Artificial Intelligence and Robotics Commons^™

Examining The Effects Of Race On Human-Ai Cooperation, Akil A. Atkins, Christopher L. Dancy, Matthew S. Brown

Faculty Conference Papers and Presentations

Recent literature has shown that racism and implicit racial biases can affect one’s actions in major ways, from the time it takes police to decide whether they shoot an armed suspect, to a decision on whether to trust a stranger. Given that race is a social/power construct, artifacts can also be racialized, and these racialized agents have also been found to be treated differently based on their perceived race. We explored whether people’s decision to cooperate with an AI agent during a task (a modified version of the Stag hunt task) is affected by the knowledge that the AI agent …

Computational Frameworks For Multi-Robot Cooperative 3d Printing And Planning, Laxmi Prasad Poudel

Graduate Theses and Dissertations

This dissertation proposes a novel cooperative 3D printing (C3DP) approach for multi-robot additive manufacturing (AM) and presents scheduling and planning strategies that enable multi-robot cooperation in the manufacturing environment. C3DP is the first step towards achieving the overarching goal of swarm manufacturing (SM). SM is a paradigm for distributed manufacturing that envisions networks of micro-factories, each of which employs thousands of mobile robots that can manufacture different products on demand. SM breaks down the complicated supply chain used to deliver a product from a large production facility from one part of the world to another. Instead, it establishes a network …

Leveraging Big Data For Pattern Recognition Of Socio-Demographic And Climatic Factors In Correlation With Eye Disorders In Telangana State, India, Amna Alalawi, Les Sztandera, Parth Lalakia, Anthony Vipin Das, Sai Prashanthi Gumpili, Richard Derman

Kanbar College Faculty Papers

Purpose: Big data is the new gold, especially in health care. Advances in collecting and processing electronic medical records (EMR) coupled with increasing computer capabilities have resulted in an increased interest in the use of big data in health care. Ophthalmology has been an area of focus where results have shown to be promising. The objective of this study was to determine whether the EMR at a multi-tier ophthalmology network in India can contribute to the management of patient care, through studying how climatic and socio-demographic factors relate to eye disorders and visual impairment in the State of Telangana.

Methods: …

Improving Collection Understanding For Web Archives With Storytelling: Shining Light Into Dark And Stormy Archives, Shawn M. Jones

Computer Science Theses & Dissertations

Collections are the tools that people use to make sense of an ever-increasing number of archived web pages. As collections themselves grow, we need tools to make sense of them. Tools that work on the general web, like search engines, are not a good fit for these collections because search engines do not currently represent multiple document versions well. Web archive collections are vast, some containing hundreds of thousands of documents. Thousands of collections exist, many of which cover the same topic. Few collections include standardized metadata. Too many documents from too many collections with insufficient metadata makes collection understanding …

Scheduling Allocation And Inventory Replenishment Problems Under Uncertainty: Applications In Managing Electric Vehicle And Drone Battery Swap Stations, Amin Asadi

Graduate Theses and Dissertations

In this dissertation, motivated by electric vehicle (EV) and drone application growth, we propose novel optimization problems and solution techniques for managing the operations at EV and drone battery swap stations. In Chapter 2, we introduce a novel class of stochastic scheduling allocation and inventory replenishment problems (SAIRP), which determines the recharging, discharging, and replacement decisions at a swap station over time to maximize the expected total profit. We use Markov Decision Process (MDP) to model SAIRPs facing uncertain demands, varying costs, and battery degradation. Considering battery degradation is crucial as it relaxes the assumption that charging/discharging batteries do not …

Trust In And Ethical Design Of Carebots: The Case For Ethics Of Care, Gary Kok Yew Chan

Research Collection Yong Pung How School Of Law

The paper has two main objectives: to examine the challenges arising from the use of carebots as well as to discuss how the design of carebots can deal with these challenges. First, it notes that the use of carebots to take care of the physical and mental health of the elderly, children and the disabled as well as to serve as assistive tools and social companions encounter a few main challenges. They relate to the extent of the care robots’ ability to care for humans, potential deception by robot morphology and communications, (over)reliance on or attachment to robots, and the …

