{"title":"On the Randomness Cost of Linear Secure Computation : (Invited Presentation)","authors":"Yanliang Zhou, Hua Sun, Shengli Fu","doi":"10.1109/CISS.2019.8692860","DOIUrl":"https://doi.org/10.1109/CISS.2019.8692860","url":null,"abstract":"We consider the problem of secure computation, where K users, each holding an independent message, wish to compute a function on the messages without revealing any additional information. We show that to compute M generic linear independent combinations of the messages securely (i.e., for the linear secure computation problem), it suffices to use $minleft(leftlceilfrac{K-M-1}{2}rightrceil,~Mright)$ randomness symbols per message symbol (i.e., the randomness cost is no larger than $minleft(leftlceilfrac{K-M-1}{2}rightrceil,~Mright)$). The optimality of the achieved randomness cost remains open.","PeriodicalId":123696,"journal":{"name":"2019 53rd Annual Conference on Information Sciences and Systems (CISS)","volume":"117 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131420334","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}
{"title":"Performance Comparison of Minimum Variance, Market and Eigen Portfolios for US Equities","authors":"Anqi Xiong, A. Akansu","doi":"10.1109/CISS.2019.8693035","DOIUrl":"https://doi.org/10.1109/CISS.2019.8693035","url":null,"abstract":"The Sharpe ratios and PNL curves of minimum variance, market and eigenportfolios for stocks in the Dow Jones Industrial Average (DJIA) index are calculated. We employed in this study a) the exponential function to approximate the measured cross correlations of the end of day (EOD) returns for US equities in DJIA, and b) their empirical correlation and covariance matrices to design the three portfolio types, and compare their market performance from May 4, 1999 to November 1, 2018. It is shown that the performances of portfolios derived by using exponential model based and empirical correlation and covariance matrices are consistent. We also displayed the PNL curve of DIA for performance comparison. It is observed from these PNLs that the first eigenportfolio significantly outperforms the other portfolios and DIA.","PeriodicalId":123696,"journal":{"name":"2019 53rd Annual Conference on Information Sciences and Systems (CISS)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128644491","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}
Daiki Mitsumoto, T. Hori, S. Sagayama, H. Yamasue, Keiho Owada, Masaki Kojima, K. Ochi, Nobutaka Ono
{"title":"Autism Spectrum Disorder Discrimination Based on Voice Activities Related to Fillers and Laughter","authors":"Daiki Mitsumoto, T. Hori, S. Sagayama, H. Yamasue, Keiho Owada, Masaki Kojima, K. Ochi, Nobutaka Ono","doi":"10.1109/CISS.2019.8692794","DOIUrl":"https://doi.org/10.1109/CISS.2019.8692794","url":null,"abstract":"Autism spectrum disorder (ASD) is a developmental disorder characterized by impairment in social communication, restricted interest and stereotyped behaviors. Since current diagnosis methods are depending on time intensive subjective assessments, the establishment of novel therapeutics could be facilitated by objective, quantitative, and reproducible methods for supporting diagnosis. To that end, we investigated acoustic features of speech which characterize the difference between ASD and typical development (TD). The focus of this paper are features related to fillers and laughter, which play important roles in communication as social signals, and were observed to be used differently by ASD and TD individuals in previous research. We investigated several such features and statistically evaluated how helpful they are for discriminating between ASD and TD. In an experiment, we applied a support vector machine (SVM) for ASD classification considering both prosodic acoustic features as well as the most significant features related to social signals. Discrimination accuracy and F-measure of were slightly improved when using not only the prosodic features but also those related to social signals.","PeriodicalId":123696,"journal":{"name":"2019 53rd Annual Conference on Information Sciences and Systems (CISS)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115422983","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}
