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Most pages of text or graphical materials in a library are black‐and‐white and most of the work that a scanner will do involves black‐and‐white images. Yet, it makes sense to buy a scanner capable of processing colour images. The difference in cost between a colour scanner and a black‐and‐white unit is relatively small, and the colour scanner allows colour pages to be converted into computer images whenever needed. In response to the demand by computer users for the ability to handle colour, new models of scanning equipment are almost all equipped to do so.

Scanners make it possible to transfer images from paper into computer equipment. Drawings (line art) and photographic images (halftones) can be picked up by scanners and then enhanced with image editing software to make the images suitable for use in computer‐generated publications.

Accurate perception of the environment using range sensors such as laser scanner, SONAR, infrared, vision, etc., for the application, such as path planning, localization, autonomous navigation, simultaneously localization and mapping, is a highly challenging area. The reliability of the perception by range sensors relies on the sensor accuracy, precision, sensor model, sensor registration, resolution, etc. Laser scanner is even though accurate and precise but still the efficient and consistent mapping of the environment is yet to be attained because laser scanner gives error as the extrinsic and intrinsic parameters varied which cause specular reflection, refraction, absorption, etc., of the laser beam. The paper aims to discuss this issue.

This paper presents an error analysis in sensory information of laser scanner due to the effect of varying the scanning angle with respect to the optical axis and surface reflectivity or refractive index of the targets. Uncertainties caused by these parameters are reduced by proposing a new technique, tilt mounting system (TMS) with designed filters of tilting the angular position of a laser scanner with the best possible selection of range and scanning angle for the robust occupancy grid mapping. Various experiments are performed in different indoor environments, and the results are validated after the implementation of the TMS approach with designed filters.

After the implementation of the proposed TMS approach with filters, the errors in the laser grid map are reduced by 15.6 percent, which results in 62.5 percent reduction in the collision of a mobile robot during autonomous navigation in the laser grid map.

The TMS approach with designed filter reduces the effect of variation in intrinsic and extrinsic parameters to generate efficient laser occupancy grid map to achieve collision-free autonomous navigation.

Laser scanning is increasingly used in many three‐dimensional (3‐D) measurement and modeling applications. It is the latest technique used in 3‐D measurement, and is becoming increasingly important within a number of applications. However, many applications require photogrammetric data in addition to laser scanning data. The purpose of this paper is to present a range and image sensor combination for three‐dimensional reconstruction of objects or scenes.

In this study, a Nikon D80 camera was mounted on an Ilris 3D laser scanner and CPP was estimated according to the laser scanner coordinate system. The estimated CPP was controlled using three different methods which were developed in this study and a sample application as coloring of point cloud using image taken by the camera mounted on the laser scanner was performed.

It was found that when a high‐resolution camera is mounted on laser scanners, camera position parameters (CPP) should be estimated very accurately with respect to the laser scanner coordinate system.

The paper shows that the combination of high‐resolution camera and laser scanners should be used for more accurate and efficient results in 3D modeling applications.

Modern service robots are designed to work in a complex indoor environment, in which the robot has to interact with the objects in different ambient light intensities (day light, tube light, halogen light and dark ambiance). The variations in sudden ambient light intensities often cause an error in the sensory information of optical sensors like laser scanner, which reduce the reliability of the sensor in applications such as mapping, path planning and object detection of a mobile robot. Laser scanner is an optical sensor, so sensory information depends upon parameters like surface reflectivity, ambient light condition, texture of the targets, etc. The purposes of this research are to investigate and remove the effect of variation in ambient light conditions on the laser scanner to achieve robust autonomous mobile robot navigation.

The objective of this study is to analyze the effect of ambient light condition (dark ambiance, tube light and halogen bulb) on the accuracy of the laser scanner for the robust autonomous navigation of mobile robot in diverse illumination environments. A proposed AIFA (Adaptive Intensity Filter Algorithm) approach is designed in robot operating system (ROS) and implemented on a mobile robot fitted with laser scanner to reduce the effect of high-intensity ambiance illumination of the environment.

It has been experimentally found that the variation in the measured distance in dark is more consistent and accurate as compared to the sensory information taken in high-intensity tube light/halogen bulbs and in sunlight. The proposed AIFA approach is implement on a laser scanner fitted on a mobile robot which navigates in the high-intensity ambiance-illuminating complex environment. During autonomous navigation of mobile robot, while implementing the AIFA filter, the proportion of cession with the obstacles is reduce to 23 per cent lesser as compared to conventional approaches.

The proposed AIFA approach reduced the effect of the varying ambient light conditions in the sensory information of laser scanner for the applications such as autonomous navigation, path planning, mapping, etc. in diverse ambiance environment.

The purpose of this research is to gather information about user experiences with overhead scanners, in order to better inform purchasing decisions.

The method of obtaining information was a survey, publicized via several listservs frequented by higher education digitization personnel, and available for four months in 2010. Participants were asked to identify their scanner, rate the extent to which they would recommend it, and describe usage patterns, speed, problems they encountered with hardware and software, and also what they like about their scanner.

In total, 52 respondents described 71 scanners covering 19 different brands (30 models, two unspecified). The number of complaint entries for hardware and software were even, with 39 responses for each (55 per cent). When asked to what extent the respondent would recommend the product, 30 per cent (21 respondents) would highly recommend their scanner (“Yes, it's great!”), 39 per cent (28 respondents) said “Yes, it's pretty good”, 25 per cent (18 respondents) would only possibly recommend it, with caveats, and 6 per cent of respondents (four) would not recommend their scanner at all.