An Adaptive Large Neighborhood Search For The Green Mixed Fleet Vehicle Routing Problem With Realistic Energy Consumption And Partial Recharges, Vincent F. Yu, Panca Jodiawan, Aldy Gunawan

Research Collection School Of Computing and Information Systems

This study addresses a variant of the Electric Vehicle Routing Problem with Mixed Fleet, named as the Green Mixed Fleet Vehicle Routing Problem with Realistic Energy Consumption and Partial Recharges. This problem contains three important characteristics — realistic energy consumption, partial recharging policy, and carbon emissions. An adaptive Large Neighborhood Search heuristic is developed for the problem. Experimental results show that the proposed ALNS finds optimal solutions for most small-scale benchmark instances in a significantly faster computational time compared to the performance of CPLEX solver. Moreover, it obtains high quality solutions for all medium- and large-scale instances under a reasonable …

Order-Agnostic Cross Entropy For Non-Autoregressive Machine Translation, Cunxiao Du, Zhaopeng Tu, Jing Jiang

Research Collection School Of Computing and Information Systems

We propose a new training objective named orderagnostic cross entropy (OAXE) for fully nonautoregressive translation (NAT) models. OAXE improves the standard cross-entropy loss to ameliorate the effect of word reordering, which is a common source of the critical multimodality problem in NAT. Concretely, OAXE removes the penalty for word order errors, and computes the cross entropy loss based on the best possible alignment between model predictions and target tokens. Since the log loss is very sensitive to invalid references, we leverage cross entropy initialization and loss truncation to ensure the model focuses on a good part of the search space. …

Claim: Curriculum Learning Policy For Influence Maximization In Unknown Social Networks, Dexun Li, Meghna Lowalekar, Pradeep Varakantham

Research Collection School Of Computing and Information Systems

Influence maximization is the problem of finding a small subset of nodes in a network that can maximize the diffusion of information. Recently, it has also found application in HIV prevention, substance abuse prevention, micro-finance adoption, etc., where the goal is to identify the set of peer leaders in a real-world physical social network who can disseminate information to a large group of people. Unlike online social networks, real-world networks are not completely known, and collecting information about the network is costly as it involves surveying multiple people. In this paper, we focus on this problem of network discovery for …

Meta-Inductive Node Classification Across Graphs, Zhihao Wen, Yuan Fang, Zemin Liu

Research Collection School Of Computing and Information Systems

Semi-supervised node classification on graphs is an important research problem, with many real-world applications in information retrieval such as content classification on a social network and query intent classification on an e-commerce query graph. While traditional approaches are largely transductive, recent graph neural networks (GNNs) integrate node features with network structures, thus enabling inductive node classification models that can be applied to new nodes or even new graphs in the same feature space. However, inter-graph differences still exist across graphs within the same domain. Thus, training just one global model (e.g., a state-of-the-art GNN) to handle all new graphs, whilst …

Mmconv: An Environment For Multimodal Conversational Search Across Multiple Domains, Lizi Liao, Le Hong Long, Zheng Zhang, Minlie Huang, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

Although conversational search has become a hot topic in both dialogue research and IR community, the real breakthrough has been limited by the scale and quality of datasets available. To address this fundamental obstacle, we introduce the Multimodal Multi-domain Conversational dataset (MMConv), a fully annotated collection of human-to-human role-playing dialogues spanning over multiple domains and tasks. The contribution is two-fold. First, beyond the task-oriented multimodal dialogues among user and agent pairs, dialogues are fully annotated with dialogue belief states and dialogue acts. More importantly, we create a relatively comprehensive environment for conducting multimodal conversational search with real user settings, structured …

How Important Is The Train-Validation Split In Meta-Learning?, Yu Bai, Minshuo Chen, Pan Zhou, Tuo Zhao, D. Jason Lee, Sham Kakade, Huan Wang, Caiming Xiong

Research Collection School Of Computing and Information Systems

Meta-learning aims to perform fast adaptation on a new task through learning a “prior” from multiple existing tasks. A common practice in meta-learning is to perform a train-validation split (train-val method) where the prior adapts to the task on one split of the data, and the resulting predictor is evaluated on another split. Despite its prevalence, the importance of the train-validation split is not well understood either in theory or in practice, particularly in comparison to the more direct train-train method, which uses all the pertask data for both training and evaluation. We provide a detailed theoretical study on whether …

