SoutheastCon 2017最新文献_第9页

The implication of renewables, BES, and EV's in a sustainable power system 可再生能源、BES和电动汽车在可持续电力系统中的意义

SoutheastCon 2017 Pub Date : 2017-03-01 DOI: 10.1109/SECON.2017.7925272

E. Collins, Bhuvana Ramachandran

引用次数: 0

Qualitative assessment of surface roughness of limestone specimens from the orientation of unwrapped triangulated point clouds 从未包裹三角形点云的方向定性评价石灰岩样品的表面粗糙度

SoutheastCon 2017 Pub Date : 2017-03-01 DOI: 10.1109/SECON.2017.7925385

A. Bliss, N. Hudyma, Stephanie Brown, J. Oglesby, Alan Harris

引用次数: 4

A deep learning based approach for long-term drought prediction 基于深度学习的长期干旱预测方法

SoutheastCon 2017 Pub Date : 2017-03-01 DOI: 10.1109/SECON.2017.7925314

Norbert A. Agana, A. Homaifar

{"title":"A deep learning based approach for long-term drought prediction","authors":"Norbert A. Agana, A. Homaifar","doi":"10.1109/SECON.2017.7925314","DOIUrl":"https://doi.org/10.1109/SECON.2017.7925314","url":null,"abstract":"Drought is a natural disaster that comes with high hazardous impacts on the society. Its effects are mostly manifested as hydrological drought. Identifying past droughts and predicting future ones is very vital in limiting their effects. However, the random and nonlinear nature of drought variables makes accurate drought prediction remain a challenging scientific problem. Neural networks have shown great promise over the last two decades in modeling nonlinear time series. But the issue of nonconvex optimization ensues when two or more hidden layers are required for highly complex phenomena. This research looks into the drought prediction problem using deep learning algorithms. We propose a Deep Belief Network consisting of two Restricted Boltzmann Machines for long-term drought prediction using lagged values of Standardized Streamflow Index (SSI) as inputs. The proposed model is applied to predict different time scale drought indices across the Gunnison River Basin located in the Upper Colorado River Basin. The study compares the efficiency of the proposed model to that of traditional approaches such as Multilayer Perceptron (MLP) and Support Vector Regression (SVR) for predicting the different time scale drought conditions. The proposed model shows an edge in performance over the traditional methods using Root Mean Square Error and Mean Absolute Error as metrics.","PeriodicalId":368197,"journal":{"name":"SoutheastCon 2017","volume":"36 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":"121493903","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: 43

A robust “Plug-and-Play” application for executing virtualized indoor Wi-Fi localization 一个强大的“即插即用”应用程序，用于执行虚拟室内Wi-Fi定位

SoutheastCon 2017 Pub Date : 2017-03-01 DOI: 10.1109/SECON.2017.7925308

Anthony O. Drummonds, Daniel T. Fokum

引用次数: 0

An accurate way to cross reference users across Social Networks 一个准确的方式来交叉参考用户跨社交网络

SoutheastCon 2017 Pub Date : 2017-03-01 DOI: 10.1109/SECON.2017.7925366

J. J. Álvarez, Florina Almenárez Mendoza, Miguel Labrador

{"title":"An accurate way to cross reference users across Social Networks","authors":"J. J. Álvarez, Florina Almenárez Mendoza, Miguel Labrador","doi":"10.1109/SECON.2017.7925366","DOIUrl":"https://doi.org/10.1109/SECON.2017.7925366","url":null,"abstract":"Social Networks have permitted people have their own virtual identities which they use to interact with other online users. It is also completely possible and not uncommon for a user to have more than one online profile or even a completely different anonymous online identity. Sometimes it is needed to unmask the anonymity of certain profiles, or to identify two difference profiles as belonging to the same user. Entity Resolution (ER) is the task of matching two different online profiles potentially from different social networks. Solving ER has a number of benefits, amongst them are enhanced terrorist screening, improved marketing strategies, elimination of duplicate profiles, identification of fake profiles, etc. Our solution compares profiles based on various different attributes such as their usernames, real names, locations, languages and other similar attributes. We developed various string similarity algorithms and used other algorithms from another project to compare profiles, without using training. The system we developed was tested in a needle-in-a-haystack scenario where the system was tasked with matching two profiles that were in a pool of extremely similar profiles.","PeriodicalId":368197,"journal":{"name":"SoutheastCon 2017","volume":"19 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":"114319385","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

Active learning intrusion detection using k-means clustering selection 基于k-均值聚类选择的主动学习入侵检测

