Polycyclic aromatic hydrocarbons (PAHs) are toxic and carcinogenic environmental contaminants originating from different sources; petrogenic, pyrogenic or biogenic. Depending on the source of contamination there will be different ratios of PAHs and the effects on the environment will differ. Petrogenic sources will be higher in concentration of alkyl substituted PAHs (APAHs) while pyrogenic sources will be higher in parent PAHs. In the present study a GC/MS method was developed to separate and calibrate PAHs, dibenzothiophenes and alkyl substituted PAHs in a mix containing 49 standards. The method was able to differentiate between PAHs and APAHs with the same mass number; up to six different compounds with the same mass number was separated. The developed method was used to analyse six different soil samples from various contamination sites. PAHs, APAHs and dibenzothiophenes were identified and quantified in all samples. In order to establish the source of contamination, the distribution pattern, the ratio between different PAHs, and the ratio between APAHs and parent PAHs were used. There was a higher ratio of APAHs/PAHs and a lower ratio between the parent PAHs in the soil samples from sites contaminated with oils compared to the other samples, indicating petrogenic source. / Polycykliska aromatiska kolväten (PAH) är giftiga och cancerframkallande miljögifter som härstammar från olika källor; petrogena, pyrogena eller biogena. Olika föroreningskällor kommer att ha olika förhållanden av PAH och effekterna på miljön kommer att skilja. Petrogena källor innehåller högre koncentrationer av alkylsubstituerade PAH (APAH) medan pyrogena källor kommer att ha högre koncentration av PAH. I denna studie har en GC/MS-metod utvecklats för att separera och kalibrera PAH, dibensotiofener och alkylsubstituerade PAH i en blandning innehållande 49 standarder. Metoden kunde skilja mellan PAH och alkylsubstituerade PAH med samma masstal; upp till sex olika föreningar med samma masstal särskildes. Den utvecklade metoden användes för att analysera sex olika jordprover från olika föroreningsplatser. PAH, APAH och dibensotiofener identifierades och kvantifieras i samtliga prover. För att fastställa föroreningskällan användes fördelningsmönstret för APAH och PAH, förhållandet mellan olika PAH och ration mellan APAH och PAH. Det fanns en högre kvot APAH/PAH i jordprover från områden som var förorenade med olja, vilket indikerar på petrogena föroreningskällor.

Αντικείμενο της παρούσας διπλωματικής εργασίας είναι η μελέτη της ακουστικής παρακολούθησης και ανάλυσης λειτουργίας μηχανών σε βιομηχανικές και μη εφαρμογές. Ασχολούμαστε κυρίως με την παρακολούθηση του θορύβου που εκπέμπουν οι μηχανές και μας ενδιαφέρει ο εντοπισμός των ηχητικών πηγών (πηγών θορύβου) προκειμένου να ληφθούν οι κατάλληλες ενέργειες. Για το σκοπό αυτό παρουσιάζονται μέθοδοι, «οπτικοποίησης» του ηχητικού πεδίου, οι οποίες κάνουν πιο εύκολη τη διαδικασία εντοπισμού. Σε αυτή τη διπλωματική εργασία παρουσιάζοντα οι βασικές αρχές της ακουστικής θεωρίας, οι βασικές διατάξεις που χρησιμοποιούνται για τη μέτρηση του ήχου. Στη συνέχεια περιγράφονται οι υπάρχουσες μέθοδοι χαρτογράφησης του ηχητικού πεδίου για τον προσδιορισμό των ηχητικών πηγών, οι διατάξεις που χρησιμοποιούνται για το σκοπό αυτό και τέλος παραθέτονται κάποιες εφαρμογές. / The object of this diploma paper is the acoustic attendance and analysis of machines in industrial and other applications. Our main concern is the noise emission from the machines and we are also interested on locating the sound (noise) sources in order to take proper actions. For this purpose methods of sound “visualization” are introduced, that make easier the process of locating the sources. In this diploma paper we also introduce the basic principles of acoustic theory and the used arrays for sound measurement. Next is the description of the existing methods of mapping the sound field in order to detect the sound sources, the instruments used for this purpose and in the end some applications.

Identifying marine pollutant sources is essential in order to assess, contain and minimize their risk. We propose a Lagrangian Particle Tracking algorithm (LPT) to study the transport of passive tracers continuously released from fixed and moving sources and to identify their source in a backward mode. The LPT is designed to operate with uncertain flow fi elds, described by an ensemble of realizations of the sea currents. Starting from a region of high probability, re- verse tracking is used to generate inverse maps. A probability-weighted distance between the resulting inverse maps and the source trajectory is then minimized to identify the likely source of pollution. We conduct realistic simulations to demonstrate the efficiency of the proposed algorithm in the Mediterranean Sea using ocean data available from Copernicus Marine Environment Monitoring Services. Passive tracers are released along the path of a ship and propagated with an ensemble of flow fi elds forward in time to generate a probability map, which is then used for the inverse problem of source identi fication. Our experiments suggest that the algorithm is able to efficiently capture the release time and source, with some test cases successfully pinpointing the release time and source up to two weeks back in time.

