Multiparty Reach and Frequency Histogram: Private, Secure, and Practical

Consider the setting where multiple parties each hold a multiset of users and the task is to estimate the reach (i.e., the number of distinct users appearing across all parties) and the frequency histogram (i.e., fraction of users appearing a given number of times across all parties). In this work we introduce a new sketch for this task, based on an exponentially distributed counting Bloom filter. We combine this sketch with a communication-efficient multi-party protocol to solve the task in the multi-worker setting. Our protocol exhibits both differential privacy and security guarantees in the honest-but-curious model and in the presence of large subsets of colluding workers; furthermore, its reach and frequency histogram estimates have a provably small error. Finally, we show the practicality of the protocol by evaluating it on internet-scale audiences.

Research on the normalisation method of logging curves: taking XJ Oilfield as an example

During the long-term exploration and development of the oilfield, it is difficult to ensure that all well logging curves are measured by the same type of instrument, the same calibration standard and the same operation mode, For different wells, there must be systematic errors caused by these reasons. Therefore, in addition to environmental correction, it is necessary to standardise logging curves. In XJ oilfield, three logging companies use wireline logging and logging while drilling to complete logging, in multi-well logging interpretation. To eliminate the systematic errors of different measuring tools, to maximise the geological information reflected by logging curves, and to make logging interpretation follow the same standard as much as possible, it is necessary to standardise the logging curve in the whole oilfield. This article takes the standardisation of well 106 in XJ oilfield as an example, the standardisation of different methods was compared, the method of combining frequency histogram and mean variance is better.

Bag of ARSRG Words (BoAW)

In recent years researchers have worked to understand image contents in computer vision. In particular, the bag of visual words (BoVW) model, which describes images in terms of a frequency histogram of visual words, is the most adopted paradigm. The main drawback is the lack of information about location and the relationships between features. For this purpose, we propose a new paradigm called bag of ARSRG (attributed relational SIFT (scale-invariant feature transform) regions graph) words (BoAW). A digital image is described as a vector in terms of a frequency histogram of graphs. Adopting a set of steps, the images are mapped into a vector space passing through a graph transformation. BoAW is evaluated in an image classification context on standard datasets and its effectiveness is demonstrated through experimental results compared with well-known competitors.

IDENTIFIKASI KESALAHAN JAWABAN MAHASISWA DITINJAU DARI KEMAMPUAN KOMUNIKASI MATEMATIS

This research aims to identify the error of students’ answers to the quations of descriptive statistics viewed from mathematical communication skill. This is a descriptive research. The subjects of this research are 36 students of class IB. The technique of data collection used in this research is test. Based on the result of the research, it can be concluded that the errors of students’ answers to the quations of descriptive statistics viewed from mathematical communication skill are: (1) the error in presenting diagram appropriate to the objective of 30.56%; (2) the error in presenting data in the frequency distribution table of 27.78%; (3) the error in presenting data from frequency histogram to frequency distribution table of 22.22%; and (4) the inconsistency in writing symbol of 36.11%. Based on the result, it is known that the most errors of the students’ answer viewed from mathematical communication skill are the inconsistency in using the symbols.Keywords: Error identification, Mathematical Communication Skill

Application of MATLAB in the Analysis of Reliability Data

This paper introduced how to use MATLAB to draw frequency histogram of reliability data distribution, estimate parameters and check up hypotheses, and realize automatic analysis of reliability data to ensure timely and precisely finishing data analysis, shorten the cycle of data disposal.

Characteristics of Video Traffic from Videoconference Applications: From H.261 to H.264

This paper presents modelling results for H.26x video traffic generated by popular videoconference software applications. The analysis of videoconference data, that were measured during realistic point-point videoconference sessions, led us to the general conclusion that the traffic can be distinguished into two categories: unconstrained and constrained. In the unconstrained traffic, there is a direct relation between the encoder and the form of the frequency histogram of the frame-size sequence. Moreover, for this type of traffic, strong correlations between successive video frames can be found. On the other hand, where bandwidth constraints are imposed during the encoding process, the generated traffic appears to exhibit similar characteristics for all the examined encoders with the very low autocorrelation values being the most notable one. On the basis of these results, this study proposes methods to calculate the parameters of a widely adopted autoregressive model for both types of traffic.