{"title":"An intuitive and most efficient Ll-norm principal component analysis algorithm for big data","authors":"Xiaowei Song","doi":"10.1109/CISS.2019.8692807","DOIUrl":"https://doi.org/10.1109/CISS.2019.8692807","url":null,"abstract":"Grassmann average (GA) can coincide with Ll- norm principal component (PC) and is scalable for millions of samples. However, it is unclear whether there exists and how much further speed improvement can be gained by revising the fixed-point optimization-based GA. In this paper, I analyze such optimization process in an intuitive way and propose its improvement, i.e., an online algorithm without any iterations. I show that it can be most efficient in the sense that it only visits each sample once per PC, with minimal memory requirement, unlike GA or MATLAB svds. It is proved to be convergent for big data.","PeriodicalId":123696,"journal":{"name":"2019 53rd Annual Conference on Information Sciences and Systems (CISS)","volume":"132 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117120689","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}
{"title":"Motion correction for fetal functional magnetic resonance imaging","authors":"D. Scheinost","doi":"10.1109/CISS.2019.8693018","DOIUrl":"https://doi.org/10.1109/CISS.2019.8693018","url":null,"abstract":"We present a novel motion correction algorithm designed specifically for fetal functional magnetic imaging resonance (fMRI). Fetal motion is a main limiting factor of fetal fMRI and standard algorithm cannot correct for fetal motion. The goals in designing the algorithm were: (i) the ability to correct for both large and small motion, (ii) the preferential weighting of fetal tissue, (iii) the development of a framework robust to artifacts, and (iv) the automatic censoring of low quality frames. The key feature of the algorithm is the use of 2nd order edge features instead of raw intensity or 1st order edge features. We demonstrate that our algorithm significantly out performs competing approaches.","PeriodicalId":123696,"journal":{"name":"2019 53rd Annual Conference on Information Sciences and Systems (CISS)","volume":"96 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126960726","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}
{"title":"Worst-Case Latency Performance Of Load Balancing Through Distributed Waterfilling Algorithm","authors":"Jiangnan Cheng, Shih-Hao Tseng, A. Tang","doi":"10.1109/CISS.2019.8692917","DOIUrl":"https://doi.org/10.1109/CISS.2019.8692917","url":null,"abstract":"Intelligent-meshed mobile edge computing (IMMEC) network puts great emphasis on providing low latency services. This naturally requires using fast-timescale load balancing to avoid excessive delay resulted from overloading any particular network node. One natural candidate solution for such load balancing is distributed waterfilling algorithm. In this paper, we analyze its performance by comparing it against an ideal centralized version. It is shown that the worst-case average total latency difference between the two algorithms grows linearly with the size of the network and the propagation delay among different nodes.","PeriodicalId":123696,"journal":{"name":"2019 53rd Annual Conference on Information Sciences and Systems (CISS)","volume":"123 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124616545","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}
{"title":"Integrating Volterra Series Model and Deep Neural Networks to Equalize Nonlinear Power Amplifiers","authors":"R. Thompson, Xiaohua Li","doi":"10.1109/CISS.2019.8693029","DOIUrl":"https://doi.org/10.1109/CISS.2019.8693029","url":null,"abstract":"The nonlinearity of power amplifiers (PAs) has been one of the severe constraints to the performance of modern wireless transceivers. This problem is even more challenging for the fifth generation (5G) cellular system since 5G signals have extremely high peak to average power ratio. This paper develops nonlinear equalizers that exploit both deep neural networks (DNNs) and Volterra series models to mitigate PA nonlinear distortions. The DNN equalizer architecture consists of multiple one-dimension convolutional layers. The input features are designed according to the Volterra series model of nonlinear PAs. This enables the DNN equalizer to mitigate nonlinear PA distortions more effectively while avoiding over-fitting under limited training data. Experiments are conducted with both simulated data based on a Doherty nonlinear PA model and real measurement data obtained from a highly nonlinear cable TV PA. The results demonstrate that the proposed DNN equalizer has superior performance over conventional nonlinear equalization approaches.","PeriodicalId":123696,"journal":{"name":"2019 53rd Annual Conference on Information Sciences and Systems (CISS)","volume":"128 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126876916","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}
