Outlier Mining Methods Based on Graph Structure Analysis

Outlier detection in high-dimensional datasets is a fundamental and challenging problem across disciplines that has also practical implications, as removing outliers from the training set improves the performance of machine learning algorithms. While many outlier mining algorithms have been proposed in the literature, they tend to be valid or efficient for specific types of datasets (time series, images, videos, etc.). Here we propose two methods that can be applied to generic datasets, as long as there is a meaningful measure of distance between pairs of elements of the dataset. Both methods start by defining a graph, where the nodes are the elements of the dataset, and the links have associated weights that are the distances between the nodes. Then, the first method assigns an outlier score based on the percolation (i.e., the fragmentation) of the graph. The second method uses the popular IsoMap non-linear dimensionality reduction algorithm, and assigns an outlier score by comparing the geodesic distances with the distances in the reduced space. We test these algorithms on real and synthetic datasets and show that they either outperform, or perform on par with other popular outlier detection methods. A main advantage of the percolation method is that is parameter free and therefore, it does not require any training; on the other hand, the IsoMap method has two integer number parameters, and when they are appropriately selected, the method performs similar to or better than all the other methods tested.Peer ReviewedPostprint (published version

Supervised machine learning for the early prediction of acute respiratory distress syndrome (ARDS).

PURPOSE: Acute respiratory distress syndrome (ARDS) is a serious respiratory condition with high mortality and associated morbidity. The objective of this study is to develop and evaluate a novel application of gradient boosted tree models trained on patient health record data for the early prediction of ARDS. MATERIALS AND METHODS: 9919 patient encounters were retrospectively analyzed from the Medical Information Mart for Intensive Care III (MIMIC-III) data base. XGBoost gradient boosted tree models for early ARDS prediction were created using routinely collected clinical variables and numerical representations of radiology reports as inputs. XGBoost models were iteratively trained and validated using 10-fold cross validation. RESULTS: On a hold-out test set, algorithm classifiers attained area under the receiver operating characteristic curve (AUROC) values of 0.905 when tested for the detection of ARDS at onset and 0.827, 0.810, and 0.790 for the prediction of ARDS at 12-, 24-, and 48-h windows prior to onset, respectively. CONCLUSION: Supervised machine learning predictions may help predict patients with ARDS up to 48 h prior to onset

Top 10 most cited articles related to SARS-CoV-2 infection of the 2020 year

Rezumat. Introducere. La sfârșitul lunii decembrie 2019, în provincia Wuhan (China) a fost raportat un focar de pneumonie atipică cauzată de un nou tip de coronavirus (SARS-CoV-2), de o contagiozitate exponenţială și letalitate înaltă. Infecţia cu COVID-19 s-a dovedit a fi o boală zoonotică cu rezervor necunoscut, transmitere de la persoană-la-persoană (prin picături, aerosolii, obiecte și suprafeţe contaminate) și cu afinitate pentru receptorul ACE2. La scurt timp sistemele medicale din lume s-au pomenit într-un colaps greu de imaginat pe cele mai diverse segmente. Material și metode. A fost dată o căutare în platforma de publicaţii „Intensive Care Medicine” pentru articolele anului 2020 cu acces deschis relaţionate cu tematica COVID-19. În ordinea descrescătoare a frecvenţei descărcărilor și citării, au fost preluate primele 10 titluri populare. Au fost examinate surse în limba engleză, cu următoarele cuvinte cheie: „management Covid-19”, „COVID-19”, „SARS-CoV-2 mortality”, „Covid-19 prevention”. Rezultate. Au fost identificate 219 de publicaţii, printre care studii pilot, reviste ale literaturii, recomandări și ghiduri de bună practică, scrisori către editor și sinteze de actualizări. Publicaţiile potenţial eligibile au inclus: studii clinice (uni- / multicentrice), fundamentale, ghiduri, epidemiologice și din domeniul sănătăţii publice. Au fost evidenţiate 10 titluri, subiectul cărora a fost infecţia cu SARS-CoV-2. Informaţia a fost analizată și sintetizată în prezenta revistă a literaturii. Concluzii. De-a lungul primului an de pandemie COVID-19, comunitatea clinico-știinţifică internaţională s-a luptat și concomitent a studiat maladia provocată de noul tip de coronavirus, demonstrând progrese cu referire la înţelegerea fiziopatologiei și caracterizarea formelor de evoluţie a maladiei, evaluarea continuă a tratamentelor antivirale, antiinflamatoare și imune existente, determinarea strategiei de oxigenare și ventilare, trasarea recomandărilor terapeutice – toate realizate contra cronometru și într-o luptă atroce pentru fiecare viaţă umană.Abstract. Introduction. At the end of the December of 2019, an outbreak of atypical pneumonia caused by a new type of coronavirus (SARS-CoV-2), with exponential contagiousness and high lethality, was reported in Wuhan Province (China). COVID-19 infection has been shown to be a zoonotic disease with unknown reservoir, person-to-person transmission (through droplets, aerosols, objects and contaminated surfaces) and with affinity for the ACE2 receptor. Soon, the medical systems of the world found themselves in an unimaginable collapse of the most segments. Material and methods. It was performed a search on the publication platform ”Intensive Care Medicine” for the open access articles related to COVID-19 published in English language during the 2020 year. In descending order according to the frequency of downloads and citations, the first 10 popular titles were taken over. Searching keywords: ”Covid-19 management”, ”COVID-19”, ”SARS-CoV-2 mortality”, ”Covid-19 prevention”. Results. It were identified 219 publications: pilot studies, literature reviews, recommendations and guides of good practice, letters to the editor and summaries of updates. Potentially eligible publications included: clinical trials (uni- / multicenter), fundamental, epidemiological and public health guidelines. Ten titles the subject of which was SARS-CoV-2 infection were highlighted. The information was analysed and synthesized in the present literature review. Conclusion. During the first year of the COVID-19 pandemic, the international medical and scientific community has been fighting and, in the same time, studying the disease caused by the new type of coronavirus. Meanwhile, it was registered a progress in understanding of the underling pathophysiology and disease forms, with continuous re-evaluation and update of existing antiviral, anti-inflammatory and immune treatments, it were determined oxygenation and ventilation strategies, underlined therapeutic recommendations – all of this timed and simultaneously with an atrocious fight for every human life

