2016 Annual Conference on Information Science and Systems (CISS)最新文献

{"title":"Computational mapping of brain networks","authors":"M. Moreno-Ortega, D. Javitt, A. Kangarlu","doi":"10.1109/CISS.2016.7513716","DOIUrl":"https://doi.org/10.1109/CISS.2016.7513716","url":null,"abstract":"Magnetic resonance imaging (MRI) has developed into an indispensible diagnostic tool in medicine. MRI has also demonstrated immense potential for researchers who are making progress in every aspect of this modality expanding its applications into uncharted territories. Computational techniques have made major contributions to MRI enabling detection of minute signals from human brain. Functional MRI (fMRI) offers imaging of the mind as well as the brain in the same session. Complex computational tools are used to visualize brain networks that offer a new powerful tool to study the brain and its disorders. Functional connectivity (fc) maps using resting state fMRI (rsfMRI) is computed by detecting temporal synchronicity of neuronal activation patterns of anatomically separated brain regions. But, a great deal of technological advancement, both in hardware and software, had to be made to make computation of brain networks possible. The critical technologies that made computational modeling of functional brain networks possible were high quality gradients for implementation of distortion free fMRI, faster pulse sequences and radio frequency (RF) coils to capture the fluctuation frequency of neuronal activity, and complex post processing computation of brain networks. rsfMRI is capable of detecting brain function that mediate high cognitive processes in normal brain. We aim to ultimately detect the disruption of this mediation in psychiatric patients. We have already obtained functional connectivity in normal subjects using fMRI data during resting state. We did this as a function of spatial resolution to explore the required computational sources and susceptibility effects on the sensitivity of fMRI to anatomic specialization. We provide a conceptual summary of the role of computational techniques in fMRI data analysis. In exploring this question, ultimately MRI's capability in accessing information at the neuronal level comes to surface. We use latest computational tools for analysis of data from human brain and offer a vision for future developments that could revolutionize the use of computational techniques in making neuropsychiatry a quantitative practice.","PeriodicalId":346776,"journal":{"name":"2016 Annual Conference on Information Science and Systems (CISS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129000988","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 Adaptive Bacterial Foraging Algorithm for color image enhancement","authors":"O. Verma, R. Chopra, Abhinav Gupta","doi":"10.1109/CISS.2016.7460467","DOIUrl":"https://doi.org/10.1109/CISS.2016.7460467","url":null,"abstract":"A new approach in spatial domain is presented for the enhancement of color images using an Adaptive Bacterial Foraging Algorithm (ABFA). The image may be classified as under-exposed or over-exposed depending upon the value of exposure. A new objective function is formulated which makes use of the fuzzy entropy. This objective function is optimized using ABFA which allows the step-size of the bacterial colony to vary dynamically over the generations. The lifetime of the bacterial colony is described by generations which are split into two phases; exploration and exploitation based on the value of step-size. Smaller step-sizes correspond to exploitation phases in which the entire bacterial colony is trying to exploit a region of interest while larger step-sizes correspond to exploration phases in which the entire bacterial colony is trying to explore the search space to find regions of interest which can then be exploited by reducing the step-size. This method is applicable on both over-exposed and under-exposed images. The proposed algorithm is found to be better and much more simplified than the existing Bacterial Foraging Algorithm (BFA) in fuzzy domain for color image enhancement upon comparison.","PeriodicalId":346776,"journal":{"name":"2016 Annual Conference on Information Science and Systems (CISS)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128701073","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":"Two-sided change detection under unknown initial state","authors":"James Falt, S. Blostein","doi":"10.1109/CISS.2016.7460539","DOIUrl":"https://doi.org/10.1109/CISS.2016.7460539","url":null,"abstract":"The problem of detecting a change in distribution of a sequence of independent and identically distributed (IID) random variables is addressed. Unlike previous approaches to sequential change detection, which assume a known initial probability density function (PDF) for the sequence, in this paper we address the case where the initial distribution of the sequence is unknown. An optimal stopping approach based on Bayesian hypothesis testing with exponential delay cost is proposed. The tradeoffs among average detection delay, probability of false alarm and probability of detecting a change in the incorrect direction are investigated. It is shown that the proposed test's probability of change detection in the incorrect direction can be made arbitrarily small without significantly increasing average detection delay for change times larger than a minimum value determined by the hypothesis testing problem itself. The proposed test also has a