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Articles 5881 - 5910 of 11190
Full-Text Articles in Artificial Intelligence and Robotics
Statistical Potentials For Rna-Protein Interactions Optimized By Cma-Es, Takayuki Kimura, Nobuaki Yasuo, Masakazu Sekijima, Brooke Lustig
Statistical Potentials For Rna-Protein Interactions Optimized By Cma-Es, Takayuki Kimura, Nobuaki Yasuo, Masakazu Sekijima, Brooke Lustig
Faculty Research, Scholarly, and Creative Activity
Characterizing RNA-protein interactions remains an important endeavor, complicated by the difficulty in obtaining the relevant structures. Evaluating model structures via statistical potentials is in principle straight-forward and effective. However, given the relatively small size of the existing learning set of RNA-protein complexes optimization of such potentials continues to be problematic. Notably, interaction-based statistical potentials have problems in addressing large RNA-protein complexes. In this study, we adopted a novel strategy with covariance matrix adaptation (CMA-ES) to calculate statistical potentials, successfully identifying native docking poses.
Ai: Friend Or Foe? (And What Business Leaders Need To Know), Singapore Management University
Ai: Friend Or Foe? (And What Business Leaders Need To Know), Singapore Management University
Perspectives@SMU
Artificial intelligence presents significant opportunities for business – as well as not insignificant threats to humanity – and governance frameworks are urgently needed to create a fair and equitable future under AI
Design Of A Two-Echelon Freight Distribution System In Last-Mile Logistics Considering Covering Locations And Occasional Drivers, Vincent F. Yu, Panca Jodiawan, Ming-Lu Hou, Aldy Gunawan
Design Of A Two-Echelon Freight Distribution System In Last-Mile Logistics Considering Covering Locations And Occasional Drivers, Vincent F. Yu, Panca Jodiawan, Ming-Lu Hou, Aldy Gunawan
Research Collection School Of Computing and Information Systems
This research addresses a new variant of the vehicle routing problem, called the two-echelon vehicle routing problem with time windows, covering options, and occasional drivers (2E-VRPTW-CO-OD). In this problem, two types of fleets are available to serve customers, city freighters and occasional drivers (ODs), while two delivery options are available to customers, home delivery and alternative delivery. For customers choosing the alternative delivery, their demands are delivered to one of the available covering locations for them to pick up. The objective of 2E-VRPTW-CO-OD is to minimize the total cost consisting of routing costs, connection costs, and compensations paid to ODs …
Mlcatchup: Automated Update Of Deprecated Machine-Learning Apis In Python, Stefanus Agus Haryono, Thung Ferdian, David Lo, Julia Lawall, Lingxiao Jiang
Mlcatchup: Automated Update Of Deprecated Machine-Learning Apis In Python, Stefanus Agus Haryono, Thung Ferdian, David Lo, Julia Lawall, Lingxiao Jiang
Research Collection School Of Computing and Information Systems
Machine learning (ML) libraries are gaining vast popularity, especially in the Python programming language. Using the latest version of such libraries is recommended to ensure the best performance and security. When migrating to the latest version of a machine learning library, usages of deprecated APIs need to be updated, which is a time-consuming process. In this paper, we propose MLCatchUp, an automated API usage update tool for deprecated APIs of popular ML libraries written in Python. MLCatchUp automatically infers the required transformation to migrate usages of deprecated API through the differences between the deprecated and updated API signatures. MLCatchUp offers …
Target-Guided Emotion-Aware Chat Machine, Wei Wei, Jiayi Liu, Xianling Mao, Guibing Guo, Feida Zhu, Pan Zhou, Yuchong Hu, Shanshan Feng
Target-Guided Emotion-Aware Chat Machine, Wei Wei, Jiayi Liu, Xianling Mao, Guibing Guo, Feida Zhu, Pan Zhou, Yuchong Hu, Shanshan Feng
Research Collection School Of Computing and Information Systems
The consistency of a response to a given post at the semantic level and emotional level is essential for a dialogue system to deliver humanlike interactions. However, this challenge is not well addressed in the literature, since most of the approaches neglect the emotional information conveyed by a post while generating responses. This article addresses this problem and proposes a unified end-to-end neural architecture, which is capable of simultaneously encoding the semantics and the emotions in a post and leveraging target information to generate more intelligent responses with appropriately expressed emotions. Extensive experiments on real-world data demonstrate that the proposed …
