Low-Power And Reconfigurable Asynchronous Asic Design Implementing Recurrent Neural Networks,
2021
University of Arkansas, Fayetteville
Low-Power And Reconfigurable Asynchronous Asic Design Implementing Recurrent Neural Networks, Spencer Nelson
Graduate Theses and Dissertations
Artificial intelligence (AI) has experienced a tremendous surge in recent years, resulting in high demand for a wide array of implementations of algorithms in the field. With the rise of Internet-of-Things devices, the need for artificial intelligence algorithms implemented in hardware with tight design restrictions has become even more prevalent. In terms of low power and area, ASIC implementations have the best case. However, these implementations suffer from high non-recurring engineering costs, long time-to-market, and a complete lack of flexibility, which significantly hurts their appeal in an environment where time-to-market is so critical. The time-to-market gap can be shortened through …
Guest Editorial: Non-Iid Outlier Detection In Complex Contexts,
2021
Singapore Management University
Guest Editorial: Non-Iid Outlier Detection In Complex Contexts, Guansong Pang, Fabrizio Angiulli, Mihai Cucuringu, Huan Liu
Research Collection School Of Computing and Information Systems
Outlier detection, also known as anomaly detection, aims at identifying data instances that are rare or significantly different from the majority of instances. Due to its significance in many critical domains like cybersecurity, fintech, healthcare, public security, and AI safety, outlier detection has been one of the most active research areas in various communities, such as machine learning, data mining, computer vision, and statistics. Traditional outlier-detection techniques generally assume that data are independent and identically distributed (IID), which are significantly challenged in complex contexts where data are actually non-IID. These contexts are ubiquitous in not only graph data, sequence data, …
Ship-Gan: Generative Modeling Based Maritime Traffic Simulator,
2021
Singapore Management University
Ship-Gan: Generative Modeling Based Maritime Traffic Simulator, Chaithanya Basrur, Arambam James Singh, Arunesh Sinha, Akshat Kumar
Research Collection School Of Computing and Information Systems
Modeling vessel movement in a maritime environment is an extremely challenging task given the complex nature of vessel behavior. Several existing multiagent maritime decision making frameworks require access to an accurate traffic simulator. We develop a system using electronic navigation charts to generate realistic and high fidelity vessel traffic data using Generative Adversarial Networks (GANs). Our proposed Ship-GAN uses a conditional Wasserstein GAN to model a vessel's behavior. The generator can simulate the travel time of vessels across different maritime zones conditioned on vessels' speeds and traffic intensity. Furthermore, it can be used as an accurate simulator for prior decision …
Dialogue State Tracking With Incremental Reasoning,
2021
Singapore Management University
Dialogue State Tracking With Incremental Reasoning, Lizi Liao, Le Hong Long, Yunshan Ma, Wenqiang Lei, Tat-Seng Chua
Research Collection School Of Computing and Information Systems
Tracking dialogue states to better interpret user goals and feed downstream policy learning is a bottleneck in dialogue management. Common practice has been to treat it as a problem of classifying dialogue content into a set of pre-defined slot-value pairs, or generating values for different slots given the dialogue history. Both have limitations on considering dependencies that occur on dialogues, and are lacking of reasoning capabilities. This paper proposes to track dialogue states gradually with reasoning over dialogue turns with the help of the back-end data. Empirical results demonstrate that our method outperforms the state-of-theart methods in terms of joint …
Edgeduet: Tiling Small Object Detection For Edge Assisted Autonomous Mobile Vision,
2021
Singapore Management University
Edgeduet: Tiling Small Object Detection For Edge Assisted Autonomous Mobile Vision, Xu Wang, Zheng Yang, Jiahang Wu, Yi Zhao, Zimu Zhou
Research Collection School Of Computing and Information Systems
Accurate, real-time object detection on resource-constrained devices enables autonomous mobile vision applications such as traffic surveillance, situational awareness, and safety inspection, where it is crucial to detect both small and large objects in crowded scenes. Prior studies either perform object detection locally on-board or offload the task to the edge/cloud. Local object detection yields low accuracy on small objects since it operates on low-resolution videos to fit in mobile memory. Offloaded object detection incurs high latency due to uploading high-resolution videos to the edge/cloud. Rather than either pure local processing or offloading, we propose to detect large objects locally while …
