Framtagning av prototyp för att läsa och dokumentera kundspecifikationer

To increase the quality in their products ABB is working towards a cleared order concept. That means that all customer specified options are to be known before they start with order calculations and construction. As it is today they use paper checklists to achieve this. One order may have several reactors, and for a reactor there can be several different alternatives. For each alternative a new checklist must be filled out.As of today all reading of the customer specification and checklist fill in with is done by hand by different persons, and sometimes the same data is read more than one time. All data is also manually inserted into the calculation tools.To decrease the risk that data is left out or gets distorted they want to have a tool to aid with the reading of the specification and the documentation of that work. Already read data can be copied over to another alternative so that it not must be read one more time. The read data are to be stored in a database so that it easily can be per automation inserted into the different design tools.

Use Multilevel Graph Partitioning Scheme to solve traveling salesman problem

The traveling salesman problem is although looking very simple problem but it is an important combinatorial problem. In this thesis I have tried to find the shortest distance tour in which each city is visited exactly one time and return to the starting city. I have tried to solve traveling salesman problem using multilevel graph partitioning approach.Although traveling salesman problem itself very difficult as this problem is belong to the NP-Complete problems but I have tried my best to solve this problem using multilevel graph partitioning it also belong to the NP-Complete problems. I have solved this thesis by using the k-mean partitioning algorithm which divides the problem into multiple partitions and solving each partition separately and its solution is used to improve the overall tour by applying Lin Kernighan algorithm on it. Through all this I got optimal solution which proofs that solving traveling salesman problem through graph partition scheme is good for this NP-Problem and through this we can solved this intractable problem within few minutes.Keywords: Graph Partitioning Scheme, Traveling Salesman Problem.

What aspects of rehabilitation provision contribute to self-reported met needs for rehabilitation one year after stroke - amount, place, operator or timing?

BACKGROUND AND OBJECTIVE: To a large extent, people who have suffered a stroke report unmet needs for rehabilitation. The purpose of this study was to explore aspects of rehabilitation provision that potentially contribute to self-reported met needs for rehabilitation 12 months after stroke with consideration also to severity of stroke. METHODS: The participants (n = 173) received care at the stroke units at the Karolinska University Hospital, Sweden. Using a questionnaire, the dependent variable, self-reported met needs for rehabilitation, was collected at 12 months after stroke. The independent variables were four aspects of rehabilitation provision based on data retrieved from registers and structured according to four aspects: amount of rehabilitation, service level (day care rehabilitation, primary care rehabilitation and home-based rehabilitation), operator level (physiotherapist, occupational therapist, speech therapist) and time after stroke onset. Multivariate logistic regression analyses regarding the aspects of rehabilitation were performed for the participants who were divided into three groups based on stroke severity at onset. RESULTS: Participants with moderate/severe stroke who had seen a physiotherapist at least once during each of the 1st, 2nd and 3rd-4th quarters of the first year (OR 8.36, CI 1.40-49.88 P = 0.020) were more likely to report met rehabilitation needs. CONCLUSION: For people with moderate/severe stroke, continuity in rehabilitation (preferably physiotherapy) during the first year after stroke seems to be associated with self-reported met needs for rehabilitation.

Real time video segmentation for recognising paint marks on bad wooden railway sleepers

Wooden railway sleeper inspections in Sweden are currently performed manually by a human operator; such inspections are based on visual analysis. Machine vision based approach has been done to emulate the visual abilities of human operator to enable automation of the process. Through this process bad sleepers are identified, and a spot is marked on it with specific color (blue in the current case) on the rail so that the maintenance operators are able to identify the spot and replace the sleeper. The motive of this thesis is to help the operators to identify those sleepers which are marked by color (spots), using an “Intelligent Vehicle” which is capable of running on the track. Capturing video while running on the track and segmenting the object of interest (spot) through this vehicle; we can automate this work and minimize the human intuitions. The video acquisition process depends on camera position and source light to obtain fine brightness in acquisition, we have tested 4 different types of combinations (camera position and source light) here to record the video and test the validity of proposed method. A sequence of real time rail frames are extracted from these videos and further processing (depending upon the data acquisition process) is done to identify the spots. After identification of spot each frame is divided in to 9 regions to know the particular region where the spot lies to avoid overlapping with noise, and so on. The proposed method will generate the information regarding in which region the spot lies, based on nine regions in each frame. From the generated results we have made some classification regarding data collection techniques, efficiency, time and speed. In this report, extensive experiments using image sequences from particular camera are reported and the experiments were done using intelligent vehicle as well as test vehicle and the results shows that we have achieved 95% success in identifying the spots when we use video as it is, in other method were we can skip some frames in pre-processing to increase the speed of video but the segmentation results we reduced to 85% and the time was very less compared to previous one. This shows the validity of proposed method in identification of spots lying on wooden railway sleepers where we can compromise between time and efficiency to get the desired result.

Can therapy dogs evoke awareness of one's past and present life in persons with Alzheimer's disease?

BACKGROUND: Persons with Alzheimer's disease (AD) sometimes express themselves through behaviours that are difficult to manage for themselves and their caregivers, and to minimise these symptoms alternative methods are recommended. For some time now, animals have been introduced in different ways into the environment of persons with dementia. Animal-Assisted Therapy (AAT) includes prescribed therapy dogs visiting the person with dementia for a specific purpose. AIM: This study aims to illuminate the meaning of the lived experience of encounters with a therapy dog for persons with Alzheimer's disease. METHOD: Video recorded sessions were conducted for each visit of the dog and its handler to a person with AD (10 times/person). The observations have a life-world approach and were transcribed and analysed using a phenomenological hermeneutical approach. RESULTS: The result shows a main theme 'Being aware of one's past and present existence', meaning to connect with one's senses and memories and to reflect upon these with the dog. The time spent with the dog shows the person recounting memories and feelings, and enables an opportunity to reach the person on a cognitive level. CONCLUSIONS: The present study may contribute to health care research and provide knowledge about the use of trained therapy dogs in the care of older persons with AD in a way that might increase quality of life and well-being in persons with dementia. IMPLICATIONS FOR PRACTICE: The study might be useful for caregivers and dog handlers in the care of older persons with dementia.