In wireless location systems, received signals may be influenced by non-line of sight (NLOS) propagation errors, which yield severe degradation of location accuracy.Therefore, to distinguish how many measurement signals are line-of-sight (LOS) and to identify them simultaneously will contribute to the increase of location accuracy.We propose a method based on recursive hypothesis testing algorithm, and use residual information to determine whether the NLOS errors are present in measurements. Since the probability distribution of measurements with NLOS errors is different from that of measurements without NLOS errors, a likelihood ratio test can be used in determining the LOS/NLOS status of the measurements. To search for an optimal threshold for the hypothesis testing, particle filtering optimization(PFO) is adopted. The PFO algorithm uses particle filtering to find the best threshold for determining the status of signals measured at all base stations (BSs). In the PFO algorithm, the clustering property of K-means is also used in separating particles, thereby the search of optimal threshold may be implemented in parallel.In this thesis, we focus on the hybrid TOA/AOA (time of arrical/angle of arrival) location method, in which localization only uses the LOS location measurements to calculate the location of a mobile station. Simulation results show that the proposed algorithm performs better than other algorithms which suffer from different degrees of NLOS errors. The proposed scheme also obtains higher identification rate of LOS-BSs in different situations by using the optimal thresholds for status detection.

Feature selection is an important pre-processing step in mining and learning. A good set of features can not only improve the accuracy of classification, but also reduce the time to derive rules. It is executed especially when the amount of attributes in a given training data is very large. This thesis thus proposes three GA-based clustering methods for attribute clustering and feature selection. In the first method, each feasible clustering result is encoded into a chromosome with positive integers and a gene in the chromosome is for an attribute. The value of a gene represents the cluster to which the attribute belongs. The fitness of each individual is evaluated using both the average accuracy of attribute substitutions in clusters and the cluster balance. The second method further extends the first method to improve the time performance. A new fitness function based on both the accuracy and the attribute dependency is proposed. It can reduce the time of scanning the data base. The third approach uses another encoding method for representing chromosomes. It can achieve a faster convergence and a better result than the second one. At last, the experimental comparison with the k-means clustering approach and with all combinations of attributes also shows the proposed approach can get a good trade-off between accuracy and time complexity. Besides, after feature selection, the rules derived from only the selected features may usually be hard to use if some values of the selected features cannot be obtained in current environments. This problem can be easily solved in our proposed approaches. The attributes with missing values can be replaced by other attributes in the same clusters. The proposed approaches thus provide flexible alternatives for feature selection.

<p>Trust is a major challenge to the consumer acceptance of e-commerce: the lack of trust is an important reason for the hesitant growth in e-commerce and for the reluctance of consumers to engage in online buying transaction. Communicating trustworthiness is therefore a major challenge companies encounter. This study concentrates on the various means communicating trustworthiness proposed by researchers. An overview of means is presented according to a buying transaction process life cycle spanning the four phases information, agreement, handling, and postpurchase. Besides enabling the categorization of the various means to develop consumer trust, the four phases in addition illuminate the dynamic aspect of trust development and allow the introduction of a simple measure to determine success in the domain of e-commerce by evaluating the repetitiveness of consumer transacting with the e-vendor. A web site analysis was conducted to evaluate the trust means usage in practice. The findings of the web site analysis indicate three general trends. First, the analyzed web sites hint at an absent exploitation of second and third degree information. Second, the results of the study obtained from the indicators regarding the later phases portray a lack of means usage during the handling and postpurchase phase. Third, the web site analysis points out multiple possibilities for e-vendors to adjust, improve, and implement additional trust means. In general, the discovered trends are an indication for e-vendors to adopt their strategies to employ trust means towards the relevant consumer perspective of the company.</p>

A new ensemble method for cluster analysis is introduced, which can be interpreted in two different ways: As complexity-reducing preprocessing stage for hierarchical clustering and as combination procedure for several partitioning results. The basic idea is to locate and combine structurally stable cluster centers and/or prototypes. Random effects of the training set are reduced by repeatedly training on resampled sets (bootstrap samples). We discuss the algorithm both from a more theoretical and an applied point of view and demonstrate it on several data sets. (author's abstract) / Series: Working Papers SFB "Adaptive Information Systems and Modelling in Economics and Management Science"

No description available.

No description available.

No description available.

This research extends fuzzy methods to consider the fuzzy validation of fuzzy land cover data at the sub-pixel level. The study analyses the relationships between fuzzy memberships generated by field survey and those generated from the classification of remotely sensed data. In so doing it examines the variations in the relationship between observed and predicted fuzzy land cover classes. This research applies three land cover classification techniques: Fuzzy sets, Fuzzy c-means and Boolean classification, and develops three models to determine fuzzy land cover change. The first model is dependent on fuzzy object change. The second model depends on the sub-pixel change through a fuzzy change matrix, for both fuzzy sets and fuzzy c-means, to compute the fuzzy change, fuzzy loss and fuzzy gain. The third model is a Boolean change model which evaluates change on a pixel-by-pixel basis. The results show that using a fuzzy change analysis presents a subtle way of mapping a heterogeneous area with common mixed pixels. Furthermore, the results show that the fuzzy change matrix gives more detail and information about land cover change and is more appropriate than fuzzy object change because it deals with sub-pixel change. Finally the research has found that a fuzzy error matrix is more suitable than an error matrix for soft classification validation because it can compare the membership from the field with the classified image. From this research there arise some important points: • Fuzzy methodologies have the ability to define the uncertainties associated with describing the phenomenon itself and the ability to take into consideration the effect of mixed pixels. • This research compared fuzzy sets and fuzzy c-means, and found the fuzzy set is more suit-able than fuzzy c-means, because the latter suffers from some disadvantages, chiefly that the sum of membership values of a data point in all the clusters must be one, so the algorithm has difficulty in handling outlying points. • This research validates fuzzy classifications by determining the fuzzy memberships in the field and comparing them with the memberships derived from the classified image.

