Clustering Methods for Electricity Consumers: An Empirical Study in Hvaler-Norway

The development of Smart Grid in Norway in specific and Europe/US in general will shortly lead to the availability of massive amount of fine-grained spatio-temporal consumption data from domestic households. This enables the application of data mining techniques for traditional problems in power system. Clustering customers into appropriate groups is extremely useful for operators or retailers to address each group differently through dedicated tariffs or customer-tailored services. Currently, the task is done based on demographic data collected through questionnaire, which is error-prone. In this paper, we used three different clustering techniques (together with their variants) to automatically segment electricity consumers based on their consumption patterns. We also proposed a good way to extract consumption patterns for each consumer. The grouping results were assessed using four common internal validity indexes. We found that the combination of Self Organizing Map (SOM) and k-means algorithms produce the most insightful and useful grouping. We also discovered that grouping quality cannot be measured effectively by automatic indicators, which goes against common suggestions in literature.Comment: 12 pages, 3 figure

Local Short Term Electricity Load Forecasting: Automatic Approaches

Short-Term Load Forecasting (STLF) is a fundamental component in the efficient management of power systems, which has been studied intensively over the past 50 years. The emerging development of smart grid technologies is posing new challenges as well as opportunities to STLF. Load data, collected at higher geographical granularity and frequency through thousands of smart meters, allows us to build a more accurate local load forecasting model, which is essential for local optimization of power load through demand side management. With this paper, we show how several existing approaches for STLF are not applicable on local load forecasting, either because of long training time, unstable optimization process, or sensitivity to hyper-parameters. Accordingly, we select five models suitable for local STFL, which can be trained on different time-series with limited intervention from the user. The experiment, which consists of 40 time-series collected at different locations and aggregation levels, revealed that yearly pattern and temperature information are only useful for high aggregation level STLF. On local STLF task, the modified version of double seasonal Holt-Winter proposed in this paper performs relatively well with only 3 months of training data, compared to more complex methods

Improving the Canny Edge Detector Using Automatic Programming: Improving Hysteresis Thresholding

We have used automatic programming to improve the hysteresis thresholding stage of the popular Canny edge detector—without increasing the computational complexity or adding extra information. The F-measure has been increased by 1.8% on a test set of natural images, and a paired student-t test and a Wilcoxon signed rank test show that the improvement is statistically significant. This is the first time evolutionary computation and automatic programming has been used to improve hysteresis thresholding. The new program has introduced complex recursive patterns that make the algorithm perform better with weak edges and retain more detail. The findings provide further evidence that an automatically designed algorithm can outperform manually created algorithms on low level image analysis problems, and that automatic programming is ideally suited for inferring suitable heuristics for such problems

Safety Culture Onboard Ships

A project focusing on identifying and describing maritime risks is being conducted in the heavily trafficked water area of the Sound, situated in northern Europe between Sweden and Denmark. This paper reports of a test of a first version of a questionnaire constructed for measuring safety culture onboard vessels.48 crew members on a Swedish registered passenger/cargo ship completed and returned the questionnaire. The crew members were able to complete the questionnaire with few unanswered questions. Acceptable homogeneity was obtained for all but one of the nine dimensions of safety culture. Significant differences on several of the safety culture dimensions were found between deck/engine vs catering personnel, men vs women and different age groups, while little differences were found for supervisors vs non-supervisors or people with varying number of years onboard. Such safety culture dimensions need to be studied in relation to reports of accidents and near-misses, to further study the true relevance of safety culture

Edge Pixel Classification Using Automatic Programming

We have considered edge detection as a classification problem, and wehave applied two popular machine learning techniques to the problem andcompared their best results to that of automatic programming. We showthat ADATE, our system for automatic programming, is capable of producingsolutions that are as good as, or better than, the best solutions generated bytwo other machine learning techniques.The results demonstrates the ability of the ADATE system to createpowerful heuristics to solve image analysis problems

Relation between the rate of tumour cell proliferation and latency time in radiation associated breast cancer.

