Preemptive Solution Research Articles

Explainable machine learning for real-time deterioration alert prediction to guide pre-emptive treatment

The Electronic Medical Record (EMR) provides an opportunity to manage patient care efficiently and accurately. This includes clinical decision support tools for the timely identification of adverse events or acute illnesses preceded by deterioration. This paper presents a machine learning-driven tool developed using real-time EMR data for identifying patients at high risk of reaching critical conditions that may demand immediate interventions. This tool provides a pre-emptive solution that can help busy clinicians to prioritize their efforts while evaluating the individual patient risk of deterioration. The tool also provides visualized explanation of the main contributing factors to its decisions, which can guide the choice of intervention. When applied to a test cohort of 18,648 patient records, the tool achieved 100% sensitivity for prediction windows 2–8 h in advance for patients that were identified at 95%, 85% and 70% risk of deterioration.

Rocky Mountain AI-High: Montai Health Is Pioneering Safe, Preemptive Solutions for Chronic Disease

Rocky Mountain AI-High: Montai Health Is Pioneering Safe, Preemptive Solutions for Chronic Disease

A pilot study to understand tooth replacement in near-harvest farmed saltwater crocodiles (Crocodylus porosus): Implications for blemish induction

Saltwater crocodiles (Crocodylus porosus) are farmed in Australia primarily for their belly skin. The desirability and ultimately the value of each skin depends on the extent and location of various industry-defined defects. Anecdotal observations suggest that conspecific interactions are the main contributors with the protrusive 4th dentary teeth (i.e. eye teeth) the most likely cause. It is well known that crocodilians undergo continual tooth replacement, yet no study has investigated tooth replacement rates or tooth growth dynamics in juvenile saltwater crocodiles. In this pilot study, we repeatedly measured eye tooth crown height and observed eye tooth replacement in individually-housed juvenile saltwater crocodiles (n = 98) accounting for 290 individual teeth. The majority of teeth were replaced every three to six months (n = 172) but nine teeth were not replaced over the 15-month study period. After a tooth was lost, the need to replace it quickly was evidenced by a faster tooth growth rate in the first three months (11.07 ± 0.17 mm) but subsequently slowed to a model-adjusted asymptote of 14.03 ± 0.27 mm (p < .001). Interestingly, teeth on the left side of the mandible were, on average, 0.43 ± 0.16 mm shorter than those on the right (p < .001) and, although just outside 5% significance, were replaced 1.20 times as often. Together this is suggestive that crocodiles may preference food capture with the left-hand side of their mouth but requires more structured behavioural observations to confirm. Unusually, the eye-teeth of eight crocodiles did not protrude, which is a normal characteristic of crocodiles compared to alligators, but instead were observed to be growing into the interior of the mouth. This study begins to provide some context to tooth biology when preemptive solutions to tooth-induced blemishes are being sought.

Automated information and control complex of hydro-gas endogenous mine processes

The automated information and control complex designed to prevent accidents, related to aerological situation in the underground workings, accounting of the received and handed over individual devices, transmission and display of measurement data, and the formation of preemptive solutions is considered. Examples for the automated workplace of an airgas control operator by individual means are given. The statistical characteristics of field data characterizing the aerological situation in the mine are obtained. The conducted studies of statistical characteristics confirm the feasibility of creating a subsystem of controlled gas distribution with an adaptive arrangement of points for gas control. The adaptive (multivariant) algorithm for processing measuring information of continuous multidimensional quantities and influencing factors has been developed.

The effect of commercial, natural and grape seed extract supplemented diets on gene expression signatures and survival of greenlip abalone (Haliotis laevigata) during heat stress

Summer mortality is a phenomenon associated with high temperature water spikes that can result in mass mortalities of abalone and other molluscs. This is a particular concern for aquaculture industries due to the economic impacts of such events. Diets containing algal supplements have been suggested as pre-emptive solutions for preventing these mass mortalities. The same has also been suggested for diets containing grape seed extract. This is due to their potential as a source of antioxidative compounds, which reduce the accumulation of harmful reactive oxygen species. This study aimed to identify functional genes associated with high survival in abalone fed diets high in antioxidative compounds during heat stress. Tentacle transcriptomes of 40 greenlip abalone (Haliotis laevigata) were investigated to determine the combined effects of differing diets and temperature on the gene expression responses by abalone. Here we compare the functional gene expression changes at 22°C and 25°C in abalone fed common commercial, live macroalgal (Ulva lactuca) and grape seed extract supplemented commercial diets as a means to understand the resulting high survival of abalone fed grape seed extract during heat stress. Twenty-four genes were differentially expressed between high survival promoting diets (macroalgae or grape seed extract supplemented commercial) relative to the purely commercial diet. Many of these genes have been suggested to be involved in antioxidant and innate immunity responses. The identification of these genes and their functional roles has enhanced our understanding of processes that contribute to summer stress resilience in abalone. Our study supports the hypothesis that diet and gene expression signatures may be indicative of the survival capabilities of abalone when exposed to heat stress.

