Lineup Instruction Verbiage's Effect on the Accuracy of Eyewitness Identifications: Michigan's Procedure

ABSTRACT Our study examined the effects of biased and unbiased lineup instructions verbiage on the accuracy of eyewitness identification in a suspect-absent photographic lineup. Seventy subjects were randomly assigned to either a biased instruction condition or an unbiased instruction condition where they watched a mocked crime video, solved word-search puzzles for five minutes, completed a suspect-absent photographic lineup, and then completed an online post-witness experience feedback questionnaire. The unbiased condition utilized photographic lineup instructions from the State Bar of Michigan's Eyewitness Identification Task Force recommended policy writing guide. For the biased condition, the instructions alluded to subjects that the suspect was present. Subjects in the unbiased condition answered correctly 45.7% of the time compared to 28.6% of those in the biased condition. Chi-square test for independence indicated no significant association between the lineup instructions verbiage and the accuracy of eyewitness identification rates. Binomial logistic regression found that the confidence level in the identification choice made, ease of making an identification, decision making time, ability to recognize the lineup appeinstructions, and group condition were not significant predictors of subjects correctly identifying the suspect. Our results would suggest that the verbiage of the lineup instructions does not increase accuracy of eyewitness identifications.

A Fusion Face Recognition Approach Based on 7-Layer Deep Learning Neural Network

This paper presents a method for recognizing human faces with facial expression. In the proposed approach, a motion history image (MHI) is employed to get the features in an expressive face. The face can be seen as a kind of physiological characteristic of a human and the expressions are behavioral characteristics. We fused the 2D images of a face and MHIs which were generated from the same face’s image sequences with expression. Then the fusion features were used to feed a 7-layer deep learning neural network. The previous 6 layers of the whole network can be seen as an autoencoder network which can reduce the dimension of the fusion features. The last layer of the network can be seen as a softmax regression; we used it to get the identification decision. Experimental results demonstrated that our proposed method performs favorably against several state-of-the-art methods.

The Policy Implications of Research on Fingerprint Examination Tasks

Most fingerprint comparisons are still done by human examiners, who examine two impressions to determine the amount of perceived detail in agreement. Examiners must rely on their training and experience to determine whether the quality and quantity of detail in agreement is sufficient to warrant an identification decision, which makes their perceptual and decision-making abilities central to our understanding of the strength of fingerprint evidence. Research on latent print examiners has documented the influence of configural processing, greater working memory, and greater consistency of eye gaze among experts relative to novices. All of these lead to universally higher accuracy relative to novices. However, examiners must contend with fatigue and the problem of non-mated prints that are somewhat similar in appearance. Surprisingly, this problem only gets worse as databases increase in size. Currently, the field contends with a relatively high number of erroneous exclusions and inconclusive decisions, which may allow a potentially guilty suspect to remain free from charges. We discuss policy implications that follow directly from the research and suggest future research directions that address unresolved issues.

Sosialisasi dan Partisipasi Masyarakat dalam Program Pemberdayaan Masyarakat Kelurahan (PPMK) di Kelurahan Klender

<p>Village community empowerment program (PPMK) aims to overcome poverty. Socialization of the programs to the community is one of the factors that can determine the participation of the community. Obtaining a description of socialization and community involvement is the purpose of this paper. The description of community participation in PPMK that was presented by Adi was analyzed with the definition of participation (community involvement in problem identification, decision-making process to solve problem, implementation of the result and evaluation on a development activity). This paper will also present the percentage of public knowledge about the program and the percentage of community involvement in the program.</p><p>Key word: poverty, empowerment, participation</p>