10 resultados para information quality

em AMS Tesi di Dottorato - Alm@DL - Università di Bologna


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The research activity carried out during the PhD course in Electrical Engineering belongs to the branch of electric and electronic measurements. The main subject of the present thesis is a distributed measurement system to be installed in Medium Voltage power networks, as well as the method developed to analyze data acquired by the measurement system itself and to monitor power quality. In chapter 2 the increasing interest towards power quality in electrical systems is illustrated, by reporting the international research activity inherent to the problem and the relevant standards and guidelines emitted. The aspect of the quality of voltage provided by utilities and influenced by customers in the various points of a network came out only in recent years, in particular as a consequence of the energy market liberalization. Usually, the concept of quality of the delivered energy has been associated mostly to its continuity. Hence the reliability was the main characteristic to be ensured for power systems. Nowadays, the number and duration of interruptions are the “quality indicators” commonly perceived by most customers; for this reason, a short section is dedicated also to network reliability and its regulation. In this contest it should be noted that although the measurement system developed during the research activity belongs to the field of power quality evaluation systems, the information registered in real time by its remote stations can be used to improve the system reliability too. Given the vast scenario of power quality degrading phenomena that usually can occur in distribution networks, the study has been focused on electromagnetic transients affecting line voltages. The outcome of such a study has been the design and realization of a distributed measurement system which continuously monitor the phase signals in different points of a network, detect the occurrence of transients superposed to the fundamental steady state component and register the time of occurrence of such events. The data set is finally used to locate the source of the transient disturbance propagating along the network lines. Most of the oscillatory transients affecting line voltages are due to faults occurring in any point of the distribution system and have to be seen before protection equipment intervention. An important conclusion is that the method can improve the monitored network reliability, since the knowledge of the location of a fault allows the energy manager to reduce as much as possible both the area of the network to be disconnected for protection purposes and the time spent by technical staff to recover the abnormal condition and/or the damage. The part of the thesis presenting the results of such a study and activity is structured as follows: chapter 3 deals with the propagation of electromagnetic transients in power systems by defining characteristics and causes of the phenomena and briefly reporting the theory and approaches used to study transients propagation. Then the state of the art concerning methods to detect and locate faults in distribution networks is presented. Finally the attention is paid on the particular technique adopted for the same purpose during the thesis, and the methods developed on the basis of such approach. Chapter 4 reports the configuration of the distribution networks on which the fault location method has been applied by means of simulations as well as the results obtained case by case. In this way the performance featured by the location procedure firstly in ideal then in realistic operating conditions are tested. In chapter 5 the measurement system designed to implement the transients detection and fault location method is presented. The hardware belonging to the measurement chain of every acquisition channel in remote stations is described. Then, the global measurement system is characterized by considering the non ideal aspects of each device that can concur to the final combined uncertainty on the estimated position of the fault in the network under test. Finally, such parameter is computed according to the Guide to the Expression of Uncertainty in Measurements, by means of a numeric procedure. In the last chapter a device is described that has been designed and realized during the PhD activity aiming at substituting the commercial capacitive voltage divider belonging to the conditioning block of the measurement chain. Such a study has been carried out aiming at providing an alternative to the used transducer that could feature equivalent performance and lower cost. In this way, the economical impact of the investment associated to the whole measurement system would be significantly reduced, making the method application much more feasible.