Conquer: Contextual Query-Aware Ranking For Video Corpus Moment Retrieval, Zhijian Hou, Chong-Wah Ngo, W. K. Chan
Conquer: Contextual Query-Aware Ranking For Video Corpus Moment Retrieval, Zhijian Hou, Chong-Wah Ngo, W. K. Chan
Research Collection School Of Computing and Information Systems
This paper tackles a recently proposed Video Corpus Moment Retrieval task. This task is essential because advanced video retrieval applications should enable users to retrieve a precise moment from a large video corpus. We propose a novel CONtextual QUery-awarE Ranking (CONQUER) model for effective moment localization and ranking. CONQUER explores query context for multi-modal fusion and representation learning in two different steps. The first step derives fusion weights for the adaptive combination of multi-modal video content. The second step performs bi-directional attention to tightly couple video and query as a single joint representation for moment localization. As query context is …
Disambiguating Mentions Of Api Methods In Stack Overflow Via Type Scoping, Kien Luong, Ferdian Thung, David Lo
Disambiguating Mentions Of Api Methods In Stack Overflow Via Type Scoping, Kien Luong, Ferdian Thung, David Lo
Research Collection School Of Computing and Information Systems
Stack Overflow is one of the most popular venues for developers to find answers to their API-related questions. However, API mentions in informal text content of Stack Overflow are often ambiguous and thus it could be difficult to find the APIs and learn their usages. Disambiguating these API mentions is not trivial, as an API mention can match with names of APIs from different libraries or even the same one. In this paper, we propose an approach called DATYS to disambiguate API mentions in informal text content of Stack Overflow using type scoping. With type scoping, we consider API methods …
Burst-Induced Multi-Armed Bandit For Learning Recommendation, Rodrigo Alves, Antoine Ledent, Marius Kloft
Burst-Induced Multi-Armed Bandit For Learning Recommendation, Rodrigo Alves, Antoine Ledent, Marius Kloft
Research Collection School Of Computing and Information Systems
In this paper, we introduce a non-stationary and context-free Multi-Armed Bandit (MAB) problem and a novel algorithm (which we refer to as BMAB) to solve it. The problem is context-free in the sense that no side information about users or items is needed. We work in a continuous-time setting where each timestamp corresponds to a visit by a user and a corresponding decision regarding recommendation. The main novelty is that we model the reward distribution as a consequence of variations in the intensity of the activity, and thereby we assist the exploration/exploitation dilemma by exploring the temporal dynamics of the …
Towards Enriching Responses With Crowd-Sourced Knowledge For Task-Oriented Dialogue, Yingxu He, Lizi Liao, Zheng Zhang, Tat-Seng Chua
Towards Enriching Responses With Crowd-Sourced Knowledge For Task-Oriented Dialogue, Yingxu He, Lizi Liao, Zheng Zhang, Tat-Seng Chua
Research Collection School Of Computing and Information Systems
Task-oriented dialogue agents are built to assist users in completing various tasks. Generating appropriate responses for satisfactory task completion is the ultimate goal. Hence, as a convenient and straightforward way, metrics such as success rate, inform rate etc., have been widely leveraged to evaluate the generated responses. However, beyond task completion, there are several other factors that largely affect user satisfaction, which remain under-explored. In this work, we focus on analyzing different agent behavior patterns that lead to higher user satisfaction scores. Based on the findings, we design a neural response generation model EnRG. It naturally combines the power of …
Aessa Young Professionals Forum Webinar “Technologies And Skills That Will Gearup The Aerospace Industry Post Pandemic” - A Global Perspective With An Emphasis On South Africa October 2021, Linda Vee Weiland
Publications
A webinar presentation for AeSSA Young Professionals.