Only 52 respondents participated in the study, reporting on a wide variety of models and brands. Five brands accounted for 69 per cent of the responses, so the quantity of responses per brand or model was far from equivalent, which is a severe weakness in terms of generalization of findings. The survey was heavily designed for open‐ended responses, which are not easily quantifiable. Follow‐up surveys should be designed to capture more easily quantifiable results, and, if possible, a larger and roughly equivalent number of responses for each model included.

Results of the survey will provide potential purchasers of overhead scanners with information that will assist them in making informed decisions and avoid expensive mistakes.

This paper gathers reports about the performance of a wide variety of overhead scanners in the field, which will help inform purchasing decisions in the immediate future.

This paper gathers reports about the performance of a wide variety of overhead scanners in the field, which will help inform purchasing decisions in the immediate future.

The purpose of this paper is to evaluate if automated vulnerability scanning accurately identifies vulnerabilities in computer networks and if this accuracy is contingent on the platforms used.

Both qualitative comparisons of functionality and quantitative comparisons of false positives and false negatives are made for seven different scanners. The quantitative assessment includes data from both authenticated and unauthenticated scans. Experiments were conducted on a computer network of 28 hosts with various operating systems, services and vulnerabilities. This network was set up by a team of security researchers and professionals.

The data collected in this study show that authenticated vulnerability scanning is usable. However, automated scanning is not able to accurately identify all vulnerabilities present in computer networks. Also, scans of hosts running Windows are more accurate than scans of hosts running Linux.

This paper focuses on the direct output of automated scans with respect to the vulnerabilities they identify. Areas such as how to interpret the results assessed by each scanner (e.g. regarding remediation guidelines) or aggregating information about individual vulnerabilities into risk measures are out of scope.

This paper describes how well automated vulnerability scanners perform when it comes to identifying security issues in a network. The findings suggest that a vulnerability scanner is a useable tool to have in your security toolbox given that user credentials are available for the hosts in your network. Manual effort is however needed to complement automated scanning in order to get satisfactory accuracy regarding network security problems.

Previous studies have focused on the qualitative aspects on vulnerability assessment. This study presents a quantitative evaluation of seven of the most popular vulnerability scanners available on the market.

The purpose of this paper is to validate the accuracy of point cloud data generated from a 3D body scanner.

A female dress form was scanned with an X‐ray computed tomography (CT) system and a 3D body scanning system. The point cloud data from four axial slices of the body scan (BS) data were compared with the corresponding axial slices from the CT data. Length and cross‐sectional area measurements of each slice were computed for each scanning technique.

The point cloud data from the body scanner were accurate to at least 2.0 percent when compared with the CT data. In many cases, the length and area measurements from the two types of scans varied by less than 1.0 percent.

Only two length measurements and a cross‐sectional area measurement were compared for each axial slice, resulting in a good first attempt of validation of the BS data. Additional methods of comparison should be employed for complete validation of the data. The dress form was scanned only once with each scanning device, so little can be said about the repeatability of the results.

Accuracy of the point cloud data from the 3D body scanner indicates that the main issues for the use of body scanners as anthropometric measurement tools are those of standardization, feature locations, and positioning of the subject.

Comparisons of point cloud data from a 3D body scanner with CT data had not previously been performed, and these results indicate that the point cloud data are accurate to at least 2.0 percent.

The purpose of this paper is to investigate the relationship between hospital adoption and use of computed tomography (CT) scanners, and magnetic resonance imaging (MRI) machines and in-patient mortality and length of stay.

This study used panel data (2007–2010) from 124 hospital corporations operating in Ontario, Canada. Imaging use focused on medical patients accounting for 25 percent of hospital discharges. Main outcomes were in-hospital mortality rates and average length of stay. A model for each outcome-technology combination was built, and controlled for hospital structural characteristics, market factors and patient characteristics.

In 2010, 36 and 59 percent of hospitals had adopted MRI machines and CT scanners, respectively. Approximately 23.5 percent of patients received CT scans and 3.5 percent received MRI scans during the study period. Adoption of these technologies was associated with reductions of up to 1.1 percent in mortality rates and up to 4.5 percent in length of stay. The imaging use–mortality relationship was non-linear and varied by technology penetration within hospitals. For CT, imaging use reduced mortality until use reached 19 percent in hospitals with one scanner and 28 percent in hospitals with 2+ scanners. For MRI, imaging use was largely associated with decreased mortality. The use of CT scanners also increased length of stay linearly regardless of technology penetration (4.6 percent for every 10 percent increase in use). Adoption and use of MRI was not associated with length of stay.

These results suggest that there may be some unnecessary use of imaging, particularly in small hospitals where imaging is contracted out. In larger hospitals, the results highlight the need to further investigate the use of imaging beyond certain thresholds. Independent of the rate of imaging use, the results also indicate that the presence of CT and MRI devices within a hospital benefits quality and efficiency.

To the authors’ knowledge, this study is the first to investigate the combined effect of adoption and use of medical imaging on outcomes specific to CT scanners and MRI machines in the context of hospital in-patient care.

With the use of 3D body scanners, body measurement techniques can be non‐contact, instant, and accurate. However, how each scanner establishes landmarks and takes the measurements should be established so that standardization of the data capture can be realized. The purpose of this study was to compare body‐scanning measurement extraction methods and terminology with traditional anthropometric methods. A total of 21 measurements were chosen as being critical to the design of well‐fitting garments. Current body scanners were analyzed for availability of information, willingness of company cooperation, and relevance to applications in the apparel industry. On each of the 21 measurements, standard measurement procedure was identified for three different scanners: [TC]², Cyberware, and SYMCAD. Of the 21 measures in the study, [TC]² was the scanner that had the most measures identified for the study and also had the capability of producing many more with specific application for apparel.