SoutheastCon 2017最新文献_第8页

From social media to public health surveillance: Word embedding based clustering method for twitter classification 从社交媒体到公共卫生监测:基于词嵌入的twitter分类聚类方法

SoutheastCon 2017 Pub Date : 2017-03-01 DOI: 10.1109/SECON.2017.7925400

Xiangfeng Dai, M. Bikdash, B. Meyer

{"title":"From social media to public health surveillance: Word embedding based clustering method for twitter classification","authors":"Xiangfeng Dai, M. Bikdash, B. Meyer","doi":"10.1109/SECON.2017.7925400","DOIUrl":"https://doi.org/10.1109/SECON.2017.7925400","url":null,"abstract":"Social media provide a low-cost alternative source for public health surveillance and health-related classification plays an important role to identify useful information. In this paper, we summarized the recent classification methods using social media in public health. These methods rely on bag-of-words (BOW) model and have difficulty grasping the semantic meaning of texts. Unlike these methods, we present a word embedding based clustering method. Word embedding is one of the strongest trends in Natural Language Processing (NLP) at this moment. It learns the optimal vectors from surrounding words and the vectors can represent the semantic information of words. A tweet can be represented as a few vectors and divided into clusters of similar words. According to similarity measures of all the clusters, the tweet can then be classified as related or unrelated to a topic (e.g., influenza). Our simulations show a good performance and the best accuracy achieved was 87.1%. Moreover, the proposed method is unsupervised. It does not require labor to label training data and can be readily extended to other classification problems or other diseases.","PeriodicalId":368197,"journal":{"name":"SoutheastCon 2017","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117164867","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 61

A potential field inspired approach to attitude motion planning with unit-quaternions 基于位场启发的四元数姿态运动规划方法

SoutheastCon 2017 Pub Date : 2017-03-01 DOI: 10.1109/SECON.2017.7925271

D. R. Isenberg

引用次数: 0

A 70 GHz Rotary Traveling Wave Oscillator (RTWO) in 65-nm CMOS 65纳米CMOS的70 GHz旋转行波振荡器(RTWO)

SoutheastCon 2017 Pub Date : 2017-03-01 DOI: 10.1109/SECON.2017.7925275

Marvin Aidoo, Goker Ariyak, F. Rabbi, Monique Kirkman-Bey, N. Dogan, Zhijian Xie

引用次数: 6

Spiking deconvolution for seismic waves using the Fractional Fourier Transform 利用分数阶傅里叶变换对地震波进行尖峰反卷积

SoutheastCon 2017 Pub Date : 2017-03-01 DOI: 10.1109/SECON.2017.7925350

S. Sud

引用次数: 1

Optimization of EEG-based imaginary motion classification using majority-voting 基于多数投票的脑电图假想运动分类优化

SoutheastCon 2017 Pub Date : 2017-03-01 DOI: 10.1109/SECON.2017.7925328

Sylvia Bhattacharya, Kaushik Bhimraj, Rami J. Haddad, M. Ahad

{"title":"Optimization of EEG-based imaginary motion classification using majority-voting","authors":"Sylvia Bhattacharya, Kaushik Bhimraj, Rami J. Haddad, M. Ahad","doi":"10.1109/SECON.2017.7925328","DOIUrl":"https://doi.org/10.1109/SECON.2017.7925328","url":null,"abstract":"Electroencephalography is widely used to record neural activity with electrodes positioned at specific locations on a human scalp. These recorded signals are interfaced with a computer which is referred to as noninvasive Brain Computer Interface (BCI). An important application of this technology is to help facilitate the lives of the tetraplegic through assimilating human brain impulses and converting them into mechanical motion. However, BCI systems are remarkably challenging to implement as recorded brain signals can be unreliable and vary in pattern throughout time. In this paper, a novel classifier structure is proposed to classify different types of imaginary motions (left hand, right hand, and imagination of words starting with the same letter) across multiple sessions using an optimized set of electrodes for each user. The proposed technique uses raw brain signals obtained utilizing 32 electrodes and classifies the imaginary motions using Artificial Neural Networks (ANN). To enhance the classification rate and optimize the set of electrodes of each subject, a majority voting system combining a set of simple ANNs is used. This electrode optimization technique achieved classification accuracies of 69.83%, 94.04% and 84.56% respectively for the three subjects considered in this study.","PeriodicalId":368197,"journal":{"name":"SoutheastCon 2017","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125253966","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 6

Simulating micro-robots to find a point of interest under noise and with limited communication using Particle Swarm Optimization 利用粒子群算法模拟微机器人在噪声和有限通信条件下寻找兴趣点

