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Articles 5731 - 5760 of 8722
Full-Text Articles in Entire DC Network
Bridging The Vocabulary Gap Between Health Seekers And Healthcare Knowledge, Liqiang Nie, Yiliang Zhao, Akbari Mohammad, Jialie Shen, Tat-Seng Chua
Bridging The Vocabulary Gap Between Health Seekers And Healthcare Knowledge, Liqiang Nie, Yiliang Zhao, Akbari Mohammad, Jialie Shen, Tat-Seng Chua
Research Collection School Of Computing and Information Systems
The vocabulary gap between health seekers and providers has hindered the cross-system operability and the interuser reusability. To bridge this gap, this paper presents a novel scheme to code the medical records by jointly utilizing local mining and global learning approaches, which are tightly linked and mutually reinforced. Local mining attempts to code the individual medical record by independently extracting the medical concepts from the medical record itself and then mapping them to authenticated terminologies. A corpus-aware terminology vocabulary is naturally constructed as a byproduct, which is used as the terminology space for global learning. Local mining approach, however, may …
On Processing Reverse K-Skyband And Ranked Reverse Skyline Queries, Yunjun Gao, Qing Liu, Baihua Zheng, Mou Li, Gang Chen, Qing Li
On Processing Reverse K-Skyband And Ranked Reverse Skyline Queries, Yunjun Gao, Qing Liu, Baihua Zheng, Mou Li, Gang Chen, Qing Li
Research Collection School Of Computing and Information Systems
In this paper, for the first time, we identify and solve the problem of efficient reverse k-skyband (RkSB) query processing. Given a set P of multi-dimensional points and a query point q, an RkSB query returns all the points in P whose dynamic k-skyband contains q. We formalize RkSB retrieval, and then propose five algorithms for computing the RkSB of an arbitrary query point efficiently. Our methods utilize a conventional data-partitioning index (e.g., R-tree) on the dataset, and employ pre-computation, reuse and pruning techniques to boost the query efficiency. In addition, we extend our solutions to tackle an interesting variant …
Simapp: A Framework For Detecting Similar Mobile Applications By Online Kernel Learning, Ning Chen, Steven C. H. Hoi, Shaohua Li, Xiaokui Xiao
Simapp: A Framework For Detecting Similar Mobile Applications By Online Kernel Learning, Ning Chen, Steven C. H. Hoi, Shaohua Li, Xiaokui Xiao
Research Collection School Of Computing and Information Systems
With the popularity of smart phones and mobile devices, the number of mobile applications (a.k.a. "apps") has been growing rapidly. Detecting semantically similar apps from a large pool of apps is a basic and important problem, as it is beneficial for various applications, such as app recommendation, app search, etc. However, there is no systematic and comprehensive work so far that focuses on addressing this problem. In order to fill this gap, in this paper, we explore multi-modal heterogeneous data in app markets (e.g., description text, images, user reviews, etc.), and present "SimApp" -- a novel framework for detecting similar …
Will This Be Quick? A Case Study Of Bug Resolution Times Across Industrial Projects, Subhajit Datta, Prasanth Lade
Will This Be Quick? A Case Study Of Bug Resolution Times Across Industrial Projects, Subhajit Datta, Prasanth Lade
Research Collection School Of Computing and Information Systems