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Nuclear Magnetic Resonance (NMR) is a branch of spectroscopy that is based on the fact that many atomic nuclei may be oriented by a strong magnetic field and will absorb radiofrequency radiation at characteristic frequencies. The parameters that can be measured on the resulting spectral lines (line positions, intensities, line widths, multiplicities and transients in time-dependent experi-ments) can be interpreted in terms of molecular structure, conformation, molecular motion and other rate processes. In this way, high resolution (HR) NMR allows performing qualitative and quantitative analysis of samples in solution, in order to determine the structure of molecules in solution and not only. In the past, high-field NMR spectroscopy has mainly concerned with the elucidation of chemical structure in solution, but today is emerging as a powerful exploratory tool for probing biochemical and physical processes. It represents a versatile tool for the analysis of foods. In literature many NMR studies have been reported on different type of food such as wine, olive oil, coffee, fruit juices, milk, meat, egg, starch granules, flour, etc using different NMR techniques. Traditionally, univariate analytical methods have been used to ex-plore spectroscopic data. This method is useful to measure or to se-lect a single descriptive variable from the whole spectrum and , at the end, only this variable is analyzed. This univariate methods ap-proach, applied to HR-NMR data, lead to different problems due especially to the complexity of an NMR spectrum. In fact, the lat-ter is composed of different signals belonging to different mole-cules, but it is also true that the same molecules can be represented by different signals, generally strongly correlated. The univariate methods, in this case, takes in account only one or a few variables, causing a loss of information. Thus, when dealing with complex samples like foodstuff, univariate analysis of spectra data results not enough powerful. Spectra need to be considered in their wholeness and, for analysing them, it must be taken in consideration the whole data matrix: chemometric methods are designed to treat such multivariate data. Multivariate data analysis is used for a number of distinct, differ-ent purposes and the aims can be divided into three main groups: • data description (explorative data structure modelling of any ge-neric n-dimensional data matrix, PCA for example); • regression and prediction (PLS); • classification and prediction of class belongings for new samples (LDA and PLS-DA and ECVA). The aim of this PhD thesis was to verify the possibility of identify-ing and classifying plants or foodstuffs, in different classes, based on the concerted variation in metabolite levels, detected by NMR spectra and using the multivariate data analysis as a tool to inter-pret NMR information. It is important to underline that the results obtained are useful to point out the metabolic consequences of a specific modification on foodstuffs, avoiding the use of a targeted analysis for the different metabolites. The data analysis is performed by applying chemomet-ric multivariate techniques to the NMR dataset of spectra acquired. The research work presented in this thesis is the result of a three years PhD study. This thesis reports the main results obtained from these two main activities: A1) Evaluation of a data pre-processing system in order to mini-mize unwanted sources of variations, due to different instrumental set up, manual spectra processing and to sample preparations arte-facts; A2) Application of multivariate chemiometric models in data analy-sis.

