Study On Balanced Energy-Consumption Routing Protocol Of Airfield Single-Lamp Monitoring System,
2020
School of Electronic Information and Automation, Civil Aviation University of China, Tianjin 300300, China;
Study On Balanced Energy-Consumption Routing Protocol Of Airfield Single-Lamp Monitoring System, Gao Mei, Bingyuan Wang, Dandan Zhang, Zhaorong Sun
Journal of System Simulation
Abstract: To extend the sensor node lifetime and balance the energy consumption of the wireless sensor network, on the basis of the protocols AL-CAME (Airfield lighting-clustering algorithm based on max energy) and ECOMP (Efficient cluster-based communication protocol), a clustered hierarchy protocol of balanced energy-consumption was proposed for the airfield single-lamp monitoring system. According to the protocol, every two sensor nodes formed a cluster, and the node with the highest remaining energy was elected to be cluster head which was responsible for data aggregation within the cluster. The balanced routing algorithm was adopted in data-transmission from cluster head to …
Study For Solar Seasonal Storage System In Transition Season,
2020
Qingdao Technological University, Qingdao 266033, China;
Study For Solar Seasonal Storage System In Transition Season, Liu Long
Journal of System Simulation
Abstract: The COP (Coefficient of Performance) of the GSHP system has decreased gradually year after year caused by imbalance energy loads especially in heating-dominated climate zones. The solar thermal energy storage system in transition season can solve the problems effectively. The practice of solar seasonal storage was carried out and supplied by a practical project. TRNSYS 16 was used to simulate the solar energy storage experiment process. The correctness of the model was verified by the experimental data and the simulation results were corrected. Results shows that the simulated results and the measured data were well matched with …
Robotic Manipulator's Visual Servo Control Based On Echo State Networks,
2020
Key Laboratory of Industrial Computer Control Engineering of Yanshan University, Qinhuangdao 066004, China;
Robotic Manipulator's Visual Servo Control Based On Echo State Networks, Guoyou Li, Xiafei Su, Xiaolei Qin, Xiangxue Shi
Journal of System Simulation
Abstract: The inaccuracy in robotic manipulator modeling, which due to the nonlinear and strong coupling of robotic manipulator itself, cannot be ignored on the study of the robotic manipulator control problem. Aiming at the inaccuracy in robotic manipulator modeling, this study led echo state network in the visual servo control system of robotic manipulator. In order to achieve the robotic manipulator positioning control, this study used the echo state network to identify inaccurate item and compensates the uncertainties of the model in the control law. The simulation model of the simulated system was built with MATLAB simulation software. The …
Integrating Finance Dictionary In Lexicon-Based Approach With Machine Learning Algorithm To Analyse The Impact Of Opec News Sentiment On Financial Market,
2020
Universiti Malaya
Integrating Finance Dictionary In Lexicon-Based Approach With Machine Learning Algorithm To Analyse The Impact Of Opec News Sentiment On Financial Market, Ling Wu
Student Works (2020-2029)
Since last few decades, machine learning algorithm which trains computers to learn from experience, is one of the most rapidly developing techniques which settles in the intersection research field of statistics and computer science. This research aims to build a properly trained machine learning classifier to study the impact of Organization of Petroleum Exporting Countries (OPEC) news sentiment on stock prices of six Malaysian public listed companies (energy sector) in the main board of Bursa Malaysia. The data used in this research are collected during the period 2012-2017. To carry out the research, firstly, lexicon-based approach is used to analyze …
Scalable Multi-Agent Reinforcement Learning For Aggregation Systems,
2020
Singapore Management University
Scalable Multi-Agent Reinforcement Learning For Aggregation Systems, Tanvi Verma
Dissertations and Theses Collection (Open Access)
Efficient sequential matching of supply and demand is a problem of interest in many online to offline services. For instance, Uber, Lyft, Grab for matching taxis to customers; Ubereats, Deliveroo, FoodPanda etc. for matching restaurants to customers. In these systems, a centralized entity (e.g., Uber) aggregates supply and assigns them to demand so as to optimize a central metric such as profit, number of requests, delay etc. However, individuals (e.g., drivers, delivery boys) in the system are self interested and they try to maximize their own long term profit. The central entity has the full view of the system and …