Resolution of problem tickets is a source of significant revenue in the worldwide software services industry. Due to the high volume of problem tickets in any large scale customer engagement, automated techniques are necessary to segregate related incoming tickets into groups. Existing techniques focus on this classification problem. In this paper, we present a case study built around the position that predicting the category of resolution times within a class of tickets and also the actual resolution times, is strongly beneficial to ticket resolution. We present an approach based on topic analysis to predict the category of resolution times of …
Analysis And Improvement On A Biometric-Based Remote User Authentication Scheme Using Smart Cards, Fengtong Wen, Willy Susilo, Guomin Yang
Analysis And Improvement On A Biometric-Based Remote User Authentication Scheme Using Smart Cards, Fengtong Wen, Willy Susilo, Guomin Yang
Research Collection School Of Computing and Information Systems
In a recent paper (BioMed Research International, 2013/491289), Khan et al. proposed an improved biometrics-based remote user authentication scheme with user anonymity. The scheme is believed to be secure against password guessing attack, user impersonation attack, server masquerading attack, and provide user anonymity, even if the secret information stored in the smart card is compromised. In this paper, we analyze the security of Khan et al.’s scheme, and demonstrate that their scheme doesn’t provide user anonymity. This also renders that their scheme is insecure against other attacks, such as off-line password guessing attack, user impersonation attacks. Subsequently, we propose a …
Biometric Authentication On Iphone And Android: Usability, Perceptions, And Influences On Adoption, Rasekhar Bhagavatula, Blase Ur, Kevin Iacovino, Su Mon Kywe, Lorrie Faith Cranor, Marios Savvides
Biometric Authentication On Iphone And Android: Usability, Perceptions, And Influences On Adoption, Rasekhar Bhagavatula, Blase Ur, Kevin Iacovino, Su Mon Kywe, Lorrie Faith Cranor, Marios Savvides
Research Collection School Of Computing and Information Systems
While biometrics have long been promoted as the future of authentication, the recent introduction of Android face unlock and iPhone fingerprint unlock are among the first large-scale deployments of biometrics for consumers. In a 10-participant, within-subjects lab study and a 198-participant online survey, we investigated the usability of these schemes, along with users ’ experiences, attitudes, and adoption decisions. Participants in our lab study found both face unlock and fingerprint unlock easy to use in typical scenarios. The notable exception was that face unlock was completely unusable in a dark room. Most participants preferred fingerprint unlock over face unlock or …
Leakage-Resilient Password Entry: Challenges, Design, And Evaluation, Qiang Yan, Jin Han, Yingjiu Li, Jianying Zhou, Robert H. Deng
Leakage-Resilient Password Entry: Challenges, Design, And Evaluation, Qiang Yan, Jin Han, Yingjiu Li, Jianying Zhou, Robert H. Deng
Research Collection School Of Computing and Information Systems
Password leakage is one of the most serious threats for password-based user authentication. Although this problem has been extensively investigated over the last two decades, there is still no widely adopted solution. In this paper, we attempt to systematically understand the challenges behind this problem and investigate the feasibility of solving it. Since password leakage usually happens when a password is input during authentication, we focus on designing leakage-resilient password entry (LRPE) schemes in this study. We develop a broad set of design criteria and use them to construct a practical LRPE scheme named CoverPad, which not only improves leakage …
Integrated Intelligence For Human-Robot Teams, Jean Oh, Et. Al.
Integrated Intelligence For Human-Robot Teams, Jean Oh, Et. Al.