Learning Index Policies For Restless Bandits With Application To Maternal Healthcare,
2021
Singapore Management University
Learning Index Policies For Restless Bandits With Application To Maternal Healthcare, Arpita Biswas, Gaurav Aggarwal, Pradeep Varakantham, Milind Tambe
Research Collection School Of Computing and Information Systems
In many community health settings, it is crucial to have a systematic monitoring and intervention process to ensure that the patients adhere to healthcare programs, such as periodic health checks or taking medications. When these interventions are expensive, they can be provided to only a fixed small fraction of the patients at any period of time. Hence, it is important to carefully choose the beneficiaries who should be provided with interventions and when. We model this scenario as a restless multi-armed bandit (RMAB) problem, where each beneficiary is assumed to transition from one state to another depending on the intervention …
A Differential Testing Approach For Evaluating Abstract Syntax Tree Mapping Algorithms,
2021
Singapore Management University
A Differential Testing Approach For Evaluating Abstract Syntax Tree Mapping Algorithms, Yuanrui Fan, Xin Xia, David Lo, Ahmed E. Hassan, Yuan Wang, Shanping Li
Research Collection School Of Computing and Information Systems
Abstract syntax tree (AST) mapping algorithms are widely used to analyze changes in source code. Despite the foundational role of AST mapping algorithms, little effort has been made to evaluate the accuracy of AST mapping algorithms, i.e., the extent to which an algorithm captures the evolution of code. We observe that a program element often has only one best-mapped program element. Based on this observation, we propose a hierarchical approach to automatically compare the similarity of mapped statements and tokens by different algorithms. By performing the comparison, we determine if eachof the compared algorithms generates inaccurate mappings for a statement …
Unveiling The Mystery Of Api Evolution In Deep Learning Frameworks: A Case Study Of Tensorflow 2,
2021
Singapore Management University
Unveiling The Mystery Of Api Evolution In Deep Learning Frameworks: A Case Study Of Tensorflow 2, Zejun Zhang, Yanming Yang, Xin Xia, David Lo, Xiaoxue Ren, John C. Grundy
Research Collection School Of Computing and Information Systems
API developers have been working hard to evolve APIs to provide more simple, powerful, and robust API libraries. Although API evolution has been studied for multiple domains, such as Web and Android development, API evolution for deep learning frameworks has not yet been studied. It is not very clear how and why APIs evolve in deep learning frameworks, and yet these are being more and more heavily used in industry. To fill this gap, we conduct a large-scale and in-depth study on the API evolution of Tensorflow 2, which is currently the most popular deep learning framework. We first extract …
A Smarter Way To Manage Mass Transit In A Smart City: Rail Network Management At Singapore’S Land Transport Authority,
2021
Singapore Management University
A Smarter Way To Manage Mass Transit In A Smart City: Rail Network Management At Singapore’S Land Transport Authority, Steven M. Miller, Thomas H. Davenport
Research Collection School Of Computing and Information Systems
There is no widely agreed upon definition of a supposed “Smart City.” Yet, when you see city employees — in this case city-state employees — working in what are obviously smarter ways, “you know it when you see it.” One such example of a smarter way to work in a smart city setting is the way that employees of the Land Transport Authority (LTA) in Singapore are using a new generation of data driven, AI-enabled support systems to manage the city’s urban rail network. We spoke to LTA officers Kong Wai, Ho (Director of Integrated Operations and Planning) and Chris …
Approximate Difference Rewards For Scalable Multigent Reinforcement Learning,
2021
Singapore Management University
Approximate Difference Rewards For Scalable Multigent Reinforcement Learning, Arambam James Singh, Akshat Kumar, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
We address the problem ofmultiagent credit assignment in a large scale multiagent system. Difference rewards (DRs) are an effective tool to tackle this problem, but their exact computation is known to be challenging even for small number of agents. We propose a scalable method to compute difference rewards based on aggregate information in a multiagent system with large number of agents by exploiting the symmetry present in several practical applications. Empirical evaluation on two multiagent domains - air-traffic control and cooperative navigation, shows better solution quality than previous approaches.
