Cosm2ic: Optimizing Real-Time Multi-Modal Instruction Comprehension,
2022
Singapore Management University
Cosm2ic: Optimizing Real-Time Multi-Modal Instruction Comprehension, Weerakoon Mudiyanselage Dulanga Kaveesha Weerakoon, Vigneshwaran Subbaraju, Minh Anh Tuan Tran, Archan Misra
Research Collection School Of Computing and Information Systems
Supporting real-time, on-device execution of multi-modal referring instruction comprehension models is an important challenge to be tackled in embodied Human-Robot Interaction. However, state-of-the-art deep learning models are resource-intensive and unsuitable for real-time execution on embedded devices. While model compression can achieve a reduction in computational resources up to a certain point, further optimizations result in a severe drop in accuracy. To minimize this loss in accuracy, we propose the COSM2IC framework, with a lightweight Task Complexity Predictor, that uses multiple sensor inputs to assess the instructional complexity and thereby dynamically switch between a set of models of varying computational intensity …
Test Mimicry To Assess The Exploitability Of Library Vulnerabilities,
2022
Singapore Management University
Test Mimicry To Assess The Exploitability Of Library Vulnerabilities, Hong Jin Kang, Truong Giang Nguyen, Bach Le, Corina S. Pasareanu, David Lo
Research Collection School Of Computing and Information Systems
Modern software engineering projects often depend on open-source software libraries, rendering them vulnerable to potential security issues in these libraries. Developers of client projects have to stay alert of security threats in the software dependencies. While there are existing tools that allow developers to assess if a library vulnerability is reachable from a project, they face limitations. Call graphonly approaches may produce false alarms as the client project may not use the vulnerable code in a way that triggers the vulnerability, while test generation-based approaches faces difficulties in overcoming the intrinsic complexity of exploiting a vulnerability, where extensive domain knowledge …
A Mean-Field Markov Decision Process Model For Spatial Temporal Subsidies In Ride-Sourcing Markets,
2022
Singapore Management University
A Mean-Field Markov Decision Process Model For Spatial Temporal Subsidies In Ride-Sourcing Markets, Zheng Zhu, Jintao Ke, Hai Wang
Research Collection School Of Computing and Information Systems
Ride-sourcing services are increasingly popular because of their ability to accommodate on-demand travel needs. A critical issue faced by ride-sourcing platforms is the supply-demand imbalance, as a result of which drivers may spend substantial time on idle cruising and picking up remote passengers. Some platforms attempt to mitigate the imbalance by providing relocation guidance for idle drivers who may have their own self-relocation strategies and decline to follow the suggestions. Platforms then seek to induce drivers to system-desirable locations by offering them subsidies. This paper proposes a mean-field Markov decision process (MF-MDP) model to depict the dynamics in ride-sourcing markets …
Legal And Regulatory Issues On Artificial Intelligence, Machine Learning, Data Science, And Big Data,
2022
Singapore Management University
Legal And Regulatory Issues On Artificial Intelligence, Machine Learning, Data Science, And Big Data, Wai Yee Wan, Michael Tsimplis, Keng Siau, Wei T. Yue, Fiona Fui-Hoon Nah, Gabriel M. Yu
Research Collection School Of Computing and Information Systems
Technological innovation creates numerous opportunities for businesses, organizations, and societies. Artificial intelligence, machine learning, data science, and big data provide opportunities for developing self-controlling systems emulating human intelligence. In some instances, these systems surpass the performance of humans. The relationship of innovative technology with the law is an important underpinning factor that is often overlooked. Law may encourage innovation but may also inhibit its development and application by adopting stringent regulatory provisions and liability regimes. This article examines the legal and regulatory issues related to new technologies such as artificial intelligence, machine learning, data science, and big data.
