Nonstationary feature extraction techniques for automatic classification of impact acoustic signals

Condition monitoring of wooden railway sleepers applications are generallycarried out by visual inspection and if necessary some impact acoustic examination iscarried out intuitively by skilled personnel. In this work, a pattern recognition solutionhas been proposed to automate the process for the achievement of robust results. Thestudy presents a comparison of several pattern recognition techniques together withvarious nonstationary feature extraction techniques for classification of impactacoustic emissions. Pattern classifiers such as multilayer perceptron, learning cectorquantization and gaussian mixture models, are combined with nonstationary featureextraction techniques such as Short Time Fourier Transform, Continuous WaveletTransform, Discrete Wavelet Transform and Wigner-Ville Distribution. Due to thepresence of several different feature extraction and classification technqies, datafusion has been investigated. Data fusion in the current case has mainly beeninvestigated on two levels, feature level and classifier level respectively. Fusion at thefeature level demonstrated best results with an overall accuracy of 82% whencompared to the human operator.

Characters Extraction for Traffic Sign Destination boards in video and still images

Traffic Control Signs or destination boards on roadways offer significant information for drivers. Regulation signs tell something like your speed, turns, etc; Warning signs warn drivers of conditions ahead to help them avoid accidents; Destination signs show distances and directions to various locations; Service signs display location of hospitals, gas and rest areas etc. Because the signs are so important and there is always a certain distance from them to drivers, to let the drivers get information clearly and easily even in bad weather or other situations. The idea is to develop software which can collect useful information from a special camera which is mounted in the front of a moving car to extract the important information and finally show it to the drivers. For example, when a frame contains on a destination drive sign board it will be text something like "Linkoping 50",so the software should extract every character of "Linkoping 50", compare them with the already known character data in the database. if there is extracted character match "k" in the database then output the destination name and show to the driver. In this project C++ will be used to write the code for this software.

Identification of cause of impairment in spiral drawings, using non-stationary feature extraction approach

Parkinson’s disease is a clinical syndrome manifesting with slowness and instability. As it is a progressive disease with varying symptoms, repeated assessments are necessary to determine the outcome of treatment changes in the patient. In the recent past, a computer-based method was developed to rate impairment in spiral drawings. The downside of this method is that it cannot separate the bradykinetic and dyskinetic spiral drawings. This work intends to construct the computer method which can overcome this weakness by using the Hilbert-Huang Transform (HHT) of tangential velocity. The work is done under supervised learning, so a target class is used which is acquired from a neurologist using a web interface. After reducing the dimension of HHT features by using PCA, classification is performed. C4.5 classifier is used to perform the classification. Results of the classification are close to random guessing which shows that the computer method is unsuccessful in assessing the cause of drawing impairment in spirals when evaluated against human ratings. One promising reason is that there is no difference between the two classes of spiral drawings. Displaying patients self ratings along with the spirals in the web application is another possible reason for this, as the neurologist may have relied too much on this in his own ratings.

Factors influencing tourism sustainability : The case of the World Heritage Falun Great Copper Mountain

This thesis focuses on identifying hindrances of achieving a sustainable tourism development on a base of a World Heritage Site. Using a case study of the World Heritage Site Falun Great Copper Mountain, the thesis assesses the situational context by using qualitative methods. Five semi- structured interviews with influential stakeholders were conducted to get an inside view of the current situation and to identify site-specific issues. The thesis identifies a number of factors that determine the successful implementation of measures leading towards sustainable tourism in the long-run; the most important being the lack of clear guidelines for the whole destination and no holistic planning approach within the municipality. The thesis concludes that despite the increased pressures towards establishment of sustainable tourism, the concept remains challenging to operationalize for the World Heritage Site without frameworks and tools from UNESCO.

Dichlorvos exposure impedes extraction and amplification of DNA from insects in museum collections

Background: The insecticides dichlorvos, paradichlorobenzene and naphthalene have been commonly used to eradicate pest insects from natural history collections. However, it is not known how these chemicals affect the DNA of the specimens in the collections. We thus tested the effect of dichlorvos, paradichlorobenzene and naphthalene on DNA of insects (Musca domestica) by extracting and amplifying DNA from specimens exposed to insecticides in two different concentrations over increasing time intervals. Results: The results clearly show that dichlorvos impedes both extraction and amplification of mitochondrial and nuclear DNA after relatively short time, whereas paradichlorobenzene and naphthalene do not. Conclusion: Collections treated with paradichlorobenzene and naphthalene, are better preserved concerning DNA, than those treated with dichlorvos. Non toxic pest control methods should, however, be preferred due to physical damage of specimens and putative health risks by chemicals.

Replacing Finned Copper withCorrugated Stainless Steel, forthe Heat Exchangers of a SolarCombisystem Store : Performance and EconomicEvaluation

The importance of investigating cost reduction in materials and components for solar thermal systems is crucial at the present time. This work focuses on the influence of two different heat exchangers on the performance of a solar thermal system. Both heat exchangers studied are immersed helically coiled, one made with corrugated stainless steel tube, and the other made with finned copper tube with smooth inner surface.A test apparatus has been designed and a simple test procedure applied in order to study heat transfer characteristics and pressure drop of both coils. Thereafter, the resulting experimental data was used to perform a parameter identification of the heat exchangers, in order to obtain a TRNSYS model with its corresponding numerical expression. Also a representative small-scale combisystem model was designed in TRNSYS, in order to study the influence of both heat exchangers on the solar fraction of the system, when working at different flow rates.It has been found that the highest solar fraction is given by the corrugated stainless steel coil, when it works at the lowest flow rate (100 l/hr). For any higher flow rate, the studied copper coil presents a higher solar fraction. The advantageous low flow performance of stainless steel heat exchanger turns out to be beneficial for the particular case of solar thermal systems, where it is well known that low flow collector loops lead to enhanced store stratification, and consequently higher solar fractions.Finally, an optimization of the stainless steel heat exchanger length is carried out, according to economic figures. For the given combisystem model and boundary conditions, the optimum length value is found between 10 and 12 m.