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This paper sets out to highlight the problem associated with the development of fieldbus diagnostics in a multi‐vendor environment and to propose a solution based on diagnostic function blocks (FB).

The work focuses on the “master‐slave” communication model in a PROFIBUS fieldbus system, where three different vendor solutions are investigated.

Although the fieldbus standards specify the type and format of the diagnostics data, the extent, location and sequence of diagnostics data within a controller are entirely vendor‐dependent. The outcome from this work defines a framework for representing the diagnostics data in the context of a special function block.

This research work defines a novel unified framework for representing the fieldbus diagnostics data using FB for multi‐vendor solutions in a PROFIBUS environment.

The purpose of this paper is to examine security incident response practices of information technology (IT) security practitioners as a diagnostic work process, including the preparation phase, detection, and analysis of anomalies.

The data set consisted of 16 semi‐structured interviews with IT security practitioners from seven organizational types (e.g. academic, government, and private). The interviews were analyzed using qualitative description with constant comparison and inductive analysis of the data to analyze diagnostic work during security incident response.

The analysis shows that security incident response is a highly collaborative activity, which may involve practitioners developing their own tools to perform specific tasks. The results also show that diagnosis during incident response is complicated by practitioners' need to rely on tacit knowledge, as well as usability issues with security tools.

Owing to the nature of semi‐structured interviews, not all participants discussed security incident response at the same level of detail. More data are required to generalize and refine the findings.

The contribution of the work is twofold. First, using empirical data, the paper analyzes and describes the tasks, skills, strategies, and tools that security practitioners use to diagnose security incidents. The findings enhance the research community's understanding of the diagnostic work during security incident response. Second, the paper identifies opportunities for future research directions related to improving security tools.

Facial expression provides abundant information for social interaction, and the analysis and utilization of facial expression data are playing a huge driving role in all areas of society. Facial expression data can reflect people's mental state. In health care, the analysis and processing of facial expression data can promote the improvement of people's health. This paper introduces several important public facial expression databases and describes the process of facial expression recognition. The standard facial expression database FER2013 and CK+ were used as the main training samples. At the same time, the facial expression image data of 16 Chinese children were collected as supplementary samples. With the help of VGG19 and Resnet18 algorithm models of deep convolution neural network, this paper studies and develops an information system for the diagnosis of autism by facial expression data.

The facial expression data of the training samples are based on the standard expression database FER2013 and CK+. FER2013 and CK+ databases are a common facial expression data set, which is suitable for the research of facial expression recognition. On the basis of FER2013 and CK+ facial expression database, this paper uses the machine learning model support vector machine (SVM) and deep convolution neural network model CNN, VGG19 and Resnet18 to complete the facial expression recognition.

In this study, ten normal children and ten autistic patients were recruited to test the accuracy of the information system and the diagnostic effect of autism. After testing, the accuracy rate of facial expression recognition is 81.4 percent. This information system can easily identify autistic children. The feasibility of recognizing autism through facial expression is verified.

The CK+ facial expression database contains some adult facial expression images. In order to improve the accuracy of facial expression recognition for children, more facial expression data of children will be collected as training samples. Therefore, the recognition rate of the information system will be further improved.

This research uses facial expression data and the latest artificial intelligence technology, which is advanced in technology. The diagnostic accuracy of autism is higher than that of traditional systems, so this study is innovative. Research topics come from the actual needs of doctors, and the contents and methods of research have been discussed with doctors many times. The system can diagnose autism as early as possible, promote the early treatment and rehabilitation of patients, and then reduce the economic and mental burden of patients. Therefore, this information system has good social benefits and application value.

Corrosion monitoring techniques fall broadly into two categories: those which provide simple numeric data for control purposes, and those which offer a spectrum of information for diagnostic purposes. Corrosion monitoring can be carried out directly at locations susceptible to corrosion, or indirectly under conditions simulating susceptible but inaccessible points. The interpretation of the data can reflect the purpose of monitoring at the particular location. A consistent form of presentation, and comparative tabulation including statistical analysis can greatly facilitate correlation and trend spotting. Broad spectrum techniques may give an early indication of new problems. An effective internal corrosion monitoring programme can make a major contribution towards the control of plant operating costs.

This study aims to investigate whether factors previously shown to influence attendance rates for appointments in general practice and general mental health services also influence attendance rates in services for people with intellectual disabilities (ID).

