39 resultados para stream processing crowdsensing scheduling traffic analysis


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Transportation of fluids is one of the most common and energy intensive processes in the industrial and HVAC sectors. Pumping systems are frequently subject to engineering malpractice when dimensioned, which can lead to poor operational efficiency. Moreover, pump monitoring requires dedicated measuring equipment, which imply costly investments. Inefficient pump operation and improper maintenance can increase energy costs substantially and even lead to pump failure. A centrifugal pump is commonly driven by an induction motor. Driving the induction motor with a frequency converter can diminish energy consumption in pump drives and provide better control of a process. In addition, induction machine signals can also be estimated by modern frequency converters, dispensing with the use of sensors. If the estimates are accurate enough, a pump can be modelled and integrated into the frequency converter control scheme. This can open the possibility of joint motor and pump monitoring and diagnostics, thereby allowing the detection of reliability-reducing operating states that can lead to additional maintenance costs. The goal of this work is to study the accuracy of rotational speed, torque and shaft power estimates calculated by a frequency converter. Laboratory tests were performed in order to observe estimate behaviour in both steady-state and transient operation. An induction machine driven by a vector-controlled frequency converter, coupled with another induction machine acting as load was used in the tests. The estimated quantities were obtained through the frequency converter’s Trend Recorder software. A high-precision, HBM T12 torque-speed transducer was used to measure the actual values of the aforementioned variables. The effect of the flux optimization energy saving feature on the estimate quality was also studied. A processing function was developed in MATLAB for comparison of the obtained data. The obtained results confirm the suitability of this particular converter to provide accurate enough estimates for pumping applications.

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Chaotic behaviour is one of the hardest problems that can happen in nonlinear dynamical systems with severe nonlinearities. It makes the system's responses unpredictable. It makes the system's responses to behave similar to noise. In some applications it should be avoided. One of the approaches to detect the chaotic behaviour is nding the Lyapunov exponent through examining the dynamical equation of the system. It needs a model of the system. The goal of this study is the diagnosis of chaotic behaviour by just exploring the data (signal) without using any dynamical model of the system. In this work two methods are tested on the time series data collected from AMB (Active Magnetic Bearing) system sensors. The rst method is used to nd the largest Lyapunov exponent by Rosenstein method. The second method is a 0-1 test for identifying chaotic behaviour. These two methods are used to detect if the data is chaotic. By using Rosenstein method it is needed to nd the minimum embedding dimension. To nd the minimum embedding dimension Cao method is used. Cao method does not give just the minimum embedding dimension, it also gives the order of the nonlinear dynamical equation of the system and also it shows how the system's signals are corrupted with noise. At the end of this research a test called runs test is introduced to show that the data is not excessively noisy.

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Ion mobility spectrometry (IMS) is a straightforward, low cost method for fast and sensitive determination of organic and inorganic analytes. Originally this portable technique was applied to the determination of gas phase compounds in security and military use. Nowadays, IMS has received increasing attention in environmental and biological analysis, and in food quality determination. This thesis consists of literature review of suitable sample preparation and introduction methods for liquid matrices applicable to IMS from its early development stages to date. Thermal desorption, solid phase microextraction (SPME) and membrane extraction were examined in experimental investigations of hazardous aquatic pollutants and potential pollutants. Also the effect of different natural waters on the extraction efficiency was studied, and the utilised IMS data processing methods are discussed. Parameters such as extraction and desorption temperatures, extraction time, SPME fibre depth, SPME fibre type and salt addition were examined for the studied sample preparation and introduction methods. The observed critical parameters were extracting material and temperature. The extraction methods showed time and cost effectiveness because sampling could be performed in single step procedures and from different natural water matrices within a few minutes. Based on these experimental and theoretical studies, the most suitable method to test in the automated monitoring system is membrane extraction. In future an IMS based early warning system for monitoring water pollutants could ensure the safe supply of drinking water. IMS can also be utilised for monitoring natural waters in cases of environmental leakage or chemical accidents. When combined with sophisticated sample introduction methods, IMS possesses the potential for both on-line and on-site identification of analytes in different water matrices.

