Evaluating scholars based on their academic collaboration activities: two indices, the RC-index and the CC-index, for quantifying collaboration activities of researchers and scientific communities

Although there are many studies for quantifying the academic performance of researchers, such as measuring the scientific performance based on the number of publications, there are no studies about quantifying the collaboration activities of researchers. This study addresses this shortcoming. Based on three measures, namely the collaboration network structure of researchers, the number of collaborations with other researchers, and the productivity index of co-authors, two new indices, the RC-Index and CC-Index, are proposed for quantifying the collaboration activities of researchers and scientific communities. After applying these indices on a data set generated from publication lists of five schools of information systems, this study concludes with a discussion of the shortcomings and advantages of these indices.     

Energy use patterns and econometric models of grape production in Hamadan province of Iran

This paper examines the energy use patterns and relationship between energy input and yield for grape production in Malayer region of Hamadan Province. Data from 50 farmers were collected using a face-to-face questionnaire method. In the surveyed vineyards, average yield and energy consumption were calculated as 18,530 kgha⁻¹ and 45,213.66 MJha⁻¹, respectively. Among input energy sources, fertilizers, electricity and farmyard manure contained highest energy shares with 37.25%, 19%, and 17.84%, respectively. The energy ratio and energy productivity were found to be 4.95 and 0.42 kgMJ⁻¹.Three econometric models were developed to estimate the impact of energy inputs on yield. The results revealed that impact of chemical, fertilizer and water on yield were significant at 1% probability level. Also, indirect and non-renewable energies were found to be rather high. Sensitivity analysis indicated that among the inputs, chemical has the highest MPP value of energy inputs. RTS (returns to scale) values for grape yield was found to be 2.15; thus, there prevailed an IRS of grape for estimated model. The net return was found to be positive as 2810.56 $ha⁻¹ for grape. The benefit-cost ratio was calculated as 2.08.     

Experimental and modelling study of the solubility of CO2 in various CaCl2 solutions at different temperatures and pressures

Study of the thermodynamic behaviour of CaCl2-H2O-CO2 systems is important in different scientific areas in the chemical and petroleum engineering fields. For example, a system including salt- H20-CO2 is a common system in CO2 geological storage. During carbonate matrix acidizing, this mixture also appears as the spent acid. Hence, study of the behaviour of this system and the solubility of CO2 in CaCl2 brine in different thermodynamic conditions is critical. In this study, CO2 solubility in 0, 1.90 and 4.80 mol/L CaCl2 solutions at 328.15 to 375.15 K and 68.9 to 206.8 bar were measured. These values are normal for oil reservoirs. A popular thermodynamic model is available in the literature for estimating the CO2 solubility in pure water and NaC1 solutions. In this paper, the available model was modified by experimental work to be applicable for CaCl2 as well. Based on the measured data, the component interaction parameters in the base model were adjusted for a CaCl2-H2O-CO2 system. The developed model could predict CO2 solubility in different conditions with remarkable accuracy, particularly for high concentration solutions and at high pressures. This improvement is up to 65% better than in the base model. This model can be used in Darcy scale models for predicting wormhole propagation during carbonate matrix acidizing.     

Simulation of novel hybrid method to improve dynamic responses with PSS and UPFC by fuzzy logic controller

In this paper, a hybrid method is proposed to damp frequency and power oscillations in the power system equipped with unified power flow controller (UPFC) and power system stabilizer (PSS) controllers. The method is robust with respect to operating point’s changes. This hybrid method consists of two stages: offline and online. In the offline stage, the coefficients of PSS and UPFC controllers for different operating points have been found by PSO algorithm; then in the second stage, online new fuzzy controller is proposed to select the best PSS and UPFC coefficients according to operating point. The proposed method is simulated for single machine infinite bus system-associated PSS and UPFC for three different operating points in MATLAB software, and results of proposed method simulation are investigated and compared with conventional PSS (CPSS) + UPFC, CPSS controllers. Simulation results show that the proposed method has a better performance.

     

Robust control of systems with sector nonlinearities via convex optimization: A data‐driven approach

In this paper, a new data‐driven method for designing robust controllers is proposed for systems with sector‐bounded nonlinearities and multimodel uncertainties. The results from the circle criterion are used to generate necessary and sufficient convex constraints that guarantee the stability of the closed‐loop system. The main feature of the proposed approach is that only the frequency response data of the linear part of the system is used for guaranteeing the stability of the closed‐loop nonlinear system. Additionally, a convex optimization problem is formulated to ensure performance with respect to the fundamental component of a sector‐bounded nonlinearity. The case study illustrates how the proposed method can be used to control uncertain systems that are subject to sector‐bounded nonlinearities.     

