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Managing the massive losses associated with large-scale disasters requires significant resources. The unexpected violence of these events generally remains a matter of casualties that urgently need to be identified in a reliable and cost-effective manner. To overcome these difficulties, many researchers have attempted to develop automated methods; moreover, a few recent research have investigated the applicability of artificial intelligence (AI)-based methods using skull, dental, and maxillofacial forensic imaging. In this review, we speculate on the advancement and potential of AI in Dental and Maxillofacial imaging that can help simplify person or victim identification and speed up the process with good accuracy. Using a few prefix search phrases, an online literature search was conducted (AI, Forensic, Skull, Dental, Imaging, Radiology) to identify papers about the advancement of AI in forensic dentistry in all kinds of radiographs, including two-dimensional (2D) and three-dimensional (3D) radiographs, cone beam computed tomography (CT) and CT. Most of the studies reported that automated methods of human identification based on 2D and 3D Dental and Skull radiographs using a convolutional neural network showed to assist in the fast and accurate identification by expertise evaluating a lot of images and quickly coming up with potential matches for identification. We advocate the application of AI techniques in the identification of individuals. However, there is a need to continue research with emphasis to validate models in skull identification. [ABSTRACT FROM AUTHOR]

This paper overviews emerging technology development by emphasizing Connected, Automated, Shared, and Electric (CASE) technologies. Existing literature on 15 CASE technologies is reviewed, and adds to the literature by consolidating important predictions of CASE-related technologies, services, and policies. Connected and automated technologies have not yet matured, and there remain many gaps in its abilities. Predictions include that shared mobility will have a large market share, electric technologies will replace internal combustion engines, and CASE-related services and policies will be used in more cities. A survey with 1,036 respondents conducted in April 2021 helps gauge how Americans make mode choices under various scenarios. Data analysis indicates that safety issues are the main factor that hinder people's willingness to use CASE-related technologies, and the low cost encourages more users to choose shared mobility. Challenges that remain, and their associated impacts, are important to consider. [ABSTRACT FROM AUTHOR]

Web data extraction has seen significant development in the last decade since its inception in the early nineties. It has evolved from a simple manual way of extracting data from web page and documents to automated extraction to an intelligent extraction using machine learning algorithms, tools and techniques. Data extraction is one of the key components of end-to-end life cycle in web data extraction process that includes navigation, extraction, data enrichment and visualization. This paper presents the journey of web data extraction over the last many years highlighting evolution of tools, techniques, frameworks and algorithms for building intelligent web data extraction systems. The paper also throws light into challenges, opportunities for future research and emerging trends over the years in web data extraction with specific focus on machine learning techniques. Both traditional and machine learning approaches to manual and automated web data extraction are experimented and results published with few use cases demonstrating the challenges in web data extraction in the event of changes in the website layout. This paper introduces novel ideas such as self-healing capability in web data extraction and proactive error detection in the event of changes in website layout as an area of future research. This unique perspective will help readers to get deeper insights in to the present and future of web data extraction. [ABSTRACT FROM AUTHOR]

Introduction: Endodontic treatment success rate relies majorly on apical and coronal sealing. In order to achieve a good hermetic seal the removal of smear layer is unavoidable. Hence this study was conducted to assess the various root canal irrigating materials. Materials and Methodology: Freshly extracted human mandibular premolar teeth were selected and were randomly divided into two groups. Inclusion criteria include those teeth that have less than 10 degrees of angulation. The study samples include 30 freshly extracted teeth that were basically divided into two groups. Group - 1 comprised of manual syringe needle irrigation, Group - 2 consisted of automated root canal irrigation. Canals were effectively dried with paper points after which the roots were split longitudinally and examined. Results: The debris score and smear layer score was observed in both the study groups namely manual needle and automated irrigation device. Interestingly a low mean score in debris as well as smear layer was observed in both the groups. (p>0.05) Moreover no statistically significant difference was prompt in the debris and the smear layer score at the apical, middle or coronal region. Conclusion: To conclude, it has been effectively observed that the manual syringe irrigation and automated irrigation devices clearly showed identical results in removing the smear an debris layer with no significant differences were elicited between the two groups. [ABSTRACT FROM AUTHOR]

Progress monitoring is an essential part of large construction projects. As manual progress monitoring is time-consuming, the need for automation emerges, especially as, nowadays, BIM for the design of buildings and laser scanning for capturing the as-built situation have become well adopted. However, to be able to compare the as-built model obtained by laser scanning to the BIM design, both models need to use the same reference system, which often is not the case. Transforming the coordinate system of the as-built model into the BIM model is a specialist process that is pre-requisite in automated construction progress monitoring. The research described in this paper is aimed at the automation of this so-called registration process and is based on the dominant planar geometry of most buildings with evident corner points in their structures. After extracting these corner points from both the as-built and the design model, a RANSAC-based pairwise assessment of the points is performed to identify potential matching points in both models using different discriminative geometric invariants. Next, the transformation for the potential matches is evaluated to find all the matching points. In the end, the most accurate transformation parameter is determined from the individual transformation parameters of all the matching corner points. The proposed method was tested and validated with a range of both simulated and real-life datasets. In all the case studies including the simulated and real-life datasets, the registration was successful and accurate. Furthermore, the method allows for the registration of the as-built models of incomplete buildings, which is essential for effective construction progress monitoring. As the method uses the standard IFC schema for data exchange with the BIM, there is no loss of geometrical information caused by data conversions and it supports the complete automation of the progress-monitoring process. [ABSTRACT FROM AUTHOR]

Evolutionary intelligence has become one of the most important directions that improve the performance and effectiveness of automated systems such as communication systems, robotics and engineering industries. Today, there are many applications of evolutionary intelligence in many engineering fields and the most important fields related to computation and informatics engineering as a part of electrical and communication engineering, as modern engineering applications are involved in these fields. The sensor network is the main data source in the world of smart systems nowadays. Additionally, it has become a field of science used in the development of the rest of scientific applications. The need to use evolutionary intelligence in sensor networks has emerged because of the problems encountered by different types of sensor networks. This paper represents a comprehensive scientific review of the role of evolutionary intelligence in sensor networks and its implications for this important part of engineering applications. This paper discusses the theoretical, mathematical and practical application of evolutionary computing with the use of evolutionary algorithms and the improvements resulting from the application of evolutionary intelligence in sensor networks. The content of this paper will review the most important of the evolutionary intelligence from principles, algorithms and applications. The problems facing the types of sensor network has been solved using evolutionary algorithms. After reviewing the evolutionary intelligence and its details in the sensor network, a performance evaluation is presented in the paper at the end of each of the targeted areas of the sensor network. This performance evaluation represents the measure of the quality of improvements provided by evolutionary intelligence in sensor network field with graphical analysis studies to demonstrate the effect of evolutionary algorithms on the sensor network. [ABSTRACT FROM AUTHOR]

