In this thesis a case of advection fog over the Baltic Sea is studied. The period examined is from June 5th to 7th 1995. Data is taken from the instrumented mast, situated on the island Östergarnsholm, a small and flat island without trees outside of Gotland. From the measurements among others the heat flux, relative humidity and temperature are analyzed. In the evening June 5th 1995 the fog is advected in over Östergarnsholm. This can both be seen from the increasing relative humidity and the decreasing temperature. Before the fog arrived the boundary layer was stably stratified. This stratification quickly changed to neutral as the fog reaches Östergarnsholm. After careful evaluation the neutral stratification is shown not to be neutral at all. The stratification closest to the ground up to 15 meters is unstable and above the stratification is stable. From this the conclusion is made that the fog is low only 15 meters high during this period. At noon June 6th the air temperature decreases dramatically below the sea surface temperature at the same time as the relative humidity increases up to 100%. The fog is now thick enough to have most of the outgoing radiation coming from the top, which decreases the temperature a few degrees. As the stability is investigated it shows unstable stratification up to the highest level (28 meters). The assumption is made that the fog is at least 30 meters deep. Also the normalized standard deviations for temperature and vertical velocity are examined to find out if they behave as the variation in the undisturbed boundary layer.2 / Sammanfattning av ”Påverkan av dimma på skiktningen och turbulenta flöden över hav” I detta arbete studeras ett fall av advektions dimma över Östersjön. Perioden undersökt är från den 5 till den 7 juni 1995. Mätmasten står på ön Östergarnsholm, en liten och låg ö utan träd utanför Gotland. Ur mätningarna fås bl.a. värmeflödet, relativa fuktigheten och temperaturen. På kvällen den 5 juni 1995 advekteras dimman in över Östergarnsholm. Detta ses både från att relativa fuktigheten stiger och att temperaturen sjunker. Innan dimman anlände var gränsskiktet stabilt skiktat. Denna skiktning ändrades snabbt till neutral då dimman når fram. Denna till synes neutrala skiktning visade sig efter noggrannare undersökning att inte alls vara neutral. Skiktet närmast marken upp till 15 meters höjd visade sig vara instabilt och däröver var det stabilt. Utifrån detta dras slutsatsen att dimman är låg endast 15 meter hög under denna period. Vid 12 tiden på dagen den 6 juni sjunker lufttemperaturen dramatiskt under ytvatten temperaturen samtidigt som relativa fuktigheten stiger upp till 100 %. Dimman är nu så pass tjock att den största delen av utstrålningen sker ifrån toppen vilket sänker luft temperaturen flera grader. Då stabiliteten undersöks visar den sig vara instabil skiktad ända upp till högsta mät nivån (28 meter). Antagandet görs att dimman är minst 30 meter djup. Även normaliserad standard avvikelse för temperaturen och den vertikala hastigheten undersöks för att ta reda på om de uppvisar samma variation som i det ostörda gränsskiktet.

