A New Anti‐forensic Scheme—Hiding the Single JPEG Compression Trace for Digital Image

To prevent image forgeries, a number of forensic techniques for digital image have been developed that can detect an image's origin, trace its processing history, and can also locate the position of tampering. Especially, the statistical footprint left by JPEG compression operation can be a valuable source of information for the forensic analyst, and some image forensic algorithm have been raised based on the image statistics in the DCT domain. Recently, it has been shown that footprints can be removed by adding a suitable anti‐forensic dithering signal to the image in the DCT domain, this results in invalid for some image forensic algorithms. In this paper, a novel anti‐forensic algorithm is proposed, which is capable of concealing the quantization artifacts that left in the single JPEG compressed image. In the scheme, a chaos‐based dither is added to an image's DCT coefficients to remove such artifacts. Effectiveness of both the scheme and the loss of image quality are evaluated through the experiments. The simulation results show that the proposed anti‐forensic scheme can verify the reliability of the JPEG forensic tools.     

TESTING FOR TEMPORALLY DIFFERENTIATED RELATIONSHIPS AMONG POTENTIALLY CRIMINOGENIC PLACES AND CENSUS BLOCK STREET ROBBERY COUNTS

This study examined street robbery patterns in Philadelphia, Pennsylvania, from the years 2009 to 2011 to determine whether the effects of potentially criminogenic places are different across different periods of the day. Census block (N = 13,164) street robbery counts across four periods (6:45 a.m . to 9:59 a.m., 10:00 a.m . to 4:29 p.m ., 4:30 p.m . to 9:14 p.m ., and 9:15 p.m. to 6:44 a.m. ) were modeled with 12 different potentially criminogenic places, 3 measures of illicit markets, 4 compositional control variables, and spatially lagged versions of the 12 potentially criminogenic places and population using simultaneously estimated negative binomial regression models. Differences in the magnitudes of the parameter estimates across the time periods were assessed with Wald tests. Overall, the patterns across the four models were mostly consistent with the effects hypothesized based on the study's crime pattern theory and time‐geography theoretical frame; yet differences in the magnitudes of the coefficients were less pronounced than hypothesized. Overall, the results provide moderate support for the crime pattern theory and time‐geography explanation of spatial‐temporal robbery patterns; however, numerous points are raised for future crime and place research.     

The Accuracy of Handheld Pre‐Arrest Breath Test Instruments as a Predictor of the Evidential Breath Alcohol Test Results

Drunk driving is a serious threat to public safety. All available and appropriate tools for curbing this threat should be employed to their full extent. The handheld pre‐arrest breath test instrument (PBT) is one tool for identifying the alcohol‐impaired driver and enforcing drunk driving legislation. A set of data was evaluated (n = 1779) where the PBT instrument was employed in drunk driving arrests to develop a multivariate predictive model. When maintained and operated by trained personnel, the PBT provides a reasonable estimate of the evidential test result within the relevant forensic range (95% prediction interval:  ± 0.003 g/210 L). ROC analysis shows that a multivariate model for PBT prediction of the evidentiary alcohol concentration above versus below the legal limit of 0.08 g/210 L has excellent performance with an AUC of 0.96. These results would be of value in evidential hearings seeking to admit the PBT results in drunk driving trials.     

Failings of Trauma‐Specific and Related Psychological Tests in Detecting Post‐Traumatic Stress Disorder in Forensic Settings

Judges and juries tend to be particularly impressed by test data, especially quantitative test data. Psychometric tests specific for assessing the presence of post‐traumatic stress disorder (PTSD) are commonly employed by forensic mental health evaluators. Most of these instruments, however, have been designed to detect PTSD in treatment or research, and not forensic, settings. Those who rely on these measures without adequate awareness of their often significant limits in correctly identifying malingering may induce finders of fact to inordinately confidently accept the presence of PTSD. This article reviews problematic structural and content components of trauma‐specific and related instruments used to evaluate PTSD and discusses the utility of specific techniques liable to be used in forensic settings to “fool” these measures.     

