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The purpose of this paper is to conduct an independent analysis of all existing geographic profiling software packages to determine if any one is more accurate than the others or if any of the software systems are any more accurate than simple spatial distribution strategies at locating the home base of serial offenders.

An analysis was conducted of all existing geographic profiling software as well as three spatial distribution methods of profiling. Differences in accuracy were assessed using four different methods; dichotomous profile accuracy, simple error measurement, profile error distance, and average top profile area.

Results indicate that not only are the different profiling software systems no more accurate than the spatial distribution control methods, but that accuracy in general was marginal at best. In addition results indicated that certain crimes, such as commercial robbery, were particularly difficult to profile and that the number of crimes in a series was not by itself a good indicator of success of a profile.

The paper shows that future research needs to focus more on determining how various factors such as city type, crime type, road network and spatial aspects of a crime series (dispersion and search area) impact profiling accuracy. In addition future research should also endeavor to determine whether these advanced strategies are substantially more accurate than other simple profiling strategies such as human prediction. Finally, future research should also seek to examine geographic profiling in a real world setting and how geographic profiling impacts the success of open investigations.

Practically, this study casts doubt not only on the overall accuracy of profiling strategies in predicting the likely home location of an offender, but also on whether probability strategies are substantially better than spatial distribution strategies.

This research was the first to independently analyze all of the existing geographic profiling systems against control methods for the purpose of determining the accuracy of these different methods.

The purpose of this paper is to present a distance accuracy-based industrial robot kinematic calibration model. Nowadays, the repeatability of the industrial robot is high, while the absolute positioning accuracy and distance accuracy are low. Many factors affect the absolute positioning accuracy and distance accuracy, and the calibration method of the industrial robot is an important factor. When the traditional calibration methods are applied on the industrial robot, the accumulative error will be involved according to the transformation between the measurement coordinate and the robot base coordinate.

In this manuscript, a distance accuracy-based industrial robot kinematic calibration model is proposed. First, a simplified kinematic model of the robot by using the modified Denavit–Hartenberg (MDH) method is introduced, then the proposed distance error-based calibration model is presented; the experiment is set up in the next section.

The experimental results show that the proposed calibration model based on MDH and distance error can improve the distance accuracy and absolute position accuracy dramatically.

The proposed calibration model based on MDH and distance error can improve the distance accuracy and absolute position accuracy dramatically.

The purpose of this paper was to compare the accuracy of linking crimes using geographical proximity between three distance measures: Euclidean (distance measured by the length of a straight line between two locations), Manhattan (distance obtained by summing north-south distance and east-west distance) and the shortest route distances.

A total of 194 cases committed by 97 serial residential burglars in Aomori Prefecture in Japan between 2004 and 2015 were used in the present study. The Mann–Whitney U test was used to compare linked (two offenses committed by the same offender) and unlinked (two offenses committed by different offenders) pairs for each distance measure. Discrimination accuracy between linked and unlinked crime pairs was evaluated using area under the receiver operating characteristic curve (AUC).

The Mann–Whitney U test showed that the distances of the linked pairs were significantly shorter than those of the unlinked pairs for all distance measures. Comparison of the AUCs showed that the shortest route distance achieved significantly higher accuracy compared with the Euclidean distance, whereas there was no significant difference between the Euclidean and the Manhattan distance or between the Manhattan and the shortest route distance. These findings give partial support to the idea that distance measures taking the impact of environmental factors into consideration might be able to identify a crime series more accurately than Euclidean distances.

Although the results suggested a difference between the Euclidean and the shortest route distance, it was small, and all distance measures resulted in outstanding AUC values, probably because of the ceiling effects. Further investigation that makes the same comparison in a narrower area is needed to avoid this potential inflation of discrimination accuracy.

The shortest route distance might contribute to improving the accuracy of crime linkage based on geographical proximity. However, further investigation is needed to recommend using the shortest route distance in practice. Given that the targeted area in the present study was relatively large, the findings may contribute especially to improve the accuracy of proactive comparative case analysis for estimating the whole picture of the distribution of serial crimes in the region by selecting more effective distance measure.