recursive algorithm to track the minimum risk hypotheses with fixed complexity per sample. Simulation results confirm the derived properties and reveal that the average delay, after an initial transient period, approaches that of the CUSUM test, which is delay-optimal if the initial state were known.","PeriodicalId":346776,"journal":{"name":"2016 Annual Conference on Information Science and Systems (CISS)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115408697","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":"Differentially private multi-party computation","authors":"P. Kairouz, Sewoong Oh, P. Viswanath","doi":"10.1109/CISS.2016.7460489","DOIUrl":"https://doi.org/10.1109/CISS.2016.7460489","url":null,"abstract":"We study the problem of multi-party computation under approximate (ε,δ) differential privacy. We assume an interactive setting with k parties, each possessing a private bit. Each party wants to compute a function defined on all the parties' bits. Differential privacy ensures that there remains uncertainty in any party's bit even when given the transcript of interactions and all the other parties' bits. This paper is a follow up to our work, where we studied multi-party computation under (ε, 0) differential privacy. We generalize the results and prove that a simple non-interactive randomized response mechanism is optimal. Our optimality result holds for all privacy levels (all values of ε and δ), heterogenous privacy levels across parties, all types of functions to be computed, all types of cost metrics, and both average and worst-case (over the inputs) measures of accuracy.","PeriodicalId":346776,"journal":{"name":"2016 Annual Conference on Information Science and Systems (CISS)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121714110","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":"Energy-efficient resource allocation for SWIPT in multiple access channels","authors":"T. A. Zewde, M. C. Gursoy","doi":"10.1109/CISS.2016.7460509","DOIUrl":"https://doi.org/10.1109/CISS.2016.7460509","url":null,"abstract":"In this paper, we study optimal resource allocation strategies for simultaneous information and power transfer (SWIPT) focusing on the system energy efficiency. We consider two-user multiple access channels in which energy harvesting (EH) and information decoding (ID) nodes are spatially separated. We formulate optimization problems that maximize system energy efficiency while taking harvested energy constraints into account. These are concave-linear fractional problems, and hence Karush-Kuhn-Tucker (KKT) conditions are necessary and sufficient to obtain globally optimal solution. Solving these optimization problems, we provide analytical expressions for optimal transmit power allocation among the source nodes, and identify the corresponding energy efficiency. We confirm the theoretical analysis via numerical results. Furthermore, we also characterize the effect of circuit power consumption on the system's efficiency as the harvested energy demand varies.","PeriodicalId":346776,"journal":{"name":"2016 Annual Conference on Information Science and Systems (CISS)","volume":"455 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116767962","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":"Doubly opportunistic beamforming for downlink multiuser MIMO","authors":"Junyoung Nam, Young-Jo Ko","doi":"10.1109/CISS.2016.7460479","DOIUrl":"https://doi.org/10.1109/CISS.2016.7460479","url":null,"abstract":"We develop a novel opportunistic beamforming scheme referred to as doubly opportunistic beamforming (DOBF), which is doubly selective in both users and beams based on a new type of channel state information (CSI) feedback to improve the limited feedback downlink system performance. DOBF benefits from very flexible scheduling at the transmitter, compared to the conventional opportunistic beamforming. We provide new findings as to how much the inaccurate signal to interference and noise ratio (SINR) estimation due to lack of scheduling information at the receivers affects the performance of zero-forcing beamforming (ZFBF) with limited feedback. On the contrary, DOBF does not suffer from such a SINR inaccuracy problem. Rather surprisingly, numerical results show that our scheme can noticeably outperform even ZFBF under a comparable amount of CSI feedback load when spatially correlated fading and performance degradation due to limited scheduling information are taken into account.","PeriodicalId":346776,"journal":{"name":"2016 Annual Conference on Information Science and Systems (CISS)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134178398","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":"Controlling information flow and energy use via adaptive synaptogenesis","authors":"W. Levy, Harang Ju, R. Baxter, C. Colbert","doi":"10.1109/CISS.2016.7460559","DOIUrl":"https://doi.org/10.1109/CISS.2016.7460559","url":null,"abstract":"The adaptive synaptogenesis algorithm is a mathematically defined, random process that, in its present form, creates a feedforward network of excitatory synapses without supervision. The algorithm is fully local and consists of three separate modification processes: random synapse formation, modification of an existing synapse's strength (both strengthening and weakening), and shedding of very weak synapses. The algorithm is shown to have desirable stability properties; further, the algorithm can be parameterized to control the synaptic energy use by a neuron and to