Research Collection School Of Computing and Information Systems
With recent advances in robotics technologies and autonomous systems, the idea of human-robot teams is gaining ever-increasing attention. In this context, our research focuses on developing an intelligent robot that can autonomously perform non-trivial, but specific tasks conveyed through natural language. Toward this goal, a consortium of researchers develop and integrate various types of intelligence into mobile robot platforms, including cognitive abilities to reason about high-level missions, perception to classify regions and detect relevant objects in an environment, and linguistic abilities to associate instructions with the robot’s world model and to communicate with human teammates in a natural way. This …
Improving Software Quality And Productivity Leveraging Mining Techniques: [Summary Of The Second Workshop On Software Mining, At Ase 2013], Ming Li, Hongyu Zhang, David Lo, Lucia Lucia
Improving Software Quality And Productivity Leveraging Mining Techniques: [Summary Of The Second Workshop On Software Mining, At Ase 2013], Ming Li, Hongyu Zhang, David Lo, Lucia Lucia
Research Collection School Of Computing and Information Systems
The second International Workshop on Software Mining (Soft-mine) was held on the 11th of November 2013. The workshop was held in conjunction with the 28th IEEE/ACM International Conference on Automated Software Engineering (ASE) in Silicon Valley, California, USA. The workshop has facilitated researchers who are interested in mining various types of software-related data and in applying data mining techniques to support software engineering tasks. During the workshop, seven papers on software mining and behavior models, execution trace mining, and bug localization and fixing were presented. One of the papers received the best paper award. Furthermore, there were two invited talk …
Are Features Equally Representative? A Feature-Centric Recommendation, Chenyi Zhang, Ke Wang, Ee-Peng Lim, Qinneng Xu, Jianling Sun, Hongkun Yu
Are Features Equally Representative? A Feature-Centric Recommendation, Chenyi Zhang, Ke Wang, Ee-Peng Lim, Qinneng Xu, Jianling Sun, Hongkun Yu
Research Collection School Of Computing and Information Systems
Typically a user prefers an item (e.g., a movie) because she likes certain features of the item (e.g., director, genre, producer). This observation motivates us to consider a feature-centric recommendation approach to item recommendation: instead of directly predicting the rating on items, we predict the rating on the features of items, and use such ratings to derive the rating on an item. This approach offers several advantages over the traditional item-centric approach: it incorporates more information about why a user chooses an item, it generalizes better due to the denser feature rating data, it explains the prediction of item ratings …
Reputationpro: The Efficient Approaches To Contextual Transaction Trust Computation In E-Commerce Environments, Haibin Zhang, Yan Wang, Xiuzhen Zhang, Ee Peng Lim
Reputationpro: The Efficient Approaches To Contextual Transaction Trust Computation In E-Commerce Environments, Haibin Zhang, Yan Wang, Xiuzhen Zhang, Ee Peng Lim
Research Collection School Of Computing and Information Systems
In e-commerce environments, the trustworthiness of a seller is utterly important to potential buyers, especially when a seller is not known to them. Most existing trust evaluation models compute a single value to reflect the general trustworthiness of a seller without taking any transaction context information into account. With such a result as the indication of reputation, a buyer may be easily deceived by a malicious seller in a transaction where the notorious value imbalance problem is involved—in other words, a malicious seller accumulates a high-level reputation by selling cheap products and then deceives buyers by inducing them to purchase …
Multidimensional Context Awareness In Mobile Devices, Zhuo Wei, Robert H. Deng, Jialie Shen, Jixiang Zhu, Kun Ouyang, Yongdong Wu
Multidimensional Context Awareness In Mobile Devices, Zhuo Wei, Robert H. Deng, Jialie Shen, Jixiang Zhu, Kun Ouyang, Yongdong Wu
Research Collection School Of Computing and Information Systems
With the increase of mobile computation ability and the development of wireless network transmission technology, mobile devices not only are the important tools of personal life (e.g., education and entertainment), but also emerge as indispensable "secretary" of business activities (e.g., email and phone call). However, since mobile devices could work under complex and dynamic local and network conditions, they are vulnerable to local and remote security attacks. In real applications, different kinds of data protection are required by various local contexts. To provide appropriate protection, we propose a multidimensional context (MContext) scheme to comprehensively model and characterize the scene and …
