Classification Improvements in Automated Gunshot Residue (GSR) Scans

Classification of particles as gunshot residues (GSRs) is conducted using a semiautomatic approach in which the system first classifies particles based on an automatic elemental analysis, and then, examiners manually analyze particles having compositions which are characteristic of or consistent with GSRs. Analyzing all the particles in the second stage is time consuming with many particles classified by the initial automated system as being potentially GSRs excluded as such by the forensic examiner. In this paper, a new algorithm is developed to improve the initial classification step. The algorithm is based on a binary tree that was trained on almost 16,000 particles from 43 stubs used to sample hands of suspects. The classification algorithm was tested on 5,900 particles from 23 independent stubs and performed very well in terms of false positive and false negative rates. A routine use of the new algorithm can reduce significantly the analysis time of GSRs.     

Early Warning of Intentions or of Capabilities? Revisiting the Israeli–Egyptian Rotem Affair, 1960

A major school of thought in Israel asserts that: (1) a cornerstone of the Israeli security doctrine is gaining early warning based more on changes of the enemy's capabilities and less on learning its intentions; and (2) that deviation from the doctrine caused the strategic surprise experienced by the state on the outbreak of the 1973 Yom Kippur war. This assertion is examined here by looking into another case in which Israel was also militarily surprised. In February 1960 the Egyptian Army deployed offensively along the joint border, while the IDF remained unaware of the situation. Israel's conduct during the affair – known as the Rotem Affair – was based on lenient assessments (derived from sigint) regarding the Egyptian intentions, ignoring their capabilities. It transpires, therefore, that dominance of ‘early warning of intentions’ has been the rule rather than the exception.     

Sketching the Lineage: The Critical Method and the Idealist Tradition

The influence of philosophical idealism on critical theory is often taken for granted, but it has rarely been the subject of scrutiny. This paper attempts to explore the logic of idealism--as it developed from Kant, to Fichte and Schelling, Hegel, and the young Marx--and the way in which it frames the dominant alternative perspectives in critical theory. The interplay between traditions should illuminate some of the contributions of critical theory, expose certain problems that plague it, and offer a few positive suggestions for those committed to the critical enterprise in our own time. Thus, this article will hopefully serve as an example of an intellectual history with a political purpose.     

A Mixture Model for the Number of Gunshot Residues Found on Suspects' Hands

Quantifying the strength of gunshot residue (GSR) evidence requires scientific knowledge about the number of particles expected to be found on individuals who were or were not involved in a shooting. However, controlled experiments demand expensive resources in terms of microscope time and labor, which restricts the data of most studies to only a small group of individuals. We suggest a novel method that exploits data collected routinely on suspects during the daily work of forensic laboratories. These observational data relate to both persons who were involved in a shooting and innocent individuals. We suggest a mixture approach with different models for the number of gunshot residue particles in each group and develop an iterative algorithm to estimate the probabilities of observing the evidence under the defense proposition that the suspect is innocent and under the prosecution assumption that he is not. The method is applied to data of more than 500 suspects collected by the Israel National Police Division of Identification and Forensic Science. The analysis shows that the probability of finding three or more GSR particles on the hands of innocent suspects is very small, less than 1.5 in 1000 cases. Our new method enables researchers to use data on real cases, possibly supplemented by experimental data, in order to estimate the probabilities of a given GSR finding under the defense and prosecution propositions.