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The cathepsin enzymes represent an important family of lysosomal proteinases with a broad spectrum of functions in many, if not in all, tissues and cell types. In addition to their primary role during the normal protein turnover, they possess highly specific proteolytic activities, including antigen processing in the immune response and a direct role in the development of obesity and tumours. In pigs, the involvement of cathepsin enzymes in proteolytic processes have important effects during the conversion of muscle to meat, due to their influence on meat texture and sensory characteristics, mainly in seasoned products. Their contribution is fundamental in flavour development of dry-curing hams. However, several authors have demonstrated that high cathepsin activity, in particular of cathepsin B, is correlated to defects of these products, such as an excessive meat softness together with abnormal free tyrosine content, astringent or metallic aftertastes and formation of a white film on the cut surface. Thus, investigation of their genetic variability could be useful to identify DNA markers associated with these dry cured hams parameters, but also with meat quality, production and carcass traits in Italian heavy pigs. Unfortunately, no association has been found between cathepsin markers and meat quality traits so far, in particular with cathepsin B activity, suggesting that other genes, besides these, affect meat quality parameters. Nevertheless, significant associations were observed with several carcass and production traits in pigs. A recent study has demonstrated that different single nucleotide polymorphisms (SNPs) localized in cathepsin D (CTSD), F (CTSF), H and Z genes were highly associated with growth, fat deposition and production traits in an Italian Large White pig population. The aim of this thesis was to confirm some of these results in other pig populations and identify new cathepsin markers in order to evaluate their effects on cathepsin activity and other production traits. Furthermore, starting from the data obtained in previous studies on CTSD gene, we also analyzed the known polymorphism located in the insulin-like growth factor 2 gene (IGF2 intron3-g.3072G>A). This marker is considered the causative mutation for the quantitative trait loci (QTL) affecting muscle mass and fat deposition in pigs. Since IGF2 maps very close to CTSD on porcine chromosome (SSC) 2, we wanted to clarify if the effects of the CTSD marker were due to linkage disequilibrium with the IGF2 intron3-g.3072G>A mutation or not. In the first chapter, we reported the results from these two SSC2 gene markers. First of all, we evaluated the effects of the IGF2 intron3-g.3072G>A polymorphism in the Italian Large White breed, for which no previous studies have analysed this marker. Highly significant associations were identified with all estimated breeding values for production and carcass traits (P<0.00001), while no effects were observed for meat quality traits. Instead, the IGF2 intron3-g.3072G>A mutation did not show any associations with the analyzed traits in the Italian Duroc pigs, probably due to the low level of variability at this polymorphic site for this breed. In the same Duroc pig population, significant associations were obtained for the CTSD marker for all production and carcass traits (P < 0.001), after excluding possible confounding effects of the IGF2 mutation. The effects of the CTSD g.70G>A polymorphism were also confirmed in a group of Italian Large White pigs homozygous for the IGF2 intron3-g.3072G allele G (IGF2 intron3-g.3072GG) and by haplotype analysis between the markers of the two considered genes. Taken together, all these data indicated that the IGF2 intron3-g.3072G>A mutation is not the only polymorphism affecting fatness and muscle deposition in pigs. In the second chapter, we reported the analysis of two new SNPs identified in cathepsin L (CTSL) and cathepsin S (CTSS) genes and the association results with meat quality parameters (including cathepsin B activity) and several production traits in an Italian Large White pig population. Allele frequencies of these two markers were evaluated in 7 different pig breeds. Furthermore, we mapped using a radiation hybrid panel the CTSS gene on SSC4. Association studies with several production traits, carried out in 268 Italian Large White pigs, indicated positive effects of the CTSL polymorphism on average daily gain, weight of lean cuts and backfat thickness (P<0.05). The results for these latter traits were also confirmed using a selective genotype approach in other Italian Large White pigs (P<0.01). In the 268 pig group, the CTSS polymorphism was associated with feed:gain ratio and average daily gain (P<0.05). Instead, no association was observed between the analysed markers and meat quality parameters. Finally, we wanted to verify if the positive results obtained for the cathepsin L and S markers and for other previous identified SNPs (cathepsin F, cathepsin Z and their inhibitor cystatin B) were confirmed in the Italian Duroc pig breed (third chapter). We analysed them in two groups of Duroc pigs: the first group was made of 218 performance-tested pigs not selected by any phenotypic criteria, the second group was made of 100 Italian Duroc pigs extreme and divergent for visible intermuscular fat trait. In the first group, the CTSL polymorphism was associated with weight of lean cuts (P<0.05), while suggestive associations were obtained for average daily gain and backfat thickness (P<0.10). Allele frequencies of the CTSL gene marker also differed positively among the visible intermuscular extreme tails. Instead, no positive effects were observed for the other DNA markers on the analysed traits. In conclusion, in agreement with the present data and for the biological role of these enzymes, the porcine CTSD and CTSL markers: a) may have a direct effect in the biological mechanisms involved in determining fat and lean meat content in pigs, or b) these markers could be very close to the putative functional mutation(s) present in other genes. These findings have important practical applications, in particular the CTSD and CTSL mutations could be applied in a marker assisted selection (MAS) both in the Italian Large White and Italian Duroc breeds. Marker assisted selection could also increase in efficiency by adding information from the cathepsin S genotype, but only in the Italian Large White breed.

