This paper investigates thematic classification of homicides for the purpose of behavioural investigative analysis (e.g. offender profiling). Previous research has predominantly used smallest space analysis (SSA) to conceptualise and classify offences into thematic groups based on crime scene behaviour data. This paper introduces a combined approach utilising multiple correspondence analysis (MCA), cluster analysis (CA), and discriminant function analysis (DFA) to define and differentiate crime scenes into expressive or instrumental and impersonal or personal crimes. MCA is used to derive the latent structural dimensions in the crime data and produce quantitative scores for each offence along these dimensions. Two-step CA was then utilised to classify offences. Offence dimensional scores were then used to predict cluster membership under DFA, producing cluster centroids corresponding to MCA dimensions. Centroids were plotted on the MCA correspondence map to simultaneously conceptualise crime classification and the latent structure of the Serbian crime data. Classification of offences based on MCA dimensional scores were 91.5% accurate. This MCA-CA-DFA approach may reduce some of the more subjective aspects of SSA methodology used in classification, whilst producing a product more amenable to objective and cumulative review. Implications for offender profiling research utilising SSA and this approach are discussed.

The current study seeks to advance the faceted multidimensional scaling (termed FMDS) procedure used in much of the investigative psychology research. To this end, recent research on street robbery by Goodwill and colleagues will be utilised to illustrate the effectiveness of a facet scale method for offender profiling. Four FMDS themes of street robbery (Con, Blitz, Confrontation and Snatch) were revealed by the crossing of two underlying axial facets: the offenders' level of violence and interaction with the victim. The facet scale method, utilising offenders' axial facet scores, was compared to previous count, proportional and centroid classification methods in the prediction of offender criminal histories. Utilising logistic regression and receiver operating characteristic analyses, the axial facet scale method was found to significantly outperform the qualitatively based dominant theme classification methods that typically employ angular and radial facets for FMDS interpretation. Implications for the use of axial facet scales within FMDS analysis for offender profiling research are discussed. Copyright © 2012 John Wiley & Sons, Ltd.

The Everything is Alive (EiA) agent system architecture is modular and scalable. It uses the E2 platform, a derivative of the Eclipse core platform, to dynamically add or remove plugin capabilities that have XML or WSDL interfaces. This paper describes two capabilities that can be modularly added to EiA agents. The capabilities described include a robot command capability that customizes an agent to operate as a robot controller and a menu-based natural language interface (MBNLI) capability that provides a human-level interface for commanding a robot.

This paper examines the efficacy of ionic liquid (IL) pretreatment on seven different commercially harvested biomass types: corn stover, miscanthus, pine, sorghum, sugarcane bagasse, switchgrass, and wheat straw in an effort to improve the production of renewable fuels and chemicals from biomass derived sugars. Initial experiments screened the pretreatment of lodgepole pine, a particularly recalcitrant biomass feedstock, with nine different imidazolium based ionic liquids. After screening, one hydrophilic and one hydrophobic ionic liquid was selected for pretreatment tests on six commercially harvested biomasses. Ultimately, the hydrophilic ionic liquid functioned better for biomass pretreatment than the hydrophobic ionic liquid. These results were then compared to a traditional dilute acid pretreatment to examine the relative effectiveness of ionic liquid pretreatment across a variety of biomass and ionic liquid types. Total theoretical sugar yields after IL pretreatment varied widely by IL and biomass type and ranged from 4.9 to 90.2%. Dilute acid pretreatment showed consistent sugar yields for herbaceous material (from 71.4 to 80.8%) but low yield for lodgepole pine (22.8%). Overall, ILs showed the potential to reach slightly higher sugar yields than dilute acid and were particularly effective for woody feedstocks. More importantly, the sugar release kinetics for IL pretreatment were three times faster than dilute acid and gave maximum sugar yields after about 24 h. Additional characterization of IL treated materials included scanning electron microscopy (SEM), x-ray diffraction (XRD), and compositional analysis. SEM and XRD showed qualitative and quantitative reductions in cellulose crystallinity (respectively) that correlated well to improved sugar release during enzymatic hydrolysis for hydrophilic ionic liquids. However, reductions in crystallinity associated with hydrophobic ionic liquids resulted in lower sugar release during enzymatic hydrolysis. Compositional analysis generally showed increased sugars content for hydrophilic ILs and increased lignin content for hydrophobic ILs.

which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.