Implications to improve the accuracy in linking crimes may contribute to assisting crime investigations and the earlier arrest of offenders.

The results of the present study provide an initial indication of the efficacy of using distance measures taking environmental factors into account.

X-ray pulsar navigation (XPNAV) is an autonomous celestial navigation technology for deep space missions. The error in the pulse time of arrival used in pulsar navigation is large for various practical reasons and thus greatly reduces the navigation accuracy of spacecraft near the Earth and in deep space. This paper aims to propose a novel method based on ranging information that improves the performance of XPNAV.

This method replaces one pulsar observation with a satellite observation. The ranging information is the difference between the absolute distance of the satellite relative to the spacecraft and the estimated distance of the satellite relative to the spacecraft. The proposed method improves the accuracy of XPNAV by combining the ranging information with the observation data of two pulsars.

The simulation results show that the proposed method greatly improves the XPNAV accuracy by 70% compared with the conventional navigation method that combines the observations of three pulsars. This research also shows that a larger angle between the orbital plane of the satellite and that of the spacecraft provides higher navigation accuracy. In addition, a greater orbital altitude difference implies higher navigation accuracy. The position error and ranging error of the satellite have approximately linear relationships with the navigation accuracy.

The novelty of this study is that the satellite ranging information is integrated into the pulsar navigation by using mathematical geometry.

In the context of information retrieval, text genre is as important as its content, and knowledge of the text genre enhances the search engine features by providing customized retrieval. The purpose of this study is to explore and evaluate the use of stylometric analysis, a quantitative analysis for the linguistics features of text, to support the task of automated text genre detection for Classical Arabic text.

Unsupervised clustering and supervised classification were applied on the King Saud University Corpus of Classical Arabic texts (KSUCCA) using the most frequent words in the corpus (MFWs) as stylometric features. Four popular distance measures established in stylometric research are evaluated for the genre detection task.

The results of the experiments show that stylometry-based genre clustering and classification align well with human-defined genre. The evidence suggests that genre style signals exist for Classical Arabic and can be used to support the task of automated genre detection.

This work targets the task of genre detection in Classical Arabic text using stylometric features, an approach that has only been previously applied to Arabic authorship attribution. The study also provides a comparison of four distance measures used in stylomtreic analysis on the KSUCCA, a corpus with over 50 million words of Classical Arabic using clustering and classification.

In the context of fixed-wing aircraft wing assembly, there is a need for a rapid and precise measurement technique to determine the center distance between two double-hole components. This paper aims to propose an optical-based spatial point distance measurement technique using the spatial triangulation method. The purpose of this paper is to design a specialized measurement system, specifically a spherically mounted retroreflector nest (SMR nest), equipped with two laser displacement sensors and a rotary encoder as the core to achieve accurate distance measurements between the double holes.

To develop an efficient and accurate measurement system, the paper uses a combination of laser displacement sensors and a rotary encoder within the SMR nest. The system is designed, implemented and tested to meet the requirements of precise distance measurement. Software and hardware components have been developed and integrated for validation.

The optical-based distance measurement system achieves high precision at 0.04 mm and repeatability at 0.02 mm within a range of 412.084 mm to 1,590.591 mm. These results validate its suitability for efficient assembly processes, eliminating repetitive errors in aircraft wing assembly.

This paper proposes an optical-based spatial point distance measurement technique, as well as a unique design of a SMR nest and the introduction of two novel calibration techniques, all of which are validated by the developed software and hardware platform.

In modern technology, the wireless sensor networks (WSNs) are generally most promising solutions for better reliability, object tracking, remote monitoring and more, which is directly related to the sensor nodes. Received signal strength indication (RSSI) is main challenges in sensor networks, which is fully depends on distance measurement. The learning algorithm based traditional models are involved in error correction, distance measurement and improve the accuracy of effectiveness. But, most of the existing models are not able to protect the user’s data from the unknown or malicious data during the signal transmission. The simulation outcomes indicate that proposed methodology may reach more constant and accurate position states of the unknown nodes and the target node in WSNs domain than the existing methods.

