Consensus Recovery Research Articles

Substance use disorder treatment success: assessing patient-reported use improvement and provider-evaluated treatment completion

Background Provider-evaluated substance use treatment completion and client-reported substance use improvement are standards in determining treatment success. The relationship between these two outcomes is anecdotally understood in practice. However, the relationship has not been empirically determined and factors related to provider/client conflicting assessments are unknown. This study investigates treatment success by investigating consensus and conflict between improvement and completion in a large national sample. Method The present study is a cross-sectional retrospective evaluation of US substance use treatment episodes from facilities receiving public funding from 2015 to 2019 (N = 5,047,714). Episodes were mostly male (64.5%), aged 25–34 (34.4%), and White (58.5%). Conflict, consensus, and client factors associated with conflicting outcome evaluations were compared with differences in proportions and their 95% confidence intervals. Logistic regression was used to predict completion from improvement, adjusting for covariates. Results For absolute percentages, clients and providers were in consensus in 48.3% of all episodes, 32.5% were in conflict, and 19.2% were missing. The adjusted analysis significantly predicted completion from improvement (aOR = 2.18, 95% CI = 2.17, 2.19). Importantly, outcome conflict demonstrated absolute meaningful associations with problem substance, referral source, employment status, service setting, and supplemental mutual-help group attendance. Conclusions Completion and improvement are somewhat associated, but most likely represent separate factors of treatment success. Addressing factors associated with outcome conflict may improve client and provider consensus and increase successful recovery. Policies and programs can set standards aligned with a uniform definition of success accounting for use improvement.

Optimal Consensus Recovery of Multi-agent System Subjected to Agent Failure

Multi-Agent Systems are susceptible to external disturbances, sensor failures or collapse of communication channel/media. Such failures disconnect the agent network and thereby hamper the consensus of the system. Quick recovery of consensus is vital to continue the normal operation of an agent-based system. However, only limited works in the past have investigated the problem of recovering the consensus of an agent-based system in the event of a failure. This work proposes a novel algorithmic approach to recover the lost consensus, when an agent-based system is subject to the failure of an agent. The main focus of the algorithm is to reconnect the multi-agent network in a way so as to increase the connectivity of the network, post recovery. The proposed algorithm may be applied to both linear and non-linear continuous-time consensus protocols. To verify the efficiency of the proposed algorithm, it has been applied and tested on two multi-agent networks. The results, thus obtained, have been compared with other state-of-the-art recovery algorithms. Finally, it has been established that the proposed algorithm achieves better connectivity and therefore, faster consensus when compared to the other state-of-the-art.

A consensus recovery approach to nonlinear multi-agent system under node failure

In large-scale networks, node failure is unavoidable and it generally brings undesirable effects on the stability and performance of the systems. Then a natural question arises: is it possible to cope with the problem arising from the node failure in the networks, while retaining the corresponding network property (or make the network systems robust against the node failure)? In this paper, a consensus recovery approach will be proposed to investigate the consensus of general directed nonlinear multi-agent networks with node failure. The objective of the consensus recovery method is to compensate for the undesirable effects of the failure nodes, and to retain the consensus property. Numerical examples are provided to demonstrate the effectiveness of the theoretical results obtained, even for large-scale multi-agent systems.

English

This paper introduces a novel method of continuous verification of simulation software used in decision-support systems for nuclear emergency management (DSNE). The proposed approach builds on methods from the field of software reliability engineering, such as N-Version Programming, Recovery Blocks, and Consensus Recovery Blocks. We introduce a new acceptance test for dispersion simulation results and a new voting scheme based on taxonomies of simulation results rather than individual simulation results. The acceptance test and the voter are used in a new scheme, which extends the Consensus Recovery Block method by a database of result taxonomies to support machine-learning. This enables the system to learn how to distinguish correct from incorrect results, with respect to the implemented numerical schemes. Considering that decision-support systems for nuclear emergency management are used in a safety-critical application context, the methods introduced in this paper help improve the reliability of the system and the trustworthiness of the simulation results used by emergency managers in the decision making process. The effectiveness of the approach has been assessed using the atmospheric dispersion forecasts of two test versions of the widely used RODOS DSNE system. ACM CCS (2012) Classification : Information systems→Information systems applications→Decision support systems→Expert systems *To cite this article: T. B. Ionescu and W. Scheuermann, Improving the Reliability of Decision-Support Systems for Nuclear Emergency Management by Leveraging Software Design Diversity, CIT. Journal of Computing and Information Technology , vol. 24, no. 1, pp. 45-63, 2016.