RFID is a cutting-edge integrated library management system that enables the instantaneous detection and recognition of library materials. RFID applications vary from book monitoring and stock management to security in general and completely automated book classifying at the moment. Shortly, RFID systems will play an important role in data collection, recognition, and analysis required for specific library operations. An RFID-enabled automated library might be a "selfservice station" that involves reducing the amount of interference from staff members. Efforts are being made to implement self-service "check-in" and "checkout" to prevent long delays in the delivery of library collection and to improve operational efficiency. Considering the significance of library security, this paper focuses on the use of Radio frequency identification (RFID) in libraries, including its elements, advantages, and the role of the librarian. The researcher collected the data of 50 users from Maharshi Dayanand University library, Rohtak, to find out the status of RFID implementation and the satisfaction level of users with the system. Most of the users are satisfied with the component and its benefits of it. [ABSTRACT FROM AUTHOR]

[Display omitted] • Robot technology was mostly frequently found in the fields of orthodontics and implantology. • Scientific evidence regarding the benefits, results and cost-efficiency of commercially available robotic solutions in dentistry is lacking. • The usage of open source software for robot control and the design of robots specifically for dental usage, in some recent articles, might be promising. To provide dental practitioners and researchers with a comprehensive and transparent evidence-based overview of physical robot initiatives in all fields of dentistry. Articles published since 1985 concerning primary data on physical robot technology in dentistry were selected. Characteristics of the papers were extracted such as the respective field of dentistry, year of publication as well as a description of its usage. Bibliographic databases PubMed, Embase, and Scopus were searched. A hand search through reference lists of all included articles was performed. The search timeline was between January 1985 and October 2020. All types of scientific literature in all languages were included concerning fields of dentistry ranging from student training to implantology. Robot technology solely for the purpose of research and maxillofacial surgery were excluded. In total, 94 articles were included in this systematic review. This study provides a systematic overview of initiatives using robot technology in dentistry since its very beginning. While there were many interesting robot initiatives reported, the overall quality of the literature, in terms of clinical validation, is low. Scientific evidence regarding the benefits, results and cost-efficiency of commercially available robotic solutions in dentistry is lacking. The rise in availability of open source control systems, compliant robot systems and the design of dentistry-specific robot technology might facilitate the process of technological development in the near future. The authors are confident that robotics will provide useful solutions in the future but, strongly, encourage an evidence-based approach when adapting to new (robot) technology. [ABSTRACT FROM AUTHOR]

Abstract Grading is one of the most vital steps in the hardwood lumber manufacturing process. For over one hundred years, hardwood lumber in North America has been graded by specially trained lumber inspectors using the National Hardwood Lumber Association (NHLA) Rules for the Inspection of Hardwood Lumber. With technology improving over time, the status quo of lumber grading is again being challenged. This paper outlines an automated lumber grading study using a Microtec Goldeneye 300 Multi-Sensor Quality Scanner™. The scanner is equipped with color cameras, dot-grid and profile lasers and an x-ray sensor to locate and classify defects at a speed of 980 linear feet per minute. The material studied was rough, kiln dried hardwood lumber of nine different commercial species. Over 1000 boards from each species were graded with the scanner and verified by a NHLA-trained human lumber inspector. This paper reviews the performance of the scanner and highlights its accuracy by species and individual grades within that species. Across the entire volume of boards scanned, the automated grading system was 99.50% on-value and 92.22% on-grade accurate. [ABSTRACT FROM AUTHOR]

Summary: In the current state of development, it is very hard to remotely evaluate the actual condition of wind turbines structures. This makes it impossible for a wind farm owner to correctly deliberate about the need of retrofitting the current wind turbine structure, as well as to decide about the possible extension of its operating lifetime. Taking into account this problem, this paper introduces the main aspects in the development of a vibration‐based monitoring system for an onshore 2.0‐MW wind turbine based on the identification of the modal properties of the most important vibration modes. Initially, the wind turbine is introduced, as well as the implemented monitoring system. Then, the main steps of the monitoring system are briefly described. A detailed attention is given to the statistical procedure based on regression models used to minimize the influence of operational and environmental effects over the features used to detect structural changes in the wind turbine. Lastly, the suitability of the system to detect damages is thus assessed, through the analysis of three common damage scenarios: onshore foundation damage; damage by scour on an offshore foundation; and blade damage. It is concluded that the system is capable of detecting damage in onshore and offshore foundations, as well as in rotor blades. The most important contribution of the paper is the definition of monitoring framework for damage detection, its implementation, and validation with monitoring data collected during more than 1 year in a utility‐scale wind turbine. [ABSTRACT FROM AUTHOR]

Retinopathy of Prematurity (ROP) is a disease of the eye and a potential source of blindness in low birth weight preterm infants. It is preventable if diagnosed and treated on time. Artificial Intelligence (AI) has played an important role in developing automated screening systems to assist medical experts. There are many traditional literature review articles available that focus on the scientific content of ROP-AI. The researchers also require a bibliometric analysis to become acquainted with the competing groups and new trends in this field. This paper gives a brief overview of ROP and AI systems for ROP screening with a statistical analysis of the Scopus database's related documents. [ABSTRACT FROM AUTHOR]

Retinopathy of Prematurity (ROP) is a disease of the eye and a potential source of blindness in low birth weight preterm infants. It is preventable if diagnosed and treated on time. Artificial Intelligence (AI) has played an important role in developing automated screening systems to assist medical experts. There are many traditional literature review articles available that focus on the scientific content of ROP-AI. The researchers also require a bibliometric analysis to become acquainted with the competing groups and new trends in this field. This paper gives a brief overview of ROP and AI systems for ROP screening with a statistical analysis of the Scopus database's related documents. [ABSTRACT FROM AUTHOR]

