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Artificial Intelligence and Robotics Commons™
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- Artificial intelligence (2)
- Scheduling (2)
- 3D object detection (1)
- Adaptive Resonance Theory operations (1)
- Adaptive large neighborhood search (1)
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- Adversarial reinforcement learning (1)
- Airport management; taxi; demand prediction (1)
- Amazon Mechanical Turk (1)
- Application programs (1)
- Autonomous Learning 2012 (1)
- Bench-mark problems (1)
- Benchmark study (1)
- Body Area Networking (1)
- Cellular UAV (1)
- Class Incremental Learning (1)
- Column generation (1)
- Computer aided software engineering (1)
- Continual Learning (1)
- Cross-docking (1)
- Crowdsourced logistics (1)
- Crowdsourcing (1)
- Cyber-security operations center (1)
- Data flow analysis (1)
- Data-driven personas (1)
- Database (1)
- De-anonymization (1)
- Disambiguation (1)
- Disaster rescue (1)
- Dynamic environments (1)
- Economic efficiency (1)
Articles 1 - 24 of 24
Full-Text Articles in Artificial Intelligence and Robotics
Objectfusion: Multi-Modal 3d Object Detection With Object-Centric Fusion, Q. Cai, Y. Pan, T. Yao, Chong-Wah Ngo, T. Mei
Objectfusion: Multi-Modal 3d Object Detection With Object-Centric Fusion, Q. Cai, Y. Pan, T. Yao, Chong-Wah Ngo, T. Mei
Research Collection School Of Computing and Information Systems
Recent progress on multi-modal 3D object detection has featured BEV (Bird-Eye-View) based fusion, which effectively unifies both LiDAR point clouds and camera images in a shared BEV space. Nevertheless, it is not trivial to perform camera-to-BEV transformation due to the inherently ambiguous depth estimation of each pixel, resulting in spatial misalignment between these two multi-modal features. Moreover, such transformation also inevitably leads to projection distortion of camera image features in BEV space. In this paper, we propose a novel Object-centric Fusion (ObjectFusion) paradigm, which completely gets rid of camera-to-BEV transformation during fusion to align object-centric features across different modalities for …
Benchmarking Library Recognition In Tweets, Ting Zhang, Divya Prabha Chandrasekaran, Ferdian Thung, David Lo
Benchmarking Library Recognition In Tweets, Ting Zhang, Divya Prabha Chandrasekaran, Ferdian Thung, David Lo
Research Collection School Of Computing and Information Systems
Software developers often use social media (such as Twitter) to shareprogramming knowledge such as new tools, sample code snippets,and tips on programming. One of the topics they talk about is thesoftware library. The tweets may contain useful information abouta library. A good understanding of this information, e.g., on thedeveloper’s views regarding a library can be beneficial to weigh thepros and cons of using the library as well as the general sentimentstowards the library. However, it is not trivial to recognize whethera word actually refers to a library or other meanings. For example,a tweet mentioning the word “pandas" may refer to …
Improving Feature Generalizability With Multitask Learning In Class Incremental Learning, Dong Ma, Chi Ian Tang, Cecilia Mascolo
Improving Feature Generalizability With Multitask Learning In Class Incremental Learning, Dong Ma, Chi Ian Tang, Cecilia Mascolo
Research Collection School Of Computing and Information Systems
Many deep learning applications, like keyword spotting [1], [2], require the incorporation of new concepts (classes) over time, referred to as Class Incremental Learning (CIL). The major challenge in CIL is catastrophic forgetting, i.e., preserving as much of the old knowledge as possible while learning new tasks. Various techniques, such as regularization, knowledge distillation, and the use of exemplars, have been proposed to resolve this issue. However, prior works primarily focus on the incremental learning step, while ignoring the optimization during the base model training. We hypothesise that a more transferable and generalizable feature representation from the base model would …
Automated Taxi Queue Management At High-Demand Venues, Mengyu Ji, Shih-Fen Cheng
Automated Taxi Queue Management At High-Demand Venues, Mengyu Ji, Shih-Fen Cheng
Research Collection School Of Computing and Information Systems
