Different Degrees Of Automation Research Articles

Automated preparation of nanoscopic structures: Graph-based sequence analysis, mismatch detection, and pH-consistent protonation with uncertainty estimates.

Structure and function in nanoscale atomistic assemblies are tightly coupled, and every atom with its specific position and even every electron will have a decisive effect on the electronic structure, and hence, on the molecular properties. Molecular simulations of nanoscopic atomistic structures therefore require accurately resolved three-dimensional input structures. If extracted from experiment, these structures often suffer from severe uncertainties, of which the lack of information on hydrogen atoms is a prominent example. Hence, experimental structures require careful review and curation, which is a time-consuming and error-prone process. Here, we present a fast and robust protocol for the automated structure analysis and pH-consistent protonation, in short, ASAP. For biomolecules as a target, the ASAP protocol integrates sequence analysis and error assessment of a given input structure. ASAP allows for p prediction from reference data through Gaussian process regression including uncertainty estimation and connects to system-focused atomistic modeling described in Brunken and Reiher (J. Chem. Theory Comput. 16, 2020, 1646). Although focused on biomolecules, ASAP can be extended to other nanoscopic objects, because most of its design elements rely on a general graph-based foundation guaranteeing transferability. The modular character of the underlying pipeline supports different degrees of automation, which allows for (i) efficient feedback loops for human-machine interaction with a low entrance barrier and for (ii) integration into autonomous procedures such as automated force field parametrizations. This facilitates fast switching of the pH-state through on-the-fly system-focused reparametrization during a molecular simulation at virtually no extra computational cost.

Comparison of Automated and Traditional Western Blotting Methods

Traditional Western blotting is one of the most used analytical techniques in biological research. However, it can be time-consuming and suffer from a lack of reproducibility. Consequently, devices with different degrees of automation have been developed. These include semi-automated techniques and fully automated devices that replicate all stages downstream of the sample preparation, including sample size separation, immunoblotting, imaging, and analysis. We directly compared traditional Western blotting with two different automated systems, iBind™ Flex, which is a semi-automated system designed to perform the immunoblotting, and JESS Simple Western™, a fully automated and capillary-based system performing all steps downstream of sample preparation and loading, including imaging and image analysis. We found that a fully automated system can save time and importantly offer valuable sensitivity. This is particularly beneficial for limited sample amounts. The downside of automation is the cost of devices and reagents. Nevertheless, automation can be a good option to increase output and facilitate sensitive protein analyses.

Human Factor Analysis of the Railway Traffic Operators

The human factor is an essential aspect of the operability and safety of many technical systems. This paper focuses on the analysis of human errors in the railway domain. The subject of human reliability analysis is the behavior of operators of station-signaling systems responsible for rail traffic management. We use a technique for human-error rate prediction as the 1st generation human reliability analysis to deal with task analyses, error identification and representation, and the quantification of human error probabilities. The paper contributes to the comparison of three technologically different railway traffic control systems, having different degrees of automation—from the manually operated (electro-mechanical), through semi-automated (relay-based) to almost fully automated (computer-based) station-signaling systems. We observe the frequency of individual operations performed in time intervals and calculate human error probability and human success probability values for each operation. Thus, we can analyze human reliability and compare the workload of operators working with control systems of different degrees of automation.

A review of the research progress of interventional medical equipment and methods for prostate cancer

AbstractBackgroundProstate cancer is a common disease in men and has a relatively high mortality rate. However, the interventional medical equipment used for prostate biopsy and brachytherapy has always been a social concern.MethodsTo understand interventional medical equipment for prostate cancer, the structure of manual, semi‐automatic and automatic medical equipment were considered as the mainline, while the corresponding research on these structures were the auxiliary lines. The characteristics and corresponding research status have been discussed.ResultsInterventional medical equipment for prostate cancer with different degrees of automation and its characteristics were determined, and the imaging principles and characteristics of computed tomography, transrectal ultrasound and magnetic resonance imaging have been briefly described.ConclusionCertain feasible research suggestions have been proposed for future development from the perspective of structure, accuracy and safety. These include flexible and compact robot structures, high‐precision image recognition and guidance, accurate dose planning and monitoring, real‐time imaging monitoring without delay, high‐precision needle insertion strategy, master‐slave control, virtual reality and remote control.