Eargate: Gait-Based User Identification With In-Ear Microphones, Andrea Ferlini, Dong Ma, Cecilia Mascolo
Eargate: Gait-Based User Identification With In-Ear Microphones, Andrea Ferlini, Dong Ma, Cecilia Mascolo
Research Collection School Of Computing and Information Systems
Human gait is a widely used biometric trait for user identification and recognition. Given the wide-spreading, steady diffusion of earworn wearables (Earables) as the new frontier of wearable devices, we investigate the feasibility of earable-based gait identification. Specifically, we look at gait-based identification from the sounds induced by walking and propagated through the musculoskeletal system in the body. Our system, EarGate, leverages an in-ear facing microphone which exploits the earable’s occlusion effect to reliably detect the user’s gait from inside the ear canal, without impairing the general usage of earphones. With data collected from 31 subjects, we show that EarGate …
Solarslam: Battery-Free Loop Closure For Indoor Localisation, Bo Wei, Weitao Xu, Chengwen Luo, Guillaume Zoppi, Dong Ma, Sen Wang
Solarslam: Battery-Free Loop Closure For Indoor Localisation, Bo Wei, Weitao Xu, Chengwen Luo, Guillaume Zoppi, Dong Ma, Sen Wang
Research Collection School Of Computing and Information Systems
In this paper, we propose SolarSLAM, a batteryfree loop closure method for indoor localisation. Inertial Measurement Unit (IMU) based indoor localisation method has been widely used due to its ubiquity in mobile devices, such as mobile phones, smartwatches and wearable bands. However, it suffers from the unavoidable long term drift. To mitigate the localisation error, many loop closure solutions have been proposed using sophisticated sensors, such as cameras, laser, etc. Despite achieving high-precision localisation performance, these sensors consume a huge amount of energy. Different from those solutions, the proposed SolarSLAM takes advantage of an energy harvesting solar cell as a …
Weakly-Supervised Video Anomaly Detection With Contrastive Learning Of Long And Short-Range Temporal Features, Yu Tian, Guansong Pang, Yuanhong Chen, Rajvinder Singh, Johan W. Verjans, Gustavo Carneiro
Weakly-Supervised Video Anomaly Detection With Contrastive Learning Of Long And Short-Range Temporal Features, Yu Tian, Guansong Pang, Yuanhong Chen, Rajvinder Singh, Johan W. Verjans, Gustavo Carneiro
Research Collection School Of Computing and Information Systems
Anomaly detection with weakly supervised video-level labels is typically formulated as a multiple instance learning (MIL) problem, in which we aim to identify snippets containing abnormal events, with each video represented as a bag of video snippets. Although current methods show effective detection performance, their recognition of the positive instances, i.e., rare abnormal snippets in the abnormal videos, is largely biased by the dominant negative instances, especially when the abnormal events are subtle anomalies that exhibit only small differences compared with normal events. This issue is exacerbated in many methods that ignore important video temporal dependencies. To address this issue, …
Constrained Contrastive Distribution Learning For Unsupervised Anomaly Detection And Localisation In Medical Images, Yu Tian, Guansong Pang, Fengbei Liu, Yuanhong Chen, Seon Ho Shin, Johan W. Verjans, Rajvinder Singh
Constrained Contrastive Distribution Learning For Unsupervised Anomaly Detection And Localisation In Medical Images, Yu Tian, Guansong Pang, Fengbei Liu, Yuanhong Chen, Seon Ho Shin, Johan W. Verjans, Rajvinder Singh
Research Collection School Of Computing and Information Systems
Unsupervised anomaly detection (UAD) learns one-class classifiers exclusively with normal (i.e., healthy) images to detect any abnormal (i.e., unhealthy) samples that do not conform to the expected normal patterns. UAD has two main advantages over its fully supervised counterpart. Firstly, it is able to directly leverage large datasets available from health screening programs that contain mostly normal image samples, avoiding the costly manual labelling of abnormal samples and the subsequent issues involved in training with extremely class-imbalanced data. Further, UAD approaches can potentially detect and localise any type of lesions that deviate from the normal patterns. One significant challenge faced …
Disentangling Hate In Online Memes, Ka Wei, Roy Lee, Rui Cao, Ziqing Fan, Jing Jiang, Wen Haw Chong
Disentangling Hate In Online Memes, Ka Wei, Roy Lee, Rui Cao, Ziqing Fan, Jing Jiang, Wen Haw Chong
