Trajectory Planning Method Of Overhead Crane,
2019
1. School of Electronic Information Engineering, Taiyuan University of Science and Technology, Taiyuan 030024, China; ;
Trajectory Planning Method Of Overhead Crane, Xuejuan Shao, Li Yao, Jinggang Zhang, Xueliang Zhang
Journal of System Simulation
Abstract: To make the trolley of bridge crane move stably with smooth acceleration, a polynomial acceleration trajectory is proposed based on the constraint conditions of the crane and the friction between the trolley and the rail. An anti-swing plan is designed employing the dynamic coupling relationship between the motion of the trolley and the load swing. Results indicate that when the length of the rope is changed, the swing angle of the trolley is still within the limits. The stability of the system is proved by constructing Lyapunov energy equations, and the Barbalat lemma confirms that the planned reference trajectory …
Thai Language Names, Place Names And Organization Names Entity Recognition,
2019
1.College of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650500, China; ;2. Key Laboratory of Intelligent Information Processing, Kunming University of Science and Technology, Kunming 650500, China;
Thai Language Names, Place Names And Organization Names Entity Recognition, Hongbin Wang, Hongkui Gao, Shen Qiang, Yantuan Xian
Journal of System Simulation
Abstract: Named entity recognition in Thai language is aimed to identify the names of a person, a locality,an organization or an institution,and so on. Due to the complexity of Thai word formation method and grammar rules, to solve this problem, the idea of the approach proposed is to treat the task of named entity recognition in Thai language as labeling the sign of a series of words in Thai sentence. Given the characteristics of Thai language itself, certain features in the context of the samples in the Thai entity recognition corpus are extracted to train the hidden Markov model and …
Multi-Seats Collaborative Task Planning Based On Improved Particle Swarm Optimization,
2019
1. Air and Missile Defense College, Air Force Engineering University, Xi’an 710051, China; ;
Multi-Seats Collaborative Task Planning Based On Improved Particle Swarm Optimization, Cai Rui, Wang Wei, Jue Qu, Hu Bo
Journal of System Simulation
Abstract: Aiming at the allocation conflict between task and operator of multi-seats collaborative task planning in command and control cabin, a multi-seats collaborative task planning method based on improved particle swarm optimization is proposed. This method describes and analyzes the multi-seats collaborative task and establishes a solution space model based on task sequence. In solving the model, the particle swarm optimization (PSO) was improved by using multi-dimensional asynchronous processing and modifying inertia weight parameters so that the efficiency and local searching ability of the PSO were improved. The example analysis shows that the model and the algorithm can effectively reduce …
High-Dimensional Clustering Method Based On Variant Bat Algorithm,
2019
1. The PLA Information Engineering University, Zhengzhou 450001, China; ;2. Science and Technology on Information Assurance Laboratory, Beijing 100072, China;
High-Dimensional Clustering Method Based On Variant Bat Algorithm, Kou Guang, Guangming Tang, Jiajing He, Hengwei Zhang
Journal of System Simulation
Abstract: With the advent of the era of big data, the information resource is growing rapidly, and the data are becoming high-dimensional. Traditional clustering methods have a good effect for low-dimensional data, but no longer apply to high-dimensional data. On the basis of existing high-dimensional clustering algorithm, a high-dimensional clustering algorithm based on intelligent optimization SSC-BA is proposed. A novel objective function is designed, which integrates the fuzzy weighting within-cluster compactness and the between-cluster separation. A variant bat algorithm is introduced to calculate the weight matrix, giving the new learning rules. Simulation experiments are made for the proposed algorithm, and …
Auditor: An R Package For Model-Agnostic Visual Validation And Diagnostics,
2019
Warsaw University of Technology
Auditor: An R Package For Model-Agnostic Visual Validation And Diagnostics, Alicja Gosiewska, Przemysław Biecek
The R Journal
Machine learning models have successfully been applied to challenges in applied in biology, medicine, finance, physics, and other fields. With modern software it is easy to train even a complex model that fits the training data and results in high accuracy on test set. However, problems often arise when models are confronted with the real-world data. This paper describes methodology and tools for model-agnostic auditing. It provides functinos for assessing and comparing the goodness of fit and performance of models. In addition, the package may be used for analysis of the similarity of residuals and for identification of outliers and …
Stressmon: Scalable Detection Of Perceived Stress And Depression Using Passive Sensing Of Changes In Work Routines And Group Interactions,
2019
Singapore Management University
Stressmon: Scalable Detection Of Perceived Stress And Depression Using Passive Sensing Of Changes In Work Routines And Group Interactions, Nur Camellia Binte Zakaria, Rajesh Balan, Youngki Lee
Research Collection School Of Computing and Information Systems
Stress and depression are a common affliction in all walks of life. When left unmanaged, stress can inhibit productivity or cause depression. Depression can occur independently of stress. There has been a sharp rise in mobile health initiatives to monitor stress and depression. However, these initiatives usually require users to install dedicated apps or multiple sensors, making such solutions hard to scale. Moreover, they emphasise sensing individual factors and overlook social interactions, which plays a significant role in influencing stress and depression while being a part of a social system. We present StressMon, a stress and depression detection system that …
Aspect And Opinion Aware Abstractive Review Summarization With Reinforced Hard Typed Decoder,
2019
Tsinghua University
Aspect And Opinion Aware Abstractive Review Summarization With Reinforced Hard Typed Decoder, Yufei Tian, Jianfei Yu, Jing Jiang
Research Collection School Of Computing and Information Systems
In this paper, we study abstractive review summarization. Observing that review summaries often consist of aspect words, opinion words and context words, we propose a two-stage reinforcement learning approach, which first predicts the output word type from the three types, and then leverages the predicted word type to generate the final word distribution. Experimental results on two Amazon product review datasets demonstrate that our method can consistently outperform several strong baseline approaches based on ROUGE scores.