Online Spatio - Temporal Demand Supply Matching,
2020
Singapore Management University
Online Spatio - Temporal Demand Supply Matching, Meghna Lowalekar
Dissertations and Theses Collection (Open Access)
The rapid growth of cities in developing world coupled with the increase in rural to urban migration have led to cities being identified as the key actor for any nation's economy. Shared mobility has become an integral part of life of people in cities as it improves efficiency and enhances transportation accessibility. As a result, the mismatch between the demand and supply of shared mobility resources has a direct impact on people's life. Thus, the goal of my dissertation is to develop solution strategies for these real-time (online) spatio-temporal demand supply matching problems for shared mobility resources which can enhance …
What Do Undergraduate Engineering Students And Preservice Teachers Learn By Collaborating And Teaching Engineering And Coding Through Robotics?,
2020
Old Dominion University
What Do Undergraduate Engineering Students And Preservice Teachers Learn By Collaborating And Teaching Engineering And Coding Through Robotics?, Jennifer Jill Kidd, Krishnanand Kaipa, Samuel J. Jacks, Stacie I. Ringleb, Pilar Pazos, Kristie Gutierrez, Orlando M. Ayala, Lillian Maria De Souza Almeida
Teaching & Learning Faculty Publications
This research paper presents preliminary results of an NSF-supported interdisciplinary collaboration between undergraduate engineering students and preservice teachers. The fields of engineering and elementary education share similar challenges when it comes to preparing undergraduate students for the new demands they will encounter in their profession. Engineering students need interprofessional skills that will help them value and negotiate the contributions of various disciplines while working on problems that require a multidisciplinary approach. Increasingly, the solutions to today's complex problems must integrate knowledge and practices from multiple disciplines and engineers must be able to recognize when expertise from outside their field can …
Monte Carlo Tree Search Applied To A Modified Pursuit/Evasion Scotland Yard Game With Rendezvous Spaceflight Operation Applications,
2020
Air Force Institute of Technology
Monte Carlo Tree Search Applied To A Modified Pursuit/Evasion Scotland Yard Game With Rendezvous Spaceflight Operation Applications, Joshua A. Daughtery
Theses and Dissertations
This thesis takes the Scotland Yard board game and modifies its rules to mimic important aspects of space in order to facilitate the creation of artificial intelligence for space asset pursuit/evasion scenarios. Space has become a physical warfighting domain. To combat threats, an understanding of the tactics, techniques, and procedures must be captured and studied. Games and simulations are effective tools to capture data lacking historical context. Artificial intelligence and machine learning models can use simulations to develop proper defensive and offensive tactics, techniques, and procedures capable of protecting systems against potential threats. Monte Carlo Tree Search is a bandit-based …
Vision And Sensor-Based Signer-Independent Framework For Arabic Sign Language Recognition,
2020
Universiti Malaya
Vision And Sensor-Based Signer-Independent Framework For Arabic Sign Language Recognition, Al-Shamayleh Ahmad Sami Abd Alkareem
Student Works (2020-2029)
Hearing and speech-impairment disability is widespread throughout the world. At present, 15 million people have this disability in the Arab world, and about 86% of them come from low- and middle-income countries. Meanwhile, sign language (SL) can be classified into standard Arabic sign language (ArSL) and local Arabic sign language (LArSL). ArSL is the formal standard and is the more acceptable SL in the Arab world; it is also considered as the medium of instructions for schools and universities as well as television news, shows and programmes. With the absence of usable ArSL recognition (ArSLR) platforms, hearing- and speech-impaired people …
Greenwatch-Shing: Using Ai To Detect Greenwashing,
2020
Singapore Management University
Greenwatch-Shing: Using Ai To Detect Greenwashing, Theodor Florian Cojoianu, Andreas G. F. Hoepner, Georgiana Ifrim, Yanan Lin
Research Collection College of Integrative Studies
