232 research outputs found
How do we evaluate risk?
No full text2019 Wall Scholar Sathish Gopalakrishnan, an Associate Professor at UBC's Electrical & Computer Engineering Department, has been exploring how individuals and societies understand risk in cyber-physical systems – artificial intelligence, robotics and their application in the world around us. That understanding can help us shape regulation and safety standards in an era of increasing automation.Applied Science, Faculty ofElectrical and Computer Engineering, Department ofUnreviewedFacult
Risk-Aware Scheduling of Dual Criticality Job Systems Using Demand Distributions
No full textWe pose the problem of scheduling Mixed Criticality (MC) job systems when there are only two criticality levels, Lo and Hi -referred to as Dual Criticality job systems- on a single processing platform, when job demands are probabilistic and their distributions are known. The current MC models require that the scheduling policy allocate as little execution time as possible to Lo-criticality jobs if the scenario of execution is of Hi criticality, and drop Lo-criticality jobs entirely as soon as the execution scenario's criticality level can be inferred and is Hi. The work incurred by "incorrectly" scheduling Lo-criticality jobs in cases of Hi realized scenarios might affect the feasibility of Hi criticality jobs; we quantify this work and call it Work Threatening Feasibility (WTF). Our objective is to construct online scheduling policies that minimize the expected WTF for the given instance, and under which the instance is feasible in a probabilistic sense that is consistent with the traditional deterministic definition of MC feasibility. We develop a probabilistic framework for MC scheduling, where feasibility is defined in terms of (chance) constraints on the probabilities that Lo and Hi jobs meet their deadlines. The probabilities are computed over the set of sample paths, or trajectories, induced by executing the policy, and those paths are dependent upon the set of execution scenarios and the given demand distributions. Our goal is to exploit the information provided by job distributions to compute the minimum expected WTF below which the given instance is not feasible in probability, and to compute a (randomized) "efficiently implementable" scheduling policy that realizes the latter quantity. We model the problem as a Constrained Markov Decision Process (CMDP) over a suitable state space and a finite planning horizon, and show that an optimal (non-stationary) Markov randomized scheduling policy exists. We derive an optimal policy by solving a Linear Program (LP). We also carry out quantitative evaluations on select probabilistic MC instances to demonstrate that our approach potentially outperforms current MC scheduling policies
Daratumumab improves the anti-myeloma effect of newly emerging multidrug therapies
No full textSathish Gopalakrishnan,1 Daryl Tan1,2 1Department of Hematology, Singapore General Hospital, Singapore, Republic of Singapore; 2Raffles Cancer Center, Raffles Hospital, Singapore, Republic of Singapore Abstract: Although the clinical outcomes of patients with multiple myeloma has improved tremendously with the advent of bortezomib and immunomodulatory drugs like thalidomide and lenalidomide, the disease remains incurable and patients will eventually be resistant to these drugs. Novel non-cross-resistant modalities of treatment are needed. Immunotherapy is potentially a very promising therapeutic modality for further development. Daratumumab is a novel, high-affinity, therapeutic human monoclonal antibody against a unique CD38 epitope. It induces tumor-cell killing through several immunological mechanisms. It has shown a favorable safety profile as monotherapy and significant single-agent activity in relapsed/refractory myeloma. It has also demonstrated strong synergism with lenalidomide and bortezomib. The potential of this agent, together with its pharmacokinetics, mode of action, early efficacy, and safety data will be detailed in this review. Keywords: daratumumab, myeloma, monoclona
An observation-based runtime configuration framework for the front-end network edge
No full textDespite the prominence of automated runtime configuration procedures, relatively little is known about managing the runtime configurations of general-purpose programming in resource-constrained IoT platforms at the network edge. For example, high-level language-written application programming (e.g., video/audio surveillance) in IoT enables local data processing to decrease latency, bandwidth, and infrastructure costs and address data safety and privacy concerns. However, without a good configuration, such computing generates undesirable performance or sudden and unexpected resource outages, leading to an application or a complete system failure. On the other hand, stringent resources in IoT make the performance of general-purpose programming highly discontinuous, which the existing linear or non-linear models can not capture. As a result, while the current configuration techniques make typical computing (e.g., cloud, High-Performance Computing (HPC)) efficient, it still needs to be determined whether or not they are efficient enough to manage general-purpose edge computing.
