Update Schedule Research Articles

Recommendations of the second update of the LONTS guidelines : Long-term opioid therapy for chronic noncancer pain

The second scheduled update of the German S3guidelines on long-term opioid therapy for chronic noncancer pain (CNCP), the LONTS (AWMF registration number 145/003), was started in December 2018. The guidelines were developed by 28scientific societies and 2 patient self-help organizations under the coordination of the German Pain Society. Asystematic literature search in the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE and Scopus databases (up until December 2018) was performed. The systematic reviews with meta-analyses of randomized controlled trials with opioids for CNCP from the previous versions of the guideline were updated. Levels of evidence were assigned according to the classification system of the Oxford Centre for Evidence-Based Medicine. The strength of the recommendations was established by formal multistep procedures in order to reach aconsensus according to the Association of the Medical Scientific Societies in Germany (AWMF) regulations. The guidelines were reviewed by four external pain physicians. Public comments were possible for 4weeks. Opioid-based analgesics are a drug-based treatment option for short-term (4-12weeks), intermediate-term (13-25weeks) and long-term (≥26weeks) therapy of chronic osteoarthritis, diabetic polyneuropathy, postherpetic neuralgia and low back pain. Contraindications are primary headaches as well as functional somatic syndromes and mental disorders with the (cardinal) symptom pain. Based on a clinical consensus the guidelines list other medical conditions for which atherapy with opioids can be considered on an individual basis. Long-term therapy of CNCP with opioids is associated with relevant risks. A responsible administration of opioids requires consideration of possible indications and contraindications as well as regular assessment of efficacy and adverse effects. Opioids remain atreatment option for CNCP if nonpharmacological therapies are not effective and/or other drugs are not effective, are not tolerated or are contraindicated.

Maximum sensitivity to update schedules of elementary cellular automata over infinite configurations

Cellular automata are discrete dynamical systems with locally defined behaviour, well known as simple models of complex systems. Classically, their dynamics derive from synchronously iterated rules over finite or infinite configurations; however, since for many natural systems to be modelled, asynchrony seems more plausible, asynchronous iteration of the rules has gained a considerable attention in recent years. One question in this context is how changing the update schedule of rule applications affects the global behaviour of the system. In particular, previous works addressed the notion of maximum sensitivity to changes in the update schemes for finite lattices. Here, we extend the notion to infinite lattices, and classify elementary cellular automata space according to such a property.

Delay Analysis of Raw Water Reservoir and Pumping Station

Inadequate or feeble preliminary work prior beginning of development of any structure may become the root for difficult issues during the development time span. Therefore, the expense of development increments digressively, the development length of the task expands and the standard of development is influenced unfavorably. This examination harps on the significance of development plans in accomplishing the point of creating great quality development work inside the predefined span. Checking constantly the interrelated connection regarding delays in development plans and contractor orders is an entangled procedure. Here the easiest and fundamental methodology is that, both for proprietor and contractor, time is cash and consequently development plan deferrals ought to be broke down and remedial measures ought to be taken in a convenient way. The principle motivation behind this examination is to research the reasons for development plan delays and the techniques for plan delay investigations. In this examination, the completion development works of a “Raw water Reservoir and Raw water Pumping Station” at Bommakal village in Karimnagar District was chosen as a contextual investigation for examining task planning and the delay analysis. The fundamental reason for this examination is to recognize the defer aspects and the impact on the undertaken work fulfillment. This investigation adopts a coordinated strategy and tries to examine the influence of consequence. A survey was led to distinguish the circumstances and end results delay from contractor and customer. From the examination, it is distinguished that the most significant deferrals from a list 20 distinct causes and 4 distinct impacts of postponements and the suggestions to diminish the postponement. The actual arranged schedule is 713 days and updated proposed schedule is 683 days the total delay was 30 days.