This paper present a deep convolutional neural network (DCNN) from the adaptation of machine learning to identify the problems on deep ranging sensor networks and overthrow the problems of unknown sensor nodes localization in WSN networks by using instance parameters of elephant herding optimization (EHO) technique and which is used to optimize the localization problem.

In this proposed method, the signal propagation properties can be extracted automatically because of this image data and RSSI data values. Rest of this manuscript shows that the ECO can find the better performance analysis of distance estimation accuracy, localized nodes and its transmission range than those traditional algorithms. ECO has been proposed as one of the main tools to promote a transformation from unsustainable development to one of sustainable development. It will reduce the material intensity of goods and services.

The proposed technique is compared to existing systems to show the proposed method efficiency. The simulation results indicate that this proposed methodology can achieve more constant and accurate position states of the unknown nodes and the target node in WSNs domain than the existing methods.

The purpose of this paper is to investigate the use of a laser tracker, a laser interferometer system and a telescopic ballbar for assessing the positioning performance of a six‐axis industrial serial robot. The paper also aims to illustrate the limitations of these three metrology instruments for the assessment of robot positioning performance and to demonstrate the inadequacy of simplistic performance tests.

Specific test methods in the case of the laser interferometer system and the telescopic ballbar are proposed. Measurements are analyzed in accordance to the ISO 9283 norm.

It is found that, in static conditions and after a relatively short warm‐up, the unidirectional position repeatability of the non‐calibrated industrial robot under study (an ABB IRB 1600) is better than 37 μm, the unidirectional orientation repeatability is at worst 87 μrad, the linear position accuracy is better than 650 μm, and the rotation accuracy is at worst 2.8 mrad (mainly because of the sixth robot axis). It was also found that the dynamic (radial) errors due to vibrations can be up to approximately ±250 μm along a small circular path at TCP speed of 700 mm/s.

It is pointed out that the use of a laser tracker (or any other large range portable 3D measurement system) is questionable for assessing – let alone analyzing in depth – the unidirectional position repeatability of some of today's industrial robots. It is also demonstrated that the laser interferometer system can be used for measuring linear errors along a linear path of motion as well as angular errors about axes orthogonal to the path of motion. Finally, it is shown that the telescopic ballbar is an excellent, comparably low‐cost, high‐precision tool for assessing the static and dynamic positioning performance of industrial robots and its use in robotics should be further developed.

This work is the first to detail the use of three metrology equipments for assessing the positioning performance of an industrial robot. Experimental results are presented and discussed. Some guidelines for optimizing the positioning performance of an industrial robot are provided.

Immersive virtual environments (IVEs) aid in perceiving spaces by providing a platform for all stakeholders to make better decisions at early design stages. Nevertheless, they are not widely used in architecture, engineering and construction (AEC) industry. This paper aims to illustrate the impact of level of details (LODs) in participants’ perception for architecture design alternatives in IVEs.

This paper presents an approach to estimate how distance perception varies between real and virtual environments when different design alternatives are implemented. First, a fully three-dimensional (3D) model for a replica meeting room was created and the level of details (LODs) inside the IVE was gradually modified. Second, a questionnaire was designed to collect responses about how the perceived experience of an IVE is compared to that of the physical environment, where the two environments have the same dimensions. Twenty-six participants were recruited in this study to estimate eight distances in the IVEs while putting on a head-mounted display.

Obtained results show that decreasing LOD has negative effect on users’ perception. Thus, when all of the available LODs were added to the IVE, the perceived perception was significantly enhanced. These findings emphasize the relation between the physical details and distance perception in IVEs and shed light on how to design virtual reality architectural models in an efficient manner.

Different experiments were conducted to analyze perception differences associated with factors such as LODs, gender and whether participants are wearing glasses.

Reports on developments at Optimet in the R&D Group, where a novel distance probe performs high accuracy distance measurement over broad length scales. Considers applications.