Statusas tarpusavio savybių sistemoje yra labai reikšmingas asmenybę formuojantis veiksnys. Turėdamas tam tikrą statusą, atlikdamas tam tikrą vaidmenį, paauglys mokosi vykdyti visuomenės keliamus reikalavimus.Jeigu aplinkinių sukurtas statusas yra paugliui priimtinas, tai pauglys gerai jaučiasi aplinkoje, gali pilnai save relizuoti. Izoliacijos sukeltos neigiamos emocijos dažnai skatina paauglį nederamai elgtis, o tai sudaro pagrindą formuotis neigiamoms asmenybės savybėms. Problema- mokytojai stokoja kompetencijos socialinių mokinių gebėjimų plėtotei. Tyrimo objektas- socialinė atskirtis paauglių tarpe. Klausimas: Kaip pasireiškia socialiniai ar pedagoginiai veiksniai, nulemiantys moksleivio statusą klasėje? Tikslas: Numatyti prevencines priemones, padedančias išvengti socialinės atskirties. Uždaviniai: 1.Apibendrinti veiksnius, turinčius įtakos moksleivių savijautai klasėje. 2.Įvardyti socialinius ir pedagoginius veiksnius, galinčius turėti poveikį moksleivio statusui klasėje. 3.Atpažinti moksleivių pasiskirstymą pagal statusą konkrečioje klasėje. 4.Įvardyti prevencines priemones, galinčias padėti mokiniui išvengti socialinės atskirties Išvados: Remiantis gautais tyrimo rezultatais galiu teigti, kad socialinės atskirties mokinių atsiradimą mokykloje lemia tiek objektyvios ( ekonominės, socialinės sąlygos), tiek subjektyvios (pedagoginės) sąlygos... [toliau žr. visą tekstą] / The position in a sistem of internal characteristic is a very important factor to forming individuality.A tenager with his / her position and a specific role learns how to accept the society position. If this position is accepted, the teenager is certain in surrounding and he/she is able to realise their personolity.Negative Emotions provocotive with isolation stimulate to behave inappropriate. This inappropriate behaviour forms the resons for negative personal characteristics. Problem: Teachers lock competence to develop students socinl abilities. Research object: Social disjuncture betnveen the teenagers. Qewstion: What do social or educotionl factors determine students‘ position in class. Aime:To understand preventive means, that help to avoid social isolation. Tasks: 1.To sum factors that influnce students feelings at school. 2.To name social and educational factors capable to bring influence students positions in class. 3.To recognize students grouping according to the position in class. 4.To name preventive means that help to avoid the social isolation. Conclusions: Mointain with the received research results that teenagers social isoletion origins determine objective( economical, social conditions) and subjective (education) conditions. Whereas they show that isoloted persons exist between teenagers... [to full text]

Peanut (Arachis hypogaea L.) has the potential to become a major source of biodiesel but for market viability, peanut oil yields must increase and specific quality requirements must be met. Oil yield in peanut is influenced by many components, including oil concentration, seed mass, and mean oil produced per seed. All of these traits can be improved through selection as long as there is sufficient genetic variation. Thus, elucidating the genetics of oil concentration, seed mass, and mean oil produced per seed in peanut is essential to advancing the development of genotypes with high oil yields. Additive genetic effects were predominant for oil concentration in two generation means analyses involving a proprietary high oil breeding line and additive genetic variance was highly significant in a complete four-parent diallel analysis. Genetic variance for weight of 50 sound mature kernels (50 SMK) and mean oil produced per SMK (OPS) was additive the diallel analysis. Narrow-sense heritability estimates were high for oil concentration in both the diallel and generation means analyses. Narrow-sense heritability was also high for 50 SMK, but was low for OPS. The low OPS heritability estimate was caused by the negative correlation between oil concentration and seed mass. Consequently, oil concentration and seed mass can be improved through early-generation selection, but large segregating populations from high oil crosses will be needed to identify progeny with elevated oil concentrations that maintain acceptable seed sizes. Increasing the ratio of oleic to linoleic acid (O/L) in peanut oil and reducing the long chain saturated fatty acid concentration (which includes arachidic, behenic, and lignoceric acids) produces high quality, stable methyl esters for biodiesel. Therefore, elucidating the inheritance of these factors and their relationships in peanut populations segregating for high oil is critical. The results from generation means analysis confirm that the high-oleic trait is under simple genetic control and can be manipulated through selection. Oil concentration was negatively correlated with oleic acid concentration in the F2 generations of both crosses and positively correlated with arachidic acid in most of the segregating generations that were evaluated. Therefore, developing a peanut genotype high in oil and oleic acid concentration that has reduced long chain saturates will require the evaluation of large numbers of segregating progeny.