A highly challenging problem that has been plaguing regulators is the inaccurate collection and sharing of safety risks for underground construction. In order to establish a mechanism that could achieve timely and accurate recognition at the pre-construction stage, Building information model (BIM) is adopted as the risk recognition platform. This paper provides the automated safety risk recognition process based on BIM which is generally composed of three parts. The first part is to build the risk database. By means of knowledge structuralizing, questionnaires, depth interviews and group decision-making, explicit and tacit knowledge source are acquired. The safety risk knowledge source is divided into three categories. SQL database is used to express the safety risk knowledge, and all safety risks are stored in the BIM-cloud. The second part is to analyse the relation between engineering information and safety risks. Risk-related engineering information is extracted from BIM models. Backus–Naur form is used to describe the syntax of languages used in computing. A mapping table of engineering information and safety risks is established. The third part concerns the automated safety risk recognition mechanism in the BIM platform. The safety risk recognition mechanism is expressed as “If e, then h (CF (h, e), λ)”. The confidence level as the link is adopted to reveal the mechanism. Finally, a case about flowing sand risk at the foundation pit bottom is conducted. The reasoning process and recognition results are demonstrated. The paper concludes by summarizing the main scientific contribution and giving direction to future research in this field. [ABSTRACT FROM AUTHOR]

This paper aims to understand the automated banking services consumption in automated teller machines (ATMs) by adults with low education levels. Data were collected in two bank agencies in one city in Brazil. Through content analysis and using the service dominant logic (SDL) as theoretical background, interviews and field observations were analyzed qualitatively. Results indicate a certain portfolio of services consumed in the bank, also indicating the way ATMs are used, usually in the presence of an intermediate, which implies loss of the purpose of a selfservice technology. The paper concludes with implications for practice and further research. [ABSTRACT FROM AUTHOR]

Locomotion scoring is time consuming and is not commonly completed on farms. Farmers also underestimate their herds' lameness prevalence, a knowledge gap that impedes lameness management. Automation of lameness detection could address this knowledge gap and facilitate improved lameness management. The literature pertinent to adding lameness detection to accelerometers is reviewed in this paper. Options for lameness detection systems are examined including the choice of sensor, raw data collected, variables extracted, and statistical classification methods used. Two categories of variables derived from accelerometer-based systems are examined. These categories are behavior measures such as lying and measures of gait. For example, one measure of gait is the time a leg is swinging during a gait cycle. Some behavior-focused studies have reported accuracy levels of greater than 80%. Cow gait measures have been investigated to a lesser extent than behavior. However, classification accuracies as high as 91% using gait measures have been reported with hardware likely to be practical for commercial farms. The need for even higher accuracy and potential barriers to adoption are discussed. Significant progress is still required to realize a system with sufficient specificity and sensitivity. Lameness detection systems using 1 accelerometer per cow and a resolution lower than 100 Hz with gait measurement functions are suggested to balance cost and data requirements. However, gait measurement using accelerometers is rather underdeveloped. Therefore, a high priority should be given to the development of novel gait measures and testing their ability to differentiate lame from nonlame cows. [ABSTRACT FROM AUTHOR]

Objectives Liver volumetry has emerged as an important tool in clinical practice. Liver volume is assessed primarily via organ segmentation of computed tomography (CT) and magnetic resonance imaging (MRI) images. The goal of this paper is to provide an accessible overview of liver segmentation targeted at radiologists and other healthcare professionals. Methods Using images from CT and MRI, this paper reviews the indications for liver segmentation, technical approaches used in segmentation software and the developing roles of liver segmentation in clinical practice. Results Liver segmentation for volumetric assessment is indicated prior to major hepatectomy, portal vein embolisation, associating liver partition and portal vein ligation for staged hepatectomy (ALPPS) and transplant. Segmentation software can be categorised according to amount of user input involved: manual, semi-automated and fully automated. Manual segmentation is considered the "gold standard" in clinical practice and research, but is tedious and time-consuming. Increasingly automated segmentation approaches are more robust, but may suffer from certain segmentation pitfalls. Emerging applications of segmentation include surgical planning and integration with MRI-based biomarkers. Conclusions Liver segmentation has multiple clinical applications and is expanding in scope. Clinicians can employ semi-automated or fully automated segmentation options to more efficiently integrate volumetry into clinical practice. [ABSTRACT FROM AUTHOR]

Brain tumor image segmentation is process of locating the interesting area in terms of objects, like tumor and extracting it for the further process of the image and getting the boundaries of the image for analysis. The bio-medical brain tumor image segmentation is a great challenging field for the today world active researchers with the standardized image datasets and various metrics used for evaluating and comparing the performance of the new algorithm with existing segmentation algorithms. In recent development, these problems are addressed using various image manipulation tools and rapid growth of computer hardware enhancement. Image segmentation was done in three ways: (1) Manual-based (2) Semi-automated-based (3) Fully automated-based. But still be a short of research in the field of brain tumor segmentation and accurate identification of tumor cells. To overcome all the above-mentioned challenges and complexity of the brain tumor segmentation, it need to understand the pre-processing of the image like, registering the image, correction of bias in image, and non-brain tissue removal. In this paper, we propose a new methodology for segmenting the brain tumor from the affected brain image in a significantly efficient way by using deep learning method. [ABSTRACT FROM AUTHOR]

Ball end magnetorheological finishing (BEMRF) is a novel method for nanofinishing of ferromagnetic as well as nonmagnetic materials. With increasing demands of precision finished products in various markets, the quality of surface finish and production rate are of prime importance. For products having complex geometries, this need intensifies as the manual finishing methods are incapable of producing uniform finish throughout the complex geometry of the surface. This paper describes the finishing of 3D surfaces using five-axis CNC BEMRF process in a fully automated manner such that a uniform finish is obtained throughout the workpiece. This eliminates the labor-intensive efforts and the subjective errors involved in manual finishing operations and increases the production rate of the finished products. A customized five-axis CNC controller is developed that enables the sequential and precise control of motion as well as process parameters in the BEMRF machine. The magnetizing current which governs the forces responsible for finishing in BEMRF process is controlled in-process through CNC part program using a specially defined "E" code for magnetizing current. A dedicated graphical user interface is also developed in Visual C# for the control of BEMRF process, enabling the user to make use of BEMRF machine without going into the complexities of the system. Using the customized five-axis CNC controller, automated finishing of a freeform mild steel workpiece is done. The finishing results obtained by the automated five-axis BEMRF machine shows uniformly finished surface profile (up to order of nanometer) on the mild steel test specimen. [ABSTRACT FROM AUTHOR]

In this paper a video-based method to automatically track instantaneous velocities of a swimmer is presented. Single cameras were used to follow a marker (LED) attached to the body. The method is inspired by particle tracking techniques, traditionally used in the field of fluid dynamics, to measure local velocities of a fluid flow. During the validation experiment, a white LED was attached to the hip of a swimmer together with a speedometer. A swimmer performed four different stroke types. The velocity profiles using LED tracking were captured and showed less noise than the speedometer measurements. Only at times when the marker disappeared above the water surface due to body role in front crawl and backstroke swimming did the LED tracking fail to capture the athlete's motion. The algorithm was tested in a 2D case with a single LED to illustrate the proof of principle, but should be suitable for implementation in a 3D analysis or multiple LED analysis. [ABSTRACT FROM AUTHOR]