Ai In Accounting: A Value-Focused Thinking Study,
2022
Singapore Management University
Ai In Accounting: A Value-Focused Thinking Study, Keng Siau, Fiona Fui-Hoon Nah, B. Eschenbrenner, L. Chen, Y. Qian
Research Collection School Of Computing and Information Systems
Artificial intelligence (AI) has been widely utilized in the accounting industry and profoundly shaped how accounting is practiced nowadays. AI is poised to make significant contributions to various accounting functions such as auditing and fraud detection by providing greater insights to improve the efficiency and effectiveness of decision-making processes. To realize the full potential of AI in accounting, a strategic approach to its implementation is necessary. In this research, we propose to utilize a qualitative study that adopts the Value-Focused Thinking approach to identify the objective necessary to achieve the full value of AI in the accounting domain. Findings from …
Special Section: Reevaluating Markets For Information,
2022
Singapore Management University
Special Section: Reevaluating Markets For Information, Robert John Kauffman, Thomas A. Weber
Research Collection School Of Computing and Information Systems
As the use of information as a productive and tradeable asset becomes more pervasive, its—often unintended—side-effects start showing. This prompts us to systematically recognize these effects and, once identified, to think about how to use them to our advantage or else mitigate them as much as may be economically and/or socially desirable. In this Special Section, we have assembled three research papers, which take a look at different interesting instances of this question, namely in the context of regulating peer-to-peer sharing markets, the substitution of knowledge workers (or their skills) by artificial intelligence (AI), and the difficulties in appropriating rents …
Analysis Of Digital Image Segmentation Algorithms,
2022
Nurafshan branch of Tashkent University of Information Technologies named after Muhammad al-Khwarizmi
Analysis Of Digital Image Segmentation Algorithms, Khalilov Sirojiddin
Karakalpak Scientific Journal
Ushbu maqolada zamonaviy axborot-kommunikatsiya texnologiyalaridan foydalanishni kengaytirish maqsadida raqamli tasvirni qayta ishlash usullari va algoritmlari tahlil qilinadi. Maqolada, shuningdek, raqamli tasvirni qayta ishlash, tasvirni segmentatsiyalash usullari, WaterShed, MeanShift, FloodFill, GrabCut algoritmlarining afzalliklari va kamchiliklari o'rganiladi.
Interdisciplinary Communication By Plausible Analogies: The Case Of Buddhism And Artificial Intelligence,
2022
University of South Florida
Interdisciplinary Communication By Plausible Analogies: The Case Of Buddhism And Artificial Intelligence, Michael Cooper
USF Tampa Graduate Theses and Dissertations
Communicating interdisciplinary information is difficult, even when two fields are ostensibly discussing the same topic. In this work, I’ll discuss the capacity for analogical reasoning to provide a framework for developing novel judgments utilizing similarities in separate domains. I argue that analogies are best modeled after Paul Bartha’s By Parallel Reasoning, and that they can be used to create a Toulmin-style warrant that expresses a generalization. I argue that these comparisons provide insights into interdisciplinary research. In order to demonstrate this concept, I will demonstrate that fruitful comparisons can be made between Buddhism and Artificial Intelligence research.
Explainable And Cooperative Autonomy Across Networks Of Distributed Systems,
2022
University of South Florida
Explainable And Cooperative Autonomy Across Networks Of Distributed Systems, Peter Joseph Jorgensen
USF Tampa Graduate Theses and Dissertations
Large networks of complex systems-of-systems are commonplace and evermore present in both mundane and extraordinary facets of human existence. From the exponential growth of connectivity via the internet and other information networks, to the miniaturization of computers and sensors, to cross-domain sensor and communication networks, these networks of distributed systems-of-systems (NDSS) present incredible benefits and challenges. Autonomy is perhaps the most important and most difficult to achieve enabling technology for efficient performance of the NDSS. Giving each individual agent in a network the ability to manage its internal state in dynamic operating environments and in pursuit of multiple complex and …
Edgenext: Efficiently Amalgamated Cnn-Transformer Architecture For Mobile Vision Applications,
2022
Mohamed bin Zayed University of Artificial Intelligence
Edgenext: Efficiently Amalgamated Cnn-Transformer Architecture For Mobile Vision Applications, Muhammad Maaz, Abdelrahman Shaker, Hisham Cholakkal, Salman Khan, Syed Waqas Zamir, Rao Anwer, Fahad Shahbaz Khan
Computer Vision Faculty Publications