Travel Recommendation Via Author Topic Model Based Collaborative Filtering, Shuhui Jiang, Xueming Qian, Jialie Shen, Tao Mei
Travel Recommendation Via Author Topic Model Based Collaborative Filtering, Shuhui Jiang, Xueming Qian, Jialie Shen, Tao Mei
Research Collection School Of Computing and Information Systems
While automatic travel recommendation has attracted a lot of attentions, the existing approaches generally suffer from different kinds of weaknesses. For example, sparsity problem can significantly degrade the performance of traditional collaborative filtering (CF). If a user only visits very few locations, accurate similar user identification becomes very challenging due to lack of sufficient information. Motivated by this concern, we propose an Author Topic Collaborative Filtering (ATCF) method to facilitate comprehensive Points of Interest (POIs) recommendation for social media users. In our approach, the topics about user preference (e.g., cultural, cityscape, or landmark) are extracted from the textual description of …
Risk Based Optimization For Improving Emergency Medical Systems, Sandhya Saisubramanian, Pradeep Varakantham, Hoong Chuin Lau
Risk Based Optimization For Improving Emergency Medical Systems, Sandhya Saisubramanian, Pradeep Varakantham, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
In emergency medical systems, arriving at the incident location a few seconds early can save a human life. Thus, this paper is motivated by the need to reduce the response time – time taken to arrive at the incident location after receiving the emergency call – of Emergency Response Vehicles, ERVs (ex: ambulances, fire rescue vehicles) for as many requests as possible. We expect to achieve this primarily by positioning the "right" number of ERVs at the "right" places and at the "right" times. Given the exponentially large action space (with respect to number of ERVs and their placement) and …
Community Discovery From Social Media By Low-Rank Matrix Recovery, Jinfeng Zhuang, Mei Tao, Steven C. H. Hoi, Xian-Sheng Hua, Yongdong Zhang
Community Discovery From Social Media By Low-Rank Matrix Recovery, Jinfeng Zhuang, Mei Tao, Steven C. H. Hoi, Xian-Sheng Hua, Yongdong Zhang
Research Collection School Of Computing and Information Systems
The pervasive usage and reach of social media have attracted a surge of attention in the multimedia research community. Community discovery from social media has therefore become an important yet challenging issue. However, due to the subjective generating process, the explicitly observed communities (e.g., group-user and user-user relationship) are often noisy and incomplete in nature. This paper presents a novel approach to discovering communities from social media, including the group membership and user friend structure, by exploring a low-rank matrix recovery technique. In particular, we take Flickr as one exemplary social media platform. We first model the observed indicator matrix …
Push Or Pull? A Website's Strategic Choice Of Content Delivery Mechanism, Dan Ma
Push Or Pull? A Website's Strategic Choice Of Content Delivery Mechanism, Dan Ma
Research Collection School Of Computing and Information Systems
Really simple syndication (RSS) technology enables an alternative delivery mechanism for online content. Instead of waiting passively for users to pull online content out, websites can push it to potential users through RSS. This is expected to significantly affect user behavior, website profitability, and market equilibrium. This research uses an economic model to study the impact of RSS adoption and examine whether it increases a website’s profit and competitive advantage. The findings are intriguing: they demonstrate that RSS can either increase or decrease website profit. In a competitive context, RSS adoption can actually be a disadvantage; in some cases, it …
Solving Uncertain Mdps With Objectives That Are Separable Over Instantiations Of Model Uncertainty, Yossiri Adulyasak, Pradeep Varakantham, Asrar Ahmed, Patrick Jaillet
Solving Uncertain Mdps With Objectives That Are Separable Over Instantiations Of Model Uncertainty, Yossiri Adulyasak, Pradeep Varakantham, Asrar Ahmed, Patrick Jaillet
Research Collection School Of Computing and Information Systems