In this paper, we seek to identify an effective management policy that could reduce supply-demand gaps at taxi queues serving high-density locations where demand surges frequently happen. Unlike current industry practice, which relies on broadcasting to attract taxis to come and serve the queue, we propose more proactive and adaptive approaches to handle demand surges. Our design objective is to reduce the cumulative supply-demand gaps as much as we could by sending notifications to individual taxis. To address this problem, we first propose a highly effective passenger demand prediction system that is based on the real-time flight arrival information. By …
A Lagrangian Column Generation Approach For The Probabilistic Crowdsourced Logistics Planning, Chung-Kyun Han, Shih-Fen Cheng
A Lagrangian Column Generation Approach For The Probabilistic Crowdsourced Logistics Planning, Chung-Kyun Han, Shih-Fen Cheng
Research Collection School Of Computing and Information Systems
In recent years we have increasingly seen the movement for the retail industry to move their operations online. Along the process, it has created brand new patterns for the fulfillment service, and the logistics service providers serving these retailers have no choice but to adapt. The most challenging issues faced by all logistics service providers are the highly fluctuating demands and the shortening response times. All these challenges imply that maintaining a fixed fleet will either be too costly or insufficient. One potential solution is to tap into the crowdsourced workforce. However, existing industry practices of relying on human planners …
When Program Analysis Meets Bytecode Search: Targeted And Efficient Inter-Procedural Analysis Of Modern Android Apps In Backdroid, Daoyuan Wu, Debin Gao, Robert H. Deng, Rocky Chang
When Program Analysis Meets Bytecode Search: Targeted And Efficient Inter-Procedural Analysis Of Modern Android Apps In Backdroid, Daoyuan Wu, Debin Gao, Robert H. Deng, Rocky Chang
Research Collection School Of Computing and Information Systems
Widely-used Android static program analysis tools,e.g., Amandroid and FlowDroid, perform the whole-app interprocedural analysis that is comprehensive but fundamentallydifficult to handle modern (large) apps. The average app size hasincreased three to four times over five years. In this paper, weexplore a new paradigm of targeted inter-procedural analysis thatcan skip irrelevant code and focus only on the flows of securitysensitive sink APIs. To this end, we propose a technique calledon-the-fly bytecode search, which searches the disassembled appbytecode text just in time when a caller needs to be located. In thisway, it guides targeted (and backward) inter-procedural analysisstep by step until reaching …
Adaptive Large Neighborhood Search For Vehicle Routing Problem With Cross-Docking, Aldy Gunawan, Audrey Tedja Widjaja, Pieter Vansteenwegen, Vincent F. Yu
Adaptive Large Neighborhood Search For Vehicle Routing Problem With Cross-Docking, Aldy Gunawan, Audrey Tedja Widjaja, Pieter Vansteenwegen, Vincent F. Yu
Research Collection School Of Computing and Information Systems
Cross-docking is considered as a method to manage and control the inventory flow, which is essential in the context of supply chain management. This paper studies the integration of the vehicle routing problem with cross-docking, namely VRPCD which has been extensively studied due to its ability to reducethe overall costs occurring in a supply chain network. Given a fleet of homogeneous vehicles for delivering a single type of product from suppliers to customers through a cross-dock facility, the objective of VRPCD is to determine the number of vehicles used and the corresponding vehicle routes, such that the vehicleoperational and transportation …
Skin-Mimo: Vibration-Based Mimo Communication Over Human Skin, Dong Ma, Yuezhong Wu, Ming Ding, Mahbub Hassan, Wen Hu
Skin-Mimo: Vibration-Based Mimo Communication Over Human Skin, Dong Ma, Yuezhong Wu, Ming Ding, Mahbub Hassan, Wen Hu
Research Collection School Of Computing and Information Systems
We explore the feasibility of Multiple-Input-Multiple-Output (MIMO) communication through vibrations over human skin. Using off-the-shelf motors and piezo transducers as vibration transmitters and receivers, respectively, we build a 2x2 MIMO testbed to collect and analyze vibration signals from real subjects. Our analysis reveals that there exist multiple independent vibration channels between a pair of transmitter and receiver, confirming the feasibility of MIMO. Unfortunately, the slow ramping of mechanical motors and rapidly changing skin channels make it impractical for conventional channel sounding based channel state information (CSI) acquisition, which is critical for achieving MIMO capacity gains. To solve this problem, we …
