Benefits and limits of machine learning for the implicit coordination on SON functions

Bedingt durch die Einführung neuer Netzfunktionen in den Mobilfunknetzen der nächsten Generation, z. B. Slicing oder Mehrantennensysteme, sowie durch die Koexistenz mehrerer Funkzugangstechnologien, werden die Optimierungsaufgaben äußerst komplex und erhöhen die OPEX (OPerational EXpenditures). Um den Nutzern Dienste mit wettbewerbsfähiger Dienstgüte (QoS) zu bieten und gleichzeitig die Betriebskosten niedrig zu halten, wurde von den Standardisierungsgremien das Konzept des selbstorganisierenden Netzes (SON) eingeführt, um das Netzmanagement um eine Automatisierungsebene zu erweitern. Es wurden dafür mehrere SON-Funktionen (SFs) vorgeschlagen, um einen bestimmten Netzbereich, wie Abdeckung oder Kapazität, zu optimieren. Bei dem konventionellen Entwurf der SFs wurde jede Funktion als Regler mit geschlossenem Regelkreis konzipiert, der ein lokales Ziel durch die Einstellung bestimmter Netzwerkparameter optimiert. Die Beziehung zwischen mehreren SFs wurde dabei jedoch bis zu einem gewissen Grad vernachlässigt. Daher treten viele widersprüchliche Szenarien auf, wenn mehrere SFs in einem mobilen Netzwerk instanziiert werden. Solche widersprüchlichen Funktionen in den Netzen verschlechtern die QoS der Benutzer und beeinträchtigen die Signalisierungsressourcen im Netz. Es wird daher erwartet, dass eine existierende Koordinierungsschicht (die auch eine Entität im Netz sein könnte) die Konflikte zwischen SFs lösen kann. Da diese Funktionen jedoch eng miteinander verknüpft sind, ist es schwierig, ihre Interaktionen und Abhängigkeiten in einer abgeschlossenen Form zu modellieren. Daher wird maschinelles Lernen vorgeschlagen, um eine gemeinsame Optimierung eines globalen Leistungsindikators (Key Performance Indicator, KPI) so voranzubringen, dass die komplizierten Beziehungen zwischen den Funktionen verborgen bleiben. Wir nennen diesen Ansatz: implizite Koordination. Im ersten Teil dieser Arbeit schlagen wir eine zentralisierte, implizite und auf maschinellem Lernen basierende Koordination vor und wenden sie auf die Koordination zweier etablierter SFs an: Mobility Robustness Optimization (MRO) und Mobility Load Balancing (MLB). Anschließend gestalten wir die Lösung dateneffizienter (d. h. wir erreichen die gleiche Modellleistung mit weniger Trainingsdaten), indem wir eine geschlossene Modellierung einbetten, um einen Teil des optimalen Parametersatzes zu finden. Wir nennen dies einen "hybriden Ansatz". Mit dem hybriden Ansatz untersuchen wir den Konflikt zwischen MLB und Coverage and Capacity Optimization (CCO) Funktionen. Dann wenden wir ihn auf die Koordinierung zwischen MLB, Inter-Cell Interference Coordination (ICIC) und Energy Savings (ES) Funktionen an. Schließlich stellen wir eine Möglichkeit vor, MRO formal in den hybriden Ansatz einzubeziehen, und zeigen, wie der Rahmen erweitert werden kann, um anspruchsvolle Netzwerkszenarien wie Ultra-Reliable Low Latency Communications (URLLC) abzudecken.Due to the introduction of new network functionalities in next-generation mobile networks, e.g., slicing or multi-antenna systems, as well as the coexistence of multiple radio access technologies, the optimization tasks become extremely complex, increasing the OPEX (OPerational EXpenditures). In order to provide services to the users with competitive Quality of Service (QoS) while keeping low operational costs, the Self-Organizing Network (SON) concept was introduced by the standardization bodies to add an automation layer to the network management. Thus, multiple SON functions (SFs) were proposed to optimize a specific network domain, like coverage or capacity. The conventional design of SFs conceived each function as a closed-loop controller optimizing a local objective by tuning specific network parameters. However, the relationship among multiple SFs was neglected to some extent. Therefore, many conflicting scenarios appear when multiple SFs are instantiated in a mobile network. Having conflicting functions in the networks deteriorates the users’ QoS and affects the signaling resources in the network. Thus, it is expected to have a coordination layer (which could also be an entity in the network), conciliating the conflicts between SFs. Nevertheless, due to interleaved linkage among those functions, it is complex to model their interactions and dependencies in a closed form. Thus, machine learning is proposed to drive a joint optimization of a global Key Performance Indicator (KPI), hiding the intricate relationships between functions. We call this approach: implicit coordination. In the first part of this thesis, we propose a centralized, fully-implicit coordination approach based on machine learning (ML), and apply it to the coordination of two well-established SFs: Mobility Robustness Optimization (MRO) and Mobility Load Balancing (MLB). We find that this approach can be applied as long as the coordination problem is decomposed into three functional planes: controllable, environmental, and utility planes. However, the fully-implicit coordination comes at a high cost: it requires a large amount of data to train the ML models. To improve the data efficiency of our approach (i.e., achieving good model performance with less training data), we propose a hybrid approach, which mixes ML with closed-form models. With the hybrid approach, we study the conflict between MLB and Coverage and Capacity Optimization (CCO) functions. Then, we apply it to the coordination among MLB, Inter-Cell Interference Coordination (ICIC), and Energy Savings (ES) functions. With the hybrid approach, we find in one shot, part of the parameter set in an optimal manner, which makes it suitable for dynamic scenarios in which fast response is expected from a centralized coordinator. Finally, we present a manner to formally include MRO in the hybrid approach and show how the framework can be extended to cover challenging network scenarios like Ultra-Reliable Low Latency Communications (URLLC)

