Intelligent Street Light Monitoring System Using Wireless Sensor Network

This aim of this project is to develop a system to monitor the condition of the street light using wireless network. To achieve this objective, a sensor is developed and to be placed at a street light. The project concerns about the communications between a few sensors, one on a street light with another one on a different street light

Switching GAN-based Image Filters to Improve Perception for Autonomous Driving

Autonomous driving holds the potential to increase human productivity, reduce accidents caused by human errors, allow better utilization of roads, reduce traffic accidents and congestion, free up parking space and provide many other advantages. Perception of Autonomous Vehicles (AV) refers to the use of sensors to perceive the world, e.g. using cameras to detect and classify objects. Traffic scene understanding is a key research problem in perception in autonomous driving, and semantic segmentation is a useful method to address this problem. Adverse weather conditions are a reality that AV must contend with. Conditions like rain, snow, haze, etc. can drastically reduce visibility and thus affect computer vision models. Models for perception for AVs are currently designed for and tested on predominantly ideal weather conditions under good illumination. The most complete solution may be to have the segmentation networks be trained on all possible adverse conditions. Thus a dataset to train a segmentation network to make it robust to rain would need to have adequate data that cover these conditions well. Moreover, labeling is an expensive task. It is particularly expensive for semantic segmentation, as each object in a scene needs to be identified and each pixel annotated in the right class. Thus, the adverse weather is a challenging problem for perception models in AVs. This thesis explores the use of Generative Adversarial Networks (GAN) in order to improve semantic segmentation. We design a framework and a methodology to evaluate the proposed approach. The framework consists of an Adversity Detector, and a series of denoising filters. The Adversity Detector is an image classifier that takes as input clear weather or adverse weather scenes, and attempts to predict whether the given image contains rain, or puddles, or other conditions that can adversely affect semantic segmentation. The filters are denoising generative adversarial networks that are trained to remove the adverse conditions from images in order to translate the image to a domain the segmentation network has been trained on, i.e. clear weather images. We use the prediction from the Adversity Detector to choose which GAN filter to use. The methodology we devise for evaluating our approach uses the trained filters to output sets of images that we can then run segmentation tasks on. This, we argue, is a better metric for evaluating the GANs than similarity measures such as SSIM. We also use synthetic data so we can perform systematic evaluation of our technique. We train two kinds of GANs, one that uses paired data (CycleGAN), and one that does not (Pix2Pix). We have concluded that GAN architectures that use unpaired data are not sufficiently good models for denoising. We train the denoising filters using the other architecture and we found them easy to train, and they show good results. While these filters do not show better performance than when we train our segmentation network with adverse weather data, we refer back to the point that training the segmentation network requires labelled data which is expensive to collect and annotate, particularly for adverse weather and lighting conditions. We implement our proposed framework and report a 17\% increase in performance in segmentation over the baseline results obtained when we do not use our framework

Increase budget revenues of various levels by economically limiting tax paying potential

The article is devoted to the analysis of the economic limitation of tax potential in budget revenues. Moreover, this paper makes scrutinized investigations on the assessment of tax potential and tax paying potential. Therefore, analyses make both theoretical and practical conclusions with suitable recommendations on the growth of tax revenues in the budget system. Keywords: tax, taxation, tax potential, tax burden, tax capacity DOI: 10.7176/EJBM/11-10-10 Publication date: April 30th 201

Mobilnost in identiteta v umetnosti in literaturi Etel Adnan

This article is based on a literary reading of two books by Etel Adnan: In the Heart of the Heart of Another Country and Of Cities & Women (Letters to Fawwaz), and on an interview that the author personally conducted with her in 2018. It examines Adnan’s sense of nomadism in her art and literature. She is born into a nomadic culture and moves as an intellectual nomad from Lebanon to Paris, and then to California, and finally returns to Lebanon before having to escape due to the civil war. Her nomadism gives her an inspiring openness, creating a state of béance – the freedom from borders postulated by Bouraoui.Članek temelji na literarni analizi dveh knjig Etel Adnan, in sicer V srcu srca druge države (In the Heart of the Heart of Another Country) in Mesta in ženske (Pisma Fawwazu) (Cities&Women, Letters to Fawwaz) ter osebnem intervjuju z umetnico iz leta 2018. Osrednja tema članka je preučevanje vpliva nomadstva v umetnosti in literaturi Etel Adnan. Umetnica izhaja iz nomadske kulture in se je kot intelektualna nomadka iz Libanona najprej preselila v Pariz, nato v Kalifornijo, ko pa se je končno vrnila v Libanon, je morala državo zaradi državljanske vojne znova zapustiti. Njena navdihujoča odprtost izhaja iz nomadskega načina življenja, ki ustvarja stanje béance, kar, kot predvideva Bourauoi, pomeni »svobodo od meja«

Paramètres de conception optimaux pour maximiser le rapport contraste à bruit pour scanners TEP avec temps de vol

