The innovation of cotton fiber from recycled cloth as coloring agent for polypropylene via injection moulding

Plastics can be coloured in many different ways. In the present application, the colouring agent that is used in the plastic industries are the dyes and pigments. Both methods are sustantially different and produce specific results. Dyes are defined as colourants that are (completely) soluble in a polymer at the processing temperature. Pigments are organic or inorganic solid particles that are insoluble in polymers..

Investigation related to multispectral imaging systems

A summary of technical progress made during a five year research program directed toward the development of operational information systems based on multispectral sensing and the use of these systems in earth-resource survey applications is presented. Efforts were undertaken during this program to: (1) improve the basic understanding of the many facets of multispectral remote sensing, (2) develop methods for improving the accuracy of information generated by remote sensing systems, (3) improve the efficiency of data processing and information extraction techniques to enhance the cost-effectiveness of remote sensing systems, (4) investigate additional problems having potential remote sensing solutions, and (5) apply the existing and developing technology for specific users and document and transfer that technology to the remote sensing community

Methods of Technical Prognostics Applicable to Embedded Systems

Hlavní cílem dizertace je poskytnutí uceleného pohledu na problematiku technické prognostiky, která nachází uplatnění v tzv. prediktivní údržbě založené na trvalém monitorování zařízení a odhadu úrovně degradace systému či jeho zbývající životnosti a to zejména v oblasti komplexních zařízení a strojů. V současnosti je technická diagnostika poměrně dobře zmapovaná a reálně nasazená na rozdíl od technické prognostiky, která je stále rozvíjejícím se oborem, který ovšem postrádá větší množství reálných aplikaci a navíc ne všechny metody jsou dostatečně přesné a aplikovatelné pro embedded systémy. Dizertační práce přináší přehled základních metod použitelných pro účely predikce zbývající užitné životnosti, jsou zde popsány metriky pomocí, kterých je možné jednotlivé přístupy porovnávat ať už z pohledu přesnosti, ale také i z pohledu výpočetní náročnosti. Jedno z dizertačních jader tvoří doporučení a postup pro výběr vhodné prognostické metody s ohledem na prognostická kritéria. Dalším dizertačním jádrem je představení tzv. částicového filtrovaní (particle filtering) vhodné pro model-based prognostiku s ověřením jejich implementace a porovnáním. Hlavní dizertační jádro reprezentuje případovou studii pro velmi aktuální téma prognostiky Li-Ion baterii s ohledem na trvalé monitorování. Případová studie demonstruje proces prognostiky založené na modelu a srovnává možné přístupy jednak pro odhad doby před vybitím baterie, ale také sleduje možné vlivy na degradaci baterie. Součástí práce je základní ověření modelu Li-Ion baterie a návrh prognostického procesu.The main aim of the thesis is to provide a comprehensive overview of technical prognosis, which is applied in the condition based maintenance, based on continuous device monitoring and remaining useful life estimation, especially in the field of complex equipment and machinery. Nowadays technical prognosis is still evolving discipline with limited number of real applications and is not so well developed as technical diagnostics, which is fairly well mapped and deployed in real systems. Thesis provides an overview of basic methods applicable for prediction of remaining useful life, metrics, which can help to compare the different approaches both in terms of accuracy and in terms of computational/deployment cost. One of the research cores consists of recommendations and guide for selecting the appropriate forecasting method with regard to the prognostic criteria. Second thesis research core provides description and applicability of particle filtering framework suitable for model-based forecasting. Verification of their implementation and comparison is provided. The main research topic of the thesis provides a case study for a very actual Li-Ion battery health monitoring and prognostics with respect to continuous monitoring. The case study demonstrates the prognostic process based on the model and compares the possible approaches for estimating both the runtime and capacity fade. Proposed methodology is verified on real measured data.

System Identification for Nonlinear Control Using Neural Networks

An approach to incorporating artificial neural networks in nonlinear, adaptive control systems is described. The controller contains three principal elements: a nonlinear inverse dynamic control law whose coefficients depend on a comprehensive model of the plant, a neural network that models system dynamics, and a state estimator whose outputs drive the control law and train the neural network. Attention is focused on the system identification task, which combines an extended Kalman filter with generalized spline function approximation. Continual learning is possible during normal operation, without taking the system off line for specialized training. Nonlinear inverse dynamic control requires smooth derivatives as well as function estimates, imposing stringent goals on the approximating technique