Fuzzy Multi-criteria Approach for Component Selection of Fault Tolerant Software System under Consensus Recovery Block Scheme

The vibrant and advanced software development tools not only provide software with versatile functions for radical users but at the same time, an easy to use GUI for naive users. APS (Application Package Software) has provided a customised approach for developing independent software components which are ready to be integrated with existing software systems. The APS along with CBSE (Component Based Software Engineering) has an inordinate potential for reducing development time, cost and effort, which otherwise may extend beyond weeks or months’ time for integration. Further, the CBSE approach promotes software reusability i.e. reusing the available components. A component can be reused after fabrication which will include the fabrication cost and time. For development of economical and reliable software, components can be procured in the form of Commercial off-The Shelf (COTS) components from the vendor or may be developed in-house or can be fabricated. This decision is based on several parameters. The aim of this paper is to select the suitable mix of components using Build-or-buy strategy or considering fabrication and to propose a multi-objective model for software modular system with objective of maximizing reliability while simultaneously minimizing the cost, execution time and Source Lines of Code (SLOC) using Consensus Recovery Block Scheme.

Goal Programming Approach for Selection of COTS Components in Designing a Fault Tolerant Modular Software System under Consensus Recovery Block Scheme

The application of computer systems has now crossed many different fields. Systems are becoming more software intensive. The requirements of the customer for a more reliable software led to the fact that software reliability is now an important research area. One method to improve software reliability is by the application of redundancy. A careful use of redundancy may allow the system to tolerate faults generated during software design and coding thus improving software reliability. The fault tolerant software systems are usually developed by integrating COTS (commercial off-the-shelf) software components. This paper is designed to select optimal components for a fault tolerant modular software system so as to maximize the overall reliability of the system with simultaneously minimizing the overall cost. A chance constrained goal programming model has been designed after considering the parameters corresponding to reliability and cost of the components as random variable. The random variable in this case has been considered as value which has known mean and standard deviation. A chance constraint goal programming technique is used to solve the model. The issue of compatibility among different commercial off-the shelf alternatives is also considered in the paper. Numerical illustrations are provided to demonstrate the model.

Fuzzy multi-objective build-or-buy approach for component selection of fault tolerant software system under consensus recovery block scheme with mandatory redundancy in critical modules

During the last two decades, there has been a growing interest in component-based software engineering CBSE both in academia and industry. In component-based system development, it is common to identify software modules first. Once they are identified, we need to select appropriate software components for each module. These components can either be bought as commercial off-the-shelf COTS components and probably adapted to work in the software system or can be developed in-house. This is a 'build-or-buy' decision. This paper discusses a framework that helps a developer to decide whether to buy or to build software components while designing a fault-tolerant modular software system. This paper proposes optimisation models for optimal component selection for a fault-tolerant modular software system under the consensus recovery block scheme. It is necessary to identify critical modules in the design of a fault-tolerant modular software system and also to develop a system with a built in redundancy for critical modules. Therefore, the first optimisation model is developed for optimal component selection with the dual objective of reliability maximisation and cost minimisation of the overall system under the constraints on the delivery time and criticality of modules. The second optimisation model is an extension of the first optimisation model and discusses the issue of compatibility of components of modules. In practice, it is not possible for management to obtain precise value of reliability, cost, delivery time, etc., therefore both the models are formulated as fuzzy multi-objective optimisation models. A case study of developing a manufacturing system for medium-size enterprise is used to illustrate the proposed methodology.