Background: Patients with possible radiation induced cancer could be used to study if the rate of tumour cell proliferation is related to latency time. Such a finding could help researcher to find time periods when other initiating risk factors operate. Methods: Seventeen women with breast cancer, with a prior history of radiation treatment towards the parts or the whole breast, exclusive of the primary treatment of a breast cancer were identified. Most women had received treatment for benign disorders as hemangiomas, shoulder pain or skin infections. Three patients had been treated with mantle radiation for Hodgkin's disease prior to developing breast cancer. DNA analysis were performed, on remaining tumour tissue after hormone receptor analysis had been done, measuring the fraction of tumour cells in S-phase. Latency time (time between diagnosis and previous radiation treatment) was calculated and related to the S-phase fraction. Results: A significant inverse relationship between latency time and S-phase was found (p < 0.0025), indicating that tumours with a high S-phase had a short latency time and vice versa. Among the possible radiation induced tumours, median S-phase was 14%, comparable with a median latency time of 22 years. Very high S-phase values were associated with short latency times (eg a S-phase of 35% would be compatible with a latency time of 7 years). Conclusion: Our preliminary results indicate that S-phase is related to latency time and that the median latency time maybe as long as 22 years. Our data may also explain why breast cancer is rare before 30 years of age and if patients are diagnosed at early ages, tumours often show high S-phase values and bad prognostic signs. We postulate that these results from radiation induced breast cancer may be used to extrapolate possible latency times in patients with non radiation induced breast tumours in order to isolate possible time periods for research after other initiating events

Recurrent Neural Networks for Oil Well Event Prediction

We have conducted a comparison between three types of recurrent neural networks and their ability to predict anomalies occurring in oil wells using a publicly available dataset. We have included two types of well-known state-of-the-art recurrent neural networks and a new type with neurons evolved specifically for the dataset using automatic programming. We show that the new type of recurrent neuron offers a massive improvement over the state of the art. The overall test accuracy of the new network type is 94.6%, which is an improvement by 18.3%, or 14.6 percentage points. We also show that a network with the new neuron performs better than any other solution proposed for the dataset.publishedVersio

Managing Intra-Party Democracy: Comparing the French Socialist and British Labour Party Conferences

The French Socialists and British Labour consider intra-party democracy as a central tenet of their philosophies. It is a core value that orientates their political attitudes and defines their identity. Traditionally, they have privileged a particular type of decision-making, based on the sovereignty of the party conference. However, at the beginning of the 1990s, these meetings projected a damaging image of division and chaos. Confronted with the intense scrutiny of their internal debates by the media, the two parties had to find a better balance between their culture and practices, and the need to promote an image of unity and efficiency. They introduced a number of reforms that, they claim, have expanded the possibilities for individual members to participate while at the same time giving the two leaderships a firmer grip on decision-making. Based on qualitative research conducted over many years, this paper explores the parties' new attitudes to internal democracy and analyses the process of power redistribution within the organizations

Samarbetsprojekt för effektivare brobyggande

Den svenska anläggningsbranschen har i ett flertal utredningar fått skarp kritik på grund av dålig produktivitet. Forskning visar på samma tendenser i övriga Europa och USA. Vissa mätningar tyder på att byggandet i den svenska anläggningsbranschen har en kostnadsökning som är dubbelt så hög jämfört med övriga branscher under de senaste 20 åren. Låg produktivitet och låg innovationsförmåga i byggbranschen leder till högre kostnader som inte garanterat ger en högre kvalitet. Trenden behöver vändas så att avkastningen på investeringar i vår infrastruktur ökar! Det första steget är att integrera konstruktions- och produktionsprocesserna, vilket ger kortare ledtider för både planering och uppförande av byggnadsverk. Onödigt långa byggtider orsakar störningar för andra aktörer i samhället. I ett pågående doktorandprojekt, som är ett samarbete mellan Trafikverket, WSP och Chalmers, söks möjligheten till att öka produktiviteten inom den svenska anläggningsbranschen. Huvudspåret är att utveckla och industrialisera brobyggandet. En effektivare byggindustri skapar möjligheter till att generera ett mervärde för samhället där mervärdet exempelvis kan motsvaras av att konstruktioner byggs med högre kvalitet till samma kostnad som idag alternativt samma eller högre kvalitet till en lägre kostnad än idag. Bortsett från rena kostnader bör naturligtvis en effektivare byggindustri också se till att lösningar väljs utifrån ett hållbart samhälle men med bibehållen fokus på produktivitet och innovation. En sådan lösning kan variera från själva processen till konstruktionsdetaljer