In the pursuit of achieving ever-increasing accuracy, large and complex neural networks are usually developed. Such models demand high computational resources and therefore cannot be deployed on edge devices. It is of great interest to build resource-efficient general purpose networks due to their usefulness in several application areas. In this work, we strive to effectively combine the strengths of both CNN and Transformer models and propose a new efficient hybrid architecture EdgeNeXt. Specifically in EdgeNeXt, we introduce split depth-wise transpose attention (SDTA) encoder that splits input tensors into multiple channel groups and utilizes depth-wise convolution along with self-attention across channel …
Dynamic Prototype Convolution Network For Few-Shot Semantic Segmentation,
2022
University of Amsterdam, Netherlands
Dynamic Prototype Convolution Network For Few-Shot Semantic Segmentation, Jie Liu, Yanqi Bao, Guo-Sen Xie, Huan Xiong, Jan-Jakob Sonke, Efstratios Gavves
Machine Learning Faculty Publications
The key challenge for few-shot semantic segmentation (FSS) is how to tailor a desirable interaction among sup-port and query features and/or their prototypes, under the episodic training scenario. Most existing FSS methods im-plement such support/query interactions by solely leveraging plain operations - e.g., cosine similarity and feature concatenation - for segmenting the query objects. How-ever, these interaction approaches usually cannot well capture the intrinsic object details in the query images that are widely encountered in FSS, e.g., if the query object to be segmented has holes and slots, inaccurate segmentation al-most always happens. To this end, we propose a dynamic …
Research And Simulation Of Internet Of Vehicles Task Offloading Based On Mobile Edge Computing,
2022
School of Information and Control Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China;
Research And Simulation Of Internet Of Vehicles Task Offloading Based On Mobile Edge Computing, Peng Cheng, Wenzhu Zhang, Shuhan Xie, Zixuan Yang
Journal of System Simulation
Abstract: In order to use the computing resources of edge devices to provide high-quality services, a joint resource allocation and task offloading mechanism is designed for the Internet of Vehicles architecture based on mobile edge computing. In the mechanism, the original problem is decomposed into two sub-problems of resource allocation and offloading decision. The original problem is simplified into the resource allocation of maximizing system capacity, and the initial offloading set is obtained through the proportional resource allocation algorithm; the above problem is solved by the joint offloading decision-making and resource allocation mechanism. The stable experimental results are obtained …
Design And Realization Of 6-Dof Parachuting Simulation Training System,
2022
Naval Aviation University, Huludao 125001, China;
Design And Realization Of 6-Dof Parachuting Simulation Training System, Xiaoguang Zhou, Peng Zhu, Yuanyuan Zhang, Huan Lu, Yuan Zhou
Journal of System Simulation
Abstract: Aiming at restoring the 6-DOF motion process of each stage during parachuting, a 6-DOF parachuting simulation training system is designed and implemented. The architecture of the simulator is designed, and the realization of the sub-systems such as the motion calculation, 6-DOF motion platform, control loading system, virtual reality scene, somatosensory system and management console is explained. Compared with the same type of parachute simulator, this system has introduced a 6-DOF motion platform which can drive the trainees to simulate the various postures of parachuting. It can also help the trainees master the control methods of parachute and enhance the …
Multi-Agent Simulation For Online Fresh Food Autonomous Delivery,
2022
Tongji University, Shanghai 201804, China;
Multi-Agent Simulation For Online Fresh Food Autonomous Delivery, Miaojia Lu, Chengyuan Huang, Jing Teng
Journal of System Simulation
Abstract: Autonomous delivery can solve the last-mile delivery problems of low efficiency, high manual cost, and potential safety hazard. The autonomous delivery of the online fresh food in urban communities is discussed and a data-driven agent-based platform with the actual spatial-temporal demand is built. Three kinds of agents including the autonomous vehicles, customers, and distribution center and the simulation environment based on the actual road network are construct. To achieve the objectives of the minimum total operating costs and maximum customer satisfaction, the different static and dynamic order dispatch strategies and the route planning strategies with the principle of …
An Unsupervised Deep Neural Network For Image Fusion,
2022
School of Electrical and Information Engineering, Changzhou Institute of Technology, Changzhou 213032, China;
An Unsupervised Deep Neural Network For Image Fusion, Peipei Zhou, Xinglin Hou
Journal of System Simulation
Abstract: Due to the low dynamic range of camera, can not be expressed in the different region of the high dynamic scene a single-exposure image. An unsupervised depth neural network is constructed to fuse the multi-exposure images into a high dynamic image. Based on the VGG-Net, encoding and decoding sub-networks are designed. Guided by the structural similarity of the images before and after fusion, a loss function suitable for image fusion is designed by introducing the weight factors based on the local image information, and the valid information of the different input images is given consideration. Compared with the …