OPTIMAL COMPONENT SELECTION APPROACH FOR FAULT-TOLERANT SOFTWARE SYSTEM UNDER CRB INCORPORATING BUILD-OR-BUY DECISION

Application Package Software (APS) has emerged as a ready-to-use solution for the software industry. The software system comprises of a number of components which can be either purchased from the vendor in the form of COTS (Commercial Off-the-Shelf) or can be built in-house. Such a decision is known as Build-or-Buy decision. Under the situations wherein the software has the responsibility of supervising life-critical systems, the inception of errors in software due to inadequate or incomplete testing, is not acceptable. Such life-critical systems enforces upon meeting the quality standards of the software as unforbiddenable. This can be achieved by incorporating a fault-tolerant design that enables a system to continue its intended operation rather than failing completely when some part of the system fails. Moreover, while designing a fault-tolerant system, it must be apprehended that 100% fault tolerance can never be achieved and the closer we try to get to 100%, the more costly the system will be. The proposed model shall incorporate consensus recovery block scheme of fault tolerant techniques. Through this paper, we shall focus on build-or-buy decision for an APS in order to facilitate optimal component selection thereby, maximizing the reliability and minimizing the overall cost and source lines of code of the entire system. Further, since the proposed problem has incompleteness and unreliability of input information such as execution time and cost, hence, the environment in the proposed model is taken as fuzzy.

A Review of the Management of Patellofemoral Pain Syndrome

Objective: Patellofemoral pain syndrome (PFPS) is one of the most frequently diagnosed knee conditions in the primary care, orthopedic, and sports medicine settings. Although strength training and stretching programs have traditionally been the mainstay of patient treatment, there are no consensus recovery protocols for runners experiencing PFPS. The purpose of our review is to examine recent literature regarding the efficacy of various treatment modalities in the management of patients with PFPS. Methods: Our review included 33 articles from a PubMed literature search using the search term PFPS treatment. The search was limited to randomized controlled trials, crossover case-controlled studies, and cohort studies with ⩾ 10 participants, with trial data that were published within the last 5 years. Results: Strength training and stretching exercises continue to be strongly supported by research as effective treatment options for runners with PFPS. Recent studies have confirmed that quadriceps and hip strengthening combined with stretching in a structured physiotherapy program comprise the most effective treatment for reducing knee pain symptoms and improving functionality in patients with PFPS. As previous studies have shown, therapies such as proprioceptive training, orthotics, and taping may offer benefits as adjunctive therapies but do not show a significant benefit when they are used alone in patients with PFPS. Additionally, recent research has confirmed that surgical and pharmacologic therapies are not effective for the management of patients with PFPS. Conclusion: A large number of athletes are impacted by PFPS every year, particularly young runners. Sports medicine researchers have investigated many possible therapies for patients with PFPS; however, no clear guidelines have emerged regarding the management of the syndrome. Our review analyzes recent literature on PFPS and identifies specific treatment recommendations. The most effective and strongly supported treatment modality for patients with PFPS is a combined physiotherapy program, including strength training of the quadriceps and hip abductors and stretching of the quadriceps muscle group. Adjunctive therapies, including taping, biofeedback devices, and prefabricated orthotic inserts, may provide limited additive benefits in select populations. Surgery should be avoided in all patients with PFPS.

Consensus Recovery from Intentional Attacks in Directed Nonlinear Multi-agent Systems

Abstract Resilience or recovery of multi-agent systems against attacks is believed to be one of the most important topics in control and management of complex systems. Previous studies have mainly focused on the random failure and intentional attack targeted on node degrees, whereas consensus recovery is much less investigated. In this paper, two kinds of targeted attacks are introduced and corresponding recovery strategies are proposed to address the consensus recovery of continuous-time nonlinear multi-agent systems under directed topologies against subsequent attacks. The cut-nodes and cut-edges are chosen as the targets of attack, and the multi-agent system becomes disconnected when they are deleted from the system. The neighbor nodes of the cut-node and end nodes of the cut-edge are used to recover the connectivity of the network. It is shown that our proposed strategies can significantly improve the convergence speed of reaching consensus of the resulting multi-agent systems. A cost function is also proposed to compare different recovery strategies.