A conceptual approach to graphically compare construction schedules

Purpose This paper aims to present a graphical comparison method for construction schedules, which illustrates the differences for each individual activity. The method overlays the observed differences on a bar chart creating a representation of whether each activity is ahead, on or behind schedule at a given date. Design/methodology/approach The method is implemented using a Microsoft Project add-in (plug-in). The paper demonstrates the method and its potential uses with three illustration cases: a time impact analysis, an alternative analysis for the selection of subcontractors and a multi-baseline analysis of an as-built schedule. Findings The cases included in the paper show that the proposed method uses a simplified and familiar attribute comparison for each activity in a schedule. The method affords flexibility in presenting differences between schedules such as the start/finish dates or duration. As the method does not rely on a specific software application or analysis method, it can be implement to different software applications as well as performance or delay analysis techniques. The method also makes it possible to present multiple and selective baseline comparisons overlaid on an updated or as-built schedule. Originality/value The method graphically presents a comparison of start dates, durations and finish dates for each activity that can be integrated with any schedule. The method can be used for forensic analysis as well as project control measures during construction. As the method does not rely on any specific performance or delay calculation method, it can be applied to any forensic analysis technique and delay analysis.

About block-parallel Boolean networks: a position paper

In automata networks, it is well known that the way entities update their states over time has a major impact on their dynamics. In particular, depending on the chosen update schedule, the underlying dynamical systems may exhibit more or less asymptotic dynamical behaviours such as fixed points or limit cycles. Since such mathematical models have been used in the framework of biological networks modelling, the question of choosing appropriate update schedules has arised soon. In this note, focusing on Boolean networks, our aim is to emphasise that the adequate way of thinking regulations and genetic expression over time is certainly not to consider a wall segregating synchronicity from asynchronicity because they actually complement rather well. In particular, we highlight that specific update schedules, namely block-parallel update schedules, whose intrinsic features are still not known from a theoretical point of view, admit realistic and pertinent properties in the context of biological modelling and deserve certainly more attention from the community.

Software Release Patterns When is it a good time to update a software component?

Over the past decade the industry 4.0 witnessed a trend towards an increasing number of software components, dependencies towards third party software components, and software component release cycles. Industry 4.0 teams building software products are more frequently impacted by third party software component updates. Due to this dependency, updating a single third party software component can break an entire software product. Reasons include parallel conflicting updates of third party software components, updating to an unstable version, or updating to a major stable version without an impact analysis. The objective of this paper is to reduce the risk of breaking updates by reviewing software release patterns and proposing update scheduling recommendations.

TRUS: Towards the Real-Time Route Update Scheduling in SDN for Data Centers

Periodically data plane update is a necessary task in Software Defined Networking(SDN). Most prior approaches update many flows without considering which flows should be updated. Hence, most of them get long update delay. However, due to the dramatic increase of data arriving in data centers in the coming 5G networks, flows to be updated should be carefully chosen. Otherwise, unsatisfactory update delay may occur, which will make the route after the reconfiguration invalid for most flows and even bring about a poor user experience. In this paper, we present a Timely Route Update Scheme(TRUS). Different from previously proposed update approaches, TRUS not only meets the real-time route update demand for data centers, but also guarantees bandwidth requirements of delay-sensitive flows. Further, it can avoid the congestion on “hot” links in the update process. Simulation results verify the effectiveness of our scheme and demonstrate it can largely cut down the route update latency while obtaining a good network performance when comparing with some former approaches.

