various uncertainties associated with earthmoving projects. The first model introduces a fuzzy-based standardization for customizing the configuration of onsite data acquisition systems for earthmoving operations. While the second model consists of two interrelated modules. The first is a customized automated data acquisition module, where a variety of sensors, smart boards, and microcontrollers are used to automate the data acquisition process. This module encompasses onsite fixed unit and a set of portable units attached to each truck used in the earthmoving fleet. The fixed unit is a communication gateway (Meshlium®), which has integrated MySQL database with data processing capabilities. Each mobile unit consists of a microcontroller equipped with a smart board that hosts a GPS module as well as a number of sensors such as accelerometer, temperature and humidity sensors, load cell and automated weather station. The second is a productivity measurement and analysis module, which processes and analyzes the data collected automatically in the first module. It automates the analysis process using data mining and machine learning techniques; providing a near-real-time web-based visualized representation of measurement and analysis outcomes. Artificial Neural Network (ANN) was used to model productivity losses due to the existence of different influencing conditions. Laboratory and field work was conducted in the development and validation processes of the developed models. The work encompassed field and scaled laboratory experiments. The laboratory experiments were conducted in an open to sky terrace to allow for a reliable access to GPS satellites. Also, to make a direct connection between the data communication gateway (Meshlium®), initially installed on a PC computer to observe the received data latency. The laboratory experiments unitized 1:24 scaled loader and dumping truck to simulate loading, hauling and dumping operations. The truck was instrumented with the microcontroller equipped with an accelerometer, GPS module, load cell, and soil water content sensor. Thirty simulated earthmoving cycles were conducted using the scaled equipment. The collected data was recorded in a micro secure digital (SD) card in a comma separated value (CSV) format. The field work was carried out in the city of Saint-Laurent, Montreal, Quebec, Canada using a passenger vehicle to mimic the hauling truck operational modes. Fifteen Field simulated earthmoving cycles were performed. In this work two roads with different surface conditions, but of equal length (1150 m) represented the haul and return roads. These two roads were selected to validate the developed road condition analysis algorithm and to study the model’s capability in determining the consequences of adverse road conditions on the haul and return durations and thus on the tuck and fleet productivity. The data collected from the lab experiments and field work was used as input for the developed model. The developed model has shown perfect recognition of the state of truck throughout the fifteen field simulated earthmoving cycles. The developed road condition analysis algorithm has demonstrated an accuracy of 83.3% and 82.6% in recognizing road bumps and potholes, respectively. Also, the results indicated tiny variances in measuring the durations compared with actual durations using time laps displayed on a smart cell telephone; with an average invalidity percentage AIP% of 1.89 % and 1.33% for the joint hauling and return duration and total cycle duration, respectively

The Effect of Mobile Gamification on Brand Loyalty

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Fourth Annual Workshop on Space Operations Applications and Research (SOAR 90)

The papers from the symposium are presented. Emphasis is placed on human factors engineering and space environment interactions. The technical areas covered in the human factors section include: satellite monitoring and control, man-computer interfaces, expert systems, AI/robotics interfaces, crew system dynamics, and display devices. The space environment interactions section presents the following topics: space plasma interaction, spacecraft contamination, space debris, and atomic oxygen interaction with materials. Some of the above topics are discussed in relation to the space station and space shuttle