Impact of COVID-19 on cardiovascular testing in the United States versus the rest of the world

Objectives: This study sought to quantify and compare the decline in volumes of cardiovascular procedures between the United States and non-US institutions during the early phase of the coronavirus disease-2019 (COVID-19) pandemic. Background: The COVID-19 pandemic has disrupted the care of many non-COVID-19 illnesses. Reductions in diagnostic cardiovascular testing around the world have led to concerns over the implications of reduced testing for cardiovascular disease (CVD) morbidity and mortality. Methods: Data were submitted to the INCAPS-COVID (International Atomic Energy Agency Non-Invasive Cardiology Protocols Study of COVID-19), a multinational registry comprising 909 institutions in 108 countries (including 155 facilities in 40 U.S. states), assessing the impact of the COVID-19 pandemic on volumes of diagnostic cardiovascular procedures. Data were obtained for April 2020 and compared with volumes of baseline procedures from March 2019. We compared laboratory characteristics, practices, and procedure volumes between U.S. and non-U.S. facilities and between U.S. geographic regions and identified factors associated with volume reduction in the United States. Results: Reductions in the volumes of procedures in the United States were similar to those in non-U.S. facilities (68% vs. 63%, respectively; p = 0.237), although U.S. facilities reported greater reductions in invasive coronary angiography (69% vs. 53%, respectively; p < 0.001). Significantly more U.S. facilities reported increased use of telehealth and patient screening measures than non-U.S. facilities, such as temperature checks, symptom screenings, and COVID-19 testing. Reductions in volumes of procedures differed between U.S. regions, with larger declines observed in the Northeast (76%) and Midwest (74%) than in the South (62%) and West (44%). Prevalence of COVID-19, staff redeployments, outpatient centers, and urban centers were associated with greater reductions in volume in U.S. facilities in a multivariable analysis. Conclusions: We observed marked reductions in U.S. cardiovascular testing in the early phase of the pandemic and significant variability between U.S. regions. The association between reductions of volumes and COVID-19 prevalence in the United States highlighted the need for proactive efforts to maintain access to cardiovascular testing in areas most affected by outbreaks of COVID-19 infection

Congreso Internacional de Responsabilidad Social Apuestas para el desarrollo regional.