Human factors and automation in future railway systems

This special issue contributes to the achievement of challenges related to human factors and automation dedicated to future railway systems. It includes transverse research topics by considering several emerging trends as the design of learning systems, of grades of automation, of cooperative system, or of analysis approaches about feedback of experience. To do so, contributions are detailed in different railway organization levels as training, design, operation, or maintenance. There are based on field studies, on simulation environments or on accident reports. They reveal the value of taking the human into account in the control and supervisory loop for the design, the analysis and the evaluation of future railway systems. Human-centered automation can indeed make system more resilient to various risks and threats by including human contributions through different degrees of automation and modalities of human–machine interaction.

A fuzzy mid-term capacity and production planning model for a manufacturing system with cloud-based capacity

Most of the past cloud manufacturing (CMfg) studies investigated the short-term production planning or job scheduling of a CMfg system, while the mid-term or long-term capacity and production planning of a CMfg system has rarely been addressed. In addition, most existing methods are suitable for CMfg systems comprising three-dimensional (3D) printers, computer numerical control (CNC) machines or robots, but ignore the coordination and transportation required for moving jobs across factories. To fill these gaps, a fuzzy mid-term capacity and production planning model for a manufacturer with cloud-based capacity is proposed in this study. The proposed methodology guides a manufacturer in choosing between non-cloud-based capacity and cloud-based capacity. It can be applied to factories utilizing machines with different degrees of automation including highly automatic equipment (such as 3D printers, CNC machines, and robots) and lowly automatic (legacy) machines, while existing methods assume that orders can be easily transferred between machines that are often highly automatic. In the proposed methodology, first, various types of capacity are unequally prioritized. Then, a fuzzy mixed-integer nonlinear programming model is formulated and optimized to make the mid-term or long-term capacity and production plan of a factory. The fuzzy capacity and production planning model is designed for factories with parallel machines. The proposed methodology has been applied to a case to illustrate its applicability. According to the experimental results, the proposed methodology successfully reduced total costs by up to 8%. The advantage of the proposed methodology over existing practices in fulfilling customers’ demand was also obvious.

Communication between road users and the influence of increased car automation

For a smooth, safe and comfortable cooperation of all actors in traffic good communication is essential. In view of the progressing automation in traffic the impacts on communication have to be considered. This paper puts a special focus on car automation's impact on the communication between road users including interaction between highly automated vehicles and vulnerable road users (VRUs). The main research objective was to develop relevant assumptions concerning changing conditions of communication. To reach this objective, interviews with experts were carried out. The results show that various developments between the two poles - (1) implementation controlled by certain societal strategies or (2) implementation that just takes its course - are considered possible. Enhanced automation could lead to the decrease in the use of interpersonal communication while the use of digital communication gains the upper hand. Such a development, on the one hand is seen as a chance for the improvement of traffic safety and efficiency. On the other hand, interviewed experts also identify risks such as misunderstandings between VRUs and automated cars, with fatal outcomes, or reductions in traffic flow. This is expected to be the case especially during the transition phase where vehicles with different degrees of automation are on the road and where many road users outside vehicles move about, e.g. in densely inhabited areas, where ~70% of the citizens in industrial countries live nowadays.

Area-wide real-world test scenarios of poor visibility for safe development of automated vehicles

IntroductionAutomated vehicles in everyday real-world traffic are predicted to be developed soon (Gasser et al., Rechtsfolgen zunehmender Fahrzeugautomatisierung, Wirtschaftsverlag NW, Berichte der Bundesanstalt für Straßenwesen F83, 2012). New technologies such as advanced object detection and artificial intelligence (AI) that use machine or deep-learning algorithms will support meeting all the maneuvering challenges involved in different degrees of automation (Society of Automotive Engineers - SAE international, Levels of driving automation for on road vehicles, Warrendale, PA., 2014; National Highway Traffic Safety Administration – NHTSA, Preliminary statement of policy concerning automated vehicles, Washington, DC, 2018). For automated series production, these vehicles of course must be safe in real-world traffic under all weather conditions. Therefore, system validation, ethical aspects and testing of automated vehicle functions are fundamental basics for successfully developing, market launching, ethical and social acceptance.MethodIn order to test and validate critical poor visibility detection challenges of automated vehicles with reasonable expenditure, a first area-wide analysis has been conducted. Because poor visibility restricts human perception similar corresponding to machine perception it was based on a text analysis of 1.28 million area-wide police accident reports – followed by an in-depth case-by-case analysis of 374 identified cases concerning bad weather conditions (see chap. 1.3). For this purpose the first time ever a nationwide analysis included all police reports in the whole area within the state of Saxony from the year 2004 until 2014.ResultsWithin this large database, 374 accidents were found due to perception limitations – caused by “rain”, “fog”, “snow”, “glare”/“blinding” and “visual obstruction” – for the detailed case-by-case investigation. All those challenging traffic scenarios are relevant for automated driving. They will form a key aspect for safe development, validation and testing of machine perception within automated driving functions.ConclusionsThis first area-wide analysis does not only rely on samples as in previous in-depth analyses. It provides relevant real-world traffic scenarios for testing of automated vehicles. For the first time this analysis is carried out knowing the place, time and context of each accident over the total investigated area of an entire federal state. Thus, the accidents that have been analyzed include all kinds of representative situations that can occur on motorways, highways, main roads, side streets or urban traffic. The scenarios can be extrapolated to include similar road networks worldwide. These results additionally will be taken into account for developing standards regarding early simulations as well as for the subsequent real-life testing. In the future, vehicle operation data and traffic simulations could be included as well. Based on these relevant real-world accidents culled from the federal accident database for Saxony, the authors recommend further development of internationally valid guidelines based on ethical, legal requirements and social acceptance.