Markov Decision Problems, MDPs offer an effective mechanism for planning under uncertainty. However, due to unavoidable uncertainty over models, it is difficult to obtain an exact specification of an MDP. We are interested in solving MDPs, where transition and reward functions are not exactly specified. Existing research has primarily focussed on computing infinite horizon stationary policies when optimizing robustness, regret and percentile based objectives. We focus specifically on finite horizon problems with a special emphasis on objectives that are separable over individual instantiations of model uncertainty (i.e., objectives that can be expressed as a sum over instantiations of model uncertainty): …
Ciphercard: A Token-Based Approach Against Camera-Based Shoulder Surfing Attacks On Common Touchscreen Devices, Teddy Seyed, Xing-Dong Yang, Anthony Tang, Saul Greenberg, Jiawei Gu, Bin Zhu, Xiang Ciao
Ciphercard: A Token-Based Approach Against Camera-Based Shoulder Surfing Attacks On Common Touchscreen Devices, Teddy Seyed, Xing-Dong Yang, Anthony Tang, Saul Greenberg, Jiawei Gu, Bin Zhu, Xiang Ciao
Research Collection School Of Computing and Information Systems
We present CipherCard, a physical token that defends against shoulder-surfing attacks on user authentication on capacitive touchscreen devices. When CipherCard is placed over a touchscreen’s pin-pad, it remaps a user’s touch point on the physical token to a different location on the pin-pad. It hence translates a visible user password into a different system password received by a touchscreen, but is hidden from observers as well as the user. CipherCard enhances authentication security through Two-Factor Authentication (TFA), in that both the correct user password and a specific card are needed for successful authentication. We explore the design space of CipherCard, …
Stability Of Transportation Networks Under Adaptive Routing Policies, Sebastien Boyer, Sebastien Blandin, Laura Wynter
Stability Of Transportation Networks Under Adaptive Routing Policies, Sebastien Boyer, Sebastien Blandin, Laura Wynter
Research Collection School Of Computing and Information Systems
Growing concerns regarding urban congestion, and the recent explosion of mobile devices able to provide real-time information to traffic users have motivated increasing reliance on real-time route guidance for the online management of traffic networks. However, while the theory of traffic equilibria is very well-known, much fewer results exist on the stability of such equilibria, especially in the context of adaptive routing policy. In this work, we consider the problem of characterizing the stability properties of traffic equilibria in the context of online adaptive route choice induced by GPS-based decision making. We first extend the recent framework of “Markovian Traffic …
Mechanism Design For Near Real-Time Retail Payment And Settlement Systems, Zhiling Guo, Robert John Kauffman, Mei Lin, Dan Ma
Mechanism Design For Near Real-Time Retail Payment And Settlement Systems, Zhiling Guo, Robert John Kauffman, Mei Lin, Dan Ma
Research Collection School Of Computing and Information Systems
have made extensive use of interbank netting systems, in which payments are accumulated for end-of-day settlement. This approach, known as deferred net settlement (DNS), reduces the liquidity needs of a payment system, but bears inherent operational risks. As large dollar volumes of retail payments accumulate swiftly, real-time gross settlement (RTGS) is an attractive option. It permits immediate settlement of transactions during the day, but it brings up other risks that require consideration. We propose a hybrid payment management system involving elements of both DNS and RTGS. We explore several hybrid system mechanism designs to allow payment prioritization, reduce payment delays, …
Software Puzzle: A Countermeasure To Resource-Inflated Denial-Of-Service Attacks, Yongdong Wu, Zhigang Zhao, Bao Feng, Robert H. Deng
Software Puzzle: A Countermeasure To Resource-Inflated Denial-Of-Service Attacks, Yongdong Wu, Zhigang Zhao, Bao Feng, Robert H. Deng
Research Collection School Of Computing and Information Systems
Denial-of-service (DoS) and distributed DoS (DDoS) are among the major threats to cyber-security, and client puzzle, which demands a client to perform computationally expensive operations before being granted services from a server, is a well-known countermeasure to them. However, an attacker can inflate its capability of DoS/DDoS attacks with fast puzzle-solving software and/or built-in graphics processing unit (GPU) hardware to significantly weaken the effectiveness of client puzzles. In this paper, we study how to prevent DoS/DDoS attackers from inflating their puzzle-solving capabilities. To this end, we introduce a new client puzzle referred to as software puzzle. Unlike the existing client …