Fuzzy optimization approach to component selection of fault-tolerant software system

In developing software systems, a manager’s goal is to design software using limited resources and meet the user requirements. One of the important user requirements concerns the reliability of the software. The decision to choose the right software modules (components) becomes extremely difficult because of the number of parameters to be considered while making the decision. If suitable components are not available, then the decision process is further complicated with build versus buy decisions. In this paper, we have formulated a fuzzy multi-objective approach to optimal decision “build-or-buy” for component selection for a fault-tolerant modular software system under the consensus recovery block scheme. A joint optimization model is formulated where the two objectives are maximization of system reliability and minimization of the system cost with a constraint on delivery time. An example of developing a retail system for small-and-medium-size enterprises is used to illustrate the proposed methodology.

Consensus Recovery in Networked Multi-Agent Time-Delay Systems Against Targeted Attacks

Consensus Recovery in Networked Multi-Agent Time-Delay Systems Against Targeted Attacks

Optimal Component Selection Problem for Cots Based Software System under Consensus Recovery Block Scheme: A Goal Programming Approach

Cost, reliability and time are the three main quality attributes of a software system. Now days much software are designed on COTS component in order to facilitate timely development with reduced cost and improved reliability. Software deigned to handle critical control systems have very high reliability requirements. Fault tolerance is designed in these systems for some or all of the software modules so that execution can be resumed even after failure with minimal loss of data and time. Designing fault tolerance requires extra resources. Even though reliability requirement are very high the developers can’t spend endless resources on any project. This is a trade off problem between reliability and cost. Many such problems have been discussed in literature considering distinct objectives and constraints and have given good results. An effective approach to discuss this problem is to formulate a multi-objective problem with cost minimization and reliability maximization as the two objectives with an upper bound on cost and lower bound on reliability. In this paper we formulate this bi-criteria problem and discuss the solution methodology. The problem is formulated for consensus recovery block fault tolerant scheme. In case a feasible solution for the problem exists, criterion vector approach is used to solve the problem and otherwise if the bounds are contradictory a goal programming approach is used to solve the problem to obtain a compromised solution. Alternative goal solutions are obtained assigning different weights for the objective to facilitate the decision maker with correct decision.

Consensus recovery of multi-agent systems subjected to failures

Consensus recovery is one of the most important topics of multi-agent systems subjected to failures, but there are few literatures considering this theme. In this article, two disastrous failures are introduced and corresponding recovery programs are proposed to investigate the consensus recovery of multi-agent systems. The failures of multi-agent systems mainly refer to the failures to the agents and links. The cut-agent and cut-link are presented to better understand the disastrous failures of multi-agent systems, and they are the most important components of multi-agent systems. When the cut-agent and cut-link are removed from the systems, the multi-agent systems will become disconnected, and the neighbour agents of cut-agent are used to recover the consensus of multi-agent systems in this article. For different failures, the different measures are taken to restore the connectivity of multi-agent systems, so as to recover the consensus of multi-agent systems. Under the proposed recovery strategies, the convergence speed of achieving consensus of the resulting networks is considered as the main target. Moreover, there is a trade-off between the convergence speed and robustness of the resulting networks.

OPTIMAL COMPONENT SELECTION OF COTS BASED SOFTWARE SYSTEM UNDER CONSENSUS RECOVERY BLOCK SCHEME INCORPORATING EXECUTION TIME

Computer based systems have increased dramatically in scope, complexity, pervasiveness. Most industries are highly dependent on computers for their basic day to day functioning. Safe & reliable software operations are an essential requirement for many systems across different industries. The number of functions to be included in a software system is decided during the software development. Any software system must be constructed in such a way that execution can resume even after the occurrence of failure with minimal loss of data and time. Such software systems which can continue execution even in presence of faults are called fault tolerant software. When failure occurs one of the redundant software modules get executed and prevent system failure. The fault tolerant software systems are usually developed by integrating COTS (commercial off-the-shelf) software components. The motivation for using COTS components is that they will reduce overall system development costs and reduce development time. In this paper, reliability models for fault tolerant consensus recovery blocks are analyzed. In first optimization model, we formulate joint optimization problem in which reliability maximization of software system and execution time minimization for each function of software system are considered under budgetary constraint. In the second model the issue of compatibility among alternatives available for different modules, is discussed. Numerical illustrations are provided to demonstrate the developed models.