Gender And Racial Diversity In Commercial Brands’ Advertising Images On Social Media,
2019
Singapore Management University
Gender And Racial Diversity In Commercial Brands’ Advertising Images On Social Media, Jisun An, Haewoon Kwak
Research Collection School Of Computing and Information Systems
Gender and racial diversity in the mediated images from the media shape our perception of different demographic groups. In this work, we investigate gender and racial diversity of 85,957 advertising images shared by the 73 top international brands on Instagram and Facebook. We hope that our analyses give guidelines on how to build a fully automated watchdog for gender and racial diversity in online advertisements.
An Extensible Geospatial Data Framework (Geoedf) For Fair Science,
2019
Purdue University
An Extensible Geospatial Data Framework (Geoedf) For Fair Science, Carol Song, Rajesh Kalyanam, Lan Zhao
Purdue GIS Day
The growing urgency in dealing with the 21st century’s grand challenges associated with increasing population, food and water security, frequently occurring natural disasters, and changing climate demands innovative, collaborative, and multidisciplinary solutions for sustainability and resilience. However, scientific data, especially geospatial data, presents significant barriers to the effective access, use and sharing of data as they come in large volumes, from different sources, and with widely varying formats, resolutions, or annotation schemas that can differ among disciplines or even research groups. This presentation describes a recently funded NSF CSSI project to develop an open source, extensible geospatial data framework (GeoEDF), …
Combining Micro And Macro Features For Online Pattern-Of-Life Movement Prediction,
2019
Singapore Management University
Combining Micro And Macro Features For Online Pattern-Of-Life Movement Prediction, Shiau Hong Lim, Hasan Poonawala, Laura Wynter
Research Collection School Of Computing and Information Systems
We investigate the problem of predicting the future location of mobile objects, such as vehicles, ships, or people, in real time with a high degree of accuracy. Our premise is that an effective combination of recent and long-term historical data can significantly improve prediction performance by enabling a representation of the patterns-of-life of the objects. However, finding a feature representation that captures the long-term observed history of the objects in a compact yet informative manner is a key challenge in data mining and machine learning. To this end, we propose to combine “micro” features, which capture recent fine-grained trends, with …
Gender And Racial Diversity In Commercial Brands' Advertising Images On Social Media,
2019
Singapore Management University
Gender And Racial Diversity In Commercial Brands' Advertising Images On Social Media, Jisun An, Haewoon Kwak
Research Collection School Of Computing and Information Systems
Gender and racial diversity in the mediated images from the media shape our perception of different demographic groups. In this work, we investigate gender and racial diversity of 85,957 advertising images shared by the 73 top international brands on Instagram and Facebook. We hope that our analyses give guidelines on how to build a fully automated watchdog for gender and racial diversity in online advertisements.