An Adaptive Gradient Method For Online Auc Maximization, Yi Ding, Peilin Zhao, Steven C. H. Hoi, Yew-Soon Ong
An Adaptive Gradient Method For Online Auc Maximization, Yi Ding, Peilin Zhao, Steven C. H. Hoi, Yew-Soon Ong
Research Collection School Of Computing and Information Systems
Learning for maximizing AUC performance is an important research problem in machine learning. Unlike traditional batch learning methods for maximizing AUC which often suffer from poor scalability, recent years have witnessed some emerging studies that attempt to maximize AUC by single-pass online learning approaches. Despite their encouraging results reported, the existing online AUC maximization algorithms often adopt simple stochastic gradient descent approaches, which fail to exploit the geometry knowledge of the data observed in the online learning process, and thus could suffer from relatively slow convergence. To overcome the limitation of the existing studies, in this paper, we propose a …
The Knowledge Accumulation And Transfer In Open-Source Software (Oss) Development, Youngsoo Kim, Lingxiao Jiang
The Knowledge Accumulation And Transfer In Open-Source Software (Oss) Development, Youngsoo Kim, Lingxiao Jiang
Research Collection School Of Computing and Information Systems
We examine the learning curves of individual software developers in Open-Source Software (OSS) Development. We collected the dataset of multi-year code change histories from the repositories for 20 open source software projects involving more than 200 developers. We build and estimate regression models to assess individual developers' learning progress (in reducing the likelihood they make a bug). Our estimation results show that developer's coding and indirect bug-fixing experiences do not decrease bug ratios while bug-fixing experience can lead to the decrease of bug ratio of learning progress. We also find that developer's coding and bug-fixing experiences in other projects do …
Multi-User Multiple Input Multiple Output (Mimo) Communication With Distributed Antenna Systems In Wireless Networks, Karthikeyan Sundaresan, Mohammad Khojastepour, Sampath Rangarajan, Jie Xiong
Multi-User Multiple Input Multiple Output (Mimo) Communication With Distributed Antenna Systems In Wireless Networks, Karthikeyan Sundaresan, Mohammad Khojastepour, Sampath Rangarajan, Jie Xiong
Research Collection School Of Computing and Information Systems
A system and a method are provided. The method includes deploying a plurality of antennas of an access point or a base station as a distributed antenna system. The method further includes configuring the distributed antenna system for multi-user wireless transmissions by applying medium access techniques and power-balanced pre-coding at the access point or the base station. The method also includes providing device localization for devices communicating with the distributed antenna system by applying time-difference-of-arrival techniques to antenna pairs from among the plurality of antennas at the access point or the base station.
A Systematic Study On Explicit-State Non-Zenoness Checking For Timed Automata, Ting Wang, Jun Sun, Xinyu Wang, Yang Liu, Yuanjie Si, Jin Song Dong, Xiaohu Yang, Xiaohong Li
A Systematic Study On Explicit-State Non-Zenoness Checking For Timed Automata, Ting Wang, Jun Sun, Xinyu Wang, Yang Liu, Yuanjie Si, Jin Song Dong, Xiaohu Yang, Xiaohong Li
Research Collection School Of Computing and Information Systems
Zeno runs, where infinitely many actions occur within finite time, may arise in Timed Automata models. Zeno runs are not feasible in reality and must be pruned during system verification. Thus it is necessary to check whether a run is Zeno or not so as to avoid presenting Zeno runs as counterexamples during model checking. Existing approaches on non-Zenoness checking include either introducing an additional clock in the Timed Automata models or additional accepting states in the zone graphs. In addition, there are approaches proposed for alternative timed modeling languages, which could be generalized to Timed Automata. In this work, …
Saliency-Guided Color-To-Gray Conversion Using Region-Based Optimization, Hao Du, Shengfeng He, Bin Sheng, Lizhuang Ma, Rynson W.H. Lau
Saliency-Guided Color-To-Gray Conversion Using Region-Based Optimization, Hao Du, Shengfeng He, Bin Sheng, Lizhuang Ma, Rynson W.H. Lau
Research Collection School Of Computing and Information Systems