A Matheuristic Algorithm For The Vehicle Routing Problem With Cross-Docking,
2021
Singapore Management University
A Matheuristic Algorithm For The Vehicle Routing Problem With Cross-Docking, Aldy Gunawan, Audrey Tedja Widjaja, Pieter Vansteenwegen, Vincent F. Yu
Research Collection School Of Computing and Information Systems
This paper studies the integration of the vehicle routing problem with cross-docking (VRPCD). The aim is to find a set of routes to deliver products from a set of suppliers to a set of customers through a cross-dock facility, such that the operational and transportation costs are minimized, without violating the vehicle capacity and time horizon constraints. A two-phase matheuristic based on column generation is proposed. The first phase focuses on generating a set of feasible candidate routes in both pickup and delivery processes by implementing an adaptive large neighborhood search algorithm. A set of destroy and repair operators are …
Adaptive Operating Hours For Improved Performance Of Taxi Fleets,
2021
Singapore Management University
Adaptive Operating Hours For Improved Performance Of Taxi Fleets, Rajiv Ranjan Kumar, Pradeep Varakantham, Shih-Fen Cheng
Research Collection School Of Computing and Information Systems
Taxi fleets and car aggregation systems are an important component of the urban public transportation system. Taxis and cars in taxi fleets and car aggregation systems (e.g., Uber) are dependent on a large number of self-controlled and profit-driven taxi drivers, which introduces inefficiencies in the system. There are two ways in which taxi fleet performance can be optimized: (i) Operational decision making: improve assignment of taxis/cars to customers, while accounting for future demand; (ii) strategic decision making: optimize operating hours of (taxi and car) drivers. Existing research has primarily focused on the operational decisions in (i) and we focus on …
Artificial Intelligence And Self-Driving Vehicles – Trust Issue,
2021
Singapore Management University
Artificial Intelligence And Self-Driving Vehicles – Trust Issue, Ru Lian, Keng Siau
Research Collection School Of Computing and Information Systems
One of the most prominent applications of artificial intelligence technologies is self-driving vehicles. Self-driving vehicles are expected to be widely available soon. Do consumers trust self-driving vehicles? Trust in self-driving technology will impact the adoption and utilization of autonomous driving technology. What are the trust issues that the consumers will be concerned about? We used a qualitative methodology in this research to identify the trust issues of consumers.
Dynamic Task Allocation In Partially Defined Environments Using A* With Bounded Costs,
2021
Embry-Riddle Aeronautical University
Dynamic Task Allocation In Partially Defined Environments Using A* With Bounded Costs, James Hendrickson
Doctoral Dissertations and Master's Theses
The sector of maritime robotics has seen a boom in operations in areas such as surveying and mapping, clean-up, inspections, search and rescue, law enforcement, and national defense. As this sector has continued to grow, there has been an increased need for single unmanned systems to be able to undertake more complex and greater numbers of tasks. As the maritime domain can be particularly difficult for autonomous vehicles to operate in due to the partially defined nature of the environment, it is crucial that a method exists which is capable of dynamically accomplishing tasks within this operational domain. By considering …
Exploring Ai And Multiplayer In Java,
2021
Minnesota State University Moorhead
Exploring Ai And Multiplayer In Java, Ronni Kurtzhals
Student Academic Conference
I conducted research into three topics: artificial intelligence, package deployment, and multiplayer servers in Java. This research came together to form my project presentation on the implementation of these topics, which I felt accurately demonstrated the various things I have learned from my courses at Moorhead State University. Several resources were consulted throughout the project, including the work of W3Schools and StackOverflow as well as relevant assignments and textbooks from previous classes. I found this project relevant to computer science and information systems for several reasons, such as the AI component and use of SQL data tables; but it was …
Exploring Complementary Strengths Of Invariant And Equivariant Representations For Few-Shot Learning,
2021
Center for Research in Computer Vision
Exploring Complementary Strengths Of Invariant And Equivariant Representations For Few-Shot Learning, Mamshad Nayeem Rizve, Salman Khan, Fahad Shahbaz Khan, Mubarak Shah
Computer Vision Faculty Publications