The rise of fake news has resulted in a wide discrepancy between the attention given to the scientific understanding of an issue versus misinformed and sometimes purposefully disinformed claims (false information that is purposely spread to deceive people) coming from outside the scientific community. One such example relates to climate change, where a nature study shows that climate change contrarians are featured in 49% more media articles than scientists, despite the overwhelming consensus in the scientific community over the significance of anthropogenic climate change. In addition, many companies worldwide make inaccurate and often misleading claims about their environmental and social …
Visual Commonsense R-Cnn,
2020
Singapore Management University
Visual Commonsense R-Cnn, Tan Wang, Jianqiang Huang, Hanwang Zhang, Qianru Sun
Research Collection School Of Computing and Information Systems
We present a novel unsupervised feature representation learning method, Visual Commonsense Region-based Convolutional Neural Network (VC R-CNN), to serve as an improved visual region encoder for high-level tasks such as captioning and VQA. Given a set of detected object regions in an image (e.g., using Faster R-CNN), like any other unsupervised feature learning methods (e.g., word2vec), the proxy training objective of VC R-CNN is to predict the contextual objects of a region. However, they are fundamentally different: the prediction of VC R-CNN is by using causal intervention: P(Y|do(X)), while others are by using the conventional likelihood: P(Y|X). This is also …
A Machine Learning Approach For Vulnerability Curation,
2020
Veracode
A Machine Learning Approach For Vulnerability Curation, Yang Chen, Andrew E. Santosa, Ming Yi Ang, Abhishek Sharma, Asankhaya Sharma, David Lo
Research Collection School Of Computing and Information Systems
Software composition analysis depends on database of open-source library vulerabilities, curated by security researchers using various sources, such as bug tracking systems, commits, and mailing lists. We report the design and implementation of a machine learning system to help the curation by by automatically predicting the vulnerability-relatedness of each data item. It supports a complete pipeline from data collection, model training and prediction, to the validation of new models before deployment. It is executed iteratively to generate better models as new input data become available. We use self-training to significantly and automatically increase the size of the training dataset, opportunistically …
Talk Like Somebody Is Watching: Understanding And Supporting Novice Live Streamers,
2020
University of Calgary
Talk Like Somebody Is Watching: Understanding And Supporting Novice Live Streamers, Terrance Mok, Colin Matthew Au Yueng, Anthony Tang, Lora Oehlberg
Research Collection School Of Computing and Information Systems
We built a chatbot system–Audience Bot–that simulates an audience for novice live streamers to engage with while streaming. New live streamers on platforms like Twitch are expected to perform and talk to themselves, even while no one is watching. We ran an observational lab study on how Audience Bot assists novice live streamers as they acclimate to multitasking–simultaneously playing a video game while performing for a (simulated) audience.
Knowledge Enhanced Neural Fashion Trend Forecasting,
2020
Singapore Management University
Knowledge Enhanced Neural Fashion Trend Forecasting, Yunshan Ma, Yujuan Ding, Xun Yang, Lizi Liao, Wai Keung Wong, Tat-Seng Chua
Research Collection School Of Computing and Information Systems
Fashion trend forecasting is a crucial task for both academia andindustry. Although some efforts have been devoted to tackling this challenging task, they only studied limited fashion elements with highly seasonal or simple patterns, which could hardly reveal thereal fashion trends. Towards insightful fashion trend forecasting,this work focuses on investigating fine-grained fashion element trends for specific user groups. We first contribute a large-scale fashion trend dataset (FIT) collected from Instagram with extracted time series fashion element records and user information. Furthermore, to effectively model the time series data of fashion elements with rather complex patterns, we propose a Knowledge Enhanced …
Sensing, Computing, And Communications For Energy Harvesting Iots: A Survey,
2020
Singapore Management University
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 …
Self-Trained Deep Ordinal Regression For End-To-End Video Anomaly Detection,
2020
Singapore Management University
Self-Trained Deep Ordinal Regression For End-To-End Video Anomaly Detection, Guansong Pang, Cheng Yan, Chunhua Shen, Anton Van Den Hengel, Xiao Bai
Research Collection School Of Computing and Information Systems