Bayes-Optimal MMSE Detector for Massive MIMO Relaying With Low-Precision ADCs/DACs

In this study, we focus on the detector design for a massive multiple-input multiple-output amplify-and-forward relaying system with low-precision analog-to-digital converters (ADCs) and digital-to-analog converters (DACs). A general relaying model with direct and relay links is considered. Several studies have been performed on the basis of simple but performance-limited linear transceivers. The optimal detector for the aforementioned setting remains unknown. To bridge this gap, we develop a minimum mean squared error detector based on the framework of variational Bayes inference. The proposed detector works similarly to the iterative turbo update, and the extrinsic information of the direct and relay links are updated through maximum ratio combining. Furthermore, our algorithm uses a partially parallel update schedule that improves the convergence compared with an intuitive method that is based on a fully parallel schedule. We then present the state evolution (SE) as an analytical framework to investigate the mean squared error and symbol error rate of the detector. By specifying the dynamics of the SE, we reveal that low-precision ADCs/DACs, that is, those using 2-4-bit quantization, realize a good tradeoff between performance and cost. Moreover, low-precision ADCs/DACs provide numerous insights into the relaying system and its design, such as the quantization step size.

Fast and Accurate Depth Estimation from Sparse Light Fields.

We present a fast and accurate method for dense depth reconstruction, which is specifically tailored to process sparse, wide-baseline light field data captured with camera arrays. In our method, the source images are over-segmented into non-overlapping compact superpixels. We model superpixel as planar patches in the image space and use them as basic primitives for depth estimation. Such superpixel-based representation yields desired reduction in both memory and computation requirements while preserving image geometry with respect to the object contours. The initial depth maps, obtained by plane-sweeping independently for each view, are jointly refined via iterative belief-propagation-like optimization in superpixel domain. During the optimization, smoothness between the neighboring superpixels and geometric consistency between the views are enforced. To ensure rapid information propagation into textureless and occluded regions, together with the immediate superpixel neighbors, candidates from larger neighborhoods are sampled. Additionally, in order to make full use of the parallel graphics hardware a synchronous message update schedule is employed allowing to process all the superpixels of all the images at once. This way, the distribution of the scene geometry becomes distinctive already after the first iterations, facilitating stability and fast convergence of the refinement procedure. We demonstrate that a few refinement iterations result in globally consistent dense depth maps even in the presence of wide textureless regions and occlusions. The experiments show that while the depth reconstruction takes about a second per full high-definition view, the accuracy of the obtained depth maps is comparable with the state-of-the-art results, which otherwise require much longer processing time.

Incorporating occupancy data in scheduling building equipment: A simulation optimization framework

A common energy-conservation method involves specifying a schedule in the building automation system (BAS) so that equipment enter a sleep mode or low power mode during predetermined off-shift hours generally defined based on the expected or perceived occupancy schedule. This paper proposes a binary programing optimization model that incorporates actual occupancy patterns for different zones in the building as well as equipment interdependence to systematically determine the optimal schedule for each equipment while maintaining a minimum required service level to meet occupant needs. The model is then integrated into a simulation optimization framework, where historical or simulated occupancy data are used to determine the optimal frequency of schedule updates and the best design option for new buildings or retrofit projects. Through a real-world case study of a university building, we illustrate how the proposed approach harnesses historical occupancy data to select the best option for re-purposing the zones/spaces in the building. The results provide important practical insights by showing the significant potential to improve common practice that typically uses the exact same schedule for all equipment in the BAS. The results further show that the choice of the design option depends on the minimum required service level. The paper also illustrates the importance of updating equipment schedules in response to possible seasonal changes in occupancy patterns throughout the year. All codes and datasets are made available in an open repository to facilitate adoption by practitioners and enable reproducibility of the results for researchers.

