5 resultados para process parameter monitoring

em Dalarna University College Electronic Archive


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This paper addresses the two opposing extremes of standardisation in franchising and the dynamics of sales in search of a juncture point in order to reduce franchisees’ uncertainties in sales and improve sales performance. A conceptual framework is developed based on both theory and practice in order to investigate the sales process of a specific franchise network. The research is conducted over a period of six weeks in form of a customised sales report considering the sales funnel concept and performance indicators along the sales process. The received quantitative data is analysed through descriptive statistics and logistic regressions in respect to what variations in the sales process can be discovered and what practices yield higher performance. The results indicate an advantage of a prioritisation guideline regarding the activities and choices to make as a salesperson over strict standardisation. Defining the sales funnel plus engaging in the process of monitoring sales in itself has proven to be a way of reducing uncertainty as the franchisor and franchisees alike inherently gain a greater understanding of the process. The extended knowledge gained from this research allowed for both practical as well as theoretical implications and expands the knowledge on standardisation of sales and the appropriateness of the sales funnel and its management for dealing with the dilemma between standardisation and flexibility of sales in franchising contexts.

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Hybrid Photovoltaic Thermal (PVT) collectors are an emerging technology that combines PV and solar thermal systems in a single solar collector producing heat and electricity simultaneously. The focus of this thesis work is to evaluate the performance of unglazed open loop PVT air system integrated on a garage roof in Borlänge. As it is thought to have a significant potential for preheating ventilation of the building and improving the PV modules electrical efficiency. The performance evaluation is important to optimize the cooling strategy of the collector in order to enhance its electrical efficiency and maximize the production of thermal energy. The evaluation process involves monitoring the electrical and thermal energies for a certain period of time and investigating the cooling effect on the performance through controlling the air mass flow provided by a variable speed fan connected to the collector by an air distribution duct. The distribution duct transfers the heated outlet air from the collector to inside the building. The PVT air collector consists of 34 Solibro CIGS type PV modules (115 Wp for each module) which are roof integrated and have replaced the traditional roof material. The collector is oriented toward the south-west with a tilt of 29 ᵒ. The collector consists of 17 parallel air ducts formed between the PV modules and the insulated roof surface. Each air duct has a depth of 0.05 m, length of 2.38 m and width of 2.38 m. The air ducts are connected to each other through holes. The monitoring system is based on using T-type thermocouples to measure the relevant temperatures, air sensor to measure the air mass flow. These parameters are needed to calculate the thermal energy. The monitoring system contains also voltage dividers to measure the PV modules voltage and shunt resistance to measure the PV current, and AC energy meters which are needed to calculate the produced electrical energy. All signals recorded from the thermocouples, voltage dividers and shunt resistances are connected to data loggers. The strategy of cooling in this work was based on switching the fan on, only when the difference between the air duct temperature (under the middle of top of PV column) and the room temperature becomes higher than 5 °C. This strategy was effective in term of avoiding high electrical consumption by the fan, and it is recommended for further development. The temperature difference of 5 °C is the minimum value to compensate the heat losses in the collecting duct and distribution duct. The PVT air collector has an area of (Ac=32 m2), and air mass flow of 0.002 kg/s m2. The nominal output power of the collector is 4 kWppv (34 CIGS modules with 115 Wppvfor each module). The collector produces thermal output energy of 6.88 kWth/day (0.21 kWth/m2 day) and an electrical output energy of 13.46 kWhel/day (0.42 kWhel/m2 day) with cooling case. The PVT air collector has a daily thermal energy yield of 1.72 kWhth/kWppv, and a daily PV electrical energy yield of 3.36 kWhel /kWppv. The fan energy requirement in this case was 0.18 kWh/day which is very small compared to the electrical energy generated by the PV collector. The obtained thermal efficiency was 8 % which is small compared to the results reported in literature for PVT air collectors. The small thermal efficiency was due to small operating air mass flow. Therefore, the study suggests increasing the air mass flow by a factor of 25. The electrical efficiency was fluctuating around 14 %, which is higher than the theoretical efficiency of the PV modules, and this discrepancy was due to the poor method of recording the solar irradiance in the location. Due to shading effect, it was better to use more than one pyranometer.

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A challenge for the clinical management of Parkinson's disease (PD) is the large within- and between-patient variability in symptom profiles as well as the emergence of motor complications which represent a significant source of disability in patients. This thesis deals with the development and evaluation of methods and systems for supporting the management of PD by using repeated measures, consisting of subjective assessments of symptoms and objective assessments of motor function through fine motor tests (spirography and tapping), collected by means of a telemetry touch screen device. One aim of the thesis was to develop methods for objective quantification and analysis of the severity of motor impairments being represented in spiral drawings and tapping results. This was accomplished by first quantifying the digitized movement data with time series analysis and then using them in data-driven modelling for automating the process of assessment of symptom severity. The objective measures were then analysed with respect to subjective assessments of motor conditions. Another aim was to develop a method for providing comparable information content as clinical rating scales by combining subjective and objective measures into composite scores, using time series analysis and data-driven methods. The scores represent six symptom dimensions and an overall test score for reflecting the global health condition of the patient. In addition, the thesis presents the development of a web-based system for providing a visual representation of symptoms over time allowing clinicians to remotely monitor the symptom profiles of their patients. The quality of the methods was assessed by reporting different metrics of validity, reliability and sensitivity to treatment interventions and natural PD progression over time. Results from two studies demonstrated that the methods developed for the fine motor tests had good metrics indicating that they are appropriate to quantitatively and objectively assess the severity of motor impairments of PD patients. The fine motor tests captured different symptoms; spiral drawing impairment and tapping accuracy related to dyskinesias (involuntary movements) whereas tapping speed related to bradykinesia (slowness of movements). A longitudinal data analysis indicated that the six symptom dimensions and the overall test score contained important elements of information of the clinical scales and can be used to measure effects of PD treatment interventions and disease progression. A usability evaluation of the web-based system showed that the information presented in the system was comparable to qualitative clinical observations and the system was recognized as a tool that will assist in the management of patients.