Purpose – The purpose of this paper is to present a new computational framework to address future preliminary design needs for aircraft subsystems. The ability to investigate multiple candidate technologies forming subsystem architectures is enabled with the provision of automated architecture generation, analysis and optimization. Main focus lies with a demonstration of the frameworks workings, as well as the optimizers performance with a typical form of application problem. Design/methodology/approach – The core aspects involve a functional decomposition, coupled with a synergistic mission performance analysis on the aircraft, architecture and component levels. This may be followed by a complete enumeration of architectures, combined with a user defined technology filtering and concept ranking procedure. In addition, a hybrid heuristic optimizer, based on ant systems optimization and a genetic algorithm, is employed to produce optimal architectures in both component composition and design parameters. The optimizer is tested on a generic architecture design problem combined with modified Griewank and parabolic functions for the continuous space. Findings – Insights from the generalized application problem show consistent rediscovery of the optimal architectures with the optimizer, as compared to a full problem enumeration. In addition multi-objective optimization reveals a Pareto front with differences in component composition as well as continuous parameters. Research limitations/implications – This paper demonstrates the frameworks application on a generalized test problem only. Further publication will consider real engineering design problems. Originality/value – The paper addresses the need for future conceptual design methods of complex systems to consider a mixed concept space of both discrete and continuous nature via automated methods. [ABSTRACT FROM AUTHOR]

[Display omitted] • An automated standard addition method coupled flow injection analysis, FB-SAM/FIA, was developed. • Spiked samples were automatically prepared by feeding back the peak height of interest in the fiagram. • FB-SAM/FIA completed the process, preparing the spiked sample to calculate the interest concentration in 20 min. • FB-SAM/FIA reduced the quantification error of interest caused by the high amount of salt in the seawater sample. The standard addition method is a powerful tool to eliminate matrix interferences and enables accurate determinations, but it is time-consuming and labor-intensive. This paper proposes a feedback standard addition method coupled flow injection analysis, FB-SAM/FIA, for the rapid and accurate determination of trace interest in seawater samples. This approach automatically prepares spiked samples by feeding back the peak height in the fiagram, thus significantly improving the sample throughput compared to the manual standard addition method. Spectrophotometric determination of NO 2 − with the Griess assay was used as an evaluation model. The proposed technique demonstrated a sample throughput of 3 samples/h, ranging from 0.0050 mg L−1 (LOD) to 0.125 mg L−1 NO 2 −. The accuracies of NO 2 − determination with FB-SAM/FIA and an absolute calibration method were tested using natural seawater and pseudo-seawater samples containing 0.040 mg L−1 NO 2 − in 0, 1, 2, 3, and 4 % sodium chloride media. With the absolute calibration method, the calculated concentration increased with an increase in salinity, reaching an overestimation of about 40 %. On the other hand, FB-SAM/FIA suppressed the errors in the range of −7.8 % to 1.3 % and applied successfully to the determination of NO 2 − in the natural seawater samples. [ABSTRACT FROM AUTHOR]

Monitoring the installation of building components offers great opportunities for enhancing not only the productivity but the performance of construction operations. Existing approaches and technologies still suffer from low level automation and lack of adaptability to material installation processes. This paper examines the feasibility of automatically tracking the installation of building components using proximity data obtained from swarm nodes. Proximity data were collected from tagged steel components during the installation process and compared with that obtained from the design model. Experiments were conducted to determine the accuracy of the swarm nodes. The error obtained from the experiments was used to set a buffer or tolerance around the components for accurately capturing the installation status in the developed system. This result has demonstrated that the application of swarm nodes has the potential to automatically track the installation of building components. [ABSTRACT FROM AUTHOR]

Current utility-scale wind turbines are highly dynamic systems excited by a large variety of loading sources. The proper operation of wind turbines thus requires a complete knowledge of the actual dynamic behavior of the system, in order to ensure the expected longevity of their main structural elements. In that context, this paper describes the monitoring project developed for a 2.0 MW wind turbine, the description of the installed monitoring system, as well as the main steps included in the methodology developed for the continuous processing of the collected data. The main results achieved during one year of monitoring are shown in detail. They allowed to accurately characterize the variability of the dynamic properties of the wind turbine, with special emphasis on the natural frequencies and damping ratios of the most important vibration modes, throughout normal operating conditions of the turbine. In addition, several shutdown events were identified and used to estimate the modal damping of the wind turbine through the analysis of free-decay responses of the structure. This monitoring project contributes to improve the knowledge on the dynamic behavior of onshore wind turbines under normal operating conditions. [ABSTRACT FROM AUTHOR]

Damage detection techniques have been widely explored over the last years driven by the advances of computational intelligence technologies. To understand the structure's dynamic behavior, some studies use modal-based methods, which are traditionally applied to reflect changes caused by damage. More recently, strategies using raw vibration measurements have gained notoriety and are proving to be a promising approach. In this context, the aim of this paper is to present a novel automated methodology for damage localization based on the extraction of features from dynamic data using domain knowledge and on an unsupervised filtering process. Feature extraction is performed simultaneously in time, frequency, and quefrency domains to diversify information retrieval. In machine learning (ML), this filtering procedure is called feature selection (FS) and is applied herein with the goal to decrease redundancy and increase the relevance of the feature set by eliminating a portion of it in view of a predefined criterion. The main concept is that the proposed method can customize its features concerning the structure, providing generality about any type of geometry, material, and excitation it encounters. The damage-sensitive index is computed through an outlier analysis, where percentile intervals are created based on the filtered features from the structure's healthy state. Thus, any anomalies surrounding this initial state should be automatically located. The method was successfully tested in five applications, two of them being full-scale bridges, which shows a promising performance for real-world monitoring situations. Some of its significant achievements are single and multiple damage location, structural reinforcement detection, quantification of severity in progressive damage scenarios, and robustness to noise due to varying traffic and/or environmental conditions. Such a reliability is tied to an efficient default parameters setup, enabling an automated damage localization algorithm. [ABSTRACT FROM AUTHOR]