Research On Fire Emergency Evacuation Simulation Based On Cooperative Deep Reinforcement Learning,
2022
1.Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China;2.University of Chinese Academy of Sciences, Beijing 100049, China;
Research On Fire Emergency Evacuation Simulation Based On Cooperative Deep Reinforcement Learning, Lingjia Ni, Xiaoxia Huang, Hongga Li, Zibo Zhang
Journal of System Simulation
Abstract: The fire accident is a major threat to the public safety, in which the high temperature, toxic and harmful gases seriously interfer the selection of the evacuation routes. Deep reinforcement learning is introduced into the research of emergency evacuation simulation, and a cooperative double deep Q network algorithm is proposed for the multi-agent environment. A fire scene model that changes dynamically over time is established to provide the real-time information on the distribution of the dangerous areas for the evacuation. The independent agent neural networks are integrated and the multi-agent unified deep neural network is established to realize the …
Simulation Of Multi-Layer Ship Evacuation System Based On Improved A* Algorithm,
2022
School of Auyomation, Wuhan University of Technology, Wuhan 430070, China;
Simulation Of Multi-Layer Ship Evacuation System Based On Improved A* Algorithm, Dun Meng, Zhuo Hu, Huajun Zhang
Journal of System Simulation
Abstract: Aiming at the low efficiency of emergency evacuation at sea, an emergency evacuation system based on improved A* algorithm is proposed. Based on the network flow model, the traversal mode of the adjacency node is used to complete the path search, and the influence of the path personnel density and path obstacles is added to the calculation of the cost, which makes the algorithm more practical. In order to improve the efficiency of the algorithm, the node optimization of the network is carried out, and a multi-path optimal scheme is proposed in the case of single layer with multiple …
A High Spectral-Efficiency Maritime Very-High-Frequency Communication Technology And Simulation,
2022
1.College of Information Science and Technology, Dalian Maritime University, Dalian 116026, China;
A High Spectral-Efficiency Maritime Very-High-Frequency Communication Technology And Simulation, Xinyu Dou, Xiaohui Chen, Dequn Liang, Bin Lin
Journal of System Simulation
Abstract: Marine communications cannot follow the development route on land of developing high frequency resources and high spectral-efficiency modulation technologies in 5G and 6G high-speed communication. The data rate and spectral-efficiency of maritime communications are low and are difficult to be improved. A high spectral-efficiency maritime very-high-frequency (VHF) communication technology based on multi-carrier time-delay overlapping modulation (MC-TDOP) is proposed. The core is delaying the subcarriers in turn and directly overlapping them in time domain. The orthogonality between the subcarriers can be neglected, thus the spectral-efficiency can be further enhanced from the fundamental information modulations. The results show that the proposed …
Simulation Method Of Virtual Human Pose Optimization Based On Vr Peripherals,
2022
1.School of Mechanical Engineering, Shanghai Jiaotong University, Shanghai 200240, China;
Simulation Method Of Virtual Human Pose Optimization Based On Vr Peripherals, Muqing Wang, Lei Zhang, Xiumin Fan, Xiaomeng Luo, Wenmin Zhu
Journal of System Simulation
Abstract: The commonly used VR peripheral is the position tracker worn on the operator body and is not very convenient. Focus on the problem, a visual sensor combination-based scheme is proposed to realize the simple and real-time unmarked virtual human driven simulation. On the basis of the parameterized human model SMPL, by minimizing the objective function of multiple error terms, the driven accuracy of the virtual human is improved, and the fitted human body model conforming to the operator form and posture is calculated and the ergonomic evaluation is realized. The module is verified by a case of evaluation in …
Multi-Person Interactive Globe System Based On Ar Technology,
2022
1.Beijing Key Laboratory of Big Data Technology for Food Safety, Beijing Technology and Business University, Beijing 100048, China;
Multi-Person Interactive Globe System Based On Ar Technology, Yiling Sun, Yi Chen, Guihua Shan, Xiaoxing Li
Journal of System Simulation
Abstract: The characteristic of multi-source, high-dimensional, time-varying and massive of the Earth big data is difficult to be understood and analyzed. Aiming at this problem and for the science popularization needs, an AR-based multi-person interactive globe system is proposed and implemented. A system architecture integrating AR technology is proposed to realize the seamless overlay combination effect of the virtual information and the physical globe. A data visualization display scheme is designed to realize the visualization of the Earth big data in three-dimensional space. A lightweight multi-person multi-terminal collaboration mechanism is proposed to improve the practicality and interestingness of the system. …