control the net information received by a neuron. In addition to the fundamental mathematics on which the algorithm is based, the interaction of parameter settings with characterized random inputs are described. Finally, specific extensions of the algorithm are suggested.","PeriodicalId":346776,"journal":{"name":"2016 Annual Conference on Information Science and Systems (CISS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124843274","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":"Prediction of granular time-series energy consumption for manufacturing jobs from analysis and learning of historical data","authors":"C. Duerden, L. Shark, G. Hall, Joe Howe","doi":"10.1109/CISS.2016.7460575","DOIUrl":"https://doi.org/10.1109/CISS.2016.7460575","url":null,"abstract":"In the manufacturing sector, the consideration of energy consumption during the scheduling and execution of jobs can offer significant benefits from an infrastructural and financial perspective. While numerous methods have been proposed for predicting the energy consumption of manufacturing machinery, they typically do not treat them as dynamic pieces of equipment which can lead to issues with long term accuracy. Furthermore, these models produce predictions at a high level of abstraction which can lead to sub-optimal utilization. This paper addresses these shortcomings and presents a new methodology based around the usage and inference of historical energy data. Multiple energy profiles for identical jobs are stored along with information regarding the machines mechanical conditions, allowing the system to compensate for machine-related changes to the energy consumption. Where historical data is lacking, analysis of how the machine's condition affects job energy consumption over time, allows for the use of Support Vector Regression to generate temporary synthetic energy profiles compensated for probable machine conditions.","PeriodicalId":346776,"journal":{"name":"2016 Annual Conference on Information Science and Systems (CISS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125764102","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":"Design and implementation of an underlay control channel for NC-OFDM-based networks","authors":"Ratnesh Kumbhkar, G. Sridharan, N. Mandayam, I. Seskar, S. Kompella","doi":"10.1109/CISS.2016.7460506","DOIUrl":"https://doi.org/10.1109/CISS.2016.7460506","url":null,"abstract":"This paper designs an underlay control channel for noncontiguous-OFDM-based cognitive networks. Noncontiguous OFDM (NC-OFDM) provides a fast and flexible manner of accessing disjoint parts of the spectrum and is ideally suited for dynamic spectrum access. While similar to OFDM, NC-OFDM explicitly restricts transmission to only certain subcarriers that are free of incumbent transmissions. In particular, this paper considers designing a control channel for a cognitive network consisting of multiple point-to-point (p2p) links that operate over a wide bandwidth that might encompass some primary transmissions. In such a scenario, control channel becomes vital not only to share basic transmission parameters but also to aid timing and frequency recovery of NC-OFDM transmission; a nontrivial problem in itself. The proposed design is a low-power underlay transmission that spans the entire bandwidth regardless of any incumbent transmissions and uses direct sequence spread spectrum (DSSS). The control channel operates in one of two modes. The first mode aids timing and frequency recovery through a two-step process, while the second mode is used for control data transmission. To enable multiple access, the p2p links use orthogonal pseudo-noise (PN) sequences. The proposed control channel is implemented on USRPs in the ORBIT testbed using GNU Radio. Experimental results suggest robust timing and frequency offset recovery even in the presence of concurrent primary transmissions and support for about 10 to 20kbps over a 1 MHz bandwidth at an uncoded symbol-error-rate of about 10-2 under typical operating conditions.","PeriodicalId":346776,"journal":{"name":"2016 Annual Conference on Information Science and Systems (CISS)","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127248946","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":"Multiperiod subscription pricing for cellular wireless entrants","authors":"Xinyi Hu, Y. Shan, G. Kesidis, S. Sarkar, R. Dhar, S. Fdida","doi":"10.1109/CISS.2016.7460523","DOIUrl":"https://doi.org/10.1109/CISS.2016.7460523","url":null,"abstract":"We consider a two-player game involving a large incumbent (or incumbent oligopoly) and small entrant into a cellular-wireless access provider marketplace. The entrant's customers must pay roaming charges. We assume that the roaming charges are transparent to the user and regulated to prevent an incumbent from creating barriers to entry in the marketplace. To be able to reckon suitable (regulated) roaming charges, in this paper we consider a potentially stricter model of competition than [7] (though still not all subscribers to the lowest-cost provider), and a revenue function for the entrant that considers future revenue streams when its deployment is greater and its customers therefore do not roam as much, i.e., a multiperiod/longitudinal revenue model.","PeriodicalId":346776,"journal":{"name":"2016 Annual Conference on Information Science and Systems (CISS)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127785844","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}