Sensing, Computing, And Communications For Energy Harvesting Iots: A Survey, Dong Ma, Guohao Lan, Mahbub Hassan, Wen Hu, Sajal K. Das
Sensing, Computing, And Communications For Energy Harvesting Iots: A Survey, Dong Ma, Guohao Lan, Mahbub Hassan, Wen Hu, Sajal K. Das
Research Collection School Of Computing and Information Systems
With the growing number of deployments of Internet of Things (IoT) infrastructure for a wide variety of applications, the battery maintenance has become a major limitation for the sustainability of such infrastructure. To overcome this problem, energy harvesting offers a viable alternative to autonomously power IoT devices, resulting in a number of battery-less energy harvesting IoTs (or EH-IoTs) appearing in the market in recent years. Standards activities are also underway, which involve wireless protocol design suitable for EH-IoTs as well as testing procedures for various energy harvesting methods. Despite the early commercial and standards activities, IoT sensing, computing and communications …
Enhancing Cellular Communications For Uavs Via Intelligent Reflective Surface, Dong Ma, Ming Ding, Mahbub Hassan
Enhancing Cellular Communications For Uavs Via Intelligent Reflective Surface, Dong Ma, Ming Ding, Mahbub Hassan
Research Collection School Of Computing and Information Systems
Intelligent reflective surfaces (IRSs) capable of reconfiguring their electromagnetic absorption and reflection properties in real-time are offering unprecedented opportunities to enhance wireless communication experience in challenging environments. In this paper, we analyze the potential of IRS in enhancing cellular communications for UAVs, which currently suffers from poor signal strength due to the down-tilt of base station antennas optimized to serve ground users. We consider deployment of IRS on building walls, which can be remotely configured by cellular base stations to coherently direct the reflected radio waves towards specific UAVs in order to increase their received signal strengths. Using the recently …
Two Can Play That Game: An Adversarial Evaluation Of A Cyber-Alert Inspection System, Ankit Shah, Arunesh Sinha, Rajesh Ganesan, Sushil Jajodia, Hasan Cam
Two Can Play That Game: An Adversarial Evaluation Of A Cyber-Alert Inspection System, Ankit Shah, Arunesh Sinha, Rajesh Ganesan, Sushil Jajodia, Hasan Cam
Research Collection School Of Computing and Information Systems
Cyber-security is an important societal concern. Cyber-attacks have increased in numbers as well as in the extent of damage caused in every attack. Large organizations operate a Cyber Security Operation Center (CSOC), which forms the first line of cyber-defense. The inspection of cyber-alerts is a critical part of CSOC operations (defender or blue team). Recent work proposed a reinforcement learning (RL) based approach for the defender’s decision-making to prevent the cyber-alert queue length from growing large and overwhelming the defender. In this article, we perform a red team (adversarial) evaluation of this approach. With the recent attacks on learning-based decision-making …
Worker Demographics And Earnings On Amazon Mechanical Turk: An Exploratory Analysis, Kotaro Hara, Kristy Milland, Benjamin V. Hanrahan, Chris Callison-Burch, Abigail Adams, Saiph Savage, Jeffrey P. Bigham
Worker Demographics And Earnings On Amazon Mechanical Turk: An Exploratory Analysis, Kotaro Hara, Kristy Milland, Benjamin V. Hanrahan, Chris Callison-Burch, Abigail Adams, Saiph Savage, Jeffrey P. Bigham
Research Collection School Of Computing and Information Systems
Prior research reported that workers on Amazon Mechanical Turk (AMT) are underpaid, earning about $2/h. But the prior research did not investigate the difference in wage due to worker characteristics (e.g., country of residence). We present the first data-driven analysis on wage gap on AMT. Using work log data and demographic data collected via online survey, we analyse the gap in wage due to different factors. We show that there is indeed wage gap; for example, workers in the U.S. earn $3.01/h while those in India earn $1.41/h on average.