Task Similarity Aware Meta Learning: Theory-Inspired Improvement On Maml, Pan Zhou, Yingtian Zpu, Xiaotong Yuan, Jiashi Feng, Caiming Xiong, Steven C. H. Hoi

Research Collection School Of Computing and Information Systems

Few-shot learning ability is heavily desired for machine intelligence. By meta-learning a model initialization from training tasks with fast adaptation ability to new tasks, model-agnostic meta-learning (MAML) has achieved remarkable success in a number of few-shot learning applications. However, theoretical understandings on the learning ability of MAML remain absent yet, hindering developing new and more advanced meta learning methods in a principled way. In this work, we solve this problem by theoretically justifying the fast adaptation capability of MAML when applied to new tasks. Specifically, we prove that the learnt meta-initialization can benefit the fast adaptation to new tasks with …

Design And Development Of Techniques To Ensure Integrity In Fog Computing Based Databases, Abdulwahab Fahad S. Alazeb

Graduate Theses and Dissertations

The advancement of information technology in coming years will bring significant changes to the way sensitive data is processed. But the volume of generated data is rapidly growing worldwide. Technologies such as cloud computing, fog computing, and the Internet of things (IoT) will offer business service providers and consumers opportunities to obtain effective and efficient services as well as enhance their experiences and services; increased availability and higher-quality services via real-time data processing augment the potential for technology to add value to everyday experiences. This improves human life quality and easiness. As promising as these technological innovations, they are prone …

Oesense: Employing Occlusion Effect For In-Ear Human Sensing, Dong Ma, Andrea Ferlini, Cecilia Mascolo

Research Collection School Of Computing and Information Systems

Smart earbuds are recognized as a new wearable platform for personal-scale human motion sensing. However, due to the interference from head movement or background noise, commonly-used modalities (e.g. accelerometer and microphone) fail to reliably detect both intense and light motions. To obviate this, we propose OESense, an acoustic-based in-ear system for general human motion sensing. The core idea behind OESense is the joint use of the occlusion effect (i.e., the enhancement of low-frequency components of bone-conducted sounds in an occluded ear canal) and inward-facing microphone, which naturally boosts the sensing signal and suppresses external interference. We prototype OESense as an …

Signal Processing And Data Analysis For Real-Time Intermodal Freight Classification Through A Multimodal Sensor System., Enrique J. Sanchez Headley

Graduate Theses and Dissertations

Identifying freight patterns in transit is a common need among commercial and municipal entities. For example, the allocation of resources among Departments of Transportation is often predicated on an understanding of freight patterns along major highways. There exist multiple sensor systems to detect and count vehicles at areas of interest. Many of these sensors are limited in their ability to detect more specific features of vehicles in traffic or are unable to perform well in adverse weather conditions. Despite this limitation, to date there is little comparative analysis among Laser Imaging and Detection and Ranging (LIDAR) sensors for freight detection …

Methods For Detecting Floodwater On Roadways From Ground Level Images, Cem Sazara

Computational Modeling & Simulation Engineering Theses & Dissertations

Recent research and statistics show that the frequency of flooding in the world has been increasing and impacting flood-prone communities severely. This natural disaster causes significant damages to human life and properties, inundates roads, overwhelms drainage systems, and disrupts essential services and economic activities. The focus of this dissertation is to use machine learning methods to automatically detect floodwater in images from ground level in support of the frequently impacted communities. The ground level images can be retrieved from multiple sources, including the ones that are taken by mobile phone cameras as communities record the state of their flooded streets. …

Deep Learning Approaches For Seagrass Detection In Multispectral Imagery, Kazi Aminul Islam

Electrical & Computer Engineering Theses & Dissertations

Seagrass forms the basis for critically important marine ecosystems. Seagrass is an important factor to balance marine ecological systems, and it is of great interest to monitor its distribution in different parts of the world. Remote sensing imagery is considered as an effective data modality based on which seagrass monitoring and quantification can be performed remotely. Traditionally, researchers utilized multispectral satellite images to map seagrass manually. Automatic machine learning techniques, especially deep learning algorithms, recently achieved state-of-the-art performances in many computer vision applications. This dissertation presents a set of deep learning models for seagrass detection in multispectral satellite images. It …