A genetic algorithm‐based flow update scheduler for software‐defined networks

SummarySoftware‐defined networking (SDN) facilitates network programmability through a central controller. It dynamically modifies the network configuration to adapt to the changes in the network. In SDN, the controller updates the network configuration through flow updates, ie, installing the flow rules in network devices. However, during the network update, improper scheduling of flow updates can lead to a number of problems including overflowing of the switch flow table memory and the link bandwidth. Another challenge is minimizing the network update completion time during large‐network updates triggered by events such as traffic engineering path updates. The existing centralized approaches do not search the solution space for flow update schedules with optimal completion time. We proposed a hybrid genetic algorithm‐based flow update scheduling method (the GA‐Flow Scheduler). By searching the solution space, the GA‐Flow Scheduler attempts to minimize the completion time of the network update without overflowing the flow table memory of the switches and the link bandwidth. It can be used in combination with other existing flow scheduling methods to improve the network performance and reduce the flow update completion time. In this paper, the GA‐Flow Scheduler is combined with a stand‐alone method called the three‐step method. Through large‐scale experiments, we show that the proposed hybrid approach could reduce the network update time and packet loss. It is concluded that the proposed GA‐Flow Scheduler provides improved performance over the stand‐alone three‐step method. Also, it handles the above‐mentioned network update problems in SDN.

An Agent-Based Model Driven Decision Support System for Reactive Aggregate Production Scheduling in the Green Coffee Supply Chain

The aim of this paper is to contribute to the thread of research regarding the need for logistic systems for planning and scheduling/rescheduling within the agro-industry. To this end, an agent-based model driven decision support system for the agri-food supply chain is presented. Inputs in this research are taken from a case example of a Mexican green coffee supply chain. In this context, the decision support agent serves the purposes of deriving useful knowledge to accomplish (i) the decision regarding the estimation of Cherry coffee yield obtained at the coffee plantation, and the Parchment coffee sample verification decision, using fuzzy logic involving an inference engine with IF-THEN type rules; (ii) the production plan establishment decision, using a decision-making rule approach based upon the coupling of IF-THEN fuzzy inference rules and equation-based representation by means of mixed integer programming with the aim to maximize customer service level; and (iii) the production plan update decision using mathematical equations once the customer service level falls below the expected level. Three scenarios of demand patterns were considered to conduct the experiments: increasing, unimodal and decreasing. We found that the input inventory and output inventory vary similar over time for the unimodal demand pattern, not the case for both the increasing and decreasing demand patterns. For the decreasing demand pattern, ten tardy orders for the initial production schedule, an 88% service level, and nineteen tardy orders from the estimated production results, a 77% service level. This value falls below the expected level. Consequently, the updated aggregate production schedule resulted in ten tardy orders and an 88% service level.

PMU118 USE OF COMPUTER-ASSISTED METHODS TO REALIZE THE CONCEPT OF A LIVING SYSTEMATIC REVIEW VIA AN ONLINE PLATFORM

Developed by Cochrane, the concept of a “living” systematic literature review (SLR) refers to an SLR that is continually updated. The timely publication of results is intrinsic to this concept. We developed an online platform (“PSE-LiveSLR™”) that supports continual updating via computer-assisted methods and prioritizes rapid data indexing and communication. To commence each SLR, protocol including population, interventions, comparators, outcomes and study design (PICOS) criteria were developed according to standards put forth by Cochrane for acute myeloid leukemia, myelodysplastic syndrome, multiple myeloma and non-small cell lung cancer. Once an initial evidence base was established, scheduled updates were executed. Major databases (Cochrane, Embase, Medline, Pubmed) were automatically searched on a monthly basis, while relevant congress abstracts were added upon their release. Computer-assisted tools were used to augment reviewer efforts, enabling rapid review and extraction. Immediately upon generation, data were used to populate a guideline-consistent, fully interactive, web-based portal that allows further customization of SLR criteria. The platform successfully supported reviews across 4 selected oncology indications. Serialized, partially automated updates ensured that SLRs performed through the platform were never more than 1 month out-of-date, a pace that more than matches the pace of research publication. Users were automatically notified as new data were incorporated, resulting on average 2 updates per month with >50 new publications added per indication per month and over 1000 new publications in January-May 2019. Conventional SLRs that are updated semi-annually, if at all, are often outpaced by the rate of data production and publication. With the acknowledgement that up-to-date evidence is crucial for policy and practice decisions, SLR methodology is evolving. With this platform, continuous SLR updates and rapid data distribution are achievable, which may address key challenges faced by conventional SLRs and transform Cochrane’s living SLR from concept to reality.