System Development of an Unmanned Ground Vehicle and Implementation of an Autonomous Navigation Module in a Mine Environment

There are numerous benefits to the insights gained from the exploration and exploitation of underground mines. There are also great risks and challenges involved, such as accidents that have claimed many lives. To avoid these accidents, inspections of the large mines were carried out by the miners, which is not always economically feasible and puts the safety of the inspectors at risk. Despite the progress in the development of robotic systems, autonomous navigation, localization and mapping algorithms, these environments remain particularly demanding for these systems. The successful implementation of the autonomous unmanned system will allow mine workers to autonomously determine the structural integrity of the roof and pillars through the generation of high-fidelity 3D maps. The generation of the maps will allow the miners to rapidly respond to any increasing hazards with proactive measures such as: sending workers to build/rebuild support structure to prevent accidents. The objective of this research is the development, implementation and testing of a robust unmanned ground vehicle (UGV) that will operate in mine environments for extended periods of time. To achieve this, a custom skid-steer four-wheeled UGV is designed to operate in these challenging underground mine environments. To autonomously navigate these environments, the UGV employs the use of a Light Detection and Ranging (LiDAR) and tactical grade inertial measurement unit (IMU) for the localization and mapping through a tightly-coupled LiDAR Inertial Odometry via Smoothing and Mapping framework (LIO-SAM). The autonomous navigation module was implemented based upon the Fast likelihood-based collision avoidance with an extension to human-guided navigation and a terrain traversability analysis framework. In order to successfully operate and generate high-fidelity 3D maps, the system was rigorously tested in different environments and terrain to verify its robustness. To assess the capabilities, several localization, mapping and autonomous navigation missions were carried out in a coal mine environment. These tests allowed for the verification and tuning of the system to be able to successfully autonomously navigate and generate high-fidelity maps

Handling of advanced persistent threats and complex incidents in healthcare, transportation and energy ICT infrastructures

In recent years, the use of information technologies in Critical Infrastructures is gradually increasing. Although this brings benefits, it also increases the possibility of security attacks. Despite the availability of various advanced incident handling techniques and tools, there is still no easy, structured, standardized and trusted way to manage and forecast interrelated cybersecurity incidents. This paper introduces CyberSANE, a novel dynamic and collaborative, warning and response system, which supports security officers and operators to recognize, identify, dynamically analyse, forecast, treat and respond to security threats and risks and and it guides them to handle effectively cyber incidents. The components of CyberSANE are described along with a description of the CyberSANE data flow. The main novelty of the CyberSANE system is the fact that it enables the combination of active incident handling approaches with reactive approaches to support incidents of compound, highly dependent Critical Information Infrastructures. The benefits and added value of using CyberSANE is described with the aid of a set of cyber-attack scenarios