{"title":"Online Linear Programming with Uncertain Constraints : (Invited Paper)","authors":"Lin Yang, M. Hajiesmaili, W. Wong","doi":"10.1109/CISS.2019.8693056","DOIUrl":"https://doi.org/10.1109/CISS.2019.8693056","url":null,"abstract":"There are many applications scenarios in different disciplines where the critical knowledge of decision making arrives in a sequential manner, so the optimization must be done in an online fashion. An important class of online optimization problems that have been extensively studied in the past is online linear programs. This paper tackles a general class of online linear programs that take into account the online arrival of the constraint entries related to the available budget and demand for different problem settings. This generalization is motivated by many recent applications on revenue management or resource allocation problems with the unknown and time-varying budget. As the main contribution of this paper, we propose a decoupling strategy that can be used to reduce the general problem into a series of subproblems with offline entries for the budget and demand. Using the proposed strategy, one can decouple the general problem, leverage the state-of-the-art algorithms for the online subproblems with fixed constraints, and achieve the same performance for the general problem. As for a case study, we apply the strategy to an extension of the one-way trading problem with the dynamic budget.","PeriodicalId":123696,"journal":{"name":"2019 53rd Annual Conference on Information Sciences and Systems (CISS)","volume":"188 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125843336","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}
Asia Mason, Michel Reece, Gian Claude, Willie L. Thompson, K. Kornegay
{"title":"Analysis of Wireless Signature Feature Sets for Commercial IoT Devices : Invited Presentation","authors":"Asia Mason, Michel Reece, Gian Claude, Willie L. Thompson, K. Kornegay","doi":"10.1109/CISS.2019.8692811","DOIUrl":"https://doi.org/10.1109/CISS.2019.8692811","url":null,"abstract":"Advances in technology have led to an increase the number and type of electronic devices interconnected through the internet, or Internet of Things (IoT) devices. These devices are available commercially and are often used for applications in home environments, office buildings, medical facilities, and others. A common protocol used in IoT devices is the Institute of Electrical and Electronics Engineers (IEEE) 802.15.4 protocol. The vulnerabilities of the standard have led to numerous attacks on devices that follow this protocol. RF fingerprinting is a technique used to authenticate and verify devices in an environment to determine if they are either authorized or rogue to add a level of security at the physical layer. The fingerprints are comprised of statistical features, such as variance, skewness, and kurtosis, extracted from instantaneous RF signal characteristics. Previous RF fingerprinting work obtained features from generic ZigBee modules. This work aims to examine signal features of commercial IoT devices that adhere to the ZigBee protocol. The analysis will highlight correlations, if any, and differences between device vendor and IoT device type.","PeriodicalId":123696,"journal":{"name":"2019 53rd Annual Conference on Information Sciences and Systems (CISS)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116043520","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}
{"title":"A Comparison of the Finite Difference and Simultaneous Perturbation Gradient Estimation Methods with Noisy Function Evaluations","authors":"Adam Blakney, Jingyi Zhu","doi":"10.1109/CISS.2019.8693046","DOIUrl":"https://doi.org/10.1109/CISS.2019.8693046","url":null,"abstract":"Gradient information is useful in many applications such as optimization and sensitivity analysis, but is often inaccessible, providing a need for gradient estimation methods. This paper presents a comparison between the finite difference (FD) and simultaneous perturbation (SP) methods for gradient estimation. In practical experiments, function evaluations correspond to incurred costs, so the number of function evaluations used to form an estimate must be taken into account. Our theoretical results, supported by our numerical experiments, show that under certain circumstances the SP estimate has a smaller mean squared error (MSE) given a fixed number of function evaluations, and that the benefit gained from the SP method becomes more pronounced as the observation environment becomes noisier. We also discuss the performance of both methods in the noise-free case. We summarize guidelines for practitioners to determine which method is preferred, depending on the dimension of the function, noise magnitude, underlying gradient magnitude, and number of function evaluations available.","PeriodicalId":123696,"journal":{"name":"2019 53rd Annual Conference on Information Sciences and Systems (CISS)","volume":"527 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116491440","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}