Capabilities measurement: an empirical investigation

Sen’s seminal contribution highlights the importance of positive freedom in the measurement of human welfare. The present paper attempts to measure this freedom aspect in an integrated approach. The main contribution of the paper is the simultaneous estimation of capability, functioning, and conversion efficiency with explicit modeling of freedom by latent variable modeling approach. The knowledge dimension of capabilities is modeled and estimated by integrating exploratory and confirmatory statistical methods in a two-stage procedure. In the first stage, Partial Least Squares method is employed to construct latent variable scores. These scores are transformed to relative scores for the sake of comparison and then used to estimate the proposed simultaneous-equation capability model by 3SLS in the second stage. The results show that capability is inversely related to resources and positively related to freedom and functioning. The computed relative capability and freedom inequality ratios are very high whereas relative functioning and efficiency inequality ratios are at a moderate level. The conventional income inequality ratio is lower as compared to the capability dimensions’ ratios and close to the Gini-coefficient. The paper extended the measurement of conversion inefficiency into voluntary and involuntary inefficiency. The paper also suggests criteria for evaluating empirical research within the capability approach framework. The paper recommends development of specific survey instruments in order to create better indicators for capability dimensions and use of latent variable modeling for constructing latent variable scores, and their subsequent use in estimation. These findings suggest a capabilities-oriented public and education policies for the enhancement of knowledge dimension of capabilities in particular and human welfare in general. The focus of education policy should be extended from investment oriented (human capital approach) to value-oriented (human capability approach).Capabilities; Freedom; Functioning; Conversion Efficiency; Latent variables; Structural equations model; PLS; LISREL; 3SLS

Light-flavor squark reconstruction at CLIC

We present a simulation study of the prospects for the mass measurement of TeV-scale light-flavored right-handed squarks at a 3 TeV e+e- collider based on CLIC technology. In the considered model, these particles decay into their standard-model counterparts and the lightest neutralino, resulting in a signature of two jets plus missing energy. The analysis is based on full GEANT4 simulations of the CLIC_ILD detector concept, including Standard Model physics backgrounds and beam-induced hadronic backgrounds from two-photon processes. The analysis serves as a generic benchmark for the reconstruction of highly energetic jets in events with substantial missing energy. Several jet finding algorithms were evaluated, with the longitudinally invariant kt algorithm showing a high degree of robustness towards beam-induced background while preserving the features typically found in algorithms developed for e+e- collisions. The presented study of the reconstruction of light-flavored squarks shows that for TeV-scale squark masses, sub-percent accuracy on the mass measurement can be achieved at CLIC.Comment: 11 pages, 5 figures, accepted for publication in EPJ

Multi-Dimensional Analysis of Poverty in Ghana Using Fuzzy Sets Theory

The paper studies the multidimensional aspects of poverty and living conditions in Ghana. The aim is to fill the vacuum that has been left by traditional uni-dimensional measures of deprivation based on poverty lines, exclusively estimated on the basis of monetary variables such as income or consumption expenditure. It combines monetary and non-monetary, and qualitative and quantitative indicators, including housing conditions, the possession of durable goods, equivalent disposable income, and equivalent expenditure, with a number of composite human welfare measures. The study employs the fuzzy-set theoretic framework to compare levels of deprivation in Ghana over time usig micro data from the last two rounds of the Ghana Living Standard Surveys (1991/1992 and 1998/1999). The estimation results of the membership functions, depicting the levels of deprivation for the various categories of deprivation indicators, show a composite deprivation degree of 0.2137 for the whole country in 1998/99 as compared to 0.2123 in 1991/92. This deprivation trend reveals that poverty levels hard scarcely changed in Ghana. In fact, it even rose slightly during the nineties, contrary to the uni-dimensional analytical GLSS 4 report of an overall broadly favourable trend in poverty in Ghana during the 1990s.Ghana, fuzzy set, multi-dimensional poverty, composite deprivation or poverty index

Evolving Ensemble Fuzzy Classifier

The concept of ensemble learning offers a promising avenue in learning from data streams under complex environments because it addresses the bias and variance dilemma better than its single model counterpart and features a reconfigurable structure, which is well suited to the given context. While various extensions of ensemble learning for mining non-stationary data streams can be found in the literature, most of them are crafted under a static base classifier and revisits preceding samples in the sliding window for a retraining step. This feature causes computationally prohibitive complexity and is not flexible enough to cope with rapidly changing environments. Their complexities are often demanding because it involves a large collection of offline classifiers due to the absence of structural complexities reduction mechanisms and lack of an online feature selection mechanism. A novel evolving ensemble classifier, namely Parsimonious Ensemble pENsemble, is proposed in this paper. pENsemble differs from existing architectures in the fact that it is built upon an evolving classifier from data streams, termed Parsimonious Classifier pClass. pENsemble is equipped by an ensemble pruning mechanism, which estimates a localized generalization error of a base classifier. A dynamic online feature selection scenario is integrated into the pENsemble. This method allows for dynamic selection and deselection of input features on the fly. pENsemble adopts a dynamic ensemble structure to output a final classification decision where it features a novel drift detection scenario to grow the ensemble structure. The efficacy of the pENsemble has been numerically demonstrated through rigorous numerical studies with dynamic and evolving data streams where it delivers the most encouraging performance in attaining a tradeoff between accuracy and complexity.Comment: this paper has been published by IEEE Transactions on Fuzzy System