Image decolorization is a fundamental problem for many real-world applications, including monochrome printing and photograph rendering. In this paper, we propose a new color-to-gray conversion method that is based on a region-based saliency model. First, we construct a parametric color-to-gray mapping function based on global color information as well as local contrast. Second, we propose a region-based saliency model that computes visual contrast among pixel regions. Third, we minimize the salience difference between the original color image and the output grayscale image in order to preserve contrast discrimination. To evaluate the performance of the proposed method in preserving contrast in …
Ambiguous Optimistic Fair Exchange: Definition And Constructions, Qiong Huang, Guomin Yang, Duncan S. Wong, Willy Susilo
Ambiguous Optimistic Fair Exchange: Definition And Constructions, Qiong Huang, Guomin Yang, Duncan S. Wong, Willy Susilo
Research Collection School Of Computing and Information Systems
Optimistic fair exchange (OFE) is a protocol for solving the problem of exchanging items or services in a fair manner between two parties, a signer and a verifier, with the help of an arbitrator which is called in only when a dispute happens between the two parties. In almost all the previous work on OFE, after obtaining a partial signature from the signer, the verifier can present it to others and show that the signer has indeed committed itself to something corresponding to the partial signature even prior to the completion of the transaction. In some scenarios, this capability given …
Special Section: Economics, Electronic Commerce, And Competitive Strategy, Eric K. Clemons, Rajiv M. Dewan, Robert John Kauffman
Special Section: Economics, Electronic Commerce, And Competitive Strategy, Eric K. Clemons, Rajiv M. Dewan, Robert John Kauffman
Research Collection School Of Computing and Information Systems
The title of this year;s special section of selected papers, whose initial versionswere presented at the “Economics and Electronic Commerce,” and “Information Technologyand Competitive Strategy” mini-tracks of the 2001 Hawaii International Conferenceon Systems Science (HICSS), reflects the increasing convergence of ideas fromEconomics and Information Systems (IS) research. This convergence has been occurringover the last several years and is related to the developments in e-commerce. ISresearch has been rapidly coming of age, driven by the ever-increasing importance ofinformation technology (IT) in the marketplace, and the need for managers, investors,policy-makers, and the public to understand how to more effectively navigate in ourhighly …
Toward Mobile Robots Reasoning Like Humans, Jean Oh, Arne Suppe, Felix Duvallet, Abdeslam Boularias, Luis Navarro-Serment, Martial Hebert, Anthony Stentz, Jerry Vinokurov, Oscar Romero, Christian Lebiere, Robert Dean
Toward Mobile Robots Reasoning Like Humans, Jean Oh, Arne Suppe, Felix Duvallet, Abdeslam Boularias, Luis Navarro-Serment, Martial Hebert, Anthony Stentz, Jerry Vinokurov, Oscar Romero, Christian Lebiere, Robert Dean
Research Collection School Of Computing and Information Systems
Robots are increasingly becoming key players in human-robot teams. To become effective teammates, robots must possess profound understanding of an environment, be able to reason about the desired commands and goals within a specific context, and be able to communicate with human teammates in a clear and natural way. To address these challenges, we have developed an intelligence architecture that combines cognitive components to carry out high-level cognitive tasks, semantic perception to label regions in the world, and a natural language component to reason about the command and its relationship to the objects in the world. This paper describes recent …
Modeling Neuromorphic Persistent Firing Networks, Ning Ning, Guoqi Li, Wei He, Kejie Huang, Li Pan, Kiruthika Ramanathan, Rong Zhao, Luping Shi
Modeling Neuromorphic Persistent Firing Networks, Ning Ning, Guoqi Li, Wei He, Kejie Huang, Li Pan, Kiruthika Ramanathan, Rong Zhao, Luping Shi
Research Collection School Of Computing and Information Systems
Neurons are believed to be the brain computational engines of the brain. A recent discovery in neurophysiology reveals that interneurons can slowly integrate spiking, share the output across a coupled network of axons and respond with persistent firing even in the absence of input to the soma or dendrites, which has not been understood and could be very important for exploring the mechanism of human cognition. The conventional models are incapable of simulating the important newly-discovered phenomenon of persistent firing induced by axonal slow integration. In this paper, we propose a computationally efficient model of neurons through modeling the axon …