Standardisation of data from real-time quantitative PCR methods – evaluation of outliers and comparison of calibration curves

BACKGROUND: As real-time quantitative PCR (RT-QPCR) is increasingly being relied upon for the enforcement of legislation and regulations dependent upon the trace detection of DNA, focus has increased on the quality issues related to the technique. Recent work has focused on the identification of factors that contribute towards significant measurement uncertainty in the real-time quantitative PCR technique, through investigation of the experimental design and operating procedure. However, measurement uncertainty contributions made during the data analysis procedure have not been studied in detail. This paper presents two additional approaches for standardising data analysis through the novel application of statistical methods to RT-QPCR, in order to minimise potential uncertainty in results. RESULTS: Experimental data was generated in order to develop the two aspects of data handling and analysis that can contribute towards measurement uncertainty in results. This paper describes preliminary aspects in standardising data through the application of statistical techniques to the area of RT-QPCR. The first aspect concerns the statistical identification and subsequent handling of outlying values arising from RT-QPCR, and discusses the implementation of ISO guidelines in relation to acceptance or rejection of outlying values. The second aspect relates to the development of an objective statistical test for the comparison of calibration curves. CONCLUSION: The preliminary statistical tests for outlying values and comparisons between calibration curves can be applied using basic functions found in standard spreadsheet software. These two aspects emphasise that the comparability of results arising from RT-QPCR needs further refinement and development at the data-handling phase. The implementation of standardised approaches to data analysis should further help minimise variation due to subjective judgements. The aspects described in this paper will help contribute towards the development of a set of best practice guidelines regarding standardising handling and interpretation of data arising from RT-QPCR experiments

Outliers treatment to improve the recognition of voice pathologies

In some of the processes used in data analysis, such as the recognition of pathologies and pathological subjects, the presence of anomalous instances in the dataset is an unfavorable situation that can lead to misleading results. This article presents a function that implements the identification of anomalies in dataset using the boxplot and standard deviation methods. Also was used the filling technique to treat these anomalies, in which the anomalous point value were substituted by a limit value determined by the boxplot or standard deviation methods. To improve the outliers methods some normalization processes based on the z-score, logarithmic and squared root methodologies were experimented. These outliers treatment were applied to the dataset used in the recognition of vocal pathologies (dysphonia, chronic laryngitis and vocal cords paralysis vs control), performed by a MLP and LSTM neural networks. After the experiments, both the standard deviation and the boxplot methods with z-score normalization showed very useful for pre-processing the dataset for voice pathologies recognition. The accuracy was improved between 3 and 13 points in percentage.info:eu-repo/semantics/publishedVersio

Combining statistical methods for detecting potential outliers in groundwater quality time series

Quality control of large-scale monitoring networks requires the use of automatic procedures to detect potential outliers in an unambiguous and reproducible manner. This paper describes a methodology that combines existing statistical methods to accommodate for the specific characteristics of measurement data obtained from groundwater quality monitoring networks: the measurement series show a large variety of dynamics and often comprise few

Robust image steganography method suited for prining = Robustna steganografska metoda prilagođena procesu tiska

