Consensus in the Presence of Multiple Opinion Leaders: Effect of Bounded Confidence

The problem of analyzing the performance of networked agents exchanging evidence in a dynamic network has recently grown in importance. This problem has relevance in signal and data fusion network applications and in studying opinion and consensus dynamics in social networks. Due to its capability of handling a wider variety of uncertainties and ambiguities associated with evidence, we use the framework of Dempster-Shafer (DS) theory to capture the opinion of an agent. We then examine the consensus among agents in dynamic networks in which an agent can utilize either a cautious or receptive updating strategy. In particular, we examine the case of bounded confidence updating where an agent exchanges its opinion only with neighboring nodes possessing 'similar' evidence. In a fusion network, this captures the case in which nodes only update their state based on evidence consistent with the node's own evidence. In opinion dynamics, this captures the notions of Social Judgment Theory (SJT) in which agents update their opinions only with other agents possessing opinions closer to their own. Focusing on the two special DS theoretic cases where an agent state is modeled as a Dirichlet body of evidence and a probability mass function (p.m.f.), we utilize results from matrix theory, graph theory, and networks to prove the existence of consensus agent states in several time-varying network cases of interest. For example, we show the existence of a consensus in which a subset of network nodes achieves a consensus that is adopted by follower network nodes. Of particular interest is the case of multiple opinion leaders, where we show that the agents do not reach a consensus in general, but rather converge to 'opinion clusters'. Simulation results are provided to illustrate the main results.Comment: IEEE Transactions on Signal and Information Processing Over Networks, to appea

Stable 1-Norm Error Minimization Based Linear Predictors for Speech Modeling

In linear prediction of speech, the 1-norm error minimization criterion has been shown to provide a valid alternative to the 2-norm minimization criterion. However, unlike 2-norm minimization, 1-norm minimization does not guarantee the stability of the corresponding all-pole filter and can generate saturations when this is used to synthesize speech. In this paper, we introduce two new methods to obtain intrinsically stable predictors with the 1-norm minimization. The first method is based on constraining the roots of the predictor to lie within the unit circle by reducing the numerical range of the shift operator associated with the particular prediction problem considered. The second method uses the alternative Cauchy bound to impose a convex constraint on the predictor in the 1-norm error minimization. These methods are compared with two existing methods: the Burg method, based on the 1-norm minimization of the forward and backward prediction error, and the iteratively reweighted 2-norm minimization known to converge to the 1-norm minimization with an appropriate selection of weights. The evaluation gives proof of the effectiveness of the new methods, performing as well as unconstrained 1-norm based linear prediction for modeling and coding of speech

Pengaruh Pajak Progresif terhadap Perilaku Konsumtif, Basis Pajak, Kepatuhan Wajib Pajak dan Pendapatan Daerah Provinsi Bali

The focus of research on the issue of progressive tax on automobiles in Bali. This policy aims to increase local revenue comes from vehicle taxes, in addition to reducing traffic congestion in cities such as Denpasar and Badung. The research objective to analyze the effect of progressive tax changes on consumer behavior, vehicle ownership (tax base), tax compliance and revenue estimates of Bali . This study used primary data sourced from taxpayers grouped respondents over the ownership of two units and more than two units of four-wheeled vehicles. The sample of respondents was taken as many as 100 people, using probability proportional to size sampling is based on vehicle ownership dispersed population in the district / city in Bali. Data were analyzed using pathway diagrams and structural equation modeling. The results show that changes in marginal tax burden has not been able to lower consumer behavior and the willingness of taxpayers in the ownership of the vehicle (the tax base), but the taxpayers still abiding in the payment of taxes on motor vehicles. Then based on estimates of the taxpayer, although there are changes in the progressive income tax expense increased in the region remains relatively small amount

Evaluating Greek equity funds using data envelopment analysis

This study assesses the relative performance of Greek equity funds employing a non-parametric method, specifically Data Envelopment Analysis (DEA). Using an original sample of cost and operational attributes we explore the e¤ect of each variable on funds' operational efficiency for an oligopolistic and bank-dominated fund industry. Our results have significant implications for the investors' fund selection process since we are able to identify potential sources of inefficiencies for the funds. The most striking result is that the percentage of assets under management affects performance negatively, a conclusion which may be related to the structure of the domestic stock market. Furthermore, we provide evidence against the notion of funds' mean-variance efficiency

Self Perceptions of Clinical Performance of Accelerated First Degree and Accelerated Second-Degree Graduates