Fire Suppression And Ignition With Unmanned Aerial Vehicles, Carrick Detweiler, Sebastian Elbaum, James Higgins, Christian Laney, Craig Allen, Dirac L. Twidwell Jr, Evan Michale Beachly

School of Computing: Faculty Publications

An unmanned aerial vehicle (UAV) can be configured for fire suppression and ignition. In some examples, the UAV includes an aerial propulsion system, an ignition system, and a control system. The ignition system includes a container of delayed-ignition balls and a dropper configured by virtue of one or more motors to actuate and drop the delayed-ignition balls. The control system is configured to cause the UAV to fly to a site of a prescribed burn and, while flying over the site of the prescribed burn, actuate one or more of the delayed-ignition balls. After actuating the one or more delayed-ignition …

Deep Peak-Shaving Transformation Planning Of Thermal Power Units Based On Approximate Dynamic Programming, Weiqing Sun, Song He, Han Dong, Kunpeng Tian

Journal of System Simulation

Abstract: The generation of renewable energy has great randomness. The lack of flexibility of thermal power unit leads to the problem of peak adjustment. Three reformation schemes for thermal power units, including the thermal power unit internal transformation, configurating energy storage, and joint transformation of the two are proposed. Taking into account the additional cost of thermal powerunit in the deep peak regulation, the planning model of thermal power units depth peak-shaving transformation considering the unit combination is proposed, and the strategy iteration approximate dynamic programming algorithm to decouple the model is presented. The “curses of dimensionality” can be avoided …

Prediction Method For Health Degree Of Front Bearing Of Wind Turbine Generator And Implementation, Yin Shi, Guolian Hou, Chi Yan, Linjuan Gong, Xiaodong Hu

Journal of System Simulation

Abstract: Aiming at the deterioration trend of front bearing of doubly-fed wind turbine generator, a new combined modeling method is proposed to predict health degree of front bearing of generator. The GMM is used to identify operating conditions of wind turbines. The temperature model of front bearing based on ELM is established respectively in each sub-condition. Combining with temperature residual characteristics and time-frequency characteristics of vibration signal, the health degree of front bearing is calculated. Based on attention mechanism, the Bi-LSTM neural network is proposed to model and predict health degree of front bearing. The result shows that the …

Design Of Lvc Simulation Test Middleware For Saas, Du Nan, Yaxin Tan

Journal of System Simulation

Abstract: LVC (Live-Virtual-Constructive) technology provides a new technical means for equipment test. In view of the large number of heterogeneous simulation resource objects and complex interaction in the LVC system test, which can not meet the test task requirements of quick response of the weapon system, the middleware and application model framework is reformed according to the remote method invocation based on TENA. The functional modules of LVC simulation middleware including model running component, publishing and ordering component, message processing component and real-time running component are designed to provide efficient real-time communication mechanism for LVC simulation and support the application …

Simulation On The Development Of Residential Distributed Photovoltaic Power Generation Under The Declining Trend Of Feed-In-Tariff, Libo Zhang, Lulu Ge, Changqi Chen, Mingduan Tang

Journal of System Simulation

Abstract: Residential Distributed Photovoltaic Generation (R-DPVG) has become the important developing force of PV generation in China. As the declining of Feed-in-Tariff (FIT), system dynamics method is used to construct a causal loop model for R-DPVG’s development, and relevant factors and their feedback mechanism are qualitatively analyzed. Then a stock-flow model is build, and the ROI, installed capacity, and policy subsidy costs of R-DPVG are simulated under some combined scenarios based on declining FIT. The simulation proves R-DPVG’s FIT will be reduced to 0.05 ~ 0.1 yuan/(kW?h) in the next three years till cancelled. FIT cutting amplitude, capacity and targets …

Approximate Method Of Spares Demand Prediction For Weibull Distribution Items Based On Piecewise Function, Songshi Shao, Zhihua Zhang, Xiaojie Mo

Journal of System Simulation

Abstract: Demand prediction model for spare parts with Weibull distribution involves multiple infinite series, therefore, spares demand calculation is a difficult issue. The approximate calculation method generally used is often subject to large errors. According to the principle of renewal function, the approximated demand calculation method for spares of Weibull distribution using piecewise function to approximate the renewal function is proposed. It effectively avoids the issue of computational complexity for spares demand prediction. Theoretical analysis shows that the proposed approximated algorithm ensures the calculation result of spares demand is less than that of engineering approximation algorithm. According to the given …