Depression is among the most prevalent mental disorders, affecting millions of people of all ages globally. Machine learning techniques have shown effective in enabling automated detection and prediction of depression for early intervention and treatment. However, they are challenged by the relative scarcity of instances of depression in the data. In this work we introduce a novel deep multi-task recurrent neural network to tackle this challenge, in which depression classification is jointly optimized with two auxiliary tasks, namely one-class metric learning and anomaly ranking. The auxiliary tasks introduce an inductive bias that improves the classification model’s generalizability on small depression …
Learning Transferable Deep Convolutional Neural Networks For The Classification Of Bacterial Virulence Factors,
2020
Singapore Management University
Learning Transferable Deep Convolutional Neural Networks For The Classification Of Bacterial Virulence Factors, Dandan Zheng, Guansong Pang, Bo Liu, Lihong Chen, Jian Yang
Research Collection School Of Computing and Information Systems
Motivation: Identification of virulence factors (VFs) is critical to the elucidation of bacterial pathogenesis and prevention of related infectious diseases. Current computational methods for VF prediction focus on binary classification or involve only several class(es) of VFs with sufficient samples. However, thousands of VF classes are present in real-world scenarios, and many of them only have a very limited number of samples available.Results: We first construct a large VF dataset, covering 3446 VF classes with 160 495 sequences, and then propose deep convolutional neural network models for VF classification. We show that (i) for common VF classes with sufficient samples, …
Simulation Modeling Method Of Distributed Supply Chain Based On Has,
2020
1. School of Automation, Huazhong University of Science and Technology, Wuhan 430074, China;;2. Key Laboratory for Image Information Processing and Intelligent controlling of Ministry of Education, Wuhan 430074, China;
Simulation Modeling Method Of Distributed Supply Chain Based On Has, Wang Jian, Huang Yang
Journal of System Simulation
Abstract: There are some shortcomings in simulation modeling method of distributed supply chain based on High Level Architecture (HLA) and Supply Chain Operation Reference (SCOR), which result in low development efficiency of system simulation modeling and low reusability of simulation objects inside the federates. To solve the problems, a simulation modeling method of distributed supply chain based on HAS(HLA-Agent-SCOR) was put forward. The supply chain structure modeling based on HLA for building structure model of supply chain was discussed. Modeling of Agent blocks integrating processes from SCOR and modeling of federates based on Agent were illustrated to create model of …
Multi-Robots Global Path Planning Based On Pso Algorithm And Cubic Spline,
2020
1. School of Physics and Information Technology, Shaanxi Normal University, Xi'an 710119, China;;
Multi-Robots Global Path Planning Based On Pso Algorithm And Cubic Spline, Qiang Ning, Gao Jie, Fengju Kang
Journal of System Simulation
Abstract: There are shortcomings such as premature convergence, high encoding dimension and unsmooth path for particle swarm optimization (PSO) algorithm to solve the robot path planning problem under free space. The particle coding is coordinates of several path nodes in the environment. The number of spline curves and the maximum turnings of path were determined by the number of path nodes. The cubic spline function was used to interpolate on the path of the starting point, path nodes and target point, thus a full path which was formed by connecting all interpolation points was obtained. Simulation results show that …
Improved Marching Cubes Algorithmand Its Three-Dimensional Meteorological Simulation,
2020
School of Geography & Remote Sensing, Nanjing University of Information Science and Technology, Nanjing 210044, China;
Improved Marching Cubes Algorithmand Its Three-Dimensional Meteorological Simulation, Shuoben Bi, Lu Yuan, Xiaowen Zeng, Mingyue Lu, Yonghua Zhang
Journal of System Simulation
Abstract: Methodof obtaining intersection points of isosurface and vowex by linear interpolation in original Marching Cubes algorithm has been replaced by the method of trisecting element boundaries. The problem of linear interpolation not suitable for meteorological data simulation is therefore solved and the number of triangular facets in isosurfacemapping is effectively reduced. While reducing redundancy and improving mapping speed, the quality of isosurface mapping is further improved. The improved Marching Cubes algorithm is applied to the simulation of meteorological model data, i.e., the isosurface of WRF data, and good results are obtained in both the speed of image rendering and …
