Potential of Core-Collapse Supernova Neutrino Detection at JUNO

JUNO is an underground neutrino observatory under construction in Jiangmen, China. It uses 20kton liquid scintillator as target, which enables it to detect supernova burst neutrinos of a large statistics for the next galactic core-collapse supernova (CCSN) and also pre-supernova neutrinos from the nearby CCSN progenitors. All flavors of supernova burst neutrinos can be detected by JUNO via several interaction channels, including inverse beta decay, elastic scattering on electron and proton, interactions on C12 nuclei, etc. This retains the possibility for JUNO to reconstruct the energy spectra of supernova burst neutrinos of all flavors. The real time monitoring systems based on FPGA and DAQ are under development in JUNO, which allow prompt alert and trigger-less data acquisition of CCSN events. The alert performances of both monitoring systems have been thoroughly studied using simulations. Moreover, once a CCSN is tagged, the system can give fast characterizations, such as directionality and light curve

Detection of the Diffuse Supernova Neutrino Background with JUNO

As an underground multi-purpose neutrino detector with 20 kton liquid scintillator, Jiangmen Underground Neutrino Observatory (JUNO) is competitive with and complementary to the water-Cherenkov detectors on the search for the diffuse supernova neutrino background (DSNB). Typical supernova models predict 2-4 events per year within the optimal observation window in the JUNO detector. The dominant background is from the neutral-current (NC) interaction of atmospheric neutrinos with 12C nuclei, which surpasses the DSNB by more than one order of magnitude. We evaluated the systematic uncertainty of NC background from the spread of a variety of data-driven models and further developed a method to determine NC background within 15\% with {\it{in}} {\it{situ}} measurements after ten years of running. Besides, the NC-like backgrounds can be effectively suppressed by the intrinsic pulse-shape discrimination (PSD) capabilities of liquid scintillators. In this talk, I will present in detail the improvements on NC background uncertainty evaluation, PSD discriminator development, and finally, the potential of DSNB sensitivity in JUNO

Real-time Monitoring for the Next Core-Collapse Supernova in JUNO

Core-collapse supernova (CCSN) is one of the most energetic astrophysical events in the Universe. The early and prompt detection of neutrinos before (pre-SN) and during the SN burst is a unique opportunity to realize the multi-messenger observation of the CCSN events. In this work, we describe the monitoring concept and present the sensitivity of the system to the pre-SN and SN neutrinos at the Jiangmen Underground Neutrino Observatory (JUNO), which is a 20 kton liquid scintillator detector under construction in South China. The real-time monitoring system is designed with both the prompt monitors on the electronic board and online monitors at the data acquisition stage, in order to ensure both the alert speed and alert coverage of progenitor stars. By assuming a false alert rate of 1 per year, this monitoring system can be sensitive to the pre-SN neutrinos up to the distance of about 1.6 (0.9) kpc and SN neutrinos up to about 370 (360) kpc for a progenitor mass of 30$M_{\odot}$ for the case of normal (inverted) mass ordering. The pointing ability of the CCSN is evaluated by using the accumulated event anisotropy of the inverse beta decay interactions from pre-SN or SN neutrinos, which, along with the early alert, can play important roles for the followup multi-messenger observations of the next Galactic or nearby extragalactic CCSN.Comment: 24 pages, 9 figure

Analys av prestanda och modellering av Ethernet-baserad fordonskommunikation

While vehicle technology is rapidly advanced, advanced driver assistance system (ADAS) stays in focus. However, all of these growing automotive applications are driving up the bandwidth requirements, therefore vehicle networks require higher bandwidth and more deterministic real-time guarantees than before.Switched Ethernet is widely used for all kinds of applications, and it gradually moves into the automotive domain. The new specification of the IEEE 802.1 Audio/Video Bridging (AVB) standard provides the QoS features needed for ADAS data streaming.In this work, we study and analyse Ethernet-based invehicle communication of both legacy Ethernet and AVB Ethernet through a simulation approach to verify the automotive network performance. Furthermore, a system engineering approach is used to achieve a more model-based design of simulation and developing prototypes in the future.Samtidigt som fordonsteknologin ökar snabbt, är det system för avancerad förarassistans (advanced driver assistance systems, ADAS) som står i fokus. Dessa ökande fordonsapplikationer driver på bandbreddskraven, och därför kräver fordonsnätverken högre bandbredd och mer determinisktiska realtidskrav än tidigare.Switchat nätverk (Switched Ethernet) används i alla möjliga applikationer och flyttar gradvis in i fordonsdomänen. Den nya specificationen av standarden IEEE 802.1 Audio/Video Bridging (AVB) tillhandahåller QoS (Quality of Service) funktioner för ADAS dataöverföring.I den här avhandlingen undersöks och analyseras Ethernetbaserad fordonskommunikation av både vanligt nätverk (Ethernet) och AVB Ethernet genom simulering för att verifiera nätverksprestandan för fordonsnätverket i fråga. En systemingenjörsinriktning har använts för att skapa en mer modell-baserad design av simuleringen, som även kan användas för att utveckla prototyper i framtiden