Abstract: A mobile sensor platform that features a non-contact guided wave piezoelectric composite transducer payload for rapid inspection of large plate-like structures is presented. The paper begins with results from an experimental B-scan of an aluminium plate. Since the current guided wave payload uses 30mm square transducers ( wide) the system provides fairly course lateral resolution that in this case is approximately equal to the width of the transducer. The paper goes on to use simulation tools to examine the practical SNR and resolution limits of this approach. When using narrow aperture transducers that provide a wide field of view it is important to apply the synthetic aperture focusing technique to maximise image resolution. It is shown that resolution is a function of both transducer aperture and robot positional uncertainty since the effectiveness of synthetic aperture techniques is directly dependent on positional accuracy. It is also shown that since systems utilising larger aperture transducers with a narrow field of view are not as dependent on synthetic array reconstruction, they can outperform systems with narrower transducers in cases where there is relatively large positional uncertainty. Lastly the resolution and relative SNR are modelled as functions of transducer aperture for the cases of B-scan and synthetic array processing. [Copyright &y& Elsevier]

Current onsite safety management always relies on time-consuming predefinitions of hazardous zones based on the managers' personal capabilities. However, in a typical labor-intensive industry such as construction, the workers themselves can provide a wealth of information for hazard identification. Historical accident-free working locations on site provide a valuable means of recognizing safe workplaces. This paper presents an approach to the automated classification of construction site zones derived from the location tracks of workers collected from a real-time location system (RTLS). Through data mining, filtering and analysis, the location tracks are transformed into grid density maps and continuous density maps. These illustrate the characteristics of spatial-temporal activities onsite as well as providing a visual representation of the distribution of safe and hazardous individual workplaces. A personnel hazard map is generated automatically based on historical accident-free location tracks from a field project using the proposed approach. Compared with the actual workplaces in terms of accuracy, precision, sensitivity and specificity, the evaluation result reveals that the hazardous areas on a construction site can be automatically classified to improve the workplace management of individual workers. The contributions of this research include an automated zone classification algorithm and an evaluation framework consisting of four indicators for hazard awareness onsite. [ABSTRACT FROM AUTHOR]

We have utilized an automated acid hydrolysis technology, followed by an abbreviated Soxhlet extraction technique to obtain fat from whole milk for the determination of persistent organic pollutants, namely polychlorinated dibenzo- p -dioxins, polychlorinated dibenzofurans and polychlorinated biphenyls. The process simply involves (1) pouring the liquid milk into the hydrolysis beaker with reagents and standards, (2) drying the obtained fat on a filter paper and (3) obtaining pure fat via the modified Soxhlet extraction using 100 mL of hexane per sample. This technique is in contrast to traditional manually intense liquid-liquid extractions and avoids the preparatory step of freeze-drying the samples for pressurized liquid extractions. Along with these extraction improvements, analytical results closely agree between the methods, thus no quality has been compromised. The native spike (n = 12) and internal standard (n = 24) precision and accuracy results are within EPA Methods 1613 and 1668 limits. While the median (n = 6) Toxic Equivalency Quotient (TEQ) for polychlorinated dibenzo- p -dioxins/polychlorinated dibenzofurans and the concentration of the marker polychlorinated biphenyls show a percent difference of 1% and 12%, respectively, compared to 315 previously analyzed milk samples at the same laboratory using liquid-liquid extraction. During our feasibility studies, both egg and fish tissue show substantial promise using this technique as well. [ABSTRACT FROM AUTHOR]

Abstract: The National Ignition Facility (NIF) is a high-energy laser facility comprised of 192 beamlines that house thousands of optics. These optics guide, amplify and tightly focus light onto a tiny target for fusion ignition research and high energy density physics experiments. The condition of these optics is key to the economic, efficient and maximally energetic performance of the laser. Our goal, and novel achievement, is to find on the optics any imperfections while they are tens of microns in size, track them through time to see if they grow and if so, remove the optic and repair the single site so the entire optic can then be re-installed for further use on the laser. This paper gives an overview of the image analysis used for detecting, measuring, and tracking sites of interest on an optic while it is installed on the beamline via in situ inspection and after it has been removed for maintenance. In this way, the condition of each optic is monitored throughout the optic''s lifetime. This overview paper will summarize key algorithms and technical developments for custom image analysis and processing and highlight recent improvements. (Associated papers will include more details on these issues.) We will also discuss the use of OI Analysis for daily operation of the NIF laser and its extension to inspection of NIF targets. [Copyright &y& Elsevier]

Abstract: Tractography based on diffusion tensor imaging (DTI) is widely used to quantitatively analyze the status of the white matter anatomy in a tract-specific manner in many types of diseases. This approach, however, involves subjective judgment in the tract-editing process to extract only the tracts of interest. This process, usually performed by manual delineation of regions of interest, is also time-consuming, and certain tracts, especially the short cortico-cortical association fibers, are difficult to reconstruct. In this paper, we propose an automated approach for reconstruction of a large number of white matter tracts. In this approach, existing anatomical knowledge about tract trajectories (called the Template ROI Set or TRS) were stored in our DTI-based brain atlas with 130 three-dimensional anatomical segmentations, which were warped non-linearly to individual DTI data. We examined the degree of matching with manual results for selected fibers. We established 30 TRSs to reconstruct 30 prominent and previously well-described fibers. In addition, TRSs were developed to delineate 29 short association fibers that were found in all normal subjects examined in this paper (N=20). Probabilistic maps of the 59 tract trajectories were created from the normal subjects and were incorporated into our image analysis tool for automated tract-specific quantification. [ABSTRACT FROM AUTHOR]

The growing need for better monitoring and control of road construction projects, together with rapid technological progress, have led to a number of interesting developments, which are reviewed below. The present paper describes the development of a real-time monitoring model capable of measuring productivity and progress automatically. The model, which uses global positioning system for on-site automated data collection, was tested and validated on site. The results of the field experiments have indicated that the expected accuracy level of the model can be assessed as ±4–5% for unstructured activities and even higher for more structured ones, such as asphalt spreading. The paper concludes that it is possible to automatically measure the performance of earthmoving operations. Based on the results, it also highlights the needs for further research. [ABSTRACT FROM AUTHOR]

In a previous paper [Artif. Intell. Med. 5 (1993) 431] we described RaPiD, a knowledge-based system for designing dental prostheses. The present paper discusses how RaPiD has been extended using techniques from computer vision and logic grammars. The first employs point distribution and active shape models (ASMs) to determine dentition from images of casts of patient’s jaws. This enables a design to be customised to, and visualised against, an image of a patient’s dentition. The second is based on the notion of a path grammar, a form of logic grammar, to generate a path linking an ordered sequence of subcomponents. The shape of an important and complex prosthesis component can be automatically seeded in this fashion. Combining these models now substantially automates the design process, beginning with a photograph of a dental cast and ending with an annotated and validated design diagram ready to guide manufacture. [Copyright &y& Elsevier]