CONSIDERING SAFETY AND SECURITY IN AV FUNCTIONS

Autonomous vehicles (AVs) are coming to our streets. Due to the presence of highly complex software systems in AVs, a new hazard analysis technique is needed to meet stringent safety standards. Also, safety and security are inter-dependent and inter-related aspects of AV. They are focused on shielding the vehicles from deliberate attacks (security issue) as well as accidental failures (safety concern), that might lead to loss of lives and injuries to the occupants. So, the current research work has two key components: functional safety and cybersecurity of the autonomous systems. For the safety analysis, we have applied System Theoretic Process Analysis (STPA), which is built on Systems Theoretic Accident Modeling and Processes (STAMP). STAMP is a powerful tool that can identify, define, analyze, and mitigate hazards from the earliest conceptual stage of development to the operation of a system. Applying STPA to autonomous vehicles demonstrates STPA's applicability to preliminary hazard analysis, alternative available, developmental tests, organizational design, and functional design of each unique safety operation. This thesis describes the STPA process used to generate system design requirements for an Autonomous Emergency Braking (AEB) system using a top-down analysis approach for the system safety. The research makes the following contributions to practicing STPA for safety and security: 1. It describes the incorporation of safety and security analysis in one process and discusses the benefits of this; 2. It provides an improved, structural approach for scenario analysis, concentrating on safety and security; 3. It demonstrates the utility of STPA for gap analysis of existing designs in the automotive domain; 4. It provides lessons learned throughout the process of applying STPA and STPA-Sec. Controlling a physical process is associated with dependability requirements in a cyber-physical system (CPS). Cyberattacks can lead to the dependability requirements not being in the acceptable range. Thus, monitoring of the cyber-physical system becomes inevitable for the detection of the deviations in the system from normal operation. One of the main issues is understanding the rationale behind these variations in a reliable manner. Understanding the reason for the variation is crucial in the execution of accurate and time-based control resolution, for mitigating the cyberattacks as well as other reasons of reduced dependability. Currently, we are using evidential networks to solve the reliability issue. In the present work, we are presenting a cyber-physical system analysis where the evidential networks are used for the detection of attacks. The results obtained from the STPA analysis, which provides the technical safety requirements, can be combined with the EN analysis, which can be used efficiently to detect the quality of the used sensor to justify whether the CPS is suitable for the safe and secure design

A paradigm shift in the EU's Common Foreign and Security Policy: from transformation to resilience

The EU's Common Foreign and Security Policy (CFSP) is thriving. To the great surprise of many observers, there has been a strong increase in the conceptual and practical activity of the CFSP over the past few months, comparable only to its revival after the Kosovo crisis. In a speech in June 2017, German Chancellor Angela Merkel evoked the European spirit and affirmed that Europe would no longer be able to rely solely on others in the future. In all European policy areas that deal with foreign, security and defence issues, new institutions and political initiatives are being created, joint security research is being initiated, and new acts of law are being prepared. How can we explain this renaissance of a policy area that was assumed dead? What legal and political dynamics have contributed to its revival? It is significant that foreign and security policy, which used to be purely political areas, are increasingly subject to legal reform and incorporation into the European legal community. Moreover, the ECJ is more and more active in dissolving the old distinctions between political and legal integration and between the EU's internal and external dimensions. (author's abstract

Training of Crisis Mappers and Map Production from Multi-sensor Data: Vernazza Case Study (Cinque Terre National Park, Italy)

This aim of paper is to presents the development of a multidisciplinary project carried out by the cooperation between Politecnico di Torino and ITHACA (Information Technology for Humanitarian Assistance, Cooperation and Action). The goal of the project was the training in geospatial data acquiring and processing for students attending Architecture and Engineering Courses, in order to start up a team of "volunteer mappers". Indeed, the project is aimed to document the environmental and built heritage subject to disaster; the purpose is to improve the capabilities of the actors involved in the activities connected in geospatial data collection, integration and sharing. The proposed area for testing the training activities is the Cinque Terre National Park, registered in the World Heritage List since 1997. The area was affected by flood on the 25th of October 2011. According to other international experiences, the group is expected to be active after emergencies in order to upgrade maps, using data acquired by typical geomatic methods and techniques such as terrestrial and aerial Lidar, close-range and aerial photogrammetry, topographic and GNSS instruments etc.; or by non conventional systems and instruments such us UAV, mobile mapping etc. The ultimate goal is to implement a WebGIS platform to share all the data collected with local authorities and the Civil Protectio