This research systematically analyzed the runtime configuration challenges for general-purpose programming in IoT. In the process, we discovered several new application performance associations and system resource variance patterns in this state space with which we address the constraints, heterogeneity, discontinuity, and scalability issues of IoT at the network edge. We applied these performance associations and other systematic state space sampling methods to address these issues as they arise in two important and prominent areas of automated runtime configuration: (1) resource-exhaustion detection and (2) performance optimization. The latter area is divided more into a pipeline configuration and b collocated performance approximation.
With cross-platform failure prediction, configuration management, and approximation techniques, we apply an intelligent and general set of configuration capabilities to general-purpose edge computing. Across various real-world case studies, our techniques outperform conventional runtime configuration techniques regarding performance improvements and approximation accuracy and pave the way for a new direction toward general-purpose edge computing.Applied Science, Faculty ofElectrical and Computer Engineering, Department ofGraduat
Characterization and improved lifetime management of serverless cloud systems
No full textThe full abstract for this thesis is available in the body of the thesis, and will be available when the embargo expires.Applied Science, Faculty ofElectrical and Computer Engineering, Department ofGraduat
Differential diffusive instabilities of miscible two-layer stratifications in porous media and Hele-Shaw cells
No full textIn porous media, a stratification of a given solution on top of another miscible solution can be buoyantly unstable because of an unstable density stratification or because of differential diffusive effects. The former is the well known Rayleigh–Taylor (RT) mechanism wherein the interface is destabilized by the denser solution overlying a less dense one in the gravity field. Whereas the latter is of particular interest in the field of oceanography, when the upper solution is less dense than the lower one with the lower component diffusing faster than the upper one, resulting in a double diffusive (DD) instability. Similarly, a diffusive-layer convection (DLC) instability has also been observed for a stable density stratification with the upper solute diffusing faster than the lower one. Though the literature on differential diffusion effects is pretty vast, very few studies have managed to establish a connection, both qualitatively and quantitatively, between numerical simulations and experimental observations, which is the basis of the present study. We report our findings in a broad parameter range where the instability mechanism could be triggered by an unstable density stratification or due to differential diffusive effects, or even both, resulting in mixed modes
Chemical composition and antibacterial activity of the rhizome oil of Hedychium larsenii
No full textKemijski sastav eteričnog ulja iz rizoma biljke Hedychium larsenii M. Dan & Sathish ispitivan je pomoću GC-FID i GC-MS. Najvažniji sastojci ulja bili su linalol i 1,8-cineol, a na monoterpene otpada 99%. Seskviterpeni su prisutni samo u zanemarivim količinama. Eterično ulje je pokazalo umjereno antibakterijsko djelovanje na Gram-pozitivne i Gram-negativne bakterije.The composition of essential oil from the rhizomes of Hedychium larsenii M. Dan & Sathish was examined by GC-FID and GC-MS techniques. 99% of the oil consisted of monoterpenoids. Sesquiterpenoids were present only in negligible quantities. Linalool and 1,8-cineole identified as the major components. The oil showed moderate antibacterial activity against Gram-positive and Gram-negative bacteria
A model for the design of wireless sensor networks using geographic routing
No full textThe design of a Wireless Sensor Network suitable to meet the applications requirements is particularly relevant in environments where it is not possible to operate after the deployment, modifying the network to respect the desired behavior. This paper proposes a model to allow performance evaluation of the network before its deployment, helping its design and the choice of the right value of the network parameters. In particular our model is tailored for wireless sensor networks using the geographic routing. The model has been both numerically analyzed and simulated showing its ability to set such parameters to meet the requirements expressed in terms of established service level
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