3D Driven Rock Quality Mapping and Landing Target Selection in the Wolfcamp Formation: A Case Study on How to Combine Geologic, Geophysical, and Engineering Data to Produce Better Well Results, Midland Basin, Texas

PurposeThe purpose of this paper is to describe and test a quantitative harm-focused approach to offender selection for investigation and surveillance. The approach incorporates a measure of crime harm as well as a time-decay function that adjusts the score downward for offenders who desist from crime.Design/methodology/approachAcross 10 of 21 high-crime police districts in the city of Philadelphia, the authors compare the mean harm scores of 60 prolific offenders selected by district analysts, 60 prolific offenders selected citywide by detectives assigned to the Gun Violence Reduction Task Force and the top 60 prolific offenders chosen from a harm-score generated list of known offenders in the ten high-crime districts.FindingsThe offenders on the harm-focused list have significantly greater mean harm scores than the offenders identified by the crime analysts or task force personnel. They have a significantly greater mean number of gun crime episodes in their offending history as well.Research limitations/implicationsThe harm-focused approach uses arrest data that may not accurately reflect convictions and which miss undetected criminal activity. A leader of a criminal organization who orchestrates criminal activities but does not engage directly may have a low harm score. Arrest data may also suffer from some inherent bias. The approach also requires the creation of a crime harm index. Determining the operational impact on overall crime reduction by focusing on offenders with higher harm scores will require further research.Practical implicationsClinical methods of target selection based on officer intuition, opinion and experience may have limitations in terms of effectiveness and accuracy. They also lack transparency and may incorporate bias, a critical consideration given the current crisis in police-community trust and legitimacy. The actuarial method of weighing the harm of past offending with a crime harm score may be more acceptable and defendable to the community. It also identifies offenders with a higher frequency of involvement in gun crimes. Until methodological limitations are better understood, a compromise may be to start with the harm-score method (data-driven) and supplement this initial list through intelligence and investigative information.Originality/valueThe paper expands crime harm indices to quantify offender triage lists. The authors also empirically demonstrate through a case study that the approach is more effective at identifying harmful offenders than methods that solely rely on the experience or intuition of either crime analysts or detectives.

In reverse engineering, data pre-processing has played an increasingly important role for rebuilding the original 3D model. However, it is usually complex, time-consuming, and difficult to realize, as there are huge amounts of redundant 3D data existed in the gained point cloud. To find a solution for this issue, point cloud data processing and streamlining technologies are reviewed firstly. Secondly, a novel pre-processing approach is proposed in three steps: point cloud registration, regional 3D triangular mesh construction and point cloud filtering. And then, the projected hexagonal area and the closest projected point are defined. At last, a parabolic antenna model is employed as a case study. After pre-processing, the number of points are decreased from 4,066,282 to 449,806 under the constraint of triangular grid size h equaling to 2mm, i.e. about 1/9 size of the original point cloud. The result demonstrates its feasibility and efficiency.