The infrared interferometric capabilities of the Large Binocular Telescope with respect to the Galactic Center

The Galactic Centre is nowadays, after its discovery in 1932 by Karl Jansky, still a major focus of current research in astrophysics. It still has a lot of secrets that are to be discovered and provides the unique opportunity to scrutinise new hypothesis. The crucial part for investigating the Galactic Centre and verifying or rejecting new theories is of course observing and measuring objects in the Galactic Centre. Primarily these measurements deal with position determination of celestial objects or determination of structures. The position determination is of great importance for proper motion measurements. Here, the position of a celestial object is measured through different epochs. These observations are not trivial and hold a lot of diffculties. One of the greatest inconveniences are disturbances in Earth’s atmosphere which must passed by signals from far away in order to reach ground based observatories. A solution is to place the observatories in space, but due to maintaining expenditure and cost for bringing the observatories into space, this solution is less practical, although of course space observatories are used for some applicatons. In order to build telescopes with bigger diameters and with a higher resolution, the only practical way is to work with ground based telescopes. In order to overcome the limitation of observing through Earth’s atmosphere, adaptive optics are used. Adaptive optics contain a deformable mirror. The surface of this mirror can be adjusted by servos such that it corrects incoming, disturbed wavefront. To do so a guiding source is required, so that the system has a reference for the correct, undisturbed wavefront. In this thesis the propagation through Earth’s atmosphere is simulated with the layer oriented simulation tools (LOST). The performed simulations contain atmospherical models and produce as result point spread functions (PSF). These PSFs contain the performed corrections of the adaptive optics and show the effects of both the corrected atmospherical and instrumental effects when imaging via ground based telescopes. The simulated telescope is the large binocular telescope (LBT) which is positioned on Mount Graham. Different constellations were simulated with different guiding stars. The obtained PSFs were convolved with different input images of the Galactic Centre which contained science cases in order to get the output image one would obtain when observing the Galactic Centre with the LBT. Finally this output image was de-convolved with PSF in order to get again the input image. This re-convolved input image was further investigated to understand how effciently the science cases can be reconstructed. A measure for the quality of the re-convolution is the error with which the science cases could be located in the re-convolved input image

AnoML-IoT: An End to End Re-configurable Multi-protocol Anomaly Detection Pipeline for Internet of Things

The rapid development in ubiquitous computing has enabled the use of microcontrollers as edge devices. These devices are used to develop truly distributed IoT-based mechanisms where machine learning (ML) models are utilized. However, integrating ML models to edge devices requires an understanding of various software tools such as programming languages and domain-specific knowledge. Anomaly detection is one of the domains where a high level of expertise is required to achieve promising results. In this work, we present AnoML which is an end-to-end data science pipeline that allows the integration of multiple wireless communication protocols, anomaly detection algorithms, deployment to the edge, fog, and cloud platforms with minimal user interaction. We facilitate the development of IoT anomaly detection mechanisms by reducing the barriers that are formed due to the heterogeneity of an IoT environment. The proposed pipeline supports four main phases: (i) data ingestion, (ii) model training, (iii) model deployment, (iv) inference and maintaining. We evaluate the pipeline with two anomaly detection datasets while comparing the efficiency of several machine learning algorithms within different nodes. We also provide the source code (https://gitlab.com/IOTGarage/anoml-iot-analytics) of the developed tools which are the main components of the pipeline.Comment: Elsevier Internet of Things, Volume 16, 100437, December 202

Cybersecurity of Industrial Cyber-Physical Systems: A Review

Industrial cyber-physical systems (ICPSs) manage critical infrastructures by controlling the processes based on the "physics" data gathered by edge sensor networks. Recent innovations in ubiquitous computing and communication technologies have prompted the rapid integration of highly interconnected systems to ICPSs. Hence, the "security by obscurity" principle provided by air-gapping is no longer followed. As the interconnectivity in ICPSs increases, so does the attack surface. Industrial vulnerability assessment reports have shown that a variety of new vulnerabilities have occurred due to this transition while the most common ones are related to weak boundary protection. Although there are existing surveys in this context, very little is mentioned regarding these reports. This paper bridges this gap by defining and reviewing ICPSs from a cybersecurity perspective. In particular, multi-dimensional adaptive attack taxonomy is presented and utilized for evaluating real-life ICPS cyber incidents. We also identify the general shortcomings and highlight the points that cause a gap in existing literature while defining future research directions.Comment: 32 pages, 10 figure

CASPER: Context-aware anomaly detection system for industrial robotic arms

With the arrival of industry 4.0, industrial control systems are converted into “smart” industrial cyber-physical systems that depend on high interconnectivity enabled by ubiquitous applications. As these applications can significantly reduce maintenance and supervision costs, the integration of these applications is done with the “cost” being the focus overlooking the security aspect that suffers from the vulnerabilities that occurred due to increased attack surface. The adversaries aim to create physical alterations by exploiting these cyber vulnerabilities via so-called “cyber-physical” attacks. In this work, we introduce CASPER, a context-aware ubiquitous machine learning-based anomaly detection infrastructure that utilizes ubiquitous computing to detect anomalies of an industrial robotic arm. CASPER monitors the robotic arm’s movements to ensure the arm follows a predetermined trajectory. The CASPER can reach an accuracy and F1 score of 97% which is promising for an industrial domain. We modify the joint velocity of an industrial robotic arm to create anomalies which we detect via CASPER