Post hoc data from 452 psychology appointments, ID diagnostic and initial screening (triage) appointments were collected from the health-care files of a community adult ID psychology service. Demographic factors (age, sex) and clinical factors (waiting time, time between appointment invitation being sent and appointment being held, presence of prior telephone call or letter, type of appointment, weekday, month) were recorded along with the attendance outcome (attended/did not attend [DNA]). The impact of the COVID-19 pandemic was also explored by documenting whether the appointment predated March 2020.

No significant associations were found between any variable investigated and attendance outcome when analysing appointment data as a whole and when splitting the data between appointment type. Weekday was found to significantly be associated with attendance outcome for appointments held during COVID-19, in which more DNA appointments occurred on a Wednesday compared to the other days of the week. No other associations were found for appointments held during the COVID-19 pandemic or for appointments held prior to the COVID-19 pandemic. These results suggest that factors which influence attendance rates in general health-care settings do not necessarily generalise to ID services.

To the best of the authors’ knowledge, this study is the first to examine whether certain demographic and clinical factors influenced attendance rates in an adult intellectual disability service.

The novel coronavirus and associated mitigation efforts have produced barriers to accessing services for adults with intellectual disabilities. This paper aims to evaluate the impact of Covid-19 on access to psychological services. The paper evaluates monthly referral rates and psychological distress scores for service users awaiting therapy.

A quantitative service evaluation was completed in a psychology service based in the North of England which specialises in supporting adults with intellectual disabilities. A single case experimental design was used to examine the impact of events in March 2020 on referral rates. Descriptive statistics and effect size calculations were used to examine the impact of prolonged waiting times on psychological distress scores.

Referral rates were examined comparing a 5-year rolling average monthly referral rate for the 12 months prior to March 2020 with the 12 months following. Findings demonstrate that events starting in March 2020 have had a considerable impact on referral rates and rates have not recovered. Eight service users were contacted to determine the impact of prolonged waiting times with results demonstrating increases in psychological distress of large effect size.

This is the only paper the authors are aware of examining the impact of the coronavirus on access to services and psychological distress for adults with intellectual disabilities. It is hoped that these findings will be able to inform both policy and practice as services continue to navigate the pandemic.

The purpose of this paper is to develop a model to estimate the value of information generated by and stored within vehicles to help people, businesses and researchers.

The authors provide a taxonomy for data within connected vehicles, as well as for actors that value such data. The authors create a monetary value model for different data generation scenarios from the perspective of multiple actors.

Actors value data differently depending on whether the information is kept within the vehicle or on peripheral devices. The model shows the US connected vehicle data market is worth between US$11.6bn and US$92.6bn.

This model estimates the value of vehicle data, but a lack of academic references for individual inputs makes finding reliable inputs difficult. The model performance is limited by the accuracy of the authors’ assumptions.

The proposed model demonstrates that connected vehicle data has higher value than people and companies are aware of, and therefore we must secure these data and establish comprehensive rules pertaining to data ownership and stewardship.

Estimating the value of data of vehicle data will help companies understand the importance of responsible data stewardship, as well as drive individuals to become more responsible digital citizens.

This is the first paper to propose a model for computing the monetary value of connected vehicle data, as well as the first paper to provide an estimate of this value.

This study investigates core framing techniques utilized by two anti-illegal immigration social movement organizations, the Minuteman Project, Inc. and the Minuteman Civil Defense Corps, both volunteer civil border patrol groups operating along the U.S.–Mexican border. Theoretically, this paper is informed by Robert Benford and David Snow's work on collective action framing. Using a case study approach, document analysis is employed to explore how four types of framing techniques (diagnostic framing, prognostic framing, motivational action framing, and credibility framing) are implemented by each group via information presented on their websites. The findings of this investigation suggest that these groups implement each of the four framing techniques in question, with the bulk of their focus resting in the diagnostic frame. Through the examination of these groups via the framing perspective, it is also found that the groups emphasize the importance of place, that is, the U.S.–Mexican border itself. The case analyses thus further framing theory by highlighting the roles that “geographic and place framing” also play. The Minuteman Project, Inc. and the Minuteman Civil Defense Corps are relatively new groups that have mobilized within the past few years. Sociologically, relatively few scholars have studied these particular groups within the larger anti-illegal immigration movement. This paper provides an in-depth analysis of how the groups utilize framing to construct their messages, missions, and goals to the public. Doing so contributes to an interesting and emerging type of civil border patrol movement and also adds to the body of work devoted to the importance of social movement framing.