SoutheastCon 2017 Pub Date : 2017-03-01 DOI: 10.1109/SECON.2017.7925267

M. Stender, Yanjun Yan, H. Karayaka, Peter Tay, Robert D. Adams

{"title":"Simulating micro-robots to find a point of interest under noise and with limited communication using Particle Swarm Optimization","authors":"M. Stender, Yanjun Yan, H. Karayaka, Peter Tay, Robert D. Adams","doi":"10.1109/SECON.2017.7925267","DOIUrl":"https://doi.org/10.1109/SECON.2017.7925267","url":null,"abstract":"This paper presents the simulation results of a swarm of micro-robots collaborating to find a point of interest in 2D space. Guided by a fitness function, the Particle Swarm Optimization (PSO) algorithm is highly efficient to explore the solution space and find such an optimum. However, in real-world scenarios in which the particles are micro-robots, there are practical constraints. The two most significant constraints are: (1) given communication and measurement noise, the fitness function evaluation will be noisy, (2) given the limited communication range of micro-robots, broadcasting the global best solution is too expensive. A neighborhood PSO (NPSO) algorithm is proposed to replace the global best by the neighborhood best. Different applications call for different fitness functions, and three benchmark functions, representing three typical scenarios, are examined: (1) a unimodal and symmetric scenario with only one global optimum, (2) a multi-modal scenario with one global optimum but many local optima, and (3) a uni-model but asymmetric scenario. For each fitness function, simulations on the effects of the two aforementioned constraints, individually or combined, are carried out. The results demonstrate that PSO is tolerant to noise up to certain level and NPSO is a practical adaptation to implement swarm intelligence in swarm robotics.","PeriodicalId":368197,"journal":{"name":"SoutheastCon 2017","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127921493","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 10

Power system optimization with an inertia study on the IEEE 30-bus test system 基于IEEE 30总线测试系统的电力系统惯性优化研究

SoutheastCon 2017 Pub Date : 2017-03-01 DOI: 10.1109/SECON.2017.7925360

Sandeep Sadanandan, B. Natarajan

引用次数: 4

FAS: Federated Auditing for Software-defined exchanges FAS:软件定义交换的联邦审计

SoutheastCon 2017 Pub Date : 2017-03-01 DOI: 10.1109/SECON.2017.7925261

Joaquín Chung, Jacob H. Cox, Russ Clark, H. Owen

{"title":"FAS: Federated Auditing for Software-defined exchanges","authors":"Joaquín Chung, Jacob H. Cox, Russ Clark, H. Owen","doi":"10.1109/SECON.2017.7925261","DOIUrl":"https://doi.org/10.1109/SECON.2017.7925261","url":null,"abstract":"The Software-defined exchange (SDX) allows multiple independent administrative domains to share computing, storage, and networking resources. One variation on the SDX applies software-defined networking (SDN) technologies to the fabric of an Internet exchange point (IXP) to support rich policy expression among participants. Similarly, Research and Education (R&E) networks are introducing SDN at exchange points to enable network operators to provision network policies over multiple independent administrative domains. The federated nature of R&E exchange points is based on a chain of trust between participant domains. However, trust and verifiability go hand in hand, an old adage says “trust, but verify”, so a responsible network operator would like to verify that his or her policies are honored by the SDN domains participating at an SDX. Moreover, some SDX participants do not want to reveal internal topology information while proving they correctly deployed the requested policies. For these reasons, we propose Federated Auditing for SDX (FAS), a federated auditing framework for SDX configuration verification, which reveals the minimal necessary information to an SDX central controller. We also show our initial proof-of-concept and preliminary evaluation.","PeriodicalId":368197,"journal":{"name":"SoutheastCon 2017","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117234787","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

A novel automated SDN architecture and orchestration framework for resilient large-scale networks 一种用于弹性大规模网络的新型自动化SDN架构和编排框架

SoutheastCon 2017 Pub Date : 2017-03-01 DOI: 10.1109/SECON.2017.7925317

D. Oliveira, M. Pourvali, Hao Bai, N. Ghani, T. Lehman, Xi Yang, M. Hayat

引用次数: 4

Development of robot swarm algorithms on an extensible framework 基于可扩展框架的机器人群算法的开发

SoutheastCon 2017 Pub Date : 2017-03-01 DOI: 10.1109/SECON.2017.7925296

S. Bhattacharya, R. Agrawal

{"title":"Development of robot swarm algorithms on an extensible framework","authors":"S. Bhattacharya, R. Agrawal","doi":"10.1109/SECON.2017.7925296","DOIUrl":"https://doi.org/10.1109/SECON.2017.7925296","url":null,"abstract":"Swarm intelligence for robots is inspired by observation of how homogenous collections of animals behave in nature to succeed in finding food and avoiding predators. Swarm robots usually lack centralized control to determine each robots individual behavior, however global behaviors can emerge through many local interactions, which are simple in nature. Studies show that simple rules executed on the individual robot can explain complex group behaviors and it is sufficient to support only local sensing and communication. The advantages of swarm intelligence are robustness at the level of the group where individual failure is not a significant problem; individual behaviors are easy to implement, and the approaches are scalable since the control mechanisms do not depend on the number of individuals in the swarm. We present an ongoing project that leverages hardware and extends software for swarm robotics. The hardware consists of robots called swarmies. A swarmie is a small robotic vehicle with a webcam, a GPS system, sensors like IMU, ultrasonic obstacle detector; a Wi-Fi antenna for wireless communication and an on-board computer. The objective of the project is to develop algorithms for the Swarmies so they can communicate and thus execute cooperative april-tag collection autonomously. The software is a ROS (Robot Operating System) controller framework for the Swarmie robots. We were able to improve the swarmie's behavior to search a space more effectively and utilize computer vision methods.","PeriodicalId":368197,"journal":{"name":"SoutheastCon 2017","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133955915","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3