FINDING OPTIMAL EXPERIMENTAL DESIGNS FOR MODELS IN BIOMEDICAL STUDIES VIA PARTICLE SWARM OPTIMIZATION

The theory of optimal experimental design provides insightful guidance on resource allocation for many dose-response studies and clinical trials. However, as more and more complicated models are developed, finding optimal designs has become an increasingly difficult task; therefore, the availability of an efficient and easy-to-use algorithm to find optimal designs is important for both researchers and practitioners. In recent years, nature-inspired algorithms like Particle Swarm Optimization(PSO) have been successfully applied to many non-statistical disciplines, such as computer science and engineering, even though there is no unified theory to explain why PSO works so well. To date, there is virtually no work in the mainstream statistical literature that applies PSO to solve statistical problems.In my dissertation, I review PSO methodology and show it is an easy and effective algorithm to generate locally D- and c-optimal designs for a variety of nonlinear statistical models commonly used in biomedical studies. I develop a new version of PSO called Ultra-dimensional PSO (UPSO) to find D-optimal designs for multi-variable exponential and Poisson regression models with up to five variables and all pairwise interactions. I use the proposed novel search strategy to find minimally supported D-optimal designs and ascertain conditions under which such optimal designs exist for such models. A remarkable discovery in my work is that locally D-optimal designs for such models can have many more support points than the number of parameters in the model. This result is both new and interesting because almost all D-optimal designs have equal or just one or two more number of points than the the number of parameters in the mean response function, see the examples in monographs by Fedorov [1972], Atkinson Atkinson et al. [2007], and recent papers by in Yang and Stufken [2009], Yang [2010]. This discovery also disproves the conjecture by Wang et al. [2006] that for M-variable interaction model (M > 2), D-optimal designs are also minimally and equally supported and have a similar structure as D-optimal designs for 2-variable model.In addition to single objective optimal designs, I apply PSO to find optimal designs for estimating parameters and interesting characteristics continuation-ratio (CR) model with non-constant slopes. Such a model has a great potential in dose finding studies because it takes both efficacy and toxicity into consideration. The optimal design I am interested in constructing is a three-objective optimal design, which provides efficient estimates for efficacy, adverse effect and all parameters in the CR model. This work is quite new because there are virtually no three-objective designs for a trinomial model reported in the literature. Through multiple objective efficiency plots, practitioners can construct the desired compound optimal design by selecting appropriate weighted average of three optimal criteria in a more flexible and informative way.I also conduct simulation studies for parameters selection in PSO, and compare the performance of PSO with other popular deterministic and metaheuristic algorithms in terms of the CPU time and the precision of the generated designs. I show that PSO outperforms its competitors for finding D- and c-optimal designs for different models I considered in my dissertation

Using animal instincts to design efficient biomedical studies via particle swarm optimization

TesisLima NorteEscuela de PosgradoPsicología EducativaEste trabajo de investigación se inició con la formulación del problema que responde a la pregunta¿Qué relación existe entre la percepción del apoyo familiar y el nivel de aprendizaje en el área de matemática de los estudiantes del primer grado de educación secundaria de la Institución Educativa N° 0137 Miguel Grau Seminario, del distrito de San Juan de Lurigancho, 2011?,tuvo por finalidad determinar la relación que existe entre la percepción del apoyo familiar y el nivel de aprendizaje en el área de Matemática de los estudiantes del primer grado de secundaria de la Institución Educativa Nº 0137 Miguel Grau Seminario del distrito de San Juan de Lurigancho, 2011. Esta investigación es de tipo “Descriptivo Correlacional”, de corte transversal y con diseñono experimental, pues nos permite demostrar la relación o correlación entre las variables que intervienen en el estudio. Es así que, mediante un análisis comparativo cuantitativo se establecerá la correlación entre la percepción del apoyo Familiar y el Nivel de Aprendizaje de los estudiantes del primer grado de secundaria de la Institución Educativa Nº 0137 Miguel Grau Seminario del distrito de San Juan de Lurigancho en el año 2011. La parte estadística se sustentan procesando los resultados obtenidos de la aplicación de los instrumentos que midieron cada variable; cuestionario para el caso de la variable Apoyo familiar, y Evaluación de Capacidades, para la variable Nivel De Aprendizaje. Las conclusiones indican que las variables están asociadas, por lo tanto se probó la hipótesis que indica que el apoyo Familiar está relacionada significativamente al nivel 0,05 sobre el aprendizaje del área de matemática de los estudiantes del primer año de secundaria