Tool Mark Identification of Skype Traffic

Author(s):  
Da-Yu Kao ◽  
Fang-Yu Lu ◽  
Fu-Ching Tsai
Keyword(s):  
2001 ◽  
Vol 1 ◽  
pp. 605-608
Author(s):  
Walter Rowe

At the beginning of a new millennium it seems a good idea to stop for a moment and take stock of the current state of forensic science. As a field of scientific research and scientific application, forensic science is a little more than a century old. Forensic science may be said to have begun in 1887 with the simultaneous publication of A. Conan Doyle’s A Study in Scarlet and Hans Gross’s Handbuch für Untersuchungsrichter. Conan Doyle’s novel introduced to the world the character of Sherlock Holmes, whose literary career would popularize the use of physical evidence in criminal investigations. Gross’s manual for examining magistrates suggests ways in which the expertise of chemists, biologists, geologists, and other natural scientists could contribute to investigations. Gross’s book was translated into a number of languages and went through various updated editions during the course of the century. The intervening century saw the development and application of fingerprinting, firearm and tool mark identification, forensic chemistry, forensic biology, forensic toxicology, forensic odontology, forensic pathology, and forensic engineering. Increasingly, the judicial systems of the industrial nations of the world have come to rely upon the expertise of scientists in a variety of disciplines. In most advanced countries, virtually all criminal prosecutions now involve the presentation of scientific testimony. This has had the beneficial effect of diminishing the reliance of courts on eyewitness testimony and defendant confessions.


Measurement ◽  
2019 ◽  
Vol 134 ◽  
pp. 209-217 ◽  
Author(s):  
Du-Ming Tsai ◽  
Daniel E. Rivera Molina

Scanning ◽  
2011 ◽  
Vol 33 (5) ◽  
pp. 272-278 ◽  
Author(s):  
Carol Gambino ◽  
Patrick McLaughlin ◽  
Loretta Kuo ◽  
Frani Kammerman ◽  
Peter Shenkin ◽  
...  
Keyword(s):  

2017 ◽  
Vol 34 (1) ◽  
pp. 123-133 ◽  
Author(s):  
Zeguang Yi ◽  
Nan Pan ◽  
Yi Liu ◽  
Yu Guo

Purpose This paper aims to reduce and eliminate the abnormal peaks which, because of the reflection in the process of laser detection, make it easier to proceed with further analysis. Design/methodology/approach To solve the above problem, an abnormal data correction algorithm based on histogram, K-Means clustering and improved robust locally weighted scatter plot smoothing (LOWESS) is put forward. The proposed algorithm does section leveling for shear plant first and then applies histogram to define the abnormal fluctuation data between the neighboring points and utilizes a K-Means clustering to eliminate the abnormal data. After that, the improved robust LOWESS method, which is based on Euclidean distance, is used to remove the noise interference and finally obtain the waveform characteristics for next data processing. Findings The experiment result of liner tool mark laser test data correction demonstrates the accuracy and reliability of the proposed algorithm. Originality/value The study enables the following points: the detection signal automatic leveling; abnormal data identification and demarcation using K-Means clustering and histogram; and data smoothing using LOWESS.


2010 ◽  
Vol 55 (4) ◽  
pp. 953-961 ◽  
Author(s):  
L. Scott Chumbley ◽  
Max D. Morris ◽  
M. James Kreiser ◽  
Charles Fisher ◽  
Jeremy Craft ◽  
...  

Author(s):  
Lei Li ◽  
Stuart A. Collins ◽  
Allen Y. Yi

The single point diamond turning process has been used extensively for direct optical surface fabrication. However, the diamond machined surfaces have characteristic periodic tool marks, which contribute to reduced optical performance such as scattering and distortion. In this paper, studies of the characteristics of diamond machined surface and scattering from the diamond machined surfaces are presented. Four different parameters, the first order optical diffraction, the zero order reflection, the surface roughness, and the residual tool mark depth, are used as indicators for the machined surface quality. Four sets of tests are presented showing the relationship between machined surface quality and machining conditions such as spindle speed, feedrate, and machining process. Finally, an empirical model is given based on the measurements.


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