Les systèmes de vidéosurveillance utilisent des caméras sophistiquées (caméras réseau, smart caméras) et des serveurs informatiques pour l’enregistrement vidéo dans un système entièrement numérique. Ces systèmes intègrent parfois des centaines de caméras et génèrent une quantité colossale de données, dépassant largement les capacités des agents humains. Ainsi, l'un des défis modernes les plus importants est de faire évoluer un système basé sur le Cloud intégrant plusieurs caméras intelligentes hétérogènes et l'adapter à une architecture Fog/Cloud pour en améliorer les performances. Les FPGA sont de plus en plus présents dans les architectures FCIoT (FoG-Cloud-IoT). Ils sont caractérisés par des modes de configuration dynamiques et partiels, permettant de s'adapter rapidement aux changements survenus tout en augmentant la puissance de calcul disponible. De telles plateformes présentent de sérieux défis scientifiques, notamment en termes de déploiement et de positionnement des FoGs.Cette thèse propose un modèle de vidéosurveillance composé de caméras intelligentes plug & play, dotées de FPGAs dynamiquement reconfigurables sur une base hiérarchique FOG/ CLOUD. Dans ce système fortement évolutif, à la fois en nombre de caméras et de cibles trackées, nous proposons une approche automatique et optimisée d’authentification des caméras et de leur association dynamique avec les FoGs. L’approche proposée comporte également une méthodologie pour l’affectation optimale des trackers matériels aux ressources électroniques disponibles pour maximiser les performances et minimiser la consommation d’énergie. Toutes les contributions ont été validées avec un prototype de taille réelle. / CCTV systems use sophisticated cameras (network cameras, smart cameras) and computer servers for video recording in a fully digital system. They often integrate hundreds of cameras generating a huge amount of data, far beyond human agent monitoring capabilities. One of the most important and modern challenges, in this field, is to scale an existing cloud-based video surveillance system with multiple heterogeneous smart cameras and adapt it to a Fog / Cloud architecture to improve performance without a significant cost overhead. Recently, FPGAs are becoming more and more present in FCIoT (FoG-Cloud-IoT) platform architectures. These components are characterized by dynamic and partial configuration modes, allowing platforms to quickly adapt themselves to changes resulting from an event, while increasing the available computing power. Today, such platforms present a certain number of serious scientific challenges, particularly in terms of deployment and positioning of FoGs. This thesis proposes a video surveillance model composed of plug & play smart cameras, equipped with dynamically reconfigurable FPGAs on a hierarchical FOG / CLOUD basis. In this highly dynamic and scalable system, both in terms of intelligent cameras (resources) and in terms of targets to track, we propose an automatic and optimized approach for camera authentication and their dynamic association with the FOG components of the system. The proposed approach also includes a methodology for an optimal allocation of hardware trackers to the electronic resources available in the system to maximize performance and minimize power consumption. All contributions have been validated with a real size prototype.

Les systèmes d'aide à la conduite (ADAS) ont pour objectif d'assister le conducteur et en particulier d'améliorer la sécurité routière. Pour cela, différents capteurs sont généralement embarqués dans les véhicules afin, par exemple, d'avertir le conducteur en cas de danger présent sur la route. L'utilisation de capteurs de type caméra est une solution économiquement avantageuse et de nombreux ADAS à base de caméra voient le jour. Malheureusement, les performances de tels systèmes se dégradent en présence de conditions météorologiques défavorables, notamment en présence de brouillard ou de pluie, ce qui obligerait à les désactiver temporairement par crainte de résultats erronés. Hors, c'est précisément dans ces conditions difficiles que le conducteur aurait potentiellement le plus besoin d'être assisté. Une fois les conditions météorologiques détectées et caractérisées par vision embarquée, nous proposons dans cette thèse de restaurer l'image dégradée à la sortie du capteur afin de fournir aux ADAS un signal de meilleure qualité et donc d'étendre la gamme de fonctionnement de ces systèmes. Dans l'état de l'art, il existe plusieurs approches traitant la restauration d'images, parmi lesquelles certaines sont dédiées à nos problématiques de brouillard ou de pluie, et d'autres sont plus générales : débruitage, rehaussement du contraste ou de la couleur, "inpainting"... Nous proposons dans cette thèse de combiner les deux familles d'approches. Dans le cas du brouillard notre contribution est de tirer profit de deux types d'approches (physique et signal) afin de proposer une nouvelle méthode automatique et adaptée au cas d'images routières. Nous avons évalué notre méthode à l'aide de critères ad hoc (courbes ROC, MSE, contraste visibles à 5 %, évaluation sur ADAS) appliqués sur des bases de données d'images de synthèse et réelles. Dans le cas de la pluie, une fois les gouttes présentes sur le pare-brise détectées, nous reconstituons les parties masquées de l'image à l'aide d'une méthode d'"inpainting" fondée sur les équations aux dérivées partielles. Les paramètres de la méthode ont été optimisés sur des images routières. Enfin, nous montrons qu'il est possible grâce à cette approche de construire trois types d'applications : prétraitement, traitement et assistance. Dans chaque famille, nous avons proposé et évalué une application spécifique : détection des panneaux dans le brouillard ; détection de l'espace navigable dans le brouillard ; affichage de l'image restaurée au conducteur. / Advanced Driver Assistance Systems (ADAS) are designed to assist the driver and in particular to improve road safety. For this purpose, various sensors are typically embedded in vehicles in order, for example, to alert the driver in case of imminent danger on the road. The use of camera type of sensor is a cost-effective solution and many ADAS based on camera are being created. Unfortunately, the performance of such systems decrease drastically in the presence of adverse weather conditions, especially in the presence of fog or rain, which could oblige to turn off the systems temporarily in order to avoid erroneous results. While, it is precisely in these difficult circumstances that the driver would potentially need the most to be assisted. Once the weather conditions detected and characterized by embedded vision, we propose in this thesis to restore the degraded image to provide a better signal to the ADAS and thus extend the operation range of these systems. In the state of the art, there are several approaches dealing with images restoration, some of which are dedicated to our fog and rain problem and others are more general : denoising, contrast or color enhancement, inpainting... We propose in this work to combine the two families of approaches. In the case of fog our contribution is to take advantage of both approaches (physical and signal) to propose a new automatic method adapted to the case of road images. We evaluated our method using ad hoc criteria (ROC curves, visible contrast to 5%, assessment on ADAS) applied to databases of synthetic and real images. In case of rain, once the drops present on the windshield are detected, we reconstruct the hidden parts of the image using a method of inpainting based on partial differential equations. The method parameters have been optimized on road images. Finally, we show that it is possible with this approach to build three types of applications : preprocessing, processing and assistance. In every family, we have proposed and evaluated a specific application : traffic signs detection during foggy weather; detection of free space in fog conditions and display of the restored image to the driver.