Predicting Audience Engagement Across Social Media Platforms In The News Domain,
2019
Hamad Bin Khalifa University
Predicting Audience Engagement Across Social Media Platforms In The News Domain, Kholoud Khalil Aldous, Jisun An, Bernard J. Jansen
Research Collection School Of Computing and Information Systems
We analyze cross-platform factors for posts on both single and multiple social media platforms for numerous news outlets to better predict audience engagement, precisely the number of likes and comments. We collect 676,779 social media posts from 53 news outlets during eight months on four social media platforms (Facebook, Instagram, Twitter, and YouTube), along with the associated comments (more than 31 million) and the number of likes (more than 840 million). We develop a framework for predicting the audience engagement based on both linguistic features of the post and social media platform factors. Among other findings, results show that content …
Estimating Glycemic Impact Of Cooking Recipes Via Online Crowdsourcing And Machine Learning,
2019
Singapore Management University
Estimating Glycemic Impact Of Cooking Recipes Via Online Crowdsourcing And Machine Learning, Helena Lee, Palakorn Achananuparp, Yue Liu, Ee-Peng Lim, Lav R. Varshney
Research Collection School Of Computing and Information Systems
Consumption of diets with low glycemic impact is highly recommended for diabetics and pre-diabetics as it helps maintain their blood glucose levels. However, laboratory analysis of dietary glycemic potency is time-consuming and expensive. In this paper, we explore a data-driven approach utilizing online crowdsourcing and machine learning to estimate the glycemic impact of cooking recipes. We show that a commonly used healthiness metric may not always be effective in determining recipes suitable for diabetics, thus emphasizing the importance of the glycemic-impact estimation task. Our best classification model, trained on nutritional and crowdsourced data obtained from Amazon Mechanical Turk (AMT), can …
Automated Morgan Keenan Classification Of Observed Stellar Spectra Collected By The Sloan Digital Sky Survey Using A Single Classifier,
2019
Central Washington University
Automated Morgan Keenan Classification Of Observed Stellar Spectra Collected By The Sloan Digital Sky Survey Using A Single Classifier, Michael J. Brice, Răzvan Andonie
All Faculty Scholarship for the College of the Sciences
The classification of stellar spectra is a fundamental task in stellar astrophysics. Stellar spectra from the Sloan Digital Sky Survey are applied to standard classification methods, k-nearest neighbors and random forest, to automatically classify the spectra. Stellar spectra are high dimensional data and the dimensionality is reduced using astronomical knowledge because classifiers work in low dimensional space. These methods are utilized to classify the stellar spectra into a complete Morgan Keenan classification (spectral and luminosity) using a single classifier. The motion of stars (radial velocity) causes machine-learning complications through the feature matrix when classifying stellar spectra. Due to the nature …
Integrating Mathematics And Biology In The Classroom: A Compendium Of Case Studies And Labs,
2019
University of North Carolina at Asheville
Integrating Mathematics And Biology In The Classroom: A Compendium Of Case Studies And Labs, Becky Sanft, Anne Walter
Annual Symposium on Biomathematics and Ecology Education and Research
No abstract provided.
Quantifying Pollen Traits To Build A Mathematical Model Of Pollen Competition - A Mathematician's Perspective,
2019
Westminster College
Quantifying Pollen Traits To Build A Mathematical Model Of Pollen Competition - A Mathematician's Perspective, Montana Ferita, Julie Fucarino, Alex Capaldi, Charlotte Beckford
Annual Symposium on Biomathematics and Ecology Education and Research
No abstract provided.
Period Drift In A Neutrally Stable Stochastic Oscillator,
2019
Illinois State University
Period Drift In A Neutrally Stable Stochastic Oscillator, Kevin Sanft
Annual Symposium on Biomathematics and Ecology Education and Research
No abstract provided.
An Agent-Based Model Of An Endangered Florida Tillansia Utriculata Population,
2019
Rhodes College
An Agent-Based Model Of An Endangered Florida Tillansia Utriculata Population, Erin N. Bodine, Alexandra Campbell, Anna C. Kula
Annual Symposium on Biomathematics and Ecology Education and Research
No abstract provided.
Topicsummary: A Tool For Analyzing Class Discussion Forums Using Topic Based Summarizations,
2019
Singapore Management University
Topicsummary: A Tool For Analyzing Class Discussion Forums Using Topic Based Summarizations, Swapna Gottipati, Venky Shankararaman, Renjini Ramesh
Research Collection School Of Computing and Information Systems
This Innovative Practice full paper, describes the application of text mining techniques for extracting insights from a course based online discussion forum through generation of topic based summaries. Discussions, either in classroom or online provide opportunity for collaborative learning through exchange of ideas that leads to enhanced learning through active participation. Online discussions offer a number of benefits namely providing additional time to reflect and synthesize information before writing, providing a natural platform for students to voice their ideas without any one student dominating the conversation, and providing a record of the student’s thoughts. An online discussion forum provides a …
On Analysing Supply And Demand In Labor Markets: Framework, Model And System,
2019
Singapore Management University
On Analysing Supply And Demand In Labor Markets: Framework, Model And System, Hendrik Santoso Sugiarto, Ee-Peng Lim, Ngak Leng Sim
Research Collection School Of Computing and Information Systems
The labor market refers to the market between job seekers and employers. As much of job seeking and talent hiring activities are now performed online, a large amount of job posting and application data have been collected and can be re-purposed for labor market analysis. In the labor market, both supply and demand are the key factors in determining an appropriate salary for both job applicants and employers in the market. However, it is challenging to discover the supply and demand for any labor market. In this paper, we propose a novel framework to built a labor market model using …