Frequency Hopping Spread Spectrum (FHSS) signaling is used across many devices operating in both regulated and unregulated bands. In either situation, if there is a malicious device operating within these bands, or more simply a user operating out of the required specifications, the identification this user important to insure communication link integrity and interference mitigation. The identification of a user involves the grouping of that users signal transmissions, and the separation of those transmission from transmissions of other users in a shared frequency band. Traditional signal separation methods often require difficult to obtain hardware fingerprinting characteristics or approximate geo-location estimates. This work will consider the characteristics of FHSS signals that can be extracted directly from signal detection. From estimates of these hopping characteristics, novel source separation with classic clustering algorithms can be performed. Background knowledge derived from the time domain representation of received waveforms can improve these clustering methods with the novel application of cannot-link pairwise constraints to signal separation. For equivalent clustering accuracy, constraint-based clustering tolerates higher parameter estimation error, caused by diminishing received signal-to-noise ratio (SNR), for example. Additionally, prior work does not fully cover the implications of detecting and estimating FHSS signals using image segmentation on a Time-Frequency (TF) waterfall. This work will compare several methods of FHSS signal detection, and discuss how each method may effect estimation accuracy and signal separation quality. The use of constraint-based clustering is shown to provide higher clustering accuracy, resulting in more reliable separation and identification of active users in comparison to traditional clustering methods. / Master of Science / The expansion of technology in areas such as smart homes and appliances, personal devices, smart vehicles, and many others, leads to more and more devices using common wireless communication techniques such as WiFi and Bluetooth. While the number of wirelessly connected users expands, the range of frequencies that support wireless communications does not. It is therefore essential that each of these devices unselfishly share the available wireless resources. If a device is using more resources than the required limits, or causing interference with other’s communications, this device will impact many others negatively and therefore preventative action must be taken to prevent further disruption in the wireless environment. Before action can be taken however, the device must first be identified in a mixture of other wireless activity. To identify a specific device, first, a wireless receiver must be in close enough proximity to detect the power that the malicious device is emitting through its wireless communication. This thesis provides a method that can be used to identify a problem user based only off of its wireless transmission behavior. The performance of this identification is shown with respect to the received signal power which represents the necessary range that a listening device must be to identify and separate a problem user from other cooperative users that are communicating wirelessly.

Polycyclic aromatic hydrocarbons (PAHs) are ubiquitous, toxic contaminants that are released to the environment from various petrogenic and pyrogenic sources. In an effort to more clearly identify and trace sources of PAHs in the environment, purification and compound specific isotope analysis methods were developed to accurately measure the stable carbon isotope ratio of individual PAHs. Development of the method included improving accuracy and precision of the isotopic measurement by producing highly pure extracts using various chromatographic techniques. The method was refined by improving compound separations using purification techniques and high resolution chromatographic columns. The purification method consists of alumina/silica gel column chromatography, gel permeation chromatography and thin layer chromatography. The mean recovery of PAHs after the purification procedure was approximately 80 %. Sample purities after purification were verified by GC/FID and full scan mass spectrometry. To better resolve peaks and provide more accurate stable carbon isotope measurements, various gas chromatographic conditions were evaluated. The precision of the method ranged between 0.08 and 0.43 . The analytical protocols were evaluated to confirm compositional and stable isotopic integrity during purification and stable isotopic analysis. To confirm the utility of the purification and isotope analysis methods, various environmental samples from marine, land and lacustrine environments were analyzed. The isolates were analyzed for the composition and the stable carbon isotope ratios of PAHs. The stable carbon isotope ratio was measured by GC/IRMS and the results, along with quantitative compound compositions, were used to characterize and identify the contaminant sources. The sources of the PAHs in the study areas were differentiated by PAH molecular ratios and confirmed by stable carbon isotope ratios. This study confirms that compound specific isotope analysis of pollutants by GC/IRMS can be used to identify PAH sources in environmental samples. The study also confirms that the purification and stable carbon isotope analysis methods that were developed can be used to accurately measure the stable carbon isotope ratios of PAHs in environmental samples for the purpose of source identification. GC/IRMS measurement of stable isotopic compositions can be an effective fingerprinting method when used in conjunction with traditional molecular composition methods.