Findings Of A User Study Of Automatically Generated Personas, Joni Salminen, Haewoon Kwak, Jisun An, Soon-Gyo Jung, Bernard J. Jansen
Findings Of A User Study Of Automatically Generated Personas, Joni Salminen, Haewoon Kwak, Jisun An, Soon-Gyo Jung, Bernard J. Jansen
Research Collection School Of Computing and Information Systems
We report findings and implications from a semi-naturalistic user study of a system for Automatic Persona Generation (APG) using large-scale audience data of an organization's social media channels conducted at the workplace of a major international corporation. Thirteen participants from a range of positions within the company engaged with the system in a use case scenario. We employed a variety of data collection methods, including mouse tracking and survey data, analyzing the data with a mixed method approach. Results show that having an interactive system may aid in keeping personas at the forefront while making customer-centric decisions and indicate that …
Fixation And Confusion: Investigating Eye-Tracking Participants' Exposure To Information In Personas, Joni Salminen, Bernard J. Jansen, Jisun An, Soon-Gyo Jung, Lene Nielsen, Haewoon Kwak
Fixation And Confusion: Investigating Eye-Tracking Participants' Exposure To Information In Personas, Joni Salminen, Bernard J. Jansen, Jisun An, Soon-Gyo Jung, Lene Nielsen, Haewoon Kwak
Research Collection School Of Computing and Information Systems
To more effectively convey relevant information to end users of persona profiles, we conducted a user study consisting of 29 participants engaging with three persona layout treatments. We were interested in confusion engendered by the treatments on the participants, and conducted a within-subjects study in the actual work environment, using eye-tracking and talk-aloud data collection. We coded the verbal data into classes of informativeness and confusion and correlated it with fixations and durations on the Areas of Interests recorded by the eye-tracking device. We used various analysis techniques, including Mann-Whitney, regression, and Levenshtein distance, to investigate how confused users differed …
Hiddencode: Hidden Acoustic Signal Capture With Vibration Energy Harvesting, Guohao Lan, Dong Ma, Mahbub Hassan, Wen Hu
Hiddencode: Hidden Acoustic Signal Capture With Vibration Energy Harvesting, Guohao Lan, Dong Ma, Mahbub Hassan, Wen Hu
Research Collection School Of Computing and Information Systems
The feasibility of using vibration energy harvesting (VEH) as an energy-efficient receiver for short-range acoustic data communication has been investigated recently. When data was encoded in acoustic signal within the energy harvesting frequency band and transmitted through a speaker, a VEH receiver was capable of decoding the data by processing the harvested energy signal. Although previous work created new opportunities for simultaneous energy harvesting and communication using the same hardware, the communication makes annoying sounds as the energy harvesting frequency band lies within the sensitive region of human auditory system. In this work, we present a novel modulation scheme to …
Proactive And Reactive Coordination Of Non-Dedicated Agent Teams Operating In Uncertain Environments, Pritee Agrawal, Pradeep Varakantham
Proactive And Reactive Coordination Of Non-Dedicated Agent Teams Operating In Uncertain Environments, Pritee Agrawal, Pradeep Varakantham
Research Collection School Of Computing and Information Systems
Domains such as disaster rescue, security patrolling etc. often feature dynamic environments where allocations of tasks to agents become ineffective due to unforeseen conditions that may require agents to leave the team. Agents leave the team either due to arrival of high priority tasks (e.g., emergency, accident or violation) or due to some damage to the agent. Existing research in task allocation has only considered fixed number of agents and in some instances arrival of new agents on the team. However, there is little or no literature that considers situations where agents leave the team after task allocation. To that …
Mechanism Design For Strategic Project Scheduling, Pradeep Varakantham, Na Fu
Mechanism Design For Strategic Project Scheduling, Pradeep Varakantham, Na Fu
Research Collection School Of Computing and Information Systems
Organizing large scale projects (e.g., Conferences, IT Shows, F1 race) requires precise scheduling of multiple dependent tasks on common resources where multiple selfish entities are competing to execute the individual tasks. In this paper, we consider a well studied and rich scheduling model referred to as RCPSP (Resource Constrained Project Scheduling Problem). The key change to this model that we consider in this paper is the presence of selfish entities competing to perform individual tasks with the aim of maximizing their own utility. Due to the selfish entities in play, the goal of the scheduling problem is no longer only …
Creating Autonomous Adaptive Agents In A Real-Time First-Person Shooter Computer Game, Di Wang, Ah-Hwee Tan
Creating Autonomous Adaptive Agents In A Real-Time First-Person Shooter Computer Game, Di Wang, Ah-Hwee Tan
Research Collection School Of Computing and Information Systems
Games are good test-beds to evaluate AI methodologies. In recent years, there has been a vast amount of research dealing with real-time computer games other than the traditional board games or card games. This paper illustrates how we create agents by employing FALCON, a self-organizing neural network that performs reinforcement learning, to play a well-known first-person shooter computer game called Unreal Tournament. Rewards used for learning are either obtained from the game environment or estimated using the temporal difference learning scheme. In this way, the agents are able to acquire proper strategies and discover the effectiveness of different weapons without …