U ovoj doktorskoj dizertaciji prezentirana je robustna steganografska metoda razvijena i prilagođena za tisak. Osnovni cilj metode je pružanje zaštite od krivotvorenja ambalaže. Zaštita ambalaže postiže se umetanjem više bitova informacije u sliku pri enkoderu, a potom maskiranjem informacije kako bi ona bila nevidljiva ljudskom oku. Informacija se pri dekoderu detektira pomoću infracrvene kamere. Preliminarna istraživanja pokazala su da u relevantnoj literaturi nedostaje metoda razvijenih za domenu tiska. Razlog za takav nedostatak jest činjenica da razvijanje steganografskih metoda za tisak zahtjeva veću količinu resursa i materijala, u odnosu na razvijanje sličnih domena za digitalnu domenu. Također, metode za tisak često zahtijevaju višu razinu kompleksnosti, budući da se tijekom reprodukcije pojavljuju razni oblici procesiranja koji mogu kompromitirati informaciju u slici [1]. Da bi se sačuvala skrivena informacija, metoda mora biti otporna na procesiranje koje se događa tijekom reprodukcije. Kako bi se postigla visoka razina otpornosti, informacija se može umetnuti unutar frekvencijske domene slike [2], [3]. Frekvencijskoj domeni slike možemo pristupiti pomoću matematičkih transformacija. Najčešće se koriste diskretna kosinusna transformacija (DCT), diskretna wavelet transformacija (DWT) i diskretna Fourierova transformacija (DFT) [2], [4]. Korištenje svake od navedenih transformacija ima određene prednosti i nedostatke, ovisno o kontekstu razvijanja metode [5]. Za metode prilagođene procesu tiska, diskretna Fourierova transformacija je optimalan odabir, budući da metode bazirane na DFT-u pružaju otpornost na geometrijske transformacije koje se događaju tijekom reprodukcije [5], [6]. U ovom istraživanju korištene su slike u cmyk prostoru boja. Svaka slika najprije je podijeljena u blokove, a umetanje informacije vrši se za svaki blok pojedinačno. Pomoću DFT-a, ???? kanal slikovnog bloka se transformira u frekvencijsku domenu, gdje se vrši umetanje informacije. Akromatska zamjena koristi se za maskiranje vidljivih artefakata nastalih prilikom umetanja informacije. Primjeri uspješnog korištenja akromatske zamjene za maskiranje artefakata mogu se pronaći u [7] i [8]. Nakon umetanja informacije u svaki slikovni blok, blokovi se ponovno spajaju u jednu, jedinstvenu sliku. Akromatska zamjena tada mijenja vrijednosti c, m i y kanala slike, dok kanal k, u kojemu se nalazi umetnuta informacija, ostaje nepromijenjen. Time nakon maskiranja akromatskom zamjenom označena slika posjeduje ista vizualna svojstva kao i slika prije označavanja. U eksperimentalnom dijelu rada koristi se 1000 slika u cmyk prostoru boja. U digitalnom okruženju provedeno je istraživanje otpornosti metode na slikovne napade specifične za reprodukcijski proces - skaliranje, blur, šum, rotaciju i kompresiju. Također, provedeno je istraživanje otpornosti metode na reprodukcijski proces, koristeći tiskane uzorke. Objektivna metrika bit error rate (BER) korištena je za evaluaciju. Mogućnost optimizacije metode testirala se procesiranjem slike (unsharp filter) i korištenjem error correction kodova (ECC). Provedeno je istraživanje kvalitete slike nakon umetanja informacije. Za evaluaciju su korištene objektivne metrike peak signal to noise ratio (PSNR) i structural similarity index measure (SSIM). PSNR i SSIM su tzv. full-reference metrike. Drugim riječima, potrebne su i neoznačena i označena slika istovremeno, kako bi se mogla utvrditi razina sličnosti između slika [9], [10]. Subjektivna analiza provedena je na 36 ispitanika, koristeći ukupno 144 uzorka slika. Ispitanici su ocijenjivali vidljivost artefakata na skali od nula (nevidljivo) do tri (vrlo vidljivo). Rezultati pokazuju da metoda posjeduje visoku razinu otpornosti na reprodukcijski proces. Također, metoda se uistinu optimizirala korištenjem unsharp filtera i ECC-a. Kvaliteta slike ostaje visoka bez obzira na umetanje informacije, što su potvrdili rezultati eksperimenata s objektivnim metrikama i subjektivna analiza

implementasi web scraping pada pembuatan aplikasi pencarian salon di daerah banten menggunakan android

Salon kecantikan sudah menjadi kebutuhan yang penting untuk sebagian orang, terutama perempuan. Berbagai perawatan ditawarkan untuk memenuhi penampilan seseorang agar terlihat menarik dan cantik, mulai dari perawatan rambut, wajah, sampai kuku hampir bisa ditemukan pada setiap salon. Terdapat berbagai salon yang dapat kita pilih namun karena banyaknya pilihan tersebut membuat kita bingung untuk memilih manakah yang lebih baik, dimanakah alamat salon tersebut, serta kita juga tidak mengetahui dimanakah salon yang menyediakan jasa sesuai dengan yang kita butuhkan. Maka tercipta ide untuk membangun aplikasi berbasis mobile dengan implementasi teknik web scraping, dengan tujuan membantu user dalam mencari salon yang di inginkan, aplikasi ini dikhususkan untuk orang-orang yang tinggal didaerah Banten, sehingga mereka dapat mencari salon sesuai dengan lokasi tempat tinggal mereka maupun lokasi lain yang mereka inginkan di daerah Banten. Mereka juga dapat mencari salon sesuai dengan jasa yang disediakan. Untuk melakukan penarikan data, yang dipakai di dalam aplikasi ini adalah metode web scraping dengan melakukan penarikan data dari website salon yang ada di google. Metode web scraping ini dilakukan dengan menggunakan Node.js. Hasil dari perancangan aplikasi yang dilakukan ini adalah aplikasi Android yang menggunakan MongoDB sebagai database. Metode perancangan sistem yang digunakan dalam penelitian ini adalah RAD (Rapid application development) karena menggunakan metode iteratif (berulang). Untuk mengukur apakah aplikasi ini sesuai dengan yang dibutuhkan user dalam mencari salon yang diinginkan maka dilakukan user acceptance test, responden terdiri dari 10 orang dengan kriteria umur di atas 15 tahun dan di nyatakan puas dengan rata-rata skala kepuasan sebesar 4 dari 5

