Cost-sensitive learning for semi-supervised hit-and-run analysis

2021 ◽  
Vol 158 ◽  
pp. 106199
Author(s):  
Siying Zhu ◽  
Jianwu Wan
Keyword(s):  
Cost Sensitive Learning ◽  
Hit And Run

Sem/X-Ray Applications to the Forensic Science Field

1976 ◽  
Vol 34 ◽  
pp. 390-391
Author(s):  
K. Culbreth
Keyword(s):  
Forensic Science ◽  
Depth Of Field ◽  
Surface Phenomena ◽  
Criminal Cases ◽  
Forensic Evidence ◽  
Science Field ◽  
X Ray ◽  
Hit And Run ◽  
Evaluation Of Evidence ◽  
Scanning Electron

The introduction of scanning electron microscopy and energy dispersive x-ray analysis to forensic science has provided additional methods by which investigative evidence can be analyzed. The importance of evidence from the scene of a crime or from the personal belongings of a victim and suspect has resulted in the development and evaluation of SEM/x-ray analysis applications to various types of forensic evidence. The intent of this paper is to describe some of these applications and to relate their importance to the investigation of criminal cases.The depth of field and high resolution of the SEM are an asset to the evaluation of evidence with respect to surface phenomena and physical matches (1). Fig. 1 shows a Phillips screw which has been reconstructed after the head and shank were separated during a hit-and-run accident.

Convergence properties of hit-and-run samplers

1998 ◽  
Vol 14 (4) ◽  
pp. 767-800
Author(s):  
Claude Bélisle ◽  
Arnon Boneh ◽  
Richard J. Caron
Keyword(s):  
Convergence Properties ◽  
Hit And Run

Hit and Run? Income Shocks and School Dropouts in Latin America

2018 ◽  
Author(s):  
Paula Cerutti ◽  
Elena Crivellaro ◽  
German Reyes ◽  
Liliana D. Sousa
Keyword(s):  
Latin America ◽  
Income Shocks ◽  
School Dropouts ◽  
Hit And Run

A Resamping Approach for Customer Gender Prediction Based on E-Commerce Data

2017 ◽  
Vol 3 (1) ◽  
pp. 76 ◽  
Author(s):  
Duong Tran Duc ◽  
Pham Bao Son ◽  
Tan Hanh ◽  
Le Truong Thien
Keyword(s):  
Data Mining ◽  
Bayesian Network ◽  
Web Applications ◽  
Service Providers ◽  
Main Idea ◽  
Classification Methods ◽  
Cost Sensitive Learning ◽  
Network Method ◽  
Demographic Attributes ◽  
Privacy Issues

Demographic attributes of customers such as gender, age, etc. provide the important information for e-commerce service providers in marketing, personalization of web applications. However, the online customers often do not provide this kind of information due to the privacy issues and other reasons. In this paper, we proposed a method for predicting the gender of customers based on their catalog viewing data on e-commerce systems, such as the date and time of access, the products viewed, etc. The main idea is that we extract the features from catalog viewing information and employ the classification methods to predict the gender of the viewers. The experiments were conducted on the datasets provided by the PAKDD’15 Data Mining Competition and obtained the promising results with a simple feature design, especially with the Bayesian Network method along with other supporting techniques such as resampling, cost-sensitive learning, boosting etc.

Hit-And-Run Mechanism of HBV-Mediated Progression to Hepatocellular Carcinoma

2005 ◽  
Vol 91 (3) ◽  
pp. 241-247 ◽  
Author(s):  
Mohamed Hessein ◽  
El Gendy Saad ◽  
Attallah A Mohamed ◽  
El Awaday M Kamel ◽  
AM Abdel Hady ◽  
...  
Keyword(s):  
Hepatitis B Virus ◽  
Hepatitis B ◽  
Tumor Formation ◽  
Genetic Changes ◽  
Allele Loss ◽  
Integration Pattern ◽  
B Virus ◽  
Regenerative Nodules ◽  
Hit And Run ◽  
Virus Integration