Energy-Constrained Data Freshness Optimization in Self-Powered Networked Embedded Systems

This article explores how to optimize the freshness of real-time data for energy harvesting (EH)-based networked embedded systems (NESs) with energy constraints. We introduce the concept of age of information (AoI) to quantitatively measure the data freshness and present a comprehensive analysis on the average AoI of the real-time data with stochastic update arrival and energy replenishment patterns for single-source EH-based systems. An optimal offline solution and an effective online solution are designed to select a sequence of real-time data updates (while discarding the remaining ones) and determine their corresponding transmission time to minimize the average AoI. We further extend these findings to multisource EH-based NESs, and present an optimal offline solution and an efficient online solution to schedule updates for each data source to optimize the average AoI. The correctness of the analysis and the effectiveness of the proposed solutions have been validated through extensive experiments by comparing to the state-of-the-art methods. According to the experimental results, the proposed solutions reduce the average AoI by 47.2% and 69.1% on average comparing to the state-of-the-art solutions for single-source and multisource EH-based NESs, respectively, with low harvesting rates.

Efficient Event Scheduling of Network Update

Changes in network state are a common source of instability in networks. An update event typically involves multiple flows that compete for network resources at the cost of rescheduling and migrating some existing flows. Previous network updating schemes tackle such flows independently, rather than as the entity of an update event. They only optimize the flow-level metrics for the flows involved in an update event. In this paper, we present an event-level abstraction of network update that groups flows of an update event and schedules them together to minimize the event completion time (ECT). We then study the scheduling problem of multiple update events for achieving high scheduling efficiency and preserving fairness. The designed least migration traffic first (LMTF) method schedules all update events in the FIFO order, but it avoids head-of-line blocking by randomly fine-tuning the queue order of some events. It can considerably reduce the update cost, the average, and tail ECTs of update events. In addition, we design a general parallel-LMTF (P-LMTF) method to guarantee fairness and further improve scheduling efficiency among update events. This improves the LMTF method by opportunistically updating multiple events simultaneously. The comprehensive evaluation results indicate that the average ECT of our approach is up to $10 \times $ faster than the flow-level scheduling method for network update events, and its tail ECT is up to $6 \times $ faster. Our P-LMTF method incurs a 75% reduction in the average ECT compared with FIFO when the network utilization exceeds 70%, and it achieves a 42% reduction in tail ECT.

Bi‐objective missile rescheduling for a naval task group with dynamic disruptions

AbstractThis paper considers the rescheduling of surface‐to‐air missiles (SAMs) for a naval task group (TG), where a set of SAMs have already been scheduled to intercept a set of anti‐ship missiles (ASMs). In missile defense, the initial engagement schedule is developed according to the initial state of the defensive and attacking units. However, unforeseen events may arise during the engagement, creating a dynamic environment to be handled, and making the initial schedule infeasible or inefficient. In this study, the initial engagement schedule of a TG is assumed to be disrupted by the occurrence of a destroyed ASM, the breakdown of a SAM system, or an incoming new target ASM. To produce an updated schedule, a new biobjective mathematical model is formulated that maximizes the no‐leaker probability value for the TG and minimizes the total deviation from the initial schedule. With the problem shown to be NP‐hard, some special cases are presented that can be solved in polynomial time. We solve small size problems by the augmented ϵ‐constraint method and propose heuristic procedures to generate a set of nondominated solutions for larger problems. The results are presented for different size problems and the total effectiveness of the model is evaluated.