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Due to the growing attention of consumers towards their food, improvement of quality of animal products has become one of the main focus of research. To this aim, the application of modern molecular genetics approaches has been proved extremely useful and effective. This innovative drive includes all livestock species productions, including pork. The Italian pig breeding industry is unique because needs heavy pigs slaughtered at about 160 kg for the production of high quality processed products. For this reason, it requires precise meat quality and carcass characteristics. Two aspects have been considered in this thesis: the application of the transcriptome analysis in post mortem pig muscles as a possible method to evaluate meat quality parameters related to the pre mortem status of the animals, including health, nutrition, welfare, and with potential applications for product traceability (chapters 3 and 4); the study of candidate genes for obesity related traits in order to identify markers associated with fatness in pigs that could be applied to improve carcass quality (chapters 5, 6, and 7). Chapter three addresses the first issue from a methodological point of view. When we considered this issue, it was not obvious that post mortem skeletal muscle could be useful for transcriptomic analysis. Therefore we demonstrated that the quality of RNA extracted from skeletal muscle of pigs sampled at different post mortem intervals (20 minutes, 2 hours, 6 hours, and 24 hours) is good for downstream applications. Degradation occurred starting from 48 h post mortem even if at this time it is still possible to use some RNA products. In the fourth chapter, in order to demonstrate the potential use of RNA obtained up to 24 hours post mortem, we present the results of RNA analysis with the Affymetrix microarray platform that made it possible to assess the level of expression of more of 24000 mRNAs. We did not identify any significant differences between the different post mortem times suggesting that this technique could be applied to retrieve information coming from the transcriptome of skeletal muscle samples not collected just after slaughtering. This study represents the first contribution of this kind applied to pork. In the fifth chapter, we investigated as candidate for fat deposition the TBC1D1 [TBC1 (tre-2/USP6, BUB2, cdc16) gene. This gene is involved in mechanisms regulating energy homeostasis in skeletal muscle and is associated with predisposition to obesity in humans. By resequencing a fragment of the TBC1D1 gene we identified three synonymous mutations localized in exon 2 (g.40A>G, g.151C>T, and g.172T>C) and 2 polymorphisms localized in intron 2 (g.219G>A and g.252G>A). One of these polymorphisms (g.219G>A) was genotyped by high resolution melting (HRM) analysis and PCR-RFLP. Moreover, this gene sequence was mapped by radiation hybrid analysis on porcine chromosome 8. The association study was conducted in 756 performance tested pigs of Italian Large White and Italian Duroc breeds. Significant results were obtained for lean meat content, back fat thickness, visible intermuscular fat and ham weight. In chapter six, a second candidate gene (tribbles homolog 3, TRIB3) is analyzed in a study of association with carcass and meat quality traits. The TRIB3 gene is involved in energy metabolism of skeletal muscle and plays a role as suppressor of adipocyte differentiation. We identified two polymorphisms in the first coding exon of the porcine TRIB3 gene, one is a synonymous SNP (c.132T> C), a second is a missense mutation (c.146C> T, p.P49L). The two polymorphisms appear to be in complete linkage disequilibrium between and within breeds. The in silico analysis of the p.P49L substitution suggests that it might have a functional effect. The association study in about 650 pigs indicates that this marker is associated with back fat thickness in Italian Large White and Italian Duroc breeds in two different experimental designs. This polymorphisms is also associated with lactate content of muscle semimembranosus in Italian Large White pigs. Expression analysis indicated that this gene is transcribed in skeletal muscle and adipose tissue as well as in other tissues. In the seventh chapter, we reported the genotyping results for of 677 SNPs in extreme divergent groups of pigs chosen according to the extreme estimated breeding values for back fat thickness. SNPs were identified by resequencing, literature mining and in silico database mining. analysis, data reported in the literature of 60 candidates genes for obesity. Genotyping was carried out using the GoldenGate (Illumina) platform. Of the analyzed SNPs more that 300 were polymorphic in the genotyped population and had minor allele frequency (MAF) >0.05. Of these SNPs, 65 were associated (P<0.10) with back fat thickness. One of the most significant gene marker was the same TBC1D1 SNPs reported in chapter 5, confirming the role of this gene in fat deposition in pig. These results could be important to better define the pig as a model for human obesity other than for marker assisted selection to improve carcass characteristics.