Low-frequency noise pollution impairs burrowing activities of marine benthic invertebrates

Sounds from human activities such as shipping and seismic surveys have been progressively invading natural soundscapes and pervading oceanic ambient sounds for decades. Benthic invertebrates are important ecosystem engineers that continually rework the sediment they live in. Here, we tested how low-frequency noise (LFN), a significant component of noise pollution, affects the sediment reworking activities of selected macrobenthic invertebrates. In a controlled laboratory setup, the effects of acute LFN exposure on the behavior of three abundant bioturbators on the North Atlantic coasts were explored for the first time by tracking their sediment reworking and bioirrigation activities in noisy and control environments via luminophore and sodium bromide (NaBr) tracers, respectively. The amphipod crustacean Corophium volutator was negatively affected by LFN, exhibiting lower bioturbation rates and shallower luminophore burial depths compared to controls. The effect of LFN on the polychaete Arenicola marina and the bivalve Limecola balthica remained inconclusive, although A. marina displayed greater variability in bioirrigation rates when exposed to LFN. Furthermore, a potential stress response was observed in L. balthica that could reduce bioturbation potential. Benthic macroinvertebrates may be in jeopardy along with the crucial ecosystem-maintaining services they provide. More research is urgently needed to understand, predict, and manage the impacts of anthropogenic noise pollution on marine fauna and their associated ecosystems

A Data-Driven Predictive Model of Reliability Estimation Using State-Space Stochastic Degradation Model

The concept of the Industrial Internet of Things (IIoT) provides the foundation to apply data-driven methodologies. The data-driven predictive models of reliability estimation can become a major tool in increasing the life of assets, lowering capital cost, and reducing operating and maintenance costs. Classical models of reliability assessment mainly rely on lifetime data. Failure data may not be easily obtainable for highly reliable assets. Furthermore, the collected historical lifetime data may not be able to accurately describe the behavior of the asset in a unique application or environment. Therefore, it is not an optimal approach anymore to conduct a reliability estimation based on classical models. Fortunately, most of the industrial assets have performance characteristics whose degradation or decay over the operating time can be related to their reliability estimates. The application of the degradation methods has been recently increasing due to their ability to keep track of the dynamic conditions of the system over time. The main purpose of this study is to develop a data-driven predictive model of reliability assessment based on real-time data using a state-space stochastic degradation model to predict the critical time for initiating maintenance actions in order to enhance the value and prolonging the life of assets. The new degradation model developed in this thesis is introducing a new mapping function for the General Path Model based on series of Gamma Processes degradation models in the state-space environment by considering Poisson distributed weights for each of the Gamma processes. The application of the developed algorithm is illustrated for the distributed electrical systems as a generic use case. A data-driven algorithm is developed in order to estimate the parameters of the new degradation model. Once the estimates of the parameters are available, distribution of the failure time, time-dependent distribution of the degradation, and reliability based on the current estimate of the degradation can be obtained

Investigation of archived accurate mass data in mass spectrometry.

"This thesis presents an investigation of mass measurement accuracy in mass spectrometry using archived accurate mass measurement data obtained on different types of mass spectrometry instruments. A magnetic sector was used as the "gold standard" analyzer and other data obtained on electrospray ionization fitted with Orbitrap and a MALDI time-of-flight instrument. More than 4500 accurate masses were obtained from the EPSRC National Mass Spectrometry Service Centre at Swansea University using the above instrument types. Different ionization methods are available; each has its own characteristics. In this study the ionization techniques used are chemical ionization (Cl), electron ionization (El), electrospray ionization (ESI), fast-atom bombardment (FAB) and matrix-assisted laser desorption/ionization (MALDI). These mass analyzers have different attributes, including the mass range, resolution and mass accuracy. Mass measurement accuracies (MMAs) are reported for a number of preferred techniques. Statistical calculations were made using various software pack-ages such as SPSS, AccMass (house software), Origin, Easyfit and Excel add-ins. The data contains view outliers which can significantly affect the accuracy and precision of the data as well as affecting the underlying statistical distribution predicted.