The ability to automatically delineate forest stands and determine their age is useful for natural resources professionals. Two common approaches to estimating forest area and age-class distributions are inventory-based methods, such as Forest Inventory and Analysis (FIA), and remote sensing based methods. Vegetation Change Tracker (VCT) is an algorithm that uses time series stacks of Landsat images to identify forest disturbances. However, additional computation is required to identify type of disturbance. This paper evaluates the usefulness of machine learning tools, such as support vector machine (SVM), for reclassifying VCT disturbances as stand-clearing disturbances or partial disturbances. Overall accuracy for a 2010 VCT disturbance map of the entire state of Virginia was determined to be 87 percent. 100 percent of 2010 Virginia clearcut harvests recorded in a reference dataset were classified as disturbances by VCT. Neighboring disturbed pixels, as classified by VCT, were clumped together and reclassified as stand-clearing disturbances or partial disturbances using SVM and variables for average disturbance magnitude and shape and size metrics of the clumped pixels, with an overall accuracy rate of 86 percent. The users and producers accuracy rates for stand-clearing disturbances were 88 percent and 95 percent respectively. In addition, an algorithm was developed in R for determining years since last stand-clearing disturbance for each pixel in a time series stack of reclassified VCT disturbance maps from 1984 to 2011. Neighboring pixels of the same age, in number of years since last stand-clearing disturbance, were clumped together and correspond, in general, to clearcut harvest boundaries. [ABSTRACT FROM AUTHOR]

Background: In this paper we describe a novel method to achieve high yield bacterial expression of a small protein domain with considerable therapeutic potential; Domain I of Beta-2-glycoprotein I (β2GPI). β2GPI is intrinsic to the pathological progression of the Antiphospholipid Syndrome (APS). Patients develop autoantibodies targeting an epitope located on the N-terminal Domain I of β2GPI rendering this domain of interest as a possible therapeutic. Results: This new method of production of Domain I of β2GPI has increased the production yield by ~20 fold compared to previous methods in E.coli. This largely scalable, partially automated method produces 50-75 mg of pure, folded, active Domain I of β2GPI per litre of expression media. Conclusion: The application of this method may enable production of Domain I on sufficient scale to allow its use as a therapeutic. [ABSTRACT FROM AUTHOR]

The need for better 3D documentation of the built environment has come to the fore in recent years, led primarily by city modelling at the large scale and Building Information Modelling (BIM) at the smaller scale. Automation is seen as desirable as it removes the time-consuming and therefore costly amount of human intervention in the process of model generation. BIM is the focus of this paper as not only is there a commercial need, as will be shown by the number of commercial solutions, but also wide research interest due to the aspiration of automated 3D models from both Geomatics and Computer Science communities. The aim is to go beyond the current labour-intensive tracing of the point cloud to an automated process that produces geometry that is both open and more verifiable. This work investigates what can be achieved today with automation through both literature review and by proposing a novel point cloud processing process. We present an automated workflow for the generation of BIM data from 3D point clouds. We also present quality indicators for reconstructed geometry elements and a framework in which to assess the quality of the reconstructed geometry against a reference. [ABSTRACT FROM AUTHOR]

This paper presents the first transformation methodology of a swarm intelligence algorithm into design space exploration (DSE) of optimal datapath and unrolling factor during area-performance tradeoff in high level synthesis (HLS). To the best of the authors' belief, in the literature, the above transformation has not been performed so far for developing a fully automated integrated exploration methodology of optimal datapath and unrolling factor. DSE problem being intractable and complex in the presence of auxiliary variable such as loop unrolling factor requires administration of intelligent decision making strategies at multiple stages to yield optimal results. The major sub-contributions of this proposed algorithm includes: a) Deriving a model for execution delay computation of a loop unrolled control data flow graph (CDFG) based on available resources, b) handling area-execution delay tradeoff during our integrated DSE process; c) Sensitivity analysis of particle swarm optimization (PSO) parameters used in assisting the designer in pre-tuning the baseline parameters during final area-performance tradeoff. Results of the proposed approach indicated an average improvement in Quality of Results (QoR) of > 23% and reduction in runtime of > 92% compared to recent approaches. [ABSTRACT FROM AUTHOR]

Natural disasters all too often place human lives and property at risk. Recovery efforts following a disaster can be slow and painstaking work, and potentially put responders in harm's way. A system which helps identify defects in critical building elements (e.g., concrete columns) before responders must enter a structure could save lives. In this paper we propose such a system, centered around an image-based three-dimensional (3D) reconstruction method and a new 3D crack detection algorithm. The image-based method is capable of detecting and analyzing surface damages in 3D. We also demonstrate how a robotic platform could be used to gather the set of images from which the reconstruction is created, further reducing the risk to responders. In this regard, image-based 3D reconstructions represent a convenient method of creating 3D models because most robotic platforms can carry a lightweight camera payload. Additionally, the proposed 3D crack detection algorithm also provides the advantage of being able to operate on 3D mesh models regardless of their data collection source. Our experimental results showed that the 3D crack detection algorithm performed well on several sample building elements, successfully identifying cracks, reconstructing 3D profiles, and measuring geometrical characteristics on damaged elements and not finding any cracks on intact ones. The operation and perceived benefits of the proposed method in a post-disaster situation are also discussed in detail. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, a novel method is described for automated determination of human insulin in biological fluids using principle of sequential injection on a molecularly imprinted solid-phase extraction (MISPE) cartridge as a sample clean-up technique combined with high performance liquid chromatography (HPLC). The water-compatible molecularly imprinted polymers (MIPs) were prepared using methacrylic acid as a functional monomer, ethylene glycol dimethacrylate as a cross-linker, chloroform as a porogen and insulin as a template molecule. The imprinted polymers were then employed as the solid-phase extraction sorbent for on-line extraction of insulin from human plasma samples. To achieve the best condition, influential parameters on the extraction efficiency were thoroughly investigated. Rapid and simple analysis of the hormone was successfully accomplished through the good selectivity of the prepared sorbent coupled with HPLC. Limits of detection (LOD) and quantification (LOQ) of 0.2ngmL−1, 0.7ngmL−1, and 0.03ngmL−1, 0.1ngmL−1 were obtained in plasma and urine respectively. The obtained data exhibited the great recoveries for extraction of insulin from human plasma and pharmaceutical samples, higher than 87%. [Copyright &y& Elsevier]