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Ionic liquids, ILs, have recently been studied with accelerating interest to be used for a deconstruction/fractionation, dissolution or pretreatment processing method of lignocellulosic biomass. ILs are usually utilized combined with heat. Regarding lignocellulosic recalcitrance toward fractionation and IL utilization, most of the studies concern IL utilization in the biomass fermentation process prior to the enzymatic hydrolysis step. It has been demonstrated that IL-pretreatment gives more efficient hydrolysis of the biomass polysaccharides than enzymatic hydrolysis alone. Both cellulose (especially cellulose) and lignin are very resistant towards fractionation and even dissolution methods. As an example, it can be mentioned that softwood, hardwood and grass-type plant species have different types of lignin structures leading to the fact that softwood lignin (guaiacyl lignin dominates) is the most difficult to solubilize or chemically disrupt. In addition to the known conventional biomass processing methods, several ILs have also been found to efficiently dissolve either cellulose and/or wood samples – different ILs are suitable for different purposes. An IL treatment of wood usually results in non-fibrous pulp, where lignin is not efficiently separated and wood components are selectively precipitated, as cellulose is not soluble or degradable in ionic liquids under mild conditions. Nevertheless, new ILs capable of rather good fractionation performance have recently emerged. The capability of the IL to dissolve or deconstruct wood or cellulose depends on several factors, (e.g. sample origin, the particle size of the biomass, mechanical treatments as pulverization, initial biomassto-IL ratio, water content of the biomass, possible impurities of IL, reaction conditions, temperature etc). The aim of this study was to obtain (fermentable) saccharides and other valuable chemicals from wood by a combined heat and IL-treatment. Thermal treatments alone contribute to the degradation of polysaccharides (e.g. 150 °C alone is said to cause the degradation of polysaccharides), thus temperatures below that should be used, if the research interest lies on the IL effectiveness. On the other hand, the efficiency of the IL-treatment can also be enhanced to combine other treatment methods, (e.g. microwave heating). The samples of spruce, pine and birch sawdust were treated with either 1-Ethyl-3-methylimidazolium chloride, Emim Cl, or 1-Ethyl-3-methylimidazolium acetate, Emim Ac, (or with ionized water for comparison) at various temperatures (where focus was between 80 and 120 °C). The samples were withdrawn at fixed time intervals (the main interest treatment time area lied between 0 and 100 hours). Double experiments were executed. The selected mono- and disaccharides, as well as their known degradation products, 5-hydroxymethylfurfural, 5-HMF, and furfural were analyzed with capillary electrophoresis, CE, and high-performance liquid chromatography, HPLC. Initially, even GC and GC-MS were utilized. Galactose, glucose, mannose and xylose were the main monosaccharides that were present in the wood samples exposed to ILs at elevated temperatures; in addition, furfural and 5-HMF were detected; moreover, the quantitative amount of the two latter ones were naturally increasing in line with the heating time or the IL:wood ratio.

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The amount of biological data has grown exponentially in recent decades. Modern biotechnologies, such as microarrays and next-generation sequencing, are capable to produce massive amounts of biomedical data in a single experiment. As the amount of the data is rapidly growing there is an urgent need for reliable computational methods for analyzing and visualizing it. This thesis addresses this need by studying how to efficiently and reliably analyze and visualize high-dimensional data, especially that obtained from gene expression microarray experiments. First, we will study the ways to improve the quality of microarray data by replacing (imputing) the missing data entries with the estimated values for these entries. Missing value imputation is a method which is commonly used to make the original incomplete data complete, thus making it easier to be analyzed with statistical and computational methods. Our novel approach was to use curated external biological information as a guide for the missing value imputation. Secondly, we studied the effect of missing value imputation on the downstream data analysis methods like clustering. We compared multiple recent imputation algorithms against 8 publicly available microarray data sets. It was observed that the missing value imputation indeed is a rational way to improve the quality of biological data. The research revealed differences between the clustering results obtained with different imputation methods. On most data sets, the simple and fast k-NN imputation was good enough, but there were also needs for more advanced imputation methods, such as Bayesian Principal Component Algorithm (BPCA). Finally, we studied the visualization of biological network data. Biological interaction networks are examples of the outcome of multiple biological experiments such as using the gene microarray techniques. Such networks are typically very large and highly connected, thus there is a need for fast algorithms for producing visually pleasant layouts. A computationally efficient way to produce layouts of large biological interaction networks was developed. The algorithm uses multilevel optimization within the regular force directed graph layout algorithm.

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This paper describes the development situation of biofuel in China and the research progress and application in transportation and aviation area, including several key technologies of biofuel production: biofuel pretreatment and handling. This paper is aiming to find the best storing, transmitting, feeding and pretreating methods of various materials, as well as a comparison among the advantages and disadvantages of different pretreatment methods, which is expected to reduce cost in production process and reach the maximized benefits. Meanwhile, a case study of one biomass fuel production factory in China is presented with evaluation and analysis on their technology application.