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The continuous advancements and enhancements of wireless systems are enabling new compelling scenarios where mobile services can adapt according to the current execution context, represented by the computational resources available at the local device, current physical location, people in physical proximity, and so forth. Such services called context-aware require the timely delivery of all relevant information describing the current context, and that introduces several unsolved complexities, spanning from low-level context data transmission up to context data storage and replication into the mobile system. In addition, to ensure correct and scalable context provisioning, it is crucial to integrate and interoperate with different wireless technologies (WiFi, Bluetooth, etc.) and modes (infrastructure-based and ad-hoc), and to use decentralized solutions to store and replicate context data on mobile devices. These challenges call for novel middleware solutions, here called Context Data Distribution Infrastructures (CDDIs), capable of delivering relevant context data to mobile devices, while hiding all the issues introduced by data distribution in heterogeneous and large-scale mobile settings. This dissertation thoroughly analyzes CDDIs for mobile systems, with the main goal of achieving a holistic approach to the design of such type of middleware solutions. We discuss the main functions needed by context data distribution in large mobile systems, and we claim the precise definition and clean respect of quality-based contracts between context consumers and CDDI to reconfigure main middleware components at runtime. We present the design and the implementation of our proposals, both in simulation-based and in real-world scenarios, along with an extensive evaluation that confirms the technical soundness of proposed CDDI solutions. Finally, we consider three highly heterogeneous scenarios, namely disaster areas, smart campuses, and smart cities, to better remark the wide technical validity of our analysis and solutions under different network deployments and quality constraints.

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This Ph.D. thesis focuses on the investigation of some chemical and sensorial analytical parameters linked to the quality and purity of different categories of oils obtained by olives: extra virgin olive oils, both those that are sold in the large retail trade (supermarkets and discounts) and those directly collected at some Italian mills, and lower-quality oils (refined, lampante and “repaso”). Concurrently with the adoption of traditional and well-known analytical procedures such as gas chromatography and high-performance liquid chromatography, I carried out a set-up of innovative, fast and environmentally-friend methods. For example, I developed some analytical approaches based on Fourier transform medium infrared spectroscopy (FT-MIR) and time domain reflectometry (TDR), coupled with a robust chemometric elaboration of the results. I investigated some other freshness and quality markers that are not included in official parameters (in Italian and European regulations): the adoption of such a full chemical and sensorial analytical plan allowed me to obtain interesting information about the degree of quality of the EVOOs, mostly within the Italian market. Here the range of quality of EVOOs resulted very wide, in terms of sensory attributes, price classes and chemical parameters. Thanks to the collaboration with other Italian and foreign research groups, I carried out several applicative studies, especially focusing on the shelf-life of oils obtained by olives and on the effects of thermal stresses on the quality of the products. I also studied some innovative technological treatments, such as the clarification by using inert gases, as an alternative to the traditional filtration. Moreover, during a three-and-a-half months research stay at the University of Applied Sciences in Zurich, I also carried out a study related to the application of statistical methods for the elaboration of sensory results, obtained thanks to the official Swiss Panel and to some consumer tests.

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The wide diffusion of cheap, small, and portable sensors integrated in an unprecedented large variety of devices and the availability of almost ubiquitous Internet connectivity make it possible to collect an unprecedented amount of real time information about the environment we live in. These data streams, if properly and timely analyzed, can be exploited to build new intelligent and pervasive services that have the potential of improving people's quality of life in a variety of cross concerning domains such as entertainment, health-care, or energy management. The large heterogeneity of application domains, however, calls for a middleware-level infrastructure that can effectively support their different quality requirements. In this thesis we study the challenges related to the provisioning of differentiated quality-of-service (QoS) during the processing of data streams produced in pervasive environments. We analyze the trade-offs between guaranteed quality, cost, and scalability in streams distribution and processing by surveying existing state-of-the-art solutions and identifying and exploring their weaknesses. We propose an original model for QoS-centric distributed stream processing in data centers and we present Quasit, its prototype implementation offering a scalable and extensible platform that can be used by researchers to implement and validate novel QoS-enforcement mechanisms. To support our study, we also explore an original class of weaker quality guarantees that can reduce costs when application semantics do not require strict quality enforcement. We validate the effectiveness of this idea in a practical use-case scenario that investigates partial fault-tolerance policies in stream processing by performing a large experimental study on the prototype of our novel LAAR dynamic replication technique. Our modeling, prototyping, and experimental work demonstrates that, by providing data distribution and processing middleware with application-level knowledge of the different quality requirements associated to different pervasive data flows, it is possible to improve system scalability while reducing costs.