Currently in the United States, motivated by nursing shortages, numerous ways have been created to recruit nurses in nursing schools. Accelerated nursing programs are increasing rapidly. Colleges and Schools of Nursing around the nation are accepting students seeking their first degree, as well as those with a second degree. This study compared perceptions of clinical performance of accelerated first-degree and accelerated second-degree bachelor of nursing graduates. The intention was to identify whether, after graduation, the two groups held different self-perceptions of performance in the clinical environment. This was to determine if one group has better self-perception of performance than the other to explore how these differences can impact accelerated nursing programs and clinical performance after graduation. The results showed no significant differences in the perception of performance between the two groups; concluding degree status has little or no impact on perception of clinical practice and prediction of practice success from an accelerated program

Determinan Pendapatan Peternak Ayam Pedaging di Kecamatan Marga Kabupaten Tabanan

The demand for animal food from livestock (meat, eggs and milk) tends to increase over time in line with population growth, income, nutritional awareness, and improvements in education levels. Marga District, Tabanan Regency as the top three broiler chicken populations that are very close to the city center, still has great potential to be developed as a broiler chicken production site because there is still a lot of land and labor in rural areas that can be empowered. The increase and decrease in the broiler chicken population is certainly indirectly in line with the income of chicken farmers in Tabanan Regency, because it can be interpreted that the chicken population increases, income can increase and likewise if the chicken population decreases, then the income of farmers can also decrease. The purpose of this study was to determine the effect of labor, capital and length of business on broiler chicken production simultaneously and partially. This study uses quantitative research methods and statistical analysis, especially numerical analysis and statistical analysis with the aim of confirming the previously established hypothesis. This study used a sample of 63 farmers through data collection through interviews and questionnaires, with multiple linear regression methods, partial tests and simultaneous F tests. Based on the results of the SPSS calculation, the results obtained are that the variables of capital, use of labor and length of business simultaneously/together have a significant effect on the income of broiler chicken farmers. Capital, labor have a positive and significant effect partially on the income of chicken farmers, while the length of business has a positive but not significant effect on chicken Farmer

Estimation of Frame Independent and Enhancement Components for Speech Communication over Packet Networks

In this paper, we describe a new approach to cope with packet loss in speech coders. The idea is to split the information present in each speech packet into two components, one to independently decode the given speech frame and one to enhance it by exploiting interframe dependencies. The scheme is based on sparse linear prediction and a redefinition of the analysis-by-synthesis process. We presentMean Opinion Scores for the presented coder with different degrees of packet loss and show that it performs similarly to frame dependent coders for low packet loss probability and similarly to frame independent coders for high packet loss probability. We also present ideas on how to make the coder work synergistically with the channel loss estimate

Enhancing Sparsity in Linear Prediction of Speech by Iteratively Reweighted 1-norm Minimization

Linear prediction of speech based on 1-norm minimization has already proved to be an interesting alternative to 2-norm minimization. In particular, choosing the 1-norm as a convex relaxation of the 0-norm, the corresponding linear prediction model offers a sparser residual better suited for coding applications. In this paper, we propose a new speech modeling technique based on reweighted 1-norm minimization. The purpose of the reweighted scheme is to overcome the mismatch between 0-norm minimization and 1-norm minimization while keeping the problem solvable with convex estimation tools. Experimental results prove the effectiveness of the reweighted 1-norm minimization, offering better coding properties compared to 1-norm minimization

Data envelopment analysis in financial services: a citations network analysis of banks, insurance companies and money market funds

Development and application of the data envelopment analysis (DEA) method, have been the subject of numerous reviews. In this paper, we consider the papers that apply DEA methods specifically to financial services, or which use financial services data to experiment with a newly introduced DEA model. We examine 620 papers published in journals indexed in the Web of Science database, from 1985 to April 2016. We analyse the sample applying citations network analysis. This paper investigates the DEA method and its applications in financial services. We analyse the diffusion of DEA in three sub-samples: (1) banking groups, (2) money market funds, and (3) insurance groups by identifying the main paths, that is, the main flows of the ideas underlying each area of research. This allows us to highlight the main approaches, models and efficiency types used in each research areas. No unique methodological preference emerges within these areas. Innovations in the DEA methodologies (network models, slacks based models, directional distance models and Nash bargaining game) clearly dominate recent research. For each subsample, we describe the geographical distribution of these studies, and provide some basic statistics related to the most active journals and scholars