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Vegetation growing on railway trackbeds and embankments present potential problems. The presence of vegetation threatens the safety of personnel inspecting the railway infrastructure. In addition vegetation growth clogs the ballast and results in inadequate track drainage which in turn could lead to the collapse of the railway embankment. Assessing vegetation within the realm of railway maintenance is mainly carried out manually by making visual inspections along the track. This is done either on-site or by watching videos recorded by maintenance vehicles mainly operated by the national railway administrative body. A need for the automated detection and characterisation of vegetation on railways (a subset of vegetation control/management) has been identified in collaboration with local railway maintenance subcontractors and Trafikverket, the Swedish Transport Administration (STA). The latter is responsible for long-term planning of the transport system for all types of traffic, as well as for the building, operation and maintenance of public roads and railways. The purpose of this research project was to investigate how vegetation can be measured and quantified by human raters and how machine vision can automate the same process. Data were acquired at railway trackbeds and embankments during field measurement experiments. All field data (such as images) in this thesis work was acquired on operational, lightly trafficked railway tracks, mostly trafficked by goods trains. Data were also generated by letting (human) raters conduct visual estimates of plant cover and/or count the number of plants, either on-site or in-house by making visual estimates of the images acquired from the field experiments. Later, the degree of reliability of(human) raters’ visual estimates were investigated and compared against machine vision algorithms. The overall results of the investigations involving human raters showed inconsistency in their estimates, and are therefore unreliable. As a result of the exploration of machine vision, computational methods and algorithms enabling automatic detection and characterisation of vegetation along railways were developed. The results achieved in the current work have shown that the use of image data for detecting vegetation is indeed possible and that such results could form the base for decisions regarding vegetation control. The performance of the machine vision algorithm which quantifies the vegetation cover was able to process 98% of the im-age data. Investigations of classifying plants from images were conducted in in order to recognise the specie. The classification rate accuracy was 95%.Objective measurements such as the ones proposed in thesis offers easy access to the measurements to all the involved parties and makes the subcontracting process easier i.e., both the subcontractors and the national railway administration are given the same reference framework concerning vegetation before signing a contract, which can then be crosschecked post maintenance.A very important issue which comes with an increasing ability to recognise species is the maintenance of biological diversity. Biological diversity along the trackbeds and embankments can be mapped, and maintained, through better and robust monitoring procedures. Continuously monitoring the state of vegetation along railways is highly recommended in order to identify a need for maintenance actions, and in addition to keep track of biodiversity. The computational methods or algorithms developed form the foundation of an automatic inspection system capable of objectively supporting manual inspections, or replacing manual inspections.

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BACKGROUND: The recently developed Context Assessment for Community Health (COACH) tool aims to measure aspects of the local healthcare context perceived to influence knowledge translation in low- and middle-income countries. The tool measures eight dimensions (organizational resources, community engagement, monitoring services for action, sources of knowledge, commitment to work, work culture, leadership, and informal payment) through 49 items. OBJECTIVE: The study aimed to explore the understanding and stability of the COACH tool among health providers in Vietnam. DESIGNS: To investigate the response process, think-aloud interviews were undertaken with five community health workers, six nurses and midwives, and five physicians. Identified problems were classified according to Conrad and Blair's taxonomy and grouped according to an estimation of the magnitude of the problem's effect on the response data. Further, the stability of the tool was examined using a test-retest survey among 77 respondents. The reliability was analyzed for items (intraclass correlation coefficient (ICC) and percent agreement) and dimensions (ICC and Bland-Altman plots). RESULTS: In general, the think-aloud interviews revealed that the COACH tool was perceived as clear, well organized, and easy to answer. Most items were understood as intended. However, seven prominent problems in the items were identified and the content of three dimensions was perceived to be of a sensitive nature. In the test-retest survey, two-thirds of the items and seven of eight dimensions were found to have an ICC agreement ranging from moderate to substantial (0.5-0.7), demonstrating that the instrument has an acceptable level of stability. CONCLUSIONS: This study provides evidence that the Vietnamese translation of the COACH tool is generally perceived to be clear and easy to understand and has acceptable stability. There is, however, a need to rephrase and add generic examples to clarify some items and to further review items with low ICC.