För att installera flera operativsystem samtidigt finns det olika verktyg avsedda för att underlätta denna process. Det finns både kommersiella- och gratisalternativ ute på marknaden. En av de ledande kommersiella replikeringsmjukvarorna är Symantec Ghost. I detta arbete jämförs Symantec Ghosts mot Free open-source ghost (FOG) för att mäta användbarheten med avseende på kritiska attribut. Kritiska attribut är baserade på utförandet av en fullständig replikeringsprocess samt hur en användare upplever hanteringen av mjukvaran. Resultaten består av både kvalitativa och kvantitativa resultat som sammanställs i en jämförelsematris som presenterar för- och nackdelar med mjukvarorna. Resultaten visar att användbarheten är relativt likvärdig men att FOG presterar lite bättre än Symantec Ghost.

Food service establishments that use onsite wastewater treatment systems are experiencing hydraulic and organic overloading of pretreatment systems and/or drain fields. Design guidelines for these systems are typically provided in State regulations and based on residential hydraulic applications. For the purposes of this research, hydraulic loading indicates the daily flow of water directed to the wastewater system. Organic loading refers to the composition of the wastewater as quantified by five-day biochemical oxygen demand (BOD5), total fats, oils and greases (FOG), and total suspended solids (TSS). The first part of this study included an analysis of the central tendencies of analytical data of four wastewater parameters from 28 restaurants representing a broad spectrum of restaurant types. Field sampling consisted of two sets of grab samples collected from each restaurant for six consecutive days at approximately the same time each day. These sets were collected approximately two weeks apart. The numerical data included BOD5, FOG, and TSS. The fourth parameter evaluated was daily flow. Data exploration and statistical analyses of the numerical data from the 28 restaurants was performed with the standard gamma probability distribution model in ExcelTM and used to determine inferences of the analytical data. The analysis shows higher hydraulic and organic values for restaurant wastewater than residential wastewater. The second part of the study included a statistical analysis of restaurant management practices and primary cuisine types and their influence on BOD5, FOG, TSS, and daily flow to determine if management practices and/or cuisine types may be influencing wastewater composition and flow. A self-reporting survey was utilized to collect management practice and cuisine type information. Survey response information and analytical data were entered into an ExcelTM spreadsheet and subsequently incorporated into SASTM statistical software for statistical analysis. Analysis indicated that the number of seats in a restaurant, use of self-serve salad bars, and primary cuisine types are statistically significant indicators of wastewater characteristics.