Implementasi Sistem Informasi dan Manajemen Pendidik dan Tenaga Kependidikan dalam Pembayaran Tunjangan Profesi Guru Madrasah

The purpose of this study is to analyze SIMPATIKA implementation in the payment of Madrasah Teacher professional allowances and what are the obstacles in the implementation of SIMPATIKA, using qualitative methods. The informants of this study were the Apparatus of the Ministry of Religion of the City of Binjai, IT and Madrasah Teachers. The results showed that the Implementation of Information Systems and Management of Educators and Education Personnel (SIMPATIKA) in Madrasah Teacher Professional Allowance Payments in the Binjai City Ministry of Religion Office had not run optimally, this can be seen from several dimensions below: When viewed from the communication dimension, Submission of information from SIMPATIKA implementation is not done thoroughly and information is only done through social media. If viewed from the dimension of human resources in the implementation of SIMPATIKA in the Ministry of Religion of the City of Binjai, in the process of forming a decision letter is still done manually so that employees require a long time to recap the data and inadequate non-human resources in this application system in implementation SIMPATIKA. And experiencing some obstacles in the implementation of SIMPATIKA, namely the lack of staff / employees in the implementation of SIMPATIKA, and inadequate management information system (SIM) in the SIMPATIKA time / Schedule update process and the need to increase socialization that is considered less comprehensive for all Madrasah Teachers in the Binjai City Ministry of Religion.

Accuracy Of The Relative Value Scale Update Committee's Time Estimates And Physician Fee Schedule For Joint Replacement.

Even though relative value units guide 70percent of physician payment, little research has assessed their accuracy. We analyzed actual service time for total hip and knee replacements at two academic hospitals in the period January1, 2013-October1, 2016, using electronic health record time-stamp data, and we compared that time with the Medicare Physician Fee Schedule and most recent Relative Value Scale Update Committee recommendations. We found that the committee and fee schedule overestimated the operating time of original hip replacements by 18percent and original knee replacements by 23percent. Revision hip replacements were overestimated by 61percent and knee replacements by 48percent. In a multivariate analysis we found that faster operating time was not associated with more complications or admissions to the intensive care unit. Complication rates varied tenfold across physicians and twofold across hospitals. The fee schedule and the committee significantly overestimated operating times for original and revision hip and knee replacements. Policy makers should use empirical time-stamp data instead of self-reported estimates to determine physician payment.

Concurrency in Boolean networks

Boolean networks (BNs) are widely used to model the qualitative dynamics of biological systems. Besides the logical rules determining the evolution of each component with respect to the state of its regulators, the scheduling of component updates can have a dramatic impact on the predicted behaviours. In this paper, we explore the use of Read (contextual) Petri Nets (RPNs) to study dynamics of BNs from a concurrency theory perspective. After showing bi-directional translations between RPNs and BNs and analogies between results on synchronism sensitivity, we illustrate that usual updating modes for BNs can miss plausible behaviours, i.e., incorrectly conclude on the absence/impossibility of reaching specific configurations. We propose an encoding of BNs capitalizing on the RPN semantics enabling more behaviour than the generalized asynchronous updating mode. The proposed encoding ensures a correct abstraction of any multivalued refinement, as one may expect to achieve when modelling biological systems with no assumption on its time features.

Fundamental bounds on the age of information in multi-hop global status update networks

This paper studies the of in a general multi-source multi-hop wireless network with explicit channel contention. Specifically, the scenario considered in this paper assumes that each node in the network is both a source and a monitor of information, that all nodes wish to receive fresh status updates from all other nodes in the network, and that only one node can transmit in each time slot. Lower bounds for peak and average age of information are derived and expressed in terms of fundamental graph properties including the connected domination number. An algorithm to generate near-optimal periodic status update schedules based on sequential optimal flooding is also developed. These schedules are analytically shown to exactly achieve the peak age bound and also achieve the average age bound within an additive gap scaling linearly with the size of the network. Moreover, the results are sufficiently general to apply to any connected network topology. Illustrative numerical examples are presented which serve to verify the analysis for several canonical network topologies of arbitrary size, as well as every connected network with nine or fewer nodes.