Reliability analysis of N‐version programming with deadline mechanism

In this paper reliability models for fault tolerant N‐version programming and consensus recovery block (combination of N‐version programming and recovery block) with deadline mechanism are analysed. Explicit expressions for reliability of N‐version programming and consensus recovery block with exponential execution times are derived. The paper also presents optimisation models for real time N‐version programming. The objective of the optimisation problem is to maximise reliability of the software satisfying a budget constraint. The paper also includes efficient branch and bound procedure that can be used to solve the optimisation problem.

Optimization models for recovery block schemes

This paper presents optimization models for a fault tolerant software by selecting a set of versions for a given program. The objective is to maximize the reliability of the software satisfying a budget limitation. Optimization models are developed for two block recovery schemes: (1) independent recovery block and (2) consensus recovery block. The paper also presents simple formulas to calculate the reliability of the two schemes.

Optimization models for complex recovery block schemes

In this paper we consider three complex recovery block schemes: (1) nested recovery block; (2) modified recovery block; and (3) nested consensus recovery block. For all the three models: (1) we derive simple expressions for calculating the system reliability; (2) we investigate how to arrange the versions in a nested recovery block and in a nested consensus recovery block; and (3) we develop optimization models where the objective is to optimize the reliability satisfying a budget constraint. The paper also includes efficient branch and bound procedures to solve the optimization problems. Two numerical example problems are solved to illustrate the branch and bound technique. Scope and purposes Software has become an integral part of many systems. For systems such as air traffic control, space shuttle, fighter aircraft and automated-guided missiles, it is usually the reliability of computer software that has the most single significant impact on the performance. Virtually, all major military systems are dependent on the correct operation of defense systems’ software. For systems such as air traffic control, fighter aircraft and automated guided missiles, 80% of the life cycle cost is spent on the software. Traditionally, reliability of any hardware and software is improved by introducing redundancy. However, redundant components require additional resources. Therefore, the redundancy level needed to achieve specified reliability must be carefully determined. The main purpose of this paper is to develop reliability prediction techniques and optimization models for important fault-tolerant software such as nested recovery block, modified recovery block and nested consensus recovery block. The methods have significant use in selection of programs in COTS (commercial-off-the-shelf) environment.

Cost modeling of N-version fault-tolerant software systems for large N

A cost model determines system costs for fault-tolerant software systems. The model finds the optimal number of program versions to achieve minimum system cost of the fault-tolerant software techniques: N-version programming, recovery block, and consensus recovery block. In this case, all versions, the voter, and the acceptance test have the same reliability. When the parameters for the versions, acceptance test, and voter in the cost function are all equal, the cost of a 3-version system is always optimal, Cost(CRB)/spl Lt/Cost(RB)/spl Lt/Cost(NVP) for each target reliability differing by as much as two orders of magnitude in some cases. The cost functions were increasing functions of N. When the parameters are not equal, optimality occurred for other values of N. This was especially the case when the cost exponent for version-1 was larger than the exponents for the other versions and the acceptance test or voter. As the values of the cost exponents for the version reliabilities become larger, a smaller difference was required between the version-1 exponent and the others to produce alternate optima.

Cost modelling of fault-tolerant software

Costs of a simplex or single-version system are compared with the following three-version fault-tolerant software systems: N-version programming (NVP), recovery block (RB), and consensus recovery block (CRB). Cost is minimized subject to a system reliability constraint. The objective function of the optimization program is of the form ∑ β i /(1 − r i ) χ i where the constants β i and α i are fixed and the r, are variables that are reliabilities of the versions, the acceptance test in the case of RB and CRB and the voter in the case of NVP and CRB. The costs are compared for different values of β i and for values of α i = 0.5, I, and 2. Assuming that failures are independent, CRB followed by RB are the most cost-justifiable fault-tolerant techniques considered. Unless the voter is perfect, NVP does not compete cost-wise with the other two methods. Indeed, in some cases it is worse than a simplex system.