Abstract : Time-of-flight (TOF) positron emission tomography (PET) scanners improve contrast-tonoise ratio (CNR) that translates into reducing the scan time or the required injected dose. During the past years, TOF PET has evolved towards temporal resolutions of the order of 200 ps, corresponding to a spatial uncertainty of 30 mm along the line of response (LOR) defined by the two annihilation photons. Although this location uncertainty is sufficient to improve the effective sensitivity of clinical scanners, resolving small size tissues such as a lymph node, or small animal organs would require the timing performance to be less than 50 ps to resolve objects smaller than ⇠ 10 mm. A coincidence time resolution around 10 ps would even allow to avoid tomographic reconstruction of PET images. Obtaining good image performance in PET demands tackling simultaneously all image quality parameters, including spatial resolution, sensitivity, and CNR. However, this involves difficult trade-offs as studies have demonstrated that choices made at the design level for the detector configuration may enhance some image quality parameters but are then detrimental to others. It is therefore mandatory to identify and carefully investigate the factors contributing to the CNR, one of the most important parameter for image quality. One such factor is the choice of crystal thickness that affects coincidence time resolution and thus CNR. Although improved coincidence time resolution increases the chance of small lesion detectability, trade-offs should be studied to find an optimum compromise maximizing the image performance. The motivation underlying this research is to determine the limit where TOF adds gain in small animal PET imaging and also investigate trade-offs between crystal length, timing resolution, and sensitivity to find the optimum image quality. These trade-offs target the coincidence time resolution improvement to enhance CNR performance without compromising the other parameters of image quality. It is demonstrated that a coincidence time resolution of 100 ps is the threshold where TOF starts to improve the image performance of a small animal scanner. In addition, it is shown that the crystal thickness can be reduced by 19 % without loss on the imaging performance. A model is also proposed that describes the CNR performance with a relatively high level of confidence at early stages of the design, and can be used as a guide to design the future generation of scanners. This is followed by introducing a new phantom purposely designed to study TOF benefits and impacts on lesion detectability for PET scanners.Les scanners de tomographie d’émission par positrons (TEP) par temps de vol (TdV) augmentent le rapport contraste à bruit (RCB) en réduisant le bruit de fond. Ceci se traduit par un temps d’acquisition plus court ou une dose réduite. Au cours des années, la TEP-TdV a évolué vers des résolutions temporelles de l’ordre de 200 ps, ce qui correspond à une incertitude spatiale de 30 mm. Bien que cela soit suffisant pour améliorer la sensibilité effective des scanners cliniques, résoudre des petites structures comme les ganglions lymphatiques, ou des organes de petits animaux nécessite des résolutions temporelles inférieures à 50 ps pour résoudre un objet inférieur à ∼ 10 mm. Une résolution temporelle de 10 mm permettrait même d’éviter la reconstruction tomographique des images TEP. L’obtention d’une bonne performance d’image en TEP nécessite d’aborder simultanément tous les paramètres de qualité d’image, y compris la résolution spatiale, la sensibilité et le RCB. Cependant, il est peu probable que cela se produise, car des études ont démontré que les choix de conception du détecteur peuvent favoriser certains paramètres de qualité d’image, mais en dégrader d’autres. On doit donc cibler les facteurs contribuant au RCB, l’un des paramètres importants de la qualité d’image. Un de ces facteurs est le choix de l’épaisseur du cristal qui affecte la résolution temporelle et donc, le RCB. Bien qu’une résolution temporelle améliorée augmente la détectabilité des petites lésions, on doit étudier les compromis afin de trouver un point d’équilibre offrant à la meilleure performance d’image possible. La motivation de cette recherche est de déterminer la limite à partir de laquelle le TdV améliore la qualité de l’imagerie des petits animaux et également, d’étudier les compromis nécessaires entre la longueur des cristaux, la résolution temporelle et la sensibilité pour atteindre la qualité d’image optimale. Ces compromis ciblent l’amélioration de la résolution temporelle pour améliorer les performances du RCB sans compromettre les autres paramètres de qualité d’image. Ces travaux démontrent qu’une résolution temporelle de 100 ps est le seuil à partir duquel le TdV améliore le performance RBC de l’imagerie des petits animaux. De plus, ils montrent que le volume du cristal peut être réduit de 19 % sans détériorer l’image. Un modèle est également proposé pour prédire le RCB avec un niveau de confiance relativement élevé et il peut être utilisé comme guide pour concevoir la prochaine génération de scanners. L’introduction d’une nouvelle mire élaborée pour étudier les avantages et les impacts du TdV sur la détectabilité des lésions pour les scanners TdV est par la suite présentée

A New Hybrid Method of IPv6 Addressing in the Internet of Things

Humans have always been seeking greater control over their surrounding objects. Today, with the help of Internet of Things (IoT), we can fulfill this goal. In order for objects to be connected to the internet, they should have an address, so that they can be detected and tracked. Since the number of these objects are very large and never stop growing, addressing space should be used, which can respond to this number of objects. In this regard, the best option is IPv6. Addressing has different methods, the most important of which are introduced in this paper. The method presented in this paper is a hybrid addressing method which uses EPC and ONS IP. The method proposed in this paper provides a unique and hierarchical IPv6 address for each object. This method is simple and does not require additional hardware for implantation. Further, the addressing time of this method is short while its scalability is high, and is compatible with different EPC standards