Evaluating fault tolerance approaches in multi-agent systems

A multi-agent system (MAS) is a distributed system that consists of multiple agents working together to solve mutual problems. Even though MASs are well suited for the development of complex distributed systems, the number of real-world usages is still small. One of the main reasons for this is that MASs are very fragile. In a typical, large-scale MAS, the rate of failure grows with the number of hosts, the number of deployed agents, and the duration of the agent’s task execution. For this reason, numerous approaches have been introduced to deal with aspects of failure handling. However, the absence of centralized control and a large number of individual intelligent components makes it difficult to detect and treat errors. The risk of uncontrollable fault propagation is high and can seriously impact on system performance. There are two important factors that limit the usage of MASs: (1) existing fault tolerance (FT) approaches are not generic, as they focus on and improve specific issues of FT; and (2) despite the plethora of available FT approaches and theories, there is a remarkable lack of general metrics, tools, benchmarks, and experimental methods for formal validation and comparison of existing or newly developed FT approaches. As FT approaches in MASs become a well-established field, the need for generalized, standardized evaluation of FT approaches emerges as imperative. In this paper, we first present a detailed overview of existing FT solutions, approaches, and techniques in agent platform hosted MASs. From that overview, we derive the commonalities in existing research. Next, we present the main contribution of our paper: an evaluation methodology, with a set of metrics, for comparing FT approaches in MASs. We adopt an engineering perspective on the problem, defining a methodology and metrics that are both implementation- and domain-independent. The metrics are formalized with an acyclic directed graph. By using our methodology, evaluators can select an appropriate FT approach for targeted MAS application, thus improving MAS usability, stability, and development speed. In order to show the viability of our approach, a case study that compares two FT approaches for a targeted MAS is presented. The case study results show that our methodology can be used for selecting an appropriate FT approach for the targeted MAS.     

Experimental determination of mechanical properties and short-time creep of AISI 304 stainless steel at elevated temperatures

The high temperature properties of AISI 304 stainless steel were studied.Basic data about the employed experimental equipment,testing procedures,and specimen geometry were given.The experimental setup was used to obtain stress-strain diagrams from tensile tests at room temperature as well as several elevated temperatures.Furthermore,the specimens were subjected to short-time creep tests at various temperatures.Stress levels for creep testing were established as a percentage of yield stress.The results indic...     

Analysis of service platforms by a portfolio approach

This work provides a framework for techno-business analysis of service platforms that can be used for evaluation of business models and strategic positions in collaborative service provision. It is based on the following modeling tools: techno-business model, generic service platform approximate, scenario modeling techniques, and service and enabler portfolio analysis. Our modeling approach is a synthesis of qualitative and quantitative analyses. We show that Markowitz’ portfolio theory (financial risk-return analysis) can also be applied on service and on enablers portfolios if their specificity is realistically modeled. We demonstrate the most important modeling procedures theoretically and evaluate them practically on a chosen service delivery platform. Our research results and experiences show that service portfolio theory is very useful for evaluation of business strategies of different industrial actors, participating in collaborative service provision.     

Hypoproteinemia as a prognostic risk factor for arteriovenous fistula failure

Introduction: Any vascular access is of limited duration with many factors which influence survival in patients on chronic hemodialysis (HD). Hypoproteinemia as a marker of chronic illness is common among chronic HD patients. Our aim was to analyze the survival of the primary arteriovenous fistula (AVFs) and the risk factors which influence their patency and to test the hypothesis that patients with normal values of serum proteins have lower risk of AVF failure compared to patients with hypoproteinemia. Methods: Seven hundred thirty‐four consecutive patients were included who underwent creation of an AVF. The patients were prospectively followed‐up for 2 years. Only patients with AVF function after a month from its creation were analyzed. The patients were divided into two subgroups, with normal and low serum protein levels (<65 g/L). Findings: At follow‐up 497 (67.7%) AVFs were still functional while 237 (32.3%) AVFs failed due to thrombosis or stenosis. Serum proteins and AVFs created on the forearm were positive predictors while diabetes was a negative predictor of longer AVF survival (P < 0.001; P = 0.003; P = 0.043). When comparing patients with normal and low serum protein levels (<65 g/L), mean survival time was significantly longer in patients with normal serum levels (P < 0.001). Discussion: In this study, hypoproteinemia was an independent prognostic marker for AVF failure at 2 years. Hypoproteinemia, based on our results, is an independent, more sensitive and prognostic marker of possible vascular access failure than the presence of other common factors which influence shorter AVF survival.     