Quo Vadis Breast Tissue Engineering?

Quo Vadis Breast Tissue Engineering?

Enabling Local Solutions to Global Problems: The Role of Cultural Intelligence in Building Global SOF Networks

In order to provide regional solutions to potentially world-wide problems, global special operations forces (SOF) networks maximize the benefits of SOF, in particular, their aptitude and ability to perform in a culturally intelligent manner. Indeed, to be able to facilitate regional solutions to potentially global problems, SOF need to exhibit high levels of cultural intelligence, which requires an understanding of culture combined with an ability to apply strategic thinking. By being able to address issues critically and creatively – the hallmarks of strategic thinking – while understanding and behaving appropriately in a variety of cultural contexts, SOF, acting within global networks, provide collective, cost effective, pre-emptive solutions for an increasingly volatile and interconnected world. This article explores methods for increasing levels of cultural intelligence and highlights the benefits of doing so while also warning of the pitfalls of not behaving in a culturally intelligent manner. This article is available in Journal of Strategic Security: http://scholarcommons.usf.edu/jss/vol7/iss2/5

DEMON: preemptive route recovery for AODV in multi-hop wireless networks based on performance degradation monitoring

Reactive routing protocols like ad hoc on-demand distance vector (AODV) have been widely proposed for multi-hop wireless networks (MWNs). However, these types of routing protocols only recover routes after route break detection. Considerable research efforts have been devoted to minimizing the route recovery delay or to anticipating link breaks by using preemptive mechanisms. To the best of our knowledge, state-of-the-art solutions in this space are mainly focused on mobility prediction. However, as we argue in this paper, other phenomena like interference and congestion should also be taken into account, since they can also negatively affect the performance of routes and even cause disconnections. This article presents a novel preemptive solution for AODV called performance degradation monitoring, which allows preemptive route recovery based on passive estimation of link data loss rate. Extensive simulations demonstrate that our proposal, which is sensitive to link quality degradation regardless of its nature, improves network performance in a wide range of scenarios.

Preemptive and non-preemptive generalized min sum set cover

In the (non-preemptive) Generalized Min Sum Set Cover Problem, we are given $$n$$ ground elements and a collection of sets $$\mathcal{S }= \{S_1, S_2, \ldots , S_m\}$$ where each set $$S_i \in 2^{[n]}$$ has a positive requirement $$\kappa (S_i)$$ that has to be fulfilled. We would like to order all elements to minimize the total (weighted) cover time of all sets. The cover time of a set $$S_i$$ is defined as the first index $$j$$ in the ordering such that the first $$j$$ elements in the ordering contain $$\kappa (S_i)$$ elements in $$S_i$$ . This problem was introduced by Azar et al. (2009) with interesting motivations in web page ranking and broadcast scheduling. For this problem, constant approximations are known by Bansal et al. (2010) and Skutella and Williamson (Oper Res Lett 39(6):433---436, 2011). We study the version where preemption is allowed. The difference is that elements can be fractionally scheduled and a set $$S$$ is covered in the moment when $$\kappa (S)$$ amount of elements in $$S$$ are scheduled. We give a 2-approximation for this preemptive problem. Our linear programming relaxation and analysis are completely different from the aforementioned previous works. We also show that any preemptive solution can be transformed into a non-preemptive one by losing a factor of 6.2 in the objective function. As a byproduct, we obtain an improved $$12.4$$ -approximation for the non-preemptive problem.

A binary branch and bound algorithm to minimize maximum scheduling cost

This paper examines a single machine scheduling problem of minimizing the maximum scheduling cost that is nondecreasing with job completion time. Job release dates and precedence constraints are considered. We assume that each job can be processed exactly once without preemption. This is a classical scheduling problem, and is specifically useful in the scheduling of medical treatments. We develop a simple branch and bound algorithm to solve the scheduling problem optimally. A binary branching technique is developed. We use a preemptive solution approach to locate a lower bound, and design a simple heuristic to find an upper bound. Our algorithm is easy to implement and finds optimal schedules in one CPU minute for almost all instances tested, with up to 1000 jobs.