AnoML-IoT: an end to end re-configurable multi-protocol anomaly detection pipeline for Internet of Things

The rapid development in ubiquitous computing has enabled the use of microcontrollers as edge devices. These devices are used to develop truly distributed IoT-based mechanisms where machine learning (ML) models are utilized. However, integrating ML models to edge devices requires an understanding of various software tools such as programming languages and domain-specific knowledge. Anomaly detection is one of the domains where a high level of expertise is required to achieve promising results. In this work, we present AnoML which is an end-to-end data science pipeline that allows the integration of multiple wireless communication protocols, anomaly detection algorithms, deployment to the edge, fog, and cloud platforms with minimal user interaction. We facilitate the development of IoT anomaly detection mechanisms by reducing the barriers that are formed due to the heterogeneity of an IoT environment. The proposed pipeline supports four main phases: (i) data ingestion, (ii) model training, (iii) model deployment, (iv) inference and maintaining. We evaluate the pipeline with two anomaly detection datasets while comparing the efficiency of several machine learning algorithms within different nodes. We also provide the source code of the developed tools which are the main components of the pipeline

Cybersecurity of industrial cyber-physical systems: a review

Industrial cyber-physical systems (ICPSs) manage critical infrastructures by controlling the processes based on the “physics” data gathered by edge sensor networks. Recent innovations in ubiquitous computing and communication technologies have prompted the rapid integration of highly interconnected systems to ICPSs. Hence, the “security by obscurity” principle provided by air-gapping is no longer followed. As the interconnectivity in ICPSs increases, so does the attack surface. Industrial vulnerability assessment reports have shown that a variety of new vulnerabilities have occurred due to this transition. Although there are existing surveys in this context, very little is mentioned regarding the outputs of these reports. While these reports show that the most exploited vulnerabilities occur due to weak boundary protection, these vulnerabilities also occur due to limited or ill defined security policies. However, current literature focuses on intrusion detection systems (IDS), network traffic analysis (NTA) methods, or anomaly detection techniques. Hence, finding a solution for the problems mentioned in these reports is relatively hard. We bridge this gap by defining and reviewing ICPSs from a cybersecurity perspective. In particular, multi-dimensional adaptive attack taxonomy is presented and utilized for evaluating real-life ICPS cyber incidents. Finally, we identify the general shortcomings and highlight the points that cause a gap in existing literature while defining future research directions

CT-guided transthoracic biopsy: histopathologic results and complication rates

PURPOSEWe aimed to investigate the effectiveness and complications of transthoracic CT-guided biopsy techniques.METHODSA total of 94 CT-guided percutaneous transthoracic biopsy procedures performed in 85 patients were retrospectively evaluated. Core biopsy technique was used in 87 procedures and transthoracic fine-needle aspiration biopsy was used in seven procedures.RESULTSDiagnostic results were achieved in 79 of 94 biopsy procedures. Pathology results were malignant in 54 patients, suspicious for malignancy in three patients, benign in five patients, and benign nonspecific in 17 patients. Specific diagnoses were obtained in 59 patients (62.8%) using core biopsy, but no specific diagnosis could be reached with transthoracic fine-needle aspiration biopsy. Complications included pneumothorax in 27 patients (28.7%) and parenchymal hemorrhage during and after the procedure in eight patients (8.5%). CONCLUSIONSCT-guided percutaneous transthoracic needle biopsy is a highly accurate procedure for histopathological diagnosis of thoracic masses. In addition, percutaneous transthoracic biopsy has an acceptably low complication rate and it reduces the need for more invasive surgical procedures

A rare cause of pituitary apoplexy: Cabergoline therapy

© 2018, Acta Endocrinologica Foundation. All rights reserved.Pituitary apoplexy (PA) is a life-threatening clinical syndrome. Dopamine receptor agonists are the drugs of choice in the treatment of prolactinomas. The use of cabergoline is reported to cause an increased risk of PA, particularly in macroprolactinomas of cystic nature. In this report, we present a patient with a cystic macroprolactinoma who developed PA on the 16th week of cabergoline treatment

Eagle syndrome causing vascular compression with cervical rotation : case report

BACKGROUND: Eagle syndrome is a condition caused by an elongated styloid process. Unilateral face, neck and ear pain, stinging pain, foreign body sensation and dysphagia can be observed with this syndrome. Rarely, the elongated styloid process may cause pain by compressing the cervical segment of the internal carotid and the surrounding sympathetic plexus, and that pain spreading along the artery can cause neurological symptoms such as vertigo and syncope. CASE REPORT: In this case report we presented a very rare eagle syndrome with neurological symptoms that occurred suddenly with cervical rotation. The symptoms disappeared as suddenly as they occurred, with the release of pressure in neutral position. We also discussed CT angiographic findings of this case. CONCLUSIONS: Radiological diagnosis of the Eagle syndrome that is manifested with a wide variety of symptoms and causes diagnostic difficulties when it is not considered in the differential diagnosis is easy in patients with specific findings. CT angiography is a fast and effective examination in terms of showing compression in patients with the Eagle syndrome that is considered to be atypical and causes vascular compression