Model based inertial sensing of human body motion kinematics in sit-to-stand movement

The paper presents the design and validation of a three-segment human body model. The model is aimed at the reconstruction of motion trajectories of the shank, thigh and HAT (Head-Arms-Trunk) segments in sit-to-stand-motion using low cost inertial sensors. For this purpose the Extended Kalman filter is applied for fusion of model data and data acquired through measurements. The simplifications, like motion constraint to sagittal plane, symmetry of movement and assumption of ideal joints are introduced in the model. Model validation was performed on simulated data and on measurements data acquired with the Optotrak optical motion analysis system. Obtained results are presented and discussed.     

Tool wear estimation using an analytic fuzzy classifier and support vector machines

A new type of continuous hybrid tool wear estimator is proposed in this paper. It is structured in the form of two modules for classification and estimation. The classification module is designed by using an analytic fuzzy logic concept without a rule base. Thereby, it is possible to utilize fuzzy logic decision-making without any constraints in the number of tool wear features in order to enhance the module robustness and accuracy. The final estimated tool wear parameter value is obtained from the estimation module. It is structured by using a support vector machine nonlinear regression algorithm. The proposed estimator implies the usage of a larger number and various types of features, which is in line with the concept of a closer integration between machine tools and different types of sensors for tool condition monitoring.     

Pilot Studies of Ozonation for Inactivation of Artemia salina Nauplii in Ballast Water

A pilot-plant study was conducted in the Republic of Croatia to determine the applicability of ozonation for inactivation of non-indigenous species and to provide necessary information regarding use of ozone as a ballast water treatment option. Nauplii of the brine shrimp Artemia salina were used as model organisms to investigate the efficacy of ozonation at three different ozone dosages (2.4, 3.7 and 10.9 mg L^?1). Mortality of Artemia nauplii at 98.6%, was achieved after 3 h of exposure in ozone-treated water with the highest ozone dosage. Our results indicated that ozonation is a promising treatment for controlling non-indigenous and potentially invasive species; however, to draw more general conclusions, several species with higher level of resistance to ozone are required and will be studied in the future.     

Accounting for dynamics in attribute-importance and for competitor performance to enhance reliability of BPNN-based importance-performance analysis

Importance-performance analysis (IPA) is a decision-support tool used in prioritizing quality improvements of products/services. Recently, back-propagation neural network (BPNN)-based approaches have been proposed to deal with the problem of asymmetric effects in customer satisfaction formation. Though reliability of IPA is increased by the integration of BPNN, shortcomings of the analytical framework remain that (a) it does not provide insight into forms and degrees of these asymmetric effects, (b) it does not account for differences between the relevance and determinance of quality attributes, and (c) it neglects the competitor dimension in attribute-prioritization. Since all these issues have important managerial implications, the authors of this study propose an extended BPNN-based IPA that uses a multidimensional operationalization of attribute-importance, and that considers competitive performance levels. Using data from an airline satisfaction survey, an empirical test reveals that the proposed approach significantly outperforms conventional BPNN-based IPA. In particular, conventional BPNN-IPA would mislead managerial action with regard to 3 out of 8 quality components (37.5%).     

Mitochondrial DNA Fragmentation to Monitor Processing Parameters in High Acid,Plant‐Derived Foods

Mitochondrial DNA (mtDNA) fragmentation was assessed in acidified foods. Using quantitative polymerase chain reaction, C_t values measured from fresh, fermented, pasteurized, and stored cucumber mtDNA were determined to be significantly different (P > 0.05) based on processing and shelf‐life. This indicated that the combination of lower temperature thermal processes (hot‐fill at 75 °C for 15 min) and acidified conditions (pH = 3.8) was sufficient to cause mtDNA fragmentation. In studies modeling high acid juices, pasteurization (96 °C, 0 to 24 min) of tomato serum produced C_t values which had high correlation to time‐temperature treatment. Primers producing longer amplicons (approximately 1 kb) targeting the same mitochondrial gene gave greater sensitivity in correlating time‐temperature treatments to C_t values. Lab‐scale pasteurization studies using C_t values derived from the longer amplicon differentiated between heat treatments of tomato serum (95 °C for <2 min). MtDNA fragmentation was shown to be a potential new tool to characterize low temperature (<100 °C) high acid processes (pH < 4.6), nonthermal processes such as vegetable fermentation and holding times of acidified, plant‐derived products.