Cognitive Architectures And Autonomy: Commentary And Response, Włodzisław Duch, Ah-Hwee Tan, Stan Franklin
Cognitive Architectures And Autonomy: Commentary And Response, Włodzisław Duch, Ah-Hwee Tan, Stan Franklin
Research Collection School Of Computing and Information Systems
This paper provides a very useful and promising analysis and comparison of current architectures of autonomous intelligent systems acting in real time and specific contexts, with all their constraints. The chosen issue of Cognitive Architectures and Autonomy is really a challenge for AI current projects and future research. I appreciate and endorse not only that challenge but many specific choices and claims; in particular: (i) that “autonomy” is a key concept for general intelligent systems; (ii) that “a core issue in cognitive architecture is the integration of cognitive processes ....”; (iii) the analysis of features and capabilities missing in current …
Provable De-Anonymization Of Large Datasets With Sparse Dimensions, Anupam Datta, Divya Sharma, Arunesh Sinha
Provable De-Anonymization Of Large Datasets With Sparse Dimensions, Anupam Datta, Divya Sharma, Arunesh Sinha
Research Collection School Of Computing and Information Systems
There is a significant body of empirical work on statistical de-anonymization attacks against databases containing micro-dataabout individuals, e.g., their preferences, movie ratings, or transactiondata. Our goal is to analytically explain why such attacks work. Specifically, we analyze a variant of the Narayanan-Shmatikov algorithm thatwas used to effectively de-anonymize the Netflix database of movie ratings. We prove theorems characterizing mathematical properties of thedatabase and the auxiliary information available to the adversary thatenable two classes of privacy attacks. In the first attack, the adversarysuccessfully identifies the individual about whom she possesses auxiliaryinformation (an isolation attack). In the second attack, the adversarylearns additional …
Preface: Trends In Natural And Machine Intelligence, Jonathan H. Chan, Ah-Hwee Tan
Preface: Trends In Natural And Machine Intelligence, Jonathan H. Chan, Ah-Hwee Tan
Research Collection School Of Computing and Information Systems
Trends in natural and machine intelligence are increasingly reflecting a convergence in these two well-established fields of study. The Third International Neural Network Society Winter Conference (INNS-WC 2012) was held in Bangkok, Thailand, on October 3-5, 2012. INNS-WC2012, with an aim to bring together scientists, practitioners, and students worldwide, to discuss the past, present, and future challenges and trends in the area of natural and machine intelligence. This event has been a bi-annual conference of the International Neural Network Society (INNS) to provide a forum for international researchers to exchange latest ideas and advances on neural networks and related discipline.
Organizing And Personalizing Intelligence Gathering From The Web, Hwee-Leng Ong, Ah-Hwee Tan, Jamie Ng, Pan Hong, Qiu-Xiang Li
Organizing And Personalizing Intelligence Gathering From The Web, Hwee-Leng Ong, Ah-Hwee Tan, Jamie Ng, Pan Hong, Qiu-Xiang Li
Research Collection School Of Computing and Information Systems
In this paper, we describe how an integrated web‐based application, code‐named FOCI (Flexible Organizer for Competitive Intelligence), can help the knowledge worker in the gathering, organizing, tracking and dissemination of competitive intelligence (CI). It combines the use of a novel user‐configurable clustering, trend analysis and visualization techniques to manage information gathered from the web. FOCI allows its users to define and personalize the organization of the information clusters according to their needs and preferences into portfolios. These personalized portfolios created are saved and can be subsequently tracked and shared with other users. The paper runs through an example to show …
Impact Of Automation On Process Control Decision-Making, Steven M. Miller, Susan R. Bereiter
Impact Of Automation On Process Control Decision-Making, Steven M. Miller, Susan R. Bereiter
Research Collection School Of Computing and Information Systems
This paper investigates changes in the process control of a vehicle assembly plant which had been modernized from a principally manual procedure to one that uses programmable automation extensively. Process control is defined as the information flow and decision-making required to perform basic process operations. We investigate the effects of implementing a computer-integrated production system on the amount and types of process control decision-making and on the distribution of process control decision-making between humans and machines. After automation, the emphasis on decisions regarding product quality specifications increased and the emphasis on decisions related to flexibility in handling a variety of …
Robotics And The Conservation Of Human Resources, Robert U. Ayres, Steven M. Miller
Robotics And The Conservation Of Human Resources, Robert U. Ayres, Steven M. Miller
Research Collection School Of Computing and Information Systems
Due to rapid expansion in the field of robotics, policy issues have arisen in regard to developing human skills to deal with the new technology and to deal with the obsolescent human skills which are the inevitable result of this growth pattern. Industrialists, educators, union leaders, and government officials must work cooperatively to insure that the coming changes are made with minimum disruption. Improved training methods and courses have to be developed for the skills needed to control, manage and supervise the new machines. Some of the ways in which this can be accomplished are through offering financial incentives for …