Robust delay dependent fault estimation for a class of interconnected nonlinear time delay systems

This paper focuses on the problem of fault estimation for a class of interconnected nonlinear systems with time varying delays. In contrast to the common assumption imposed on the problem in most literature, here, there is no need for the delay rate to be less than one. Both actuator and component faults are considered within the general fault model invoked as multiplicative faults in this study. Robust adaptive observers are used to detect and estimate simultaneously the states and the parameter faults in each subsystem. The designed observers ensure a prescribed H _∞ performance level for the fault estimation error, irrespective of the uncertainties which are assumed here to be the unknown interconnections between the subsystems. With the aid of H _∞ performance index, the common assumption regarding the observer matching condition is no longer required. Sufficient conditions for asymptotic stability of the observers are derived via a matrix inequality approach with the aid of LyapunovKrasovskii function. Finally, a simulation example is presented to show the validity and feasibility of the proposed method.

     

An evolutionary approach to design practical μ synthesis controllers

This paper proposes an evolutionary approach to solve μ synthesis problem. The goal is to achieve low order, practical μ synthesis controllers without any order reduction. In the proposed approach µ synthesis problem is solved as a constraint optimization problem in which robust stability and robust performance based on μ analysis are considered as the constraint and the cost function respectively. In order to solve the optimization problem an improved particle swarm optimization (PSO) is chosen to find the required coefficients of a structure-specified controller. The performance and robustness of the proposed controller are investigated by an uncertain mass-damper-spring system and is compared with the D-K iteration controller (the conventional solution to μ synthesis problem). Simulation results demonstrate the advantages of the proposed controller in terms of simple structure and robustness against plant perturbations and disturbances in comparison with D-K iteration controller.     

Multi‐mode resource‐constrained project scheduling using modified variable neighborhood search heuristic

This paper aims at providing a fast near‐optimum solution to the multi‐mode resource‐constrained project scheduling problems (MRCPSPs), for projects with activities that have known deterministic renewable and nonrenewable resource requirements. The MRCPSP is known to be nondeterministic polynomial‐time hard and has been solved using various exact, heuristic, and meta‐heuristic procedures. In this paper, a modified variable neighborhood search heuristic algorithm is used as an advanced optimization technique that suits scheduling problems. For the experimental study, we have considered a standard set of 3929 multi‐mode benchmark instances from the project scheduling library with a range of projects comprising 10–30 activities. Moreover, for a better comparison, this research also considers a standard set of 4320 newly developed multi‐mode instances from MMLIB50, MMLIB100, and MMLIB+ datasets. With the limit of 50,000 schedules on these datasets, our proposed algorithm provides better makespan for 106, 34, and 1601 instances, respectively, which justifies the efficiency of the proposed algorithm, particularly for projects with a larger number of activities. The results reported in this paper can be used as a benchmark for other researchers to compare and improve.     

ARITO: Cyber-attack response system using accurate risk impact tolerance

We propose a novel approach for automated intrusion response systems to assess the value of the loss that could be suffered by a compromised resource. A risk assessment component of the approach measures the risk impact and is tightly integrated with our response system component. When the total risk impact exceeds a certain threshold, the response selection mechanism applies one or more responses. A multi-level response selection mechanism is proposed to gauge the intrusion damage (attack progress) relative to the response impact. This model proposes a feedback mechanism, which measures the response goodness and helps indicate the new risk level following application of the response(s). Not only does our proposed model constitutes a novel online mechanism for response activation and deactivation based on the online risk impact, it also addresses the factors inherent in assessing risk and calculating response effectiveness that are more complex in terms of detail. We have designed a sophisticated multi-step attack to penetrate Web servers, as well as to acquire root privilege. Our simulation results illustrate the efficiency of the proposed model and confirm the feasibility of the approach in real time. At the end of paper, we discuss the various ways in which an attacker might succeed in completely bypassing our response system.     

A high performance genetic algorithm using bacterial conjugation operator (HPGA)

In this paper an efficient evolutionary algorithm is proposed which could be applied to real-time problems such as robotics applications. The only parameter of the proposed algorithm is the “Population Size” which makes the proposed algorithm similar to parameter-less algorithms, and the only operator applied during the algorithm execution is the bacterial conjugation operator, which makes using and implementation of the proposed algorithm much easier. The procedure of the bacterial conjugation operator used in this algorithm is different from operators of the same name previously used in other evolutionary algorithms such as the pseudo bacterial genetic algorithm or the microbial genetic algorithm. For a collection of 23 benchmark functions and some other well-known optimization problems, the experimental results show that the proposed algorithm has better performance when compared to particle swarm optimization and a simple genetic algorithm.