Congreso Internacional de Responsabilidad Social: apuestas para el desarrollo regional [Edición 1 / Nov. 6 - 7: 2019 Bogotá D.C.]El Congreso Internacional de Responsabilidad Social “Apuestas para el Desarrollo Regional”, se llevó a cabo los días 6 y 7 de noviembre de 2019 en la ciudad de Bogotá D.C. como un evento académico e investigativo liderado por la Corporación Universitaria Minuto de Dios -UNIMINUTO – Rectoría Cundinamarca cuya pretensión fue el fomento de nuevos paradigmas, la divulgación de conocimiento renovado en torno a la Responsabilidad Social; finalidad adoptada institucionalmente como postura ética y política que impacta la docencia, la investigación y la proyección social, y cuyo propósito central es la promoción de una “sensibilización consciente y crítica ante las situaciones problemáticas, tanto de las comunidades como del país, al igual que la adquisición de unas competencias orientadas a la promoción y al compromiso con el desarrollo humano y social integral”. (UNIMINUTO, 2014). Dicha postura, de conciencia crítica y sensibilización social, sumada a la experiencia adquirida mediante el trabajo articulado con otras instituciones de índole académico y de forma directa con las comunidades, permitió establecer como objetivo central del evento la reflexión de los diferentes grupos de interés, la gestión de sus impactos como elementos puntuales que contribuyeron en la audiencia a la toma de conciencia frente al papel que se debe asumir a favor de la responsabilidad social como aporte seguro al desarrollo regional y a su vez al fortalecimiento de los Objetivos de Desarrollo Sostenible

Congreso Internacional de Responsabilidad Social Apuestas para el desarrollo regional.

Congreso Internacional de Responsabilidad Social: apuestas para el desarrollo regional [Edición 1 / Nov. 6 - 7: 2019 Bogotá D.C.]El Congreso Internacional de Responsabilidad Social “Apuestas para el Desarrollo Regional”, se llevó a cabo los días 6 y 7 de noviembre de 2019 en la ciudad de Bogotá D.C. como un evento académico e investigativo liderado por la Corporación Universitaria Minuto de Dios -UNIMINUTO – Rectoría Cundinamarca cuya pretensión fue el fomento de nuevos paradigmas, la divulgación de conocimiento renovado en torno a la Responsabilidad Social; finalidad adoptada institucionalmente como postura ética y política que impacta la docencia, la investigación y la proyección social, y cuyo propósito central es la promoción de una “sensibilización consciente y crítica ante las situaciones problemáticas, tanto de las comunidades como del país, al igual que la adquisición de unas competencias orientadas a la promoción y al compromiso con el desarrollo humano y social integral”. (UNIMINUTO, 2014). Dicha postura, de conciencia crítica y sensibilización social, sumada a la experiencia adquirida mediante el trabajo articulado con otras instituciones de índole académico y de forma directa con las comunidades, permitió establecer como objetivo central del evento la reflexión de los diferentes grupos de interés, la gestión de sus impactos como elementos puntuales que contribuyeron en la audiencia a la toma de conciencia frente al papel que se debe asumir a favor de la responsabilidad social como aporte seguro al desarrollo regional y a su vez al fortalecimiento de los Objetivos de Desarrollo Sostenible

Diseño caracterización e implementación de una arquitectura y protocolos de red de sensores inalámbricos

Magíster en Ingeniería Electrónica y de ComputadoresMaestrí

Reduction of cardiac imaging tests during the COVID-19 pandemic: The case of Italy. Findings from the IAEA Non-invasive Cardiology Protocol Survey on COVID-19 (INCAPS COVID)

Background: In early 2020, COVID-19 massively hit Italy, earlier and harder than any other European country. This caused a series of strict containment measures, aimed at blocking the spread of the pandemic. Healthcare delivery was also affected when resources were diverted towards care of COVID-19 patients, including intensive care wards. Aim of the study: The aim is assessing the impact of COVID-19 on cardiac imaging in Italy, compare to the Rest of Europe (RoE) and the World (RoW). Methods: A global survey was conducted in May–June 2020 worldwide, through a questionnaire distributed online. The survey covered three periods: March and April 2020, and March 2019. Data from 52 Italian centres, a subset of the 909 participating centres from 108 countries, were analyzed. Results: In Italy, volumes decreased by 67% in March 2020, compared to March 2019, as opposed to a significantly lower decrease (p &lt; 0.001) in RoE and RoW (41% and 40%, respectively). A further decrease from March 2020 to April 2020 summed up to 76% for the North, 77% for the Centre and 86% for the South. When compared to the RoE and RoW, this further decrease from March 2020 to April 2020 in Italy was significantly less (p = 0.005), most likely reflecting the earlier effects of the containment measures in Italy, taken earlier than anywhere else in the West. Conclusions: The COVID-19 pandemic massively hit Italy and caused a disruption of healthcare services, including cardiac imaging studies. This raises concern about the medium- and long-term consequences for the high number of patients who were denied timely diagnoses and the subsequent lifesaving therapies and procedures