Research Collection School Of Computing and Information Systems
Hateful and offensive content detection has been extensively explored in a single modality such as text. However, such toxic information could also be communicated via multimodal content such as online memes. Therefore, detecting multimodal hateful content has recently garnered much attention in academic and industry research communities. This paper aims to contribute to this emerging research topic by proposing DisMultiHate, which is a novel framework that performed the classification of multimodal hateful content. Specifically, DisMultiHate is designed to disentangle target entities in multimodal memes to improve the hateful content classification and explainability. We conduct extensive experiments on two publicly available …
Deep Fakes: The Algorithms That Create And Detect Them And The National Security Risks They Pose, Nick Dunard
Deep Fakes: The Algorithms That Create And Detect Them And The National Security Risks They Pose, Nick Dunard
James Madison Undergraduate Research Journal (JMURJ)
The dissemination of deep fakes for nefarious purposes poses significant national security risks to the United States, requiring an urgent development of technologies to detect their use and strategies to mitigate their effects. Deep fakes are images and videos created by or with the assistance of AI algorithms in which a person’s likeness, actions, or words have been replaced by someone else’s to deceive an audience. Often created with the help of generative adversarial networks, deep fakes can be used to blackmail, harass, exploit, and intimidate individuals and businesses; in large-scale disinformation campaigns, they can incite political tensions around the …
Computer-Aided Diagnosis Of Low Grade Endometrial Stromal Sarcoma (Lgess), Xinxin Yang, Mark Stamp
Computer-Aided Diagnosis Of Low Grade Endometrial Stromal Sarcoma (Lgess), Xinxin Yang, Mark Stamp
Faculty Research, Scholarly, and Creative Activity
Low grade endometrial stromal sarcoma (LGESS) accounts for about 0.2% of all uterine cancer cases. Approximately 75% of LGESS patients are initially misdiagnosed with leiomyoma, which is a type of benign tumor, also known as fibroids. In this research, uterine tissue biopsy images of potential LGESS patients are preprocessed using segmentation and stain normalization algorithms. We then apply a variety of classic machine learning and advanced deep learning models to classify tissue images as either benign or cancerous. For the classic techniques considered, the highest classification accuracy we attain is about 0.85, while our best deep learning model achieves an …
Tensor Pooling-Driven Instance Segmentation Framework For Baggage Threat Recognition, Taimur Hassan, Samet Akçay, Mohammed Bennamoun, Salman Khan, Naoufel Werghi
Tensor Pooling-Driven Instance Segmentation Framework For Baggage Threat Recognition, Taimur Hassan, Samet Akçay, Mohammed Bennamoun, Salman Khan, Naoufel Werghi
Computer Vision Faculty Publications
Automated systems designed for screening contraband items from the X-ray imagery are still facing difficulties with high clutter, concealment, and extreme occlusion. In this paper, we addressed this challenge using a novel multi-scale contour instance segmentation framework that effectively identifies the cluttered contraband data within the baggage X-ray scans. Unlike standard models that employ region-based or keypoint-based techniques to generate multiple boxes around objects, we propose to derive proposals according to the hierarchy of the regions defined by the contours. The proposed framework is rigorously validated on three public datasets, dubbed GDXray, SIXray, and OPIXray, where it outperforms the state-of-the-art …
Challenges And Reflection On Next-Generation Large-Scale Computer Wargame System, Guangya Si, Yanzheng Wang
Challenges And Reflection On Next-Generation Large-Scale Computer Wargame System, Guangya Si, Yanzheng Wang
Journal of System Simulation
Abstract: In view of the systematic, networked and intelligent characteristics of the future war, the major challenges of the new generation of large computer warfare system are proposed, and the next-generation large-scale computer wargame system is constructed. The key technologies of building a new generation of large computer warfare systems, such as intelligent war modeling, architecture integration, resource service management and human-computer interaction are researched.