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Abstract Background: Turner syndrome (TS) is a chromosomal abnormality (total or partial absence of one of the sexual chromosomes in some or all cells of the body), which affects approximately 1:2000 female. Principal characteristics are short stature and gonadal disgenesis. Clinical management consist of Growth Hormone (GH) treatment and oestrogen replacement therapy (HRT), to induce development of secondary characteristics and to avoid the sequelae of oestrogen deficiency. Aim of the study: To assess clinical management, quality of life (QoL) and general psychosocial adjustment of women with TS. Population: 70 adult Caucasian females with TS (mean age: 27.8, ± 7.6; range 18-48 y.). Setting: Specialist service for Rare Disease care, University Hospital. Methods: Subjects were required to fill in questionnaires collecting ASR, WHOQOL, and 8 open questions. Data were compared with those of the Italian population or to those collected in a comparison group (70 healthy females, mean age: 27.9, ±7.3, range 21-48 y.). Results: Women with TS are educated as well as the Italian Population, but they have a less successful professional life. They show good QoL in general, but they appeared less satisfied in social area. They had statistically higher scores than the comparison group for depression, anxiety and withdrawal. Are less involved in a love relationship. Diagnosis communication was mostly performed by doctors or parents, satisfaction was higher when information was given by parents. Main preoccupation about TS are infertility, feeling of being different and future health problem. Conclusions: Italian people with TS were generally well adapted and have a good QoL, but lived more often with parents and show impaired sentimental and sexual life. They have higher degree of psychological distress compared to a comparison group. Psychological intervention should firstly address parents in order to encourage an open communication on diagnosis issues and on sexual education.

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Starch is the main form in which plants store carbohydrates reserves, both in terms of amounts and distribution among different plant species. Carbohydrates are direct products of photosynthetic activity, and it is well know that yield efficiency and production are directly correlated to the amount of carbohydrates synthesized and how these are distributed among vegetative and reproductive organs. Nowadays, in pear trees, due to the modernization of orchards, through the introduction of new rootstocks and the development of new training systems, the understanding and the development of new approaches regarding the distribution and storage of carbohydrates, are required. The objective of this research work was to study the behavior of carbohydrate reserves, mainly starch, in different pear tree organs and tissues: i.e., fruits, leaves, woody organs, roots and flower buds, at different physiological stages during the season. Starch in fruit is accumulated at early stages, and reached a maximum concentration during the middle phase of fruit development; after that, its degradation begins with a rise in soluble carbohydrates. Moreover, relationships between fruit starch degradation and different fruit traits, soluble sugars and organic acids were established. In woody organs and roots, an interconversion between starch and soluble carbohydrates was observed during the dormancy period that confirms its main function in supporting the growth and development of new tissues during the following spring. Factors as training systems, rootstocks, types of bearing wood, and their position on the canopy, influenced the concentrations of starch and soluble carbohydrates at different sampling dates. Also, environmental conditions and cultural practices must be considered to better explain these results. Thus, a deeper understanding of the dynamics of carbohydrates reserves within the plant could provide relevant information to improve several management practices to increase crop yield efficiency.

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In food industry, quality assurance requires low cost methods for the rapid assessment of the parameters that affect product stability. Foodstuffs are complex in their structure, mainly composed by gaseous, liquid and solid phases which often coexist in the same product. Special attention is given to water, concerned as natural component of the major food product or as added ingredient of a production process. Particularly water is structurally present in the matrix and not completely available. In this way, water can be present in foodstuff in many different states: as water of crystallization, bound to protein or starch molecules, entrapped in biopolymer networks or adsorbed on solid surfaces of porous food particles. The traditional technique for the assessment of food quality give reliable information but are destructive, time consuming and unsuitable for on line application. The techniques proposed answer to the limited disposition of time and could be able to characterize the main compositional parameters. Dielectric interaction response is mainly related to water and could be useful not only to provide information on the total content but also on the degree of mobility of this ubiquitous molecule in different complex food matrix. In this way the proposal of this thesis is to answer at this need. Dielectric and electric tool can be used for the scope and led us to describe the complex food matrix and predict food characteristic. The thesis is structured in three main part, in the first one some theoretical tools are recalled to well assess the food parameter involved in the quality definition and the techniques able to reply at the problem emerged. The second part explains the research conducted and the experimental plans are illustrated in detail. Finally the last section is left for rapid method easily implementable in an industrial process.