SoutheastCon 2017 Pub Date : 2017-03-01 DOI: 10.1109/SECON.2017.7925383

Steven McElwee

{"title":"Active learning intrusion detection using k-means clustering selection","authors":"Steven McElwee","doi":"10.1109/SECON.2017.7925383","DOIUrl":"https://doi.org/10.1109/SECON.2017.7925383","url":null,"abstract":"Intrusion detection is an important method for identifying attacks and compromises of computer systems, but it is complicated by rapid changes in technology, the increasing interconnectedness of devices on the internet, the growing use of cyberattacks, and more sophisticated and automated attack methods and tools used by adversaries. The challenge of intrusion detection is further complicated because, as advances are made in the ability to detect attacks, similar advances are made by adversaries to thwart those detective measures. Although numerous machine learning algorithms and approaches have proven effective in detecting cyberattacks, these algorithms have limitations, especially in dealing with adversarial environments. This study addresses the problem that there is not an effective machine learning algorithm that minimizes human interaction to train and evolve the learner to adapt to changing cyberattacks and evasive tactics. This research concludes that selective sampling of unlabeled data for classification by a human expert can result in more efficient labeling for large datasets and demonstrates a more resilient approach to machine learning that utilizes active learning to interact with human subject matter experts and that adapts to changing data, thus addressing issues related to data tampering and evasion.","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":"131277545","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: 18

Nonlinear auto-regressive neural network model for forecasting Hi-Def H.265 video traffic over Ethernet Passive Optical Networks 基于非线性自回归神经网络的无源光网络高清H.265视频流量预测

SoutheastCon 2017 Pub Date : 2017-03-01 DOI: 10.1109/SECON.2017.7925331

Collin Daly, David L. Moore, Rami J. Haddad

引用次数: 5

A survey of multisensor fusion techniques, architectures and methodologies 多传感器融合技术、架构和方法综述

SoutheastCon 2017 Pub Date : 2017-03-01 DOI: 10.1109/SECON.2017.7925311

B. Chandrasekaran, S. Gangadhar, J. Conrad

引用次数: 34

Modeling information spread in polarized communities: Transitioning from legacy media to a Facebook world 在两极分化的社区中建模信息传播:从传统媒体过渡到Facebook世界

SoutheastCon 2017 Pub Date : 2017-03-01 DOI: 10.1109/SECON.2017.7925355

Indravadan Patel, Hien Nguyen, E. Belyi, Y. Getahun, S. Abdulkareem, P. Giabbanelli, Vijay K. Mago

{"title":"Modeling information spread in polarized communities: Transitioning from legacy media to a Facebook world","authors":"Indravadan Patel, Hien Nguyen, E. Belyi, Y. Getahun, S. Abdulkareem, P. Giabbanelli, Vijay K. Mago","doi":"10.1109/SECON.2017.7925355","DOIUrl":"https://doi.org/10.1109/SECON.2017.7925355","url":null,"abstract":"Rumors have played an important role in social life for centuries, with early examples including their use to steer Roman politics. Today's world includes entire industries focused on digital misinformation, whose rumors can spread quickly via social networks such as Facebook not only because of their structure (e.g., clustering) but also because individuals can place an excessively high trust in information originating from their friends. Relaying information from our friends and ignoring or being unaware of other opinions leads to polarized groups, such as liberals or conservatives in a political context. While numerous models of rumor spreads have been proposed, their focus was more often on the conditions to stop/verify one rumor than in accounting for a polarized context. In this paper, we develop a new model of rumor spread with two different susceptibility rates, which can be used to investigate cases in which the population can be sub-divided with respect to one rumor (e.g. based on political opinions or socio-economic factors such as educational attainment). We describe the dynamics of the model using differential equations, and present numerical results regarding the model behavior with respect to key parameters such as the rate with which rumors are forgotten. While our work took into account network features (e.g., average degree), it is of particular interest for future work to examine the interplay between the network structure and the distribution of susceptibility rates.","PeriodicalId":368197,"journal":{"name":"SoutheastCon 2017","volume":"29 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":"132962603","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: 4

An automated Reconfigurable-Computing Environment for accelerating software applications 用于加速软件应用程序的自动化可重构计算环境

SoutheastCon 2017 Pub Date : 2017-03-01 DOI: 10.1109/SECON.2017.7925338

Shrikant S. Jadhav, C. Gloster, Vance Alford, C. Doss, Youngsoo Kim

引用次数: 4