In many real-world problems, collecting a large number of labeled samples is infeasible. Few-shot learning (FSL) is the dominant approach to address this issue, where the objective is to quickly adapt to novel categories in presence of a limited number of samples. FSL tasks have been predominantly solved by leveraging the ideas from gradient-based meta-learning and metric learning approaches. However, recent works have demonstrated the significance of powerful feature representations with a simple embedding network that can outperform existing sophisticated FSL algorithms. In this work, we build on this insight and propose a novel training mechanism that simultaneously enforces equivariance …
Mesoscopic Traffic Simulation Model And Calibration Considering Stretching-Segment Design,
2021
1. Research Center of Intelligent Transport System, Sun Yat-Sen University, Guangzhou 510006, China; ;2. Guangdong Provincial Key Laboratory of Intelligent Transport System, Guangzhou 510006, China; ;
Mesoscopic Traffic Simulation Model And Calibration Considering Stretching-Segment Design, Zhaocheng He, Xuanhua Lin, Peilin Nie, Ronghui Zhang
Journal of System Simulation
Abstract: In order to make the simulation model fit the characteristics of urban traffic, both high accuracy and high performance, a lightweight mesoscopic traffic simulation system and the process of calibration are established. The speed-density model and vertical queue model are equivalent to the vehicle movement processes, the simulation accuracy and calibration efficiency are improved by the stretching-segment design at urban intersections of vertical queuing model, and the real individual vehicle information is used as the calibration data source. The application of the model in Xuancheng urban road network shows that, compared with the vertical queuing model, it can …
Modeling And Simulation Of Electric Vehicle Industry Development Based On System Dynamics,
2021
The Center of Collaboration and Innovation, Jiangxi University of Technology, Nanchang 330098, China;
Modeling And Simulation Of Electric Vehicle Industry Development Based On System Dynamics, Yueqiang Fu, Tiantian Xia
Journal of System Simulation
Abstract: New energy electric vehicle are the main trend of automobile industry upgrading. It plays an important role in ensuring the energy security and improving the ecological environment. It is of theoretical and practical significance to carry out research on the development of new energy electric vehicles. The affecting factors are systematically analyzed, the causal relationship model and stock flow model are established, and the dynamic equation of the model are determined and the parameter assignments are made. The model is verified and the system simulation and analysis are performed. The development trend and main influencing factors of …
Research On Some Questions Of Simulation Body Of Knowledge,
2021
1. College of Systems Engineering, National University of Defense Technology, Changsha 410073, China; ;2. The PLA's 31002 Unit, Beijing 100094, China;
Research On Some Questions Of Simulation Body Of Knowledge, Xiaogang Qiu, Duan Hong, Xie Xu, Bin Chen
Journal of System Simulation
Abstract: Simulation body of knowledge (BOK) is the knowledge required to conduct Modeling and Simulation (M&S) activities, which is a logic system consisting of concepts, propositions, and inferences that are tightly related to each other. The simulation BOK organizes the M&S knowledge in a hierarchical way, reflects the composition and structure of the knowledge in the M&S domain. The establishment of the simulation BOK is crucial to advance the M&S research and education. The requirements for establishing the simulation BOK are summarized, three basic features of the simulation knowledge, practical, systematical, and epochal are discussed, the challenges of establishing the …
Research On Combat Simulation Body Of Knowledge,
2021
1. College of Systems Engineering, National University of Defense Technology, Changsha 410073, China; ;
Research On Combat Simulation Body Of Knowledge, Xie Xu, Xiaogang Qiu, Duan Hong, Kedi Huang
Journal of System Simulation
Abstract: Combat simulation is an important research method in modern military domain, since it provides a virtual battlespace for entities of various types that are involved in a battle to interact with each other. Over last several decades, combat simulation has been widely applied in different applications, and as a result the body of knowledge of combat simulation has been extended a lot. The relevant articles and textbooks in combat simulation are extensively investigated, and a three-layer structure to organize the body of knowledge of combat simulation is proposed. Eleven knowledge areas that should be included in the combat simulation …