Aim and background Hepatitis B virus is implicated in the development of hepatocellular caracinoma. No oncogenes have been identified within the viral genome. Furthermore, it frequently fragments after integration into the hepatocyte genome. Simultaneous investigations of hepatitis B virus integration patterns and genetic changes in precancerous tissues are important to understand the role played by hepatitis B virus integration in hepatocellular caracinoma. Method We used a combination approach of dual characterization of highly polymorphic loci and the change in hepatitis B virus-DNA integration pattern. Large regenerative nodules were dissected from 6 explanted hepatitis B virus infected cirrhotic livers. Nodules within each liver segment were schematically mapped and histopathologically analyzed. Genomic DNA from each nodule was analyzed for hepatitis B virus integration and the genetic stability of 12 microsatellite loci including D3S2321, D8S1022, D17S1159, D4S2281, D5S1/2, D16S675, D16S685, D16S490, D16S526, D16S673, D16S677 and D16S690. Results Data from different liver segments revealed few viral integrations and average allele loss. The most exciting results came from a segment containing a set of clonally and spatially related nodules having similar histologic features, a progressive lineage of allele loss, HBV integration and loss of integration. Conclusions This model portrait, a scenario of genetic events that precede tumor formation where the acquisition and loss of hepatitis B virus integrations in clonally related regenerative nodules, might explain how the virus acts as a hit-and-run mutagen.

scholarly journals A case of human papillomavirus infection and vulvar cancer in a young patient – “hit and run” theory

2021 ◽  
Vol 36 ◽  
pp. 100760
Author(s):  
Stoyan Kostov ◽  
Deyan Dzhenkov ◽  
Dimitar Metodiev ◽  
Yavor Kornovski ◽  
Stanislav Slavchev ◽  
...  
Keyword(s):  
Human Papillomavirus ◽  
Young Patient ◽  
Vulvar Cancer ◽  
Human Papillomavirus Infection ◽  
Papillomavirus Infection ◽  
Hit And Run ◽  
Run Theory

Robust SVM for Cost-Sensitive Learning

2021 ◽  
Author(s):  
Jiangzhang Gan ◽  
Jiaye Li ◽  
Yangcai Xie
Keyword(s):  
Cost Sensitive Learning

scholarly journals Instance-Dependent Cost-Sensitive Learning for Detecting Transfer Fraud

2021 ◽  
Author(s):  
Sebastiaan Höppner ◽  
Bart Baesens ◽  
Wouter Verbeke ◽  
Tim Verdonck
Keyword(s):  
Cost Sensitive Learning

scholarly journals Random Sampling Many-Dimensional Sets Arising in Control

Mathematics ◽  
2021 ◽  
Vol 9 (5) ◽  
pp. 580
Author(s):  
Pavel Shcherbakov ◽  
Mingyue Ding ◽  
Ming Yuchi
Keyword(s):  
Monte Carlo ◽  
Random Sampling ◽  
Linear Matrix ◽  
Matrix Inequalities ◽  
Computational Mathematics ◽  
Closed Form Solutions ◽  
Monte Carlo Techniques ◽  
Control Optimization ◽  
Point Representation ◽  
Hit And Run

Various Monte Carlo techniques for random point generation over sets of interest are widely used in many areas of computational mathematics, optimization, data processing, etc. Whereas for regularly shaped sets such sampling is immediate to arrange, for nontrivial, implicitly specified domains these techniques are not easy to implement. We consider the so-called Hit-and-Run algorithm, a representative of the class of Markov chain Monte Carlo methods, which became popular in recent years. To perform random sampling over a set, this method requires only the knowledge of the intersection of a line through a point inside the set with the boundary of this set. This component of the Hit-and-Run procedure, known as boundary oracle, has to be performed quickly when applied to economy point representation of many-dimensional sets within the randomized approach to data mining, image reconstruction, control, optimization, etc. In this paper, we consider several vector and matrix sets typically encountered in control and specified by linear matrix inequalities. Closed-form solutions are proposed for finding the respective points of intersection, leading to efficient boundary oracles; they are generalized to robust formulations where the system matrices contain norm-bounded uncertainty.

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