Au niveau intestinal, le facteur de transcription Gata4 est exprimé dans les cellules épithéliales de la partie proximale de l’intestin grêle. Ce facteur est un régulateur de plusieurs gènes tel celui encodant la sucrase isomaltase. Quelques études ont aussi suggéré que ce facteur est impliqué dans le contrôle de l’expression de molécules de jonction, favorisant ainsi la polarisation des cellules épithéliales en culture. Dans notre laboratoire, des résultats tendent à démontrer que Gata4 est impliqué dans la réponse inflammatoire des cellules épithéliales en régulant, avec ses cofacteurs Cdx2 et Fog1, l’expression génique du peptide antimicrobien Pap1. In vivo, l’invalidation de Gata4 a montré que ce facteur de transcription est impliqué dans le maintien de l’identité et des fonctions du jéjunum par rapport à l’iléon. Cependant, aucune étude ne s’est intéressée à la régulation des molécules de jonction dans ce contexte. La présente étude a pour but de compléter l’étude de la régulation du gène Pap1 par Gata4 et d’étudier le rôle de Gata4 dans le contrôle de l’expression des molécules de jonction chez la souris. Nos résultats confirment le rôle du facteur de transcription Gata4 et de son corépresseur Fog1 dans le contrôle de l’expression de Pap1. La méthode d’interférence à l’ARN dirigée contre Fog1 a permis d’induire spontanément l’expression de Pap1 dans la lignée IEC-6/Cdx2. Chez la souris, la perte de Gata4 modifie l’expression de certaines molécules de jonction cellulaire. Des PCR quantitatifs et des immunobuvardages ont révélé que l’expression de plusieurs molécules de jonction est modulée en absence de Gata4. La Claudine 2 est la molécule de jonction dont l’expression est la plus induite autant au niveau de l’ARNm que de la protéine. Ces modifications entraînent une augmentation du passage paracellulaire du FITC-dextran fluorescent, ce qui suggère que l’épithélium est plus perméable aux macromolécules. Des infections orales par Salmonella Typhimurium ont révélé un passage accru de ces bactéries dans les animaux femelles. L’ensemble de ces travaux suggère que Gata4 est impliqué dans le contrôle de la perméabilité des jonctions intercellulaires ainsi que dans la protection des cellules épithéliales intestinales contre les bactéries.

Framtidens fordon kommer vara väldigt annorlunda jämfört med dagens fordon. Stor del av förändringen kommer ske med hjälp av IoT. Världen kommer bli oerhört uppkopplat, sensorer kommer kunna ta fram data som de flesta av oss inte ens visste fanns. Mer data betyder även mer problem. Enorma mängder data kommer genereras och distribueras av framtidens IoT-enheter och denna data behöver analyseras och lagras på effektiva sätt med hjälp av Big data principer. Fog computing är en utveckling av Cloud tekniken som föreslås som en lösning på många av de problem IoT lider utav. Är tradionella lagringsmöjligheter och analyseringsverktyg tillräckliga för den enorma volymen data som kommer produceras eller krävs det nya tekniker för att stödja utvecklingen? Denna studie kommer försöka besvara frågeställningen: ”Vilka problem och möjligheter får utvecklingen av Fog computing i personbilar för konsumenter?” Frågeställningen besvaras genom en systematisk litteraturstudie. Den systematiska litteraturstudien syfte är identifiera och tolka tidigare litteratur och forskning. Analys av materialet har skett med hjälp av öppen kodning som har använts för att sortera och kategorisera data. Resultat visar att tekniker som IoT, Big data och Fog computing är väldigt integrerade i varandra. I framtidens fordon kommer det finns mycket IoTenheter som producerar enorma mängder data. Fog computing kommer bli en effektiv lösning för att hantera de mängder data från IoT-enheterna med låg fördröjning. Möjligheterna blir nya applikationer och system som hjälper till med att förbättra säkerheten i trafiken, miljön och information om bilens tillstånd. Det finns flera risker och problem som behöver lösas innan en fullskalig version kan börja användas, risker som autentisering av data, integriteten för användaren samt bestämma vilken mobilitetsmodell som är effektivast. / Future vehicles will be very different from today's vehicles. Much of the change will be done using the IoT. The world will be very connected, sensors will be able to access data that most of us did not even know existed. More data also means more problems. Enormous amounts of data will be generated and distributed by the future's IoT devices, and this data needs to be analyzed and stored efficiently using Big data Principles. Fog computing is a development of Cloud technology that is suggested as a solution to many of the problems IoT suffer from. Are traditional storage and analysis tools sufficient for the huge volume of data that will be produced or are new technologies needed to support development? This study will try to answer the question: "What problems and opportunities does the development of Fog computing in passenger cars have for consumers?" The question is answered by a systematic literature study. The objective of the systematic literature study is to identify and interpret previous literature and research. Analysis of the material has been done by using open coding where coding has been used to sort and categorize data. Results show that technologies like IoT, Big data and Fog computing are very integrated in each other. In the future vehicles there will be a lot of IoT devices that produce huge amounts of data. Fog computing will be an effective solution for managing the amount of data from IoT devices with a low latency. The possibilities will create new applications and systems that help improve traffic safety, the environment and information about the car's state and condition. There are several risks and problems that need to be resolved before a full-scale version can be used, such as data authentication, user integrity, and deciding on the most efficient mobility model.