Improving the preemptive bound for the single machine dynamic maximum lateness problem

The preemptive lower bound is known to be the main available bound for the single machine dynamic maximum lateness problem. We propose an O ( n log n ) time improvement to this bound which reduces by more than 80% the average the gap between the preemptive solution value and the optimal solution value.

Clinical Pharmacology: A Paradigm for Individualized Medicine

Individualized medicine provides a powerful engine revolutionizing the practice of clinical pharmacology, tailoring genetic and molecular profiles of patients to improve therapeutic specificity, reduce treatment variability and minimize adverse drug events. In that context, advances in individualized medicine have transformed the science of clinical pharmacology and therapeutics from drug discovery through identification of drugable targets, development through stratification of disease risk, regulation through identifying pathways mediating off-target effects and utilization through personalizing drug regimens. This revolution in fundamental and applied therapeutics has entrained an evolution in biology and medicine. Insights in the mechanistic basis of cell, tissue and organ function, and their interface with the environment are being translated to define disease risk, identify processes mediating disease susceptibility, target mechanism-based therapies, and tailor prevention and control paradigms, providing previously unanticipated opportunities for patient-specific disease management. The emerging field of individualized medicine is transforming the practice of clinical pharmacology, driving the leading edge of discovery from the laboratory bench to the evidence basis of practice in the clinic, extending to populations, to transform healthcare and create predictive, personalized and pre-emptive solutions for tailored patient-specific therapeutic strategies.

Approximating total flow time on parallel machines

We consider the problem of optimizing the total flow time of a stream of jobs that are released over time in a multiprocessor setting. This problem is NP-hard even when there are only two machines and preemption is allowed. Although the total (or average) flow time is widely accepted as a good measurement of the overall quality of service, no approximation algorithms were known for this basic scheduling problem. This paper contains two main results. We first prove that when preemption is allowed, Shortest Remaining Processing Time (SRPT) is an O ( log ( min { n m , P } ) ) approximation algorithm for the total flow time, where n is the number of jobs, m is the number of machines, and P is the ratio between the maximum and the minimum processing time of a job. We also provide an Ω ( log ( n m + P ) ) lower bound on the (worst case) competitive ratio of any randomized algorithm for the on-line problem in which jobs are known at their release times. Thus, we show that up to a constant factor SRPT is an optimal on-line algorithm. Our second main result addresses the non-preemptive case. We present a general technique that allows to transform any preemptive solution into a non-preemptive solution at the expense of an O ( n m ) factor in the approximation ratio of the total flow time. Combining this technique with our previous result yields an O ( n m log n m ) approximation algorithm for this case. We also show an Ω ( n 1 3 − ϵ ) lower bound on the approximability of this problem (assuming P ≠ NP ).

Improving the preemptive bound for the one-machine dynamic total completion time scheduling problem

We consider the single machine dynamic total completion time scheduling problem. This problem is known to be NP-hard in the strong sense. The currently best available lower bound for the problem is known to be the optimal solution value of the corresponding preemptive problem which can be computed in O(n log n) time. We propose an improvement on this bound by exploiting the properties of the preemptive solution. The proposed improvement reduces by approximately 44% on the average the gap between the preemptive solution value and the optimal solution value.

Why are we using Java again?

article Free AccessWhy are we using Java again? Author: Paul Tyma PreEmptive Solutions, Euclid, OH PreEmptive Solutions, Euclid, OHView Profile Authors Info & Claims Communications of the ACMVolume 41Issue 6June 1998 pp 38–42https://doi.org/10.1145/276609.276617Published:01 June 1998Publication History 32citation1,291DownloadsMetricsTotal Citations32Total Downloads1,291Last 12 Months133Last 6 weeks41 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteeReaderPDF

Algorithms for preemptive scheduling of different classes of processors to do jobs with fixed times

We consider scheduling problems that involve processors of different classes and jobs with fixed start and finish times. We allow preemption of jobs, but impose restrictions on the assignment of processors to jobs. We present polynomial-time algorithms for finding the minimal-cost preemptive solutions for two special cases in which the number of job classes is at most one more than the number of processor classes. We then discuss a generalized version in which a processor can be assigned only to a subset of the jobs and a job can be done only by a subset of the processors. We prove that for this case the problem of finding a preemptive feasible schedule with a given combination of processors can be solved in polynomial time, by transforming it into a transportation-network problem. Next, we extend these results to cyclic scheduling problems. Further, we discuss some transformations among these class scheduling problems and provide simpler proofs of NP-completeness for the nonpreemptive versions of the first two cases.