Many schemes have been presented over the years to develop automated visual surveillance systems. However, these schemes typically need custom equipment, or involve significant complexity and storage requirements. In this paper we present three software-based agents built using kernel machines to perform automated, real-time intruder detection in surveillance systems. Kernel machines provide a powerful data mining technique that may be used for pattern matching in the presence of complex data. They work by first mapping the raw input data onto a (often much) higher-dimensional feature space, and then clustering in the feature space instead. The reasoning is that mapping onto the (higher-dimensional) feature space enables the comparison of additional, higher-order correlations in determining patterns between the raw data points. The agents proposed here have been built using algorithms that are adaptive, portable, do not require any expensive or sophisticated components, and are lightweight and efficient having run times of the order of hundredths of a second. Through application to real image streams from a simple, run-of-the-mill closed-circuit television surveillance system, and direct quantitative performance comparison with some existing schemes, we show that it is possible to easily obtain high detection accuracy with low computational and storage complexities. [ABSTRACT FROM AUTHOR]

Abstract: The European Scanning System, developed to analyse nuclear emulsions at high speed, has been completed with the development of a high level software infrastructure to automate and support large-scale emulsion scanning. In one year, an average installation is capable of performing data-taking and online analysis on a total surface ranging from few m2 to tens of m2, acquiring many billions of tracks, corresponding to several TB. This paper focuses on the procedures that have been implemented and on their impact on physics measurements. The system proved robust, reliable, fault-tolerant and user-friendly, and seldom needs assistance. A dedicated relational Data Base system is the backbone of the whole infrastructure, storing data themselves and not only catalogues of data files, as in common practice, being a unique case in high-energy physics DAQ systems. The logical organisation of the system is described and a summary is given of the physics measurement that are readily available by automated processing. [Copyright &y& Elsevier]

The usability of mobile applications is critical for their adoption because of the relatively small screen and awkward (sometimes virtual) keyboard, despite the recent advances of smartphones. Traditional laboratory-based usability testing is often tedious, expensive, and does not reflect real use cases. In this paper, we propose a toolkit that embeds into mobile applications the ability to automatically collect user interface (UI) events as the user interacts with the applications. The events are fine-grained and useful for quantified usability analysis. We have implemented the toolkit on Android devices and we evaluated the toolkit with a real deployed Android application by comparing event analysis (state-machine based) with traditional laboratory testing (expert based). The results show that our toolkit is effective at capturing detailed UI events for accurate usability analysis. [ABSTRACT FROM AUTHOR]

This paper presents a laser processing facility for automatic welding of aluminium and other hard to process materials widely used in modern industry. It is built on the basis of industrial Nd:YAG laser with an average power of up to 500 W, equipped with a specially designed feeder, in its original construction. The feeder allows feeding a filler wire of 0.8 mm and up in diameter into the welding area, within a wide speed range in both continuous and pulsed modes. The characteristics of laser welding of aluminium alloys such as Al-1050, Al-6061, Al-2024, Al-4047 and widely used structural and stainless steels such as AISI 304, with and without a filler wire, were studied. The processing methods that can be applied to exclude the formation of micro-cracks and pores in pulsed laser welding were determined. In particular, it was shown, that the application of a fibre optic can change the energy distribution of the laser beam that, in some cases, has a positive effect on the laser welding quality. The optimal groove shape and size designed for laser welding with wire feed, has been also determined. A simple mathematical model for the determination of the operation parameters of laser welding is presented. It is shown that the model allows predicting the laser welding results with sufficient accuracy. The welding processing parameters, depending on the type and thickness of the welded materials, were calculated. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, a novel method is described for automated determination of dextromethorphan in biological fluids using molecularly imprinted solid-phase extraction (MISPE) as a sample clean-up technique combined with high performance liquid chromatography (HPLC). The water-compatible molecularly imprinted polymers (MIPs) were prepared using methacrylic acid as functional monomer, ethylene glycol dimethacrylate as cross-linker, chloroform as porogen and dextromethorphan as template molecule. These imprinted polymers were used as solid-phase extraction sorbent for the extraction of dextromethorphan from human plasma samples. Various parameters affecting the extraction efficiency of the MIP cartridges were evaluated. The high selectivity of the sorbent coupled to the high performance liquid chromatographic system permitted a simple and rapid analysis of this drug in plasma samples with limits of detection (LOD) and quantification (LOQ) of 0.12ng/mL and 0.35ng/mL, respectively. The MIP selectivity was evaluated by analyzing of the dextromethorphan in presence of several substances with similar molecular structures and properties. Results from the HPLC analyses showed that the recoveries of dextromethorphan using MIP cartridges from human plasma samples in the range of 1–50ng/mL were higher than 87%. [Copyright &y& Elsevier]

The tortuosity of retinal blood vessels is a diagnostic parameter assessed by ophthalmologists on the basis of examples and experience; no quantitative model is specified in clinical practice. All quantitative measures proposed to date for automatic image analysis purposes are functions of the curvature of the vessel skeleton. We suggest in this paper that curvature may not be the only quantity involved in modeling tortuosity, and that vessel thickness, or caliber, may also play a role. To support this statement, we devise a novel measure of tortuosity, depending on both curvature and thickness, and test it with 200 vessels selected by our clinical author from the public digital retinal images for vessel extraction database. Results are in good accordance with clinical judgment. Comparative experiments show performance similar to or better than that of four measures reported in the literature. We conclude that there is reasonable evidence supporting the investigation of tortuosity models incorporating more measurements than just skeleton curvature, and specifically vessel caliber. [ABSTRACT FROM AUTHOR]

Traditional clinical follow-up after breast cancer is inefficient at detecting relapse and is poorly suited to detecting and ameliorating psychological problems. There is interest in developing more effective and efficient methods of follow-up. We report a prospective cohort study of the acceptability and feasibility of remote, automated telephone follow-up after breast cancer. Women with a history of breast cancer were approached at their annual follow-up visit. For participants, the follow-up questionnaire was administered on paper at baseline. In place of a clinic visit following year, the women completed the same questionnaire using an automated telephone system. All patients were given mammograms. A semi-structured interview was then conducted to assess the acceptability. The potential impact on clinic usage was assessed. In all, 110 of 121 women (91%) agreed to participate. Seventy-five patients (71%) completed follow-up using the new automated system 1 year later. Seventy-one of the 75 patients found the system easy to use. Forty-nine of the 75 (65.33%) liked the system and were happy to use it as their sole method of follow-up. A further 12% were happy to use it as part of their follow-up. In only 10.66% of participants were concerns raised which led to clinic attendance. Automated questionnaire-based telephone follow-up is acceptable to women and has the potential to reduce attendance at clinic. Further studies to validate this method further are planned. [ABSTRACT FROM AUTHOR]