Research On Description Specification Of Extensible Simulation Scenario, Xiangzhong Xu, Xiong Jun, Fengwei Shen

Journal of System Simulation

Abstract: Simulation scenario description specification is of great significance to speed the Simulation Scenario Data (SSD) preparation, to improve the quality and to promote the reuse of the SSD. An in-depth comparison between simulation scenario and military scenario is made. The composition and application process of military scenario based on the description specification are designed, above which, the design scheme of the description specification is discussed. The extensible military scenario description specification is proposed from the following two aspects, that is, the basic elements including time and coordinate system, and the data interchange format. Series of scenario instances are produced. …

Research On Chemical Simulation Environment Modeling Based On Complex Terrain, Shunhua Liu, Fang Min

Journal of System Simulation

Abstract: Environment simulation is an important part of the construction of simulation training system. Without considering terrain factors in current chemical simulation environment, there are many problems in directing and controlling, simulation interacting, estimating and evaluating of simulation training. Based on the classical Gaussian diffusion model, the new model is suitable for the complex terrain chemical simulation environment through terrain elevation correction, diffusion parameter correction and mass conservation correction. The simulated chemical hazard area is in line with the atmospheric diffusion law of complex terrain. The model presents a realistic environment and fast computing ability, which solves the problem of …

Pathfinder Algorithm For Green Pipeline Scheduling With Limited Buffers, Hu Rong, Yuming Dong, Bin Qian

Journal of System Simulation

Abstract: A Hybrid Pathfinder Algorithm (HPFA) is proposed for solving the green flow shop scheduling problem with limited buffers and energy threshold constraints (GFSSP_LBET). The optimization criteria are to minimize the total energy consumption and the makespan. In order to enhance the global search ability of HPFA, a distance-based selection scheme is designed to determine each pathfinder's followers to ensure that the near regions of any pathfinder can get a certain search. A self-learning search strategy integrating multiple operations is designed to perform multi-neighborhood search on the updated pathfinders, which can improve the local exploitation ability of HPFA. Simulation experiments …

Yard Layout Optimization For General Cargo Terminal, Zhixiong Liu, Dong Yu, Chunjun Zhang

Journal of System Simulation

Abstract: Yard layout is an important component of the port yard allocation decision which affects the cargo storage capacity and through capacity for the port yard. As to the general cargo yard, combined with the cargo type and the yard storage strategy, the yard layout optimization model for the general cargo terminal is presented based on the statistical analysis for the production data when the optimization aim is minimizing the total horizontal transport distance of the trailer. The yard layout optimization results are employed by the mathematical tool Gurobi for different storage strategies, and the yard layout optimization results are …

Research On Time Performance Simulation And Analysis Technology Of Aviation Complex Embedded System, Lingsha Zheng, Jiang Bing, Zhe Zhao, Zhaoxu Yang

Journal of System Simulation

Abstract: As a core member of an embedded system, the embedded computer's time performance plays a key role in the comprehensive performance of the system's functional performance. However, as the complexity of aviation products continues to increase, traditional system development methods are facing the challenge for verification. In order to improve the accuracy of time performance analysis for the complex embedded system, find the potential hazards in the design of scheduling early, and avoid the system comprehensive stage design iteration caused by the time system defects, the methodology of the construction of the model and the analysis method of the …

Research On Component-Based Modeling Of Simulation Entity For Logistics And Equipment Support, Cao Qi, Qun Xiang, Wenzheng Wang

Journal of System Simulation

Abstract: There has been a lack of efficient and advanced simulation training means and systems for logistics and equipment support. Aiming at the characteristics of non-antagonism, uncertainty, timeliness, parallelism and discontinuity in the simulation of support operation, the abstraction of three entities, three interaction relations and three organization relations is put forward. By using component-based modeling, the entity for logistics and equipment support is further decomposed into several attribute components and behavior components for modeling, which effectively solves the problem of entity modeling in simulation training of support operation. In this way, the conceptual modeling tool, simulation model …