Automated Processing of Personal Data for the Evaluation of Personality Traits: Legal and Ethical Issues

This paper examines the approach under the General Data Protection Regulation (GDPR) to profiling and (automated) decision-making as well as the corresponding legal and ethical implications. The definition of profiling under the GDPR is analysed in relation to different degrees of automation when it comes to decision-making based on the processing of personal or non-personal data. A two-step approach to profiling and decision-making, which can be found in the structure and wording of the GDPR, is described and analysed. It is argued that the use of this model helps understand how profiling and decision-making are conducted and how the two steps are interconnected. Furthermore, the two-step approach allows to identify various legal implications of profiling and the corresponding decision-making, such as those related to privacy and economic freedom. Further, the discussion of ethical aspects draws on two recent and controversial use cases. The first example deals with discriminatory effects that may result from profiling. The second one concerns opaque automated decision-making in the context of credit scoring. This ethical assessment is based on the ethical framework supplied by the wording of the GDPR.

The effect of individual differences in working memory in older adults on performance with different degrees of automated technology

A leading hypothesis to explain older adults’ overdependence on automation is age-related declines in working memory. However, it has not been empirically examined. The purpose of the current experiment was to examine how working memory affected performance with different degrees of automation in older adults. In contrast to the well-supported idea that higher degrees of automation, when the automation is correct, benefits performance but higher degrees of automation, when the automation fails, increasingly harms performance, older adults benefited from higher degrees of automation when the automation was correct but were not differentially harmed by automation failures. Surprisingly, working memory did not interact with degree of automation but did interact with automation correctness or failure. When automation was correct, older adults with higher working memory ability had better performance than those with lower abilities. But when automation was incorrect, all older adults, regardless of working memory ability, performed poorly.Practitioner Summary: The design of automation intended for older adults should focus on ways of making the correctness of the automation apparent to the older user and suggest ways of helping them recover when it is malfunctioning.

Integrated Relocation Model for Free-Floating Carsharing Systems

This paper presents an integrated relocation model for free-floating car-sharing (FFCS) systems. A historical data analysis conducted monthly generates demand indicators. A zone categorization identifies zones with a historical vehicle shortage or surplus and enables the estimation of the optimal vehicle distribution for the target time period. Given the current vehicle positions, the model identifies vehicle imbalances. Five macroscopic and microscopic steps using optimization and rule-based methods recommend relocations and service trips on an individual vehicle level. This process results in detailed staff operation plans. To assess the impact of relocations on the system's operation, the model was applied to an FFCS system in Munich, Germany. Three real-world field tests conducted at stages of the model's development exhibited different degrees of automation. The evaluation showed promising results. All tests had positive impacts on the main measures of success. The earnings per vehicle were increased by up to 18%. The mean idle time per trip end of all vehicles in the feet was decreased by up to 18%. The difference in idle times between the relocated vehicles and neighboring vehicles that were not relocated was decreased by up to 31%. Most important, the profit of the operator was between 4.7% and 5.8% higher than without relocations. The automation of the whole model in the last field test led to slightly lower but still very positive impacts while facilitating the whole relocation process for the operator.

Using Modeling and Simulation to Predict Operator Performance and Automation-Induced Complacency With Robotic Automation: A Case Study and Empirical Validation.