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This doctoral study conducts an empirical analysis of the impact of Word-of-Mouth (WOM) on marketing-relevant outcomes such as attitudes and consumer choice, during a high-involvement and complex service decision. Due to its importance to decisionmaking, WOM has attracted interest from academia and practitioners for decades. Consumers are known to discuss products and services with one another. These discussions help consumers to form an evaluative opinion, as WOM reduces perceived risk, simplifies complexity, and increases the confidence of consumers in decisionmaking. These discussions are also highly impactful as WOM is a trustworthy source of information, since it is independent from the company or brand. In responding to the calls for more research on what happens after WOM information is received, and how it affects marketing-relevant outcomes, this dissertation extends prior WOM literature by investigating how consumers process information in a highinvolvement service domain, in particular higher-education. Further, the dissertation studies how the form of WOM influences consumer choice. The research contributes to WOM and services marketing literature by developing and empirically testing a framework for information processing and studying the long-term effects of WOM. The results of the dissertation are presented in five research publications. The publications are based on longitudinal data. The research leads to the development of a proposed theoretical framework for the processing of WOM, based on theories from social psychology. The framework is specifically focused on service decisions, as it takes into account evaluation difficulty through the complex nature of choice criteria associated with service purchase decisions. Further, other gaps in current WOM literature are taken into account by, for example, examining how the source of WOM and service values affects the processing mechanism. The research also provides implications for managers aiming to trigger favorable WOM through marketing efforts, such as advertising and testimonials. The results provide suggestions on how to design these marketing efforts by taking into account the mechanism through which information is processed, or the form of social influence.

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This thesis is the Logistics Development Forum's assignment and the work dealing with the development of the Port of Helsinki as part of Helsinki hub. The Forum aims to develop logistics efficiency through public-private co-operation and development of the port is clearly dependent on both factors. Freight volumes in the Port of Helsinki are the biggest single factor in hub and, therefore, the role of the port of the entire hub development is strong. The aim is to look at how the port will develop as a result of changes in the foreign trade of Finland and the Northern European logistics trends in 25 years time period. Work includes the current state analysis and scenario work. The analyses are intended to find out, which trends are the most important in the port volume development. The change and effect of trends is examined through scenarios based on current state. Based on the work, the structure of Finnish export industry and international demand are in the key role in the port volume development. There is significant difference between demands of Finnish exporting products in different export markets and the development between the markets has different impacts on the port volumes by mass and cargo type. On the other hand, the Finnish economy is stuck in a prolonged recession and competition between ports has become a significant factor in the individual port's volume development. Ecological valuesand regulations have changed the competitive landscape and maritime transport emissions reductions has become an important competitive factor for short routes in the Baltic Sea, such as in the link between Helsinki and Tallinn.

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Operational excellence of individual tramp shipping companies is important in today’s market, where competition is intense, freight revenues are modest and capital costs high due to global financial crisis, and tighter regulatory framework is generating additional costs and challenges to the industry. This thesis concentrates on tramp shipping, where a tramp operator in a form of an individual case company, specialized in short-sea shipping activities in the Baltic Sea region, is searching ways to map their current fleet operations and better understand potential ways to improve the overall routing and scheduling decisions. The research problem is related to tramp fleet planning where several cargoes are carried on board at the same time, which are here systematically referred to as part cargoes. The purpose is to determine the pivotal dimensions and characteristics of these part cargo operations in tramp shipping, and offer both the individual case company and wider research community better understanding of potential risks and benefits related to utilization of part cargo operations. A mixed method research approach is utilized in this research, as the objectives are related to complex, real-life business practices in the field of supply chain management and more specifically, maritime logistics. A quantitative analysis of different voyage scenarios is executed, including alternative voyage legs with varying cost structure and customer involvement. An on-line-based questionnaire designed and prepared by case company’s decision group again provides desired data of predominant attitudes and views of most important industrial customers regarding the part cargo-related operations and potential future utilization of this business model. The results gained from these quantitative methods are complied with qualitative data collection tools, along with suitable secondary data sources. Based on results and logical analysis of different data sources, a framework for characterizing the different aspects of part cargo operations is developed, utilizing both existing research and empirical investigation of the phenomenon. As conclusions, part cargoes have the ability to be part of viable fleet operations, and even increase flexibility among the fleet to a certain extent. Naturally, several hinderers for this development is recognized as well, such as potential issues with information gathering and sharing, inefficient port activities, and increased transit times.