International Impact of COVID-19 on the Diagnosis of Heart Disease

Background: The coronavirus disease 2019 (COVID-19) pandemic has adversely affected diagnosis and treatment of noncommunicable diseases. Its effects on delivery of diagnostic care for cardiovascular disease, which remains the leading cause of death worldwide, have not been quantified. Objectives: The study sought to assess COVID-19's impact on global cardiovascular diagnostic procedural volumes and safety practices. Methods: The International Atomic Energy Agency conducted a worldwide survey assessing alterations in cardiovascular procedure volumes and safety practices resulting from COVID-19. Noninvasive and invasive cardiac testing volumes were obtained from participating sites for March and April 2020 and compared with those from March 2019. Availability of personal protective equipment and pandemic-related testing practice changes were ascertained. Results: Surveys were submitted from 909 inpatient and outpatient centers performing cardiac diagnostic procedures, in 108 countries. Procedure volumes decreased 42% from March 2019 to March 2020, and 64% from March 2019 to April 2020. Transthoracic echocardiography decreased by 59%, transesophageal echocardiography 76%, and stress tests 78%, which varied between stress modalities. Coronary angiography (invasive or computed tomography) decreased 55% (p &lt; 0.001 for each procedure). In multivariable regression, significantly greater reduction in procedures occurred for centers in countries with lower gross domestic product. Location in a low-income and lower–middle-income country was associated with an additional 22% reduction in cardiac procedures and less availability of personal protective equipment and telehealth. Conclusions: COVID-19 was associated with a significant and abrupt reduction in cardiovascular diagnostic testing across the globe, especially affecting the world's economically challenged. Further study of cardiovascular outcomes and COVID-19–related changes in care delivery is warranted

Impact of COVID-19 on Diagnostic Cardiac Procedural Volume in Oceania: The IAEA Non-Invasive Cardiology Protocol Survey on COVID-19 (INCAPS COVID)

Objectives: The INCAPS COVID Oceania study aimed to assess the impact caused by the COVID-19 pandemic on cardiac procedure volume provided in the Oceania region. Methods: A retrospective survey was performed comparing procedure volumes within March 2019 (pre-COVID-19) with April 2020 (during first wave of COVID-19 pandemic). Sixty-three (63) health care facilities within Oceania that perform cardiac diagnostic procedures were surveyed, including a mixture of metropolitan and regional, hospital and outpatient, public and private sites, and 846 facilities outside of Oceania. The percentage change in procedure volume was measured between March 2019 and April 2020, compared by test type and by facility. Results: In Oceania, the total cardiac diagnostic procedure volume was reduced by 52.2% from March 2019 to April 2020, compared to a reduction of 75.9% seen in the rest of the world (p&lt;0.001). Within Oceania sites, this reduction varied significantly between procedure types, but not between types of health care facility. All procedure types (other than stress cardiac magnetic resonance [CMR] and positron emission tomography [PET]) saw significant reductions in volume over this time period (p&lt;0.001). In Oceania, transthoracic echocardiography (TTE) decreased by 51.6%, transoesophageal echocardiography (TOE) by 74.0%, and stress tests by 65% overall, which was more pronounced for stress electrocardiograph (ECG) (81.8%) and stress echocardiography (76.7%) compared to stress single-photon emission computerised tomography (SPECT) (44.3%). Invasive coronary angiography decreased by 36.7% in Oceania. Conclusion: A significant reduction in cardiac diagnostic procedure volume was seen across all facility types in Oceania and was likely a function of recommendations from cardiac societies and directives from government to minimise spread of COVID-19 amongst patients and staff. Longer term evaluation is important to assess for negative patient outcomes which may relate to deferral of usual models of care within cardiology