The aim of this study was to develop and validate a computational model of the automation complacency effect, as operators work on a robotic arm task, supported by three different degrees of automation. Some computational models of complacency in human-automation interaction exist, but those are formed and validated within the context of fairly simplified monitoring failures. This research extends model validation to a much more complex task, so that system designers can establish, without need for human-in-the-loop (HITL) experimentation, merits and shortcomings of different automation degrees. We developed a realistic simulation of a space-based robotic arm task that could be carried out with three different levels of trajectory visualization and execution automation support. Using this simulation, we performed HITL testing. Complacency was induced via several trials of correctly performing automation and then was assessed on trials when automation failed. Following a cognitive task analysis of the robotic arm operation, we developed a multicomponent model of the robotic operator and his or her reliance on automation, based in part on visual scanning. The comparison of model predictions with empirical results revealed that the model accurately predicted routine performance and predicted the responses to these failures after complacency developed. However, the scanning models do not account for the entire attention allocation effects of complacency. Complacency modeling can provide a useful tool for predicting the effects of different types of imperfect automation. The results from this research suggest that focus should be given to supporting situation awareness in automation development.

Learning Factory on Global Production

Based on the fundamental principle of teaching psychology that retentiveness increases if students actively apply learning topics rather than only attend oral or visual presentations, the concept of learning factories becomes more and more popular. Academic education in the field of production science is imparted by means of real-world manufacturing facilities. By applying the manufacturing process of a real product, students or professionals incorporate the learning contents effectively and gain consciousness about their practical implications. Most learning factories are focused on lean manufacturing, lean administration or resource efficiency. As today manufacturing is not only subject to a single factory, but a network of globally distributed production sites, at the wbk Institute of Production Science,currently, a learning factory dealing with the topic of global production is developed. On the one hand, the curriculum of the Learning Factory Global Production (LGP) involves the specifics of local production sites with different location factors, such as different degrees of automation, cost structures and qualification levels, and their effects on the reconfigurability of the production systems. On the other hand, the interaction of the production sites in a globally distributed production network and the strategic configuration of the network are also subject to the curriculum. The manufacturing processes are exemplified by the assembly of an automotive e-motor with transmission in the learning factory on global production. The learning factory is realized in cooperation with the Robert Bosch GmbH.

Nonsupervised Ranking of Different Segmentation Approaches: Application to the Estimation of the Left Ventricular Ejection Fraction From Cardiac Cine MRI Sequences

A statistical methodology is proposed to rank several estimation methods of a relevant clinical parameter when no gold standard is available. Based on a regression without truth method, the proposed approach was applied to rank eight methods without using any a priori information regarding the reliability of each method and its degree of automation. It was only based on a prior concerning the statistical distribution of the parameter of interest in the database. The ranking of the methods relies on figures of merit derived from the regression and computed using a bootstrap process. The methodology was applied to the estimation of the left ventricular ejection fraction derived from cardiac magnetic resonance images segmented using eight approaches with different degrees of automation: three segmentations were entirely manually performed and the others were variously automated. The ranking of methods was consistent with the expected performance of the estimation methods: the most accurate estimates of the ejection fraction were obtained using manual segmentations. The robustness of the ranking was demonstrated when at least three methods were compared. These results suggest that the proposed statistical approach might be helpful to assess the performance of estimation methods on clinical data for which no gold standard is available.

Imaging of the Sinuses for Functional Sinus Surgery Using Navigational Guidance

Advances in the understanding of mucociliary activity and pathophysiology of the nasal cavity and paranasal sinuses have revolutionized the surgical management of chronic and recurrent sinusitis. The development of functional endoscopic sinus surgery (FESS) can also be seen as the pioneer task in endoscopic surgery. Today, in more than 50% of all sinus surgeries FESS is being used. Inflammatory causes are the most common indication for surgery, which can be evaluated best preoperatively using (multi-detector) computed tomography. Even today there are further relevant developments of FESS that result in alleviation of the surgeon due to different degrees of automation. Using a preoperatively acquired navigational dataset helps choosing the optimal surgical strategy. Intraoperatively the navigational dataset is at present mainly used for localization of surgical tools. These newer operation methods demand for high-quality radiological imaging and evaluation, consisting of delineation of the local (inflammatory) process, detection of disease related complications and description of anatomical variations that may be important to the surgeon. Since patients with chronic recurrent sinusitis are relatively young on average and recurrent disease or further CT examinations are not uncommon, there should always be a focus on reduction of radiation exposure as much as possible. Technical advances like cone-beam tomography seem promising to further improve dose reduction as well as spatial resolution.