A crucial problem that involves feature-based image registration algorithms is how to reliably establish the correspondence between the features detected in the sensed image and those detected in the reference image. Generally, most existing methods only use spatial relations or feature similarity, or a simple combination of them, to solve this problem, and all have some limitations. In this paper, a new feature-matching strategy is developed. It is realized by introducing a function whose independent variable is the match matrix, which describes the correspondence of the features, to combine spatial relations and organically feature similarity, and its global maximum is assumed to be reached if the sensed image is completely aligned with the reference image. Thus, the feature correspondence can be estimated by finding the maximum of the function. Two approaches are devised to solve the optimization problem. One is based on the branch-and-bound strategy to yield a global optimal solution, and the other uses an iterative algorithm that combines graduated assignment and variable metric methods to search for a local optimal solution with low computational complexity. The proposed method can work without the limitations of feature type, similarity criterion, and transform model, and its performance is evaluated using a variety of real images. Compared with some existing methods, it is fast and robust, and has the highest accuracy. [ABSTRACT FROM AUTHOR]

Abstract: Although it is accepted that trifluoroacetic acid (TFA) can cause suppression of an analyte during LC/MS analysis, this paper presents a relatively sensitive gradient method that uses a TFA mobile phase for the improved quantification of small, polar drug-like compounds. The described method was developed in a discovery drug metabolism and pharmacokinetics (DMPK) laboratory for the screening measurement of compound concentrations to calculate PK parameters and CNS exposure of compounds from a chemical series that had poor chromatography under generic methods using formic acid mobile phase. The samples were collected by a Culex automated sampling unit, and the plasma proteins were precipitated by a Tecan robot in 96-well plates. After centrifugation, the supernatant was removed, dried down using a SPE-Dry unit, and the samples were reconstituted in aqueous buffer on the robot. The samples were analyzed on an Agilent LC/MSD using a 5-min gradient on a 5cm phenyl column. No additional steps, such as the “TFA-fix”, were necessary. Although sample batches were analyzed over 6h, no drift or degradation of signal was observed. The improved chromatography resulted in a method that was selective, rugged, and had a dynamic range from 5 to 20,000nM, which was sufficient to quantitate low volume, serial plasma samples collected out to 8h postdose. [Copyright &y& Elsevier]

The forced swim test (FST) and the tail suspension test (TST) are used widely for measuring the pharmacological effects of antidepressant drugs or changes in stress-evoked behavior in mice. However, inconsistent scoring techniques and poor reproducibility may result from their reliance on subjective ratings by observers to score behavioral changes. In this paper, automated versions of the mouse FST and TST were characterized and validated against observer ratings. For the FST, a commercially available video tracking system (SMART II; San Diego Instruments) measured the duration that mice swam in water-filled cylinders at a set velocity. For the TST, a commercially available automated device (Med Associates, St. Albans, VT) measured input from a strain gauge to detect movements of mice suspended from an elevated bar. Dose-dependent effects of the antidepressant desipramine on FST and TST immobility were measured in CD-1 mice using both automated devices and manual scoring from videotapes. Similar dose–response curves were obtained using both methods. However, a wide range of correlations for raters in the FST indicated that scoring criteria varied for individual raters despite similar instructions. Automated versions of the mouse FST and TST are now available and provide several advantages, including an opportunity to standardize methods across laboratories. [Copyright &y& Elsevier]

• Pyrethroids determination can be a challenge in honey due to the matrix complexity. • Matrix compatible SPME fibers are suitable for a wide range of samples. • Optimized SPME method could achieve great figures of merit for this complex matrix. • The method can be used in routine analysis once it is fully automated and timesaving. • Sample preparation workflow is straightforward by using a single vial in all steps. Pyrethroids insecticides may constitute a major hazard to honeybees, leading to colony collapse disorder. However, the determination of pyrethroids in honey has remained a challenging undertaking for analysts to date due to the high complexity of this matrix as well as the MRLs. This paper presents a fully automated method to overcome matrix influences using matrix-compatible overcoated SPME fiber for quantitative analysis of pyrethroids in diluted honey by GC–MS. The developed method was optimized using a multivariate approach providing LOQ values much lower than the stablished MRL (0.10–10 ng/g), while granting satisfactory linearity (R2 > 0.998) in a wide linear range of 0.1–2000 ng/g, repeatability with RSDs < 10%, reproducibility RSDs < 20%, and accuracy ranging from 75 to 118% and from 82 to 120 % for inter-day and intra-day assays, respectively by using five replicates. The method herein proposed overcomes challenges presented by complex matrices while minimizing sample handling and the overall complexity of the procedure. [ABSTRACT FROM AUTHOR]

• Agent-based simulation of an automated taxi service in Zurich. • Context-specific synthetic population, Stated Preferences survey and cost-model. • Dynamic demand reacting to waiting times and price. Automated Mobility on Demand (AMoD) is a concept that has recently generated much discussion. In cases where large-scale adoption of an automated taxi service is anticipated, the service's impacts may become relevant to key transport system metrics, and thus to transport planners and policy-makers as well. In light of this increasingly important question, this paper presents an agent-based transport simulation with (single passenger) AMoD. In contrast to earlier studies, all scenario data (including demand patterns, cost assumptions and customer behaviour) is obtained for one specific area, the city of Zurich, Switzerland. The simulation study fuses information from a detailed bottom-up cost analysis of mobility services in Switzerland, a specifically tailored Stated-Preferences survey about automated mobility services conducted in the canton of Zurich, and a detailed agent-based transport simulation for the city, based on MATSim. Methodologically, a comprehensive approach is presented that iteratively runs these components to derive states in which service cost, waiting times and demand are in equilibrium for a cost-covering AMoD operator with predefined fleet size. For Zurich, several cases are examined, with 4,000 AMoD vehicles leading to the maximum demand of around 150,000 requests per day that can be attracted by the system. Within these parameters, the simulation results show that customers are willing to accept average waiting times of around 4 min at a price of 0.75 CHF/km. Further cost-covering cases with lower demand are presented, where either smaller fleet sizes lead to higher waiting times, or larger fleet sizes lead to higher costs. While our simulations indicate that an AMoD system in Zurich can bring benefits to the users, they show that the system impact is largely negative. Caused by modal shifts, our simulations show an increase of driven distance of up to 100%. All examined fleet configurations of the unregulated, cost-covering, single-passenger, door-to-door AMoD service are found to be highly counter-productive on a path towards a more shared and active transport system. Accordingly, policy recommendations for regulation are discussed. [ABSTRACT FROM AUTHOR]