Exploring Formal Model Transformation Techniques Within Model Driven Engineering, Zhu Zhi, Lei Sen, Yonglin Lei
Exploring Formal Model Transformation Techniques Within Model Driven Engineering, Zhu Zhi, Lei Sen, Yonglin Lei
Journal of System Simulation
Abstract: With the increasing complexity of simulation system and the wide use of simulation models, the higher requirements of the efficiency and quality for simulation models are needed. Currently, model-driven engineering is mostly applied in many simulation software tools, which cannot really carry out the formal analysis at the model level. Based on model driven engineering, the domain specific language with metamodeling and engineering model continuity is designed. Taking a group fire control channel system as the example, the domain specific language is designed and the conceptual models are transformed into other precise semantics to carry out the final executable …
Modeling Research Of Cognition Behavior For Intelligent Wargaming, Xiaoyuan He, Shengming Guo, Wu Lin, Li Dong, Xu Xiao, Li Li
Modeling Research Of Cognition Behavior For Intelligent Wargaming, Xiaoyuan He, Shengming Guo, Wu Lin, Li Dong, Xu Xiao, Li Li
Journal of System Simulation
Abstract: Aiming at the problem of cognitive behavior modeling in the construction and application of intelligent wargaming system, one modeling framework based on Actor-Operations-Scene (AOS) was proposed for C2 agent in wargaming. Then the realization of cognitive behavior modeling method for C2 agent was explored, including the modeling for the scenario oriented knowledge graph, intelligent situation awareness, operational planning, integrated operational control. It provides a feasible scheme for the construction and application of intelligent wargaming system.
Intelligent Wargaming System: Change Needed By Next Generation Need To Be Changed, Xiaofeng Hu, Dawei Qi
Intelligent Wargaming System: Change Needed By Next Generation Need To Be Changed, Xiaofeng Hu, Dawei Qi
Journal of System Simulation
Abstract: The future direction of wargaming system is intelligent, and the most significant feature of intelligence is the modeling of cognition. The main problems of wargaming system are summarized, the main difficulties of modeling brought by cognition and the overall framework of intelligent wargaming system design are discussed, the technical ways of transformation and upgrading based on the existing wargaming system are given from four aspects of model construction, system design, wargaming ecology and test inspection. It provides direction and reference to the development and construction of the next generation intelligent wargaming system.
Study On Next-Generation Strategic Wargame System, Wu Xi, Xianglin Meng, Jingyu Yang
Study On Next-Generation Strategic Wargame System, Wu Xi, Xianglin Meng, Jingyu Yang
Journal of System Simulation
Abstract: Strategic wargame is an important support to the strategic decision. The research status and challenges of the strategic wargame are analyzed, and the influence of big data and artificial intelligence technology on the strategic wargame system is studied. The prospects and key technologies of the next-generation strategic wargame system are studied, including the construction of event association graph for strategic topics, generation of strategic decision sparse samples based on generative adversarial nets, gaming strategy learning of human-in-loop hybrid enhancement, and public opinion dissemination modeling technology based on social network. The development trend of the strategic wargame is proposed.
Order Sorting Optimization For Four-Way Shuttle System Based On Improved Genetic Algorithm, Xinjie He, Shaowu Zhou, Hongqiang Zhang, Lianghong Wu, Zhou You
Order Sorting Optimization For Four-Way Shuttle System Based On Improved Genetic Algorithm, Xinjie He, Shaowu Zhou, Hongqiang Zhang, Lianghong Wu, Zhou You
Journal of System Simulation
Abstract: During the batch outbound operations of the four-way shuttle system, the different execution order of the system's outbound leads to the different interaction time between the four-way shuttle and the hoist will be different, which will affect the system's outbound operation time. According to the operation process of batch outbound, with the order of batch order outflow as the variable and the system outflow time as the objective function, a system order sort optimization model i established. Based to the characteristics of the model, with the improved genetic algorithm, the optimal order of the system is obtained. By changing …
Wargaming Eco-System For Intelligence Growing, Wu Lin, Xiaofeng Hu, Jiuyang Tao, Xiaoyuan He
Wargaming Eco-System For Intelligence Growing, Wu Lin, Xiaofeng Hu, Jiuyang Tao, Xiaoyuan He
Journal of System Simulation
Abstract: The construction of the next generation intelligent wargaming system can not be accomplished at one move, but through building an ecosystem to gradually grow intelligence. The basic concepts of the intelligent wargame ecosystem, and are defined the idea of dynamic openness, diversified levels and co-evolution are proposed. Drawing lessons from the human intelligence growing process and learning-evolution mechanism, the double helix model of the next generation of wargame cognitive intelligent evolution and growth is constructed. On the basis of the OLTA cycle, the wargame deduction ecosystem system framework is given. The application of the technologies, such as …