Diagnostic Value of PSA and AP Tests for the Detection of Spermatozoa in Postmortem Swabs from the Genital and Anal Region in Males

The aim of this study was to clarify whether positive results for prostate‐specific antigen (PSA) and acid phosphatase (AP) occur in postmortem swabs from the genito‐anal region in males (n = 80; 4 regions) and females (n = 20; 3 regions) and to calculate the positive predictive value (PPV) concerning the presence of spermatozoa. In male subjects, the highest incidence of positive test results was found in urethral swabs (PSA 76%, AP 71%) and the lowest frequencies appeared in perianal and rectal swabs (15–20%). Microscopic evaluation for spermatozoa was positive between 39% in urethral swabs and 1% in rectal swabs. PPV regarding positive identification of spermatozoa was 33.3% for PSA and 31.5% for AP. The combination of both tests yielded a PPV of 38.2%. In female cases, no spermatozoa were identified, and one case was PSA‐ and AP‐positive in perianal swabs. Our findings indicate that PSA and AP tests are of limited value for the postmortem detection of spermatozoa in male subjects.     

Understanding Variations of Soil Mapping Units and Associated Data for Forensic Science

Soil samples have potential to be useful in forensic investigations, but their utility may be limited due to the inherent variability of soil properties, the wide array of analytical methods, and complexity of data analysis. This study examined the differentiation of similar soils based on both gross (texture, color, mineralogy) and explicit soil properties (elemental composition, cation exchange, Fe‐oxyhydroxides). Soils were collected from Fallbrook and adjacent map units from Riverside and San Diego Counties in California. Samples were characterized using multiple techniques, including chemical extracts, X‐ray diffraction (XRD), and Fourier transform infrared spectroscopy. Results were analyzed using multiple analytical approaches to compare counties and land uses. Some analyses (XRD, extractions) were better at distinguishing among samples than others (color, texture). Ratios of rare earth elements were particularly useful for distinguishing samples between counties. This potential to “fingerprint” soils illustrates the usefulness of a comprehensive soil database for criminal investigators.     

Identification of Natural Images and Computer‐Generated Graphics Based on Statistical and Textural Features

To discriminate the acquisition pipelines of digital images, a novel scheme for the identification of natural images and computer‐generated graphics is proposed based on statistical and textural features. First, the differences between them are investigated from the view of statistics and texture, and 31 dimensions of feature are acquired for identification. Then, LIBSVM is used for the classification. Finally, the experimental results are presented. The results show that it can achieve an identification accuracy of 97.89% for computer‐generated graphics, and an identification accuracy of 97.75% for natural images. The analyses also demonstrate the proposed method has excellent performance, compared with some existing methods based only on statistical features or other features. The method has a great potential to be implemented for the identification of natural images and computer‐generated graphics.     

Who's Afraid of WikiLeaks? Missed Opportunities in Political Science Research

Leaked information, such as WikiLeaks’ Cablegate, constitutes a unique and valuable data source for researchers interested in a wide variety of policy‐oriented topics. Yet political scientists have avoided using leaked information in their research. This article argues that we can and should use leaked information as a data source in scholarly research. First, the methodological, ethical, and legal challenges related to the use of leaked information in research have been considered, concluding that none of these present serious obstacles. Second, how political scientists can use leaked information to generate novel and unique insights concerning political phenomena using a variety of quantitative and qualitative methods have been shown. Specifically, how leaked documents reveal important details concerning the Trans‐Pacific Partnership negotiations, and how leaked diplomatic cables highlight a significant disparity between the U.S. government's public attitude toward traditional knowledge and its private behavior have been demonstrated.     

It Takes a Coalition: The Community Impacts of Collaboration

Members of Congress frequently collaborate on policy initiatives, reaching out to colleagues in both parties to find common ground on solutions for the problems faced by their constituents. Using a novel dataset of over 30,000 “Dear Colleague” letters sent by members of the 111th Congress, I use the collaborative relationships that exist in the earliest stages of the policy process to measure the social influence of legislators. I demonstrate that districts represented by members of Congress who are better connected to their colleagues receive a greater share of federal grant money. I argue that this is because collaborative legislators are well‐positioned to be influential allies to strategic bureaucrats who want to maintain a broad base of support for their programs in Congress. Thus, devoting resources to building relationships with their colleagues is one way members of Congress can more effectively support the communities they represent.     

Migration Pessimism and the Subjective Well‐Being of Migrant Households in Mexico

A new migration pessimism argues that the economic benefits of international labour migration for migrant households may not justify the social costs. This article provides a test of this argument based on the author's survey of 304 households in Jerez municipio (municipality), Zacatecas, Mexico, in 2009. The results indicate that active households (those with at least one migrant abroad) perceived their economic situation to have improved more, but both their social cohesion and their happiness to be less than those of non‐active households. Social cohesion (family unity and maintenance of values) is shown to be pivotal in the happiness differential enjoyed by the non‐active households.