The implementation and first insights of the French-speaking Swiss programme for monitoring self-harm.

Self-harm is a major risk factor for suicide but remains poorly documented. No data on self-harm in French-speaking Switzerland exist. To address this deficiency, the Swiss Federal Office of Public Health commissioned a specific self-harm monitoring programme. We present and discuss its implementation and first findings. Every patient aged 18–65 years presenting for self-harm to the emergency departments of the Lausanne and Neuchâtel general hospitals were included in the monitoring programme over a 10-month period (December 2016 to September 2017). Clinicians collected anonymous sociodemographic and clinical data. The sample included 490 patients (54.9% female and 45.1% male) for 554 episodes of self-harm, showing a higher proportion of patients aged 18–34 (49.2%) than older age groups (35–49, 33.7% and 50–65, 17.1%). Patients were mostly single (56.1%) and in problematic socioeconomic situations (65.7%). Self-poisoning was the most commonly used method (58.2%) and was preferred by women (71% of females and 42.5% of males, Fisher’s exact test, p <0.001) and the majority of patients (53.3%) had experienced at least one previous episode of self-harm. The self-harm rate was 220 per 100,000 inhabitants in Lausanne and 140 in Neuchâtel. Suicidal intent was clear for 50.6% of the overall sample, unclear for 25.1% and absent for 24.3%. It differed significantly between sites (χ2(2) = 9.068, p = 0.011) as Lausanne reported more incidents of unclear intent (27.7% versus 17.4% in Neuchâtel) and Neuchâtel more incidents with absence of intent (33.1% versus 21.3% in Lausanne). In Lausanne, patients more frequently resorted to methods such as jumping from a height (11.4%) and hanging (9%) than in Neuchâtel (1.6% and 4.9%, Fisher’s exact test, p = 0.006). Our results are globally consistent with previous research on self-harm. We found significant inter-site differences in methods, suicidal intent and self-harm rates. Our findings highlight the importance of implementing local self-harm monitoring to identify specific at-risk groups and develop targeted preventive intervention

Defect localization on a PCB with functional testing

Abstract This paper describes how Linguistic Equations, an intelligent method derived from Fuzzy Algorithms, have been used in a decision-helping tool adapted to the specific needs of electronics manufacturing. In our case the company involved in the project, PKC Group, is mainly producing control cards for the telecommunication and automotive industry. In their business, nearly 70 percent of the cost of a product is material cost. Detecting defects and repairing the Printed Circuit Boards is therefore a necessity. With an ever increasing complexity of the products, defects are very likely to occur, no matter how much attention is put into their prevention. The work focused therefore on defect detection during the final testing of the product. The approach is based on experience using intelligent methods such as Fuzzy Logic or Linguistic Equations in fault diagnosis. An intelligent system based on expert knowledge was developed for analyzing test data. This analysis emphasizes localization of the defective components more than possible causes of those defects. Expert knowledge was essential for the development of the system as the number of defects is too low for a data-based approach. According to the first results, the system is successful for new products, even in the ramp-up stage. On the other hand, the underlying methodology provides techniques for tuning the tool parameters when amount of testing data increases. Diagnosis effectiveness can therefore be improved from detection of a functional area towards component level analysis. This report is engineer oriented, which means that it has to stay simple and accessible to people without research background. In the first part of this report, we will give a short description of the different methods used in the project with exemples from the case study. The second part concentrates on what has been implemented in the company, what were the needs and what are the improvements that are expected from this work