This thesis is aimed at identifying the noise sources of a wheeled tractor to reduce the noise levels below the legislative limits by controlling noise sources through proper methodologies. The study focuses firstly on identifying the noise sources of a wheeled tractor by using proper noise source identification techniques. These techniques can be summarized as sound intensity measurements, sound power level determination studies and spectral analysis of the noise data acquired in the tests. Simple sound intensity mapping techniques are used and the intensity contour maps are generated to identify the noise sources. Most important and effective noise sources are identified and the critical noise sources are focused to apply appropriate noise control strategies not only at the prototype production stages but also at the early design stages. Consequently, upon consideration of both structure-borne and flow-induced noise, the pass-by noise level and the operator&rsquo / s ear noise levels of the tractor are reduced by nearly 3 dB (A) through application of proper noise control strategies.

Polycyclic aromatic hydrocarbons (PAHs) are ubiquitous, toxic contaminants that are released to the environment from various petrogenic and pyrogenic sources. In an effort to more clearly identify and trace sources of PAHs in the environment, purification and compound specific isotope analysis methods were developed to accurately measure the stable carbon isotope ratio of individual PAHs. Development of the method included improving accuracy and precision of the isotopic measurement by producing highly pure extracts using various chromatographic techniques. The method was refined by improving compound separations using purification techniques and high resolution chromatographic columns. The purification method consists of alumina/silica gel column chromatography, gel permeation chromatography and thin layer chromatography. The mean recovery of PAHs after the purification procedure was approximately 80 %. Sample purities after purification were verified by GC/FID and full scan mass spectrometry. To better resolve peaks and provide more accurate stable carbon isotope measurements, various gas chromatographic conditions were evaluated. The precision of the method ranged between 0.08 and 0.43 . The analytical protocols were evaluated to confirm compositional and stable isotopic integrity during purification and stable isotopic analysis. To confirm the utility of the purification and isotope analysis methods, various environmental samples from marine, land and lacustrine environments were analyzed. The isolates were analyzed for the composition and the stable carbon isotope ratios of PAHs. The stable carbon isotope ratio was measured by GC/IRMS and the results, along with quantitative compound compositions, were used to characterize and identify the contaminant sources. The sources of the PAHs in the study areas were differentiated by PAH molecular ratios and confirmed by stable carbon isotope ratios. This study confirms that compound specific isotope analysis of pollutants by GC/IRMS can be used to identify PAH sources in environmental samples. The study also confirms that the purification and stable carbon isotope analysis methods that were developed can be used to accurately measure the stable carbon isotope ratios of PAHs in environmental samples for the purpose of source identification. GC/IRMS measurement of stable isotopic compositions can be an effective fingerprinting method when used in conjunction with traditional molecular composition methods.

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The proliferation of multimedia data, including digital images and videos, has led to an increase in their misuse, such as the unauthorized sharing of sensitive content, the spread of fake news, and the dissemination of misleading propaganda. To address these issues, the research field of multimedia forensics has developed tools to distinguish genuine multimedia from fakes and identify the sources of those who share sensitive content. However, the accuracy and reliability of multimedia forensics tools are threatened by recent technological advancements in new multimedia processing software and camera devices. For example, source attribution involves attributing an image or video to a specific camera device, which is crucial for addressing privacy violations, cases of revenge porn, and instances of child pornography. These tools exploit forensic traces unique to each camera’s manufacturing process, such as Photo Response Non-Uniformity (PRNU). Nevertheless, image and video processing transformations can disrupt the consistency of PRNU, necessitating the development of new methods for its recovery. Conversely, to distinguish genuine multimedia from fakes, AI-based image and video forgery localization methods have also emerged. However, they constantly face challenges from new, more sophisticated AI-forgery techniques and are hindered by factors like AI-aided post-processing and, in the case of videos, lower resolutions, and stronger compression. This doctoral study investigates the relevance of exploiting temporal information during the parameters estimation used to reverse complex spatial transformations for source attribution, and video forgery localization in low-resolution H.264 post-processed inpainted videos. Two novel methods will be presented that model the set of parameters involved in reversing in-camera and out-camera complex spatial transformations applied to images and videos as time series, improving source attribution accuracy and computational efficiency. Regarding video inpainting localization, a novel dataset of videos inpainted and post-processed with Temporal Consistency Networks will be introduced, and we will present our solution to improve video inpainting localization by taking into account spatial and temporal inconsistencies at dense optical flow level. The research presented in this dissertation has resulted in several publications that contribute to the field of multimedia forensics, addressing challenges related to source attribution and video forgery localization.