Application Of Two-Population Fish Swarm Algorithm In Distributed Portfolio, Fuyu Wang, Tang Tao
Application Of Two-Population Fish Swarm Algorithm In Distributed Portfolio, Fuyu Wang, Tang Tao
Journal of System Simulation
Abstract: Aiming at the disadvantages of artificial fish swarm algorithm, such as low precision and easily falling into local optimum, combining the idea of gravity algorithm and teaching optimization, a two-population fish swarm search algorithm is proposed. Cross-thinking is adopted to optimize the results obtained by the two populations and avoid the local optimization. Metropoils criterion of simulated annealing is added to the standard function verifies the algorithm, and the results show that the two-population fish swarm algorithm is better than the traditional artificial fish swarm algorithm and the known literature algorithm. Based on the known literature, a distributed …
Learning Ant Colony Algorithm For Green Multi-Depot Vehicle Routing Problem, Hu Rong, Wenbo Chen, Bin Qian, Guo Ning, Fenghong Xiang
Learning Ant Colony Algorithm For Green Multi-Depot Vehicle Routing Problem, Hu Rong, Wenbo Chen, Bin Qian, Guo Ning, Fenghong Xiang
Journal of System Simulation
Abstract: Considering the congested roads situation of urban central areas in China, a speed calculation method based on vehicle driving sections is designed, and a model for the Green Multi-Depot Vehicle Routing Problem with Total Fuel-Consumption cost Criterion (TFC-GMDVRP) is established, considering simultaneously the vehicle travel distance, load, and speed factors. A learning ant colony optimization algorithm (LACO), combining a knowledge model and an ant colony optimization algorithm (ACO), is proposed for solving the TFC-GMDVRP. In order to improve the performance and robustness of the algorithm's global search, the parameter knowledge that contains the different …
Hurricane Trajectory Outlier Detection Method Based On Variational Auto-Encode, Wanting Qin, Songyang Lao, Tang Jun, Lu Cong
Hurricane Trajectory Outlier Detection Method Based On Variational Auto-Encode, Wanting Qin, Songyang Lao, Tang Jun, Lu Cong
Journal of System Simulation
Abstract: Hurricanes often cause incalculable human and economic losses, and the trajectory outlier detection can provide the auxiliary information or abnormal warning of the disaster. On deep learning, a method of hurricane trajectory outlier detection based on variable auto encoder (VAEOD) is proposed in this paper. The trajectory is divided into equal sequence sub trajectories based on the sliding window as the input of VAE. The trajectory reconstruction model is trained by the VAE. The parallel, vertical and angle distance of reconstructed trajectory and the input trajectory are compared to find out the outlier trajectory segments. The simulation experiment on …
Research And Application On Space-Launching Mission Simulated Rehearsal Technology, Xiuluo Liu, Wang Jia, Wu Feng, Liu Yang, Ailiang Zhang, Wang Min
Research And Application On Space-Launching Mission Simulated Rehearsal Technology, Xiuluo Liu, Wang Jia, Wu Feng, Liu Yang, Ailiang Zhang, Wang Min
Journal of System Simulation
Abstract: High-density space launching tasks need the new requirements for space-launching mission rehearsal. The new concept of space-launching mission simulated rehearsal is proposed, the definition and content are presented in detail,and the technology research objective and key works are analyzed. The technology implementation architecture is established on five dimensions of the domain resources, developing tools, simulation modeling, fundamental function design and domain application. On the basis of simulation, the working process is given, the simulation software architecture is designed, and the simulation application tool is developed. The simulation results are also given, which validate the method and technology.
Mechanism Design For Entities' Passive Dimensional Sensing Interaction In Discrete Event Simulations, Yan Fei, Bin Gan, Zhaodi Chen, Wenjuan Ma, Luyao Li, Zhang Ke
Mechanism Design For Entities' Passive Dimensional Sensing Interaction In Discrete Event Simulations, Yan Fei, Bin Gan, Zhaodi Chen, Wenjuan Ma, Luyao Li, Zhang Ke
Journal of System Simulation
Abstract: Dimensional sensing interaction mechanism is a method of computing the entities' visibility on the basis of the position and visible range, and informing when and where the entities can perceive each other. Entities' active computing on the relative position needs a lot of computation and is low efficiency, and slow down the simulation execution at last. The mechanism and framework of the passive dimensional sensing interaction, including the spatial grid models, discrete movement models, and passive sense models are researched. Dimensional sensing interaction manager is designed to realize the computation of entities' dimensional sensing interaction in discrete event-based battle …