Economic Evaluation and Optimization of the Degree of Automation in Insurance Processes

In the context of value and customer orientation there are various requirements concerning the process – especially in insurance companies: processes are meant to be standardized, automated, and flexible. It is in question whether a fast and cheap automated processing is preferred to manual handling. For which claims and which process steps is it of economic value to have the flexibility and the competence and ability to solve problems of human operators at your disposal? Various combinations, representing different degrees of automation, are possible. The different degrees of automation for the processing of an insurance claims are compared and resulting cash flows are determined. It is essential to include all consequences that can be attributed to a single process and to consider customer reactions and restrictions to the capacity of processing. Instead of using heuristic rules to decide on automation in practice, here the decision is flexible and depends on the given situation. Viewing an aggregated number of insurance claims it is possible to deduce information about the performance of the process. The model is exemplarily illustrated with help of a part of the process for handling own damage glass claims.

Classifying Sonar Images: Can a Computer‐Driven Process Identify Eels?

AbstractThe purpose of this study was to explore the extent to which a computer‐driven process can be used to classify sonar images. The data we present come from a feasibility study for a hydroacoustic monitoring system aimed at the automatic detection of downstream‐migrating adult American eels Anguilla rostrata in the intake canal of a small hydroelectric station. The images were collected by a dual‐frequency identification sonar with sufficient resolution to show the distinct shape and swimming motion of eels, and thus to allow confident visual identification. The goal was to find a set of image processing, tracking, and pattern recognition techniques that would reproduce the results of the visual classification. Of the three classification methods that we tested with our example data set, neural network analysis had the lowest misclassification rate for eels (7% of the eels being misclassified as debris) and the second‐lowest misclassification rate for debris (5% of the debris being misclassified as eels). Discriminant function analysis misclassified 12% of the eels as debris and 4% of the debris as eels. A K‐nearest‐neighbor analysis initially provided the poorest results (17% misclassified eels and 12% misclassified debris). However, after applying an algebraic correction, K‐nearest‐neighbor analysis yielded an accurate estimate of the number of eels in the data set. We discuss the value of flagging cases of uncertain classification, how image processing and feature selection can affect the results, and how the numeric ratio of the targets present determines what error rates are acceptable. We conclude that, depending on the application, different degrees of automation may be achieved, ranging from a relatively high degree of human supervision in the classification of all potential targets to a fully automated process that requires only periodic quality control and adjustments of the classification model.

The influence of production systems on physiological responses measured in urine and saliva

AbstractThe aim of the present study was to investigate physiological effects of highly similar production systems with different degrees of automation by use of urinary catecholamines and cortisol as well as salivary cortisol. Furthermore, it was determined whether the physiological response was related to real‐time self‐reports in terms of feelings of positive and negative arousal, physical exertion, and sleepiness. Sixteen healthy women sorting wooden slats participated in the study. The work was highly repetitive and demanded intense concentration and rapid qualified decisions. The women rotated between three production systems with varying degrees of automation. Real‐time logbooks were completed and urine was collected five times and saliva seven times on four workdays and on one day off. When working at the most automated production system urinary concentrations of adrenaline and noradrenaline were 14 per cent lower compared to those obtained when working at the other production systems. For salivary cortisol, the profile over the day differed between production systems. The type of production system did not affect urinary cortisol. Feelings of positive and negative arousal were associated with increased concentrations of urinary adrenaline, while sleepiness was associated with lower salivary cortisol. These associations were independent of the relationship between production systems and biomarkers. In conclusion, decreased physiological arousal was observed in response to increased automation and real‐time self‐reports appeared to be related to specific physiological systems. Copyright © 2003 John Wiley & Sons, Ltd.

A Modular System for Milling and Boring Machines With Different Degrees of Automation

TODAY'S situation in the machine tool market combined with the ever changing variety of complex components to be machined, places high demands of flexibility on modern machine tools.

Real Time Control of Water Systems

The evolution of digital computer control of water supply, distribution and disposal is presented. Explanations of the difference in intensity of the use of computer control in water and electrical systems are given.The main control problems of water distribution are presented in mathematical and non-mathematical terms. Early attemps of the real time solution of the network equations and actual installation of digital control of water supply systems are described. The use of self-tuning control technique as an alternative to the computer aided control of water systems, commonly employed in actual installations, in suggested.The water disposal control problem and several actual installations with different degrees of automation are briefly treated.