Advancements in technology have brought about a wide variety of devices, such as embedded devices with sensors and actuators, personal computers, smart devices, and health devices. Many of these devices are categorized as “wearables,” meaning that they are intended to be carried and used on one’s body. As this category increases in popularity and functionality, developers will need a convenient way for these devices to communicate with each other and store information in a standardized and ecient manner. The Fog protocol and FogKit framework developed and demonstrated for this thesis address these issues by providing a set of powerful features, including data posting, data querying, event notifications, and network status requests. These features are defined as convenient JSON formatted messages which can be communicated between Bluetooth peripherals using an iOS device running FogKit as router and server.

Indiana University-Purdue University Indianapolis (IUPUI) / Soil moisture is a key variable in dryland ecosystems. Knowing how and to what extent soil moisture is influenced by rainfall and non-rainfall waters (e.g., dew, fog, and water vapor) is essential to understand dryland dynamics. The hyper-arid environment of the Namib Desert with its frequent occurrence of fog events provides an ideal place to conduct research on the rainfall and non-rainfall effects on soil moisture dynamics. Rainfall and soil moisture records was collected from three locations (gravel plain at Gobabeb (GPG), sand dune at Gobabeb (SDG), and gravel plain at Kleinberg (GPK)) within the Namib Desert using CS655 Water Content Reflectometer and tipping-buckets, respectively. The fog data was collected from the FogNet stations. Field observations of rainfall and soil moisture from three study sites suggested that soil moisture dynamics follow rainfall patterns at two gravel plain sites, whereas no significant relationships was observed at the sand dune site. The stochastic modeling results showed that most of soil moisture dynamics can be simulated except the rainless periods. Model sensitivity in response to different soil and vegetation parameters was investigated under diverse soil textures. Sensitivity analyses suggested that soil hygroscopic point (sh), field capacity (sfc) were two main parameters controlling the model output. Despite soil moisture dynamics can be partially explained by rainfall, soil moisture dynamics during rainless period still poorly understood. In addition, characterization of fog distribution in the Namib Desert is still lacking. To this end, nearly two years’ continuous daily records of fog were used to derive fog distribution. The results suggested that fog is able to be well - characterized by a Poisson process with two parameters (arrival rate and average depth). Field observations indicated that there is a moderate positive relationship between soil moisture and fog at GPG and the relationship tend to be less significant at the other two sites. A modified modeling results suggested that mean and general patterns of soil moisture can be captured by the modeling. This thesis is of practical importance for understanding soil moisture dynamics in response to the rainfall and fog changing conditions.

Vehicular ad hoc networks (VANETs) facilitate vehicles to broadcast beacon messages to ensure road safety. The rogue nodes in VANETs broadcast malicious information leading to potential hazards, including the collision of vehicles. Previous researchers used either cryptography, trust values, or past vehicle data to detect rogue nodes, but they suffer from high processing delay, overhead, and false-positive rate (FPR). We propose fog-based rogue nodes detection (F-RouND), a fog computing scheme, which dynamically creates a fog utilizing the on-board units (OBUs) of all vehicles in the region for rogue nodes detection. The novelty of F-RouND lies in providing low processing delays and FPR at high vehicle densities. The performance of our F-RouND framework was carried out with simulations using OMNET ++ and SUMO simulators. Results show that F-RouND ensures 45% lower processing delays, 12% lower overhead, and 36% lower FPR at high vehicle densities compared to existing rogue nodes detection schemes.