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This paper aims to identify and appropriately respond to any socio-technical gaps within organisational information and cybersecurity practices. This culminates in the equal emphasis of both the social, technical and environmental factors affecting security practices.

The socio-technical systems theory was used to develop a conceptual process model for analysing organisational practices in terms of their social, technical and environmental influence. The conceptual process model was then applied to specifically analyse some selected information and cybersecurity frameworks. The outcome of this exercise culminated in the design of a socio-technical systems cybersecurity framework that can be applied to any new or existing information and cybersecurity solutions in the organisation. A framework parameter to help continuously monitor the mutual alignment of the social, technical and environmental dimensions of the socio-technical systems cybersecurity framework was also introduced.

The results indicate a positive application of the socio-technical systems theory to the information and cybersecurity domain. In particular, the application of the conceptual process model is able to successfully categorise the selected information and cybersecurity practices into either social, technical or environmental practices. However, the validation of the socio-technical systems cybersecurity framework requires time and continuous monitoring in a real-life environment.

This research is beneficial to chief security officers, risk managers, information technology managers, security professionals and academics. They will gain more knowledge and understanding about the need to highlight the equal importance of both the social, technical and environmental dimensions of information and cybersecurity. Further, the less emphasised dimension is posited to open an equal but mutual security vulnerability gap as the more emphasised dimension. Both dimensions must, therefore, equally and jointly be emphasised for optimal security performance in the organisation.

The application of socio-technical systems theory to the information and cybersecurity domain has not received much attention. In this regard, the research adds value to the information and cybersecurity studies where too much emphasis is placed on security software and hardware capabilities.

This paper aims to present an optimization method of the input driving signal of a piezoelectric inkjet printhead to improve droplet consistency and increase jetting frequency.

The optimization target is the transient pressure in the nozzle caused by the input driving signal, which directly generates the droplets. After demonstrating the linearity of the driving input and system pressure, an analytic model as a transfer function was developed, allowing calculation of the pressure vibration in the nozzle for an arbitrary input. Different patterns of input signal were parameterized and applied into the optimizing function, which represents the difference between the ideal and the actual pressure vibration. By determining the function minimum, the optimized parameters of the input signal were estimated.

Optimization results of different input patterns were compared and verified by the numerical model of the printhead, and it was revealed that the optimization method that combined the quenching pulse and an increased falling time interval was more effective than use of a single method.

After the process of optimization, a new type of input signal to the piezoelectric inkjet printhead was showed. By this method, the frequency of the printhead could be increased without losing consistency of droplets.

The purpose of this paper is to deal with a new dispatching and optimization of reactive power sources in power systems.

The methodology is first based on an optimal movement of existing reactive sources as a first phase, then an optimal investment in a second phase and finally a combination of the two previous phases as the third one. The methodology showed also the advantage of a two‐levels procedure, considering an initial minimal compensation before minimizing the active losses. The solution of the global non‐linear problem is performed using the projected and augmented Lagrange method associated with the reduced gradient and the DFP methods.

In waiting for new investment programs which are planned for limited periods, the study presents an alternative of optimizing the reactive power compensation by a movement of the power sources or some of them, satisfying all system constraints and minimizing also the active power losses.

The planners and operators are able to decide what cases are to be considered for reactive power dispatch; the proposed program gives a proposal solution to almost all changes that can occur to the power system (incident, contingency, load variation, development).

In multihop wireless networks, the number of neighbors has an important role in the network performance since links are dynamically formed between a node and its neighbors. This paper aims to investigate this issue.

The paper quantitatively studies the effects of the average number of neighbors in multihop wireless networks on the network connectivity, the number of hops needed to traverse a certain distance, which can be used to determine the hop diameter of a network, and the total energy consumed by packet transmission, which can be used to choose an optimum average number of neighbors that minimizes the energy consumption. This paper also presents an analysis of the energy consumption that can be applied to a wide range of access protocols and show the effect of a variety of factors.

Results show that the minimum average number of neighbors to guarantee the overall network connectivity depends on the size of a network coverage. There is a sharp knee in the network connectivity with decrease of the average number of neighbors, N. If the distance between a source and destination, d, is known, the number of hops needed to reach the destination is usually between d/R∼2d/R, where R is the transmission range. A larger average number of neighbors N leads to a smaller number of hops to traverse a certain distance, which in turn results in a smaller traffic load caused by relaying packets. However, a bigger N also causes more collisions when a contention medium access scheme is used, which leads to more energy consumed by packet transmission. The results show that the optimum N which minimizes the energy is obtained by balancing several factors affecting the energy.

The paper provides a useful study on the effects of the number of neighbors in multihop wireless networks.

The purpose of this paper is to propose a grey clustering evaluation model based on analytic hierarchy process (AHP) and interval grey number (IGN) to solve the clustering evaluation problem with IGNs.

First, the centre-point triangular whitenisation weight function with real numbers is built, and then by using interval mean function, the whitenisation weight function is extended to IGNs. The weights of evaluation indexes are determined by AHP. Finally, this model is used to evaluate the flight safety of a Chinese airline. The results indicate that the model is effective and reasonable.

When IGN meets certain conditions, the centre-point triangular whitenisation weight function based on IGN is not multiple-cross and it is normative. It provides a certain standard and basis for obtaining the effective evaluation indexes and determining the scientific evaluation of the grey class.

The traditional grey clustering model is extended to the field of IGN. It can make full use of all the information of the IGN, so the result of the evaluation is more objective and reasonable, which provides supports for solving practical problems.

This study proposes targeted modernization of the Department of Defense (DoD's) Joint Forces Ammunition Logistics information system by implementing the optimized innovative information technology open architecture design and integrating Radio Frequency Identification Device data technologies and real-time optimization and control mechanisms as the critical technology components of the solution. The innovative information technology, which pursues the focused logistics, will be deployed in 36 months at the estimated cost of $568 million in constant dollars. We estimate that the Systems, Applications, Products (SAP)-based enterprise integration solution that the Army currently pursues will cost another $1.5 billion through the year 2014; however, it is unlikely to deliver the intended technical capabilities.

Fuzzy-based metaheuristic algorithm is used to optimize the fuzzy controllers for the nonlinear level control system subject to uncertainty specially in the main actuator that has lost effectiveness (LOE). To optimize the fuzzy controller, type-1 harmonic search (HS) and interval type-2 (HS) will be used.

The type-1 and type-2 fuzzy-based HS algorithms are designed for optimization of fuzzy controllers for Fault-Tolerant Control (FTC) applications, and this research proposes a fuzzy-based HS metaheuristic method. The performance of a fuzzy logic-based HS algorithm applied to a nonlinear two-tank level control process with a main actuator that has lost effectiveness (LOE) and also the same controller will be tested on DC motor angular position control with and without noise.

The key contribution of this work is the discovery of the best approach for generating an optimal vector of values for the fuzzy controller's membership function optimization. This is done in order to improve the controller's performance, bringing the process value of the two-tank level control process closer to the target process value (set point). It is worth noting that the type-1 fuzzy controller that has been optimized is an interval type-2 fuzzy system, which can handle more uncertainty than a type-1 fuzzy system.

The type-1 and type-2 fuzzy-based HS algorithms are designed for optimization of fuzzy controllers for FTC applications, and this research proposes a fuzzy-based HS metaheuristic method. The performance of a fuzzy logic-based HS algorithm applied to a nonlinear two-tank level control process with a main actuator that has LOE will be tested on DC motor angular position control with noise. Two nonlinear uncertain processes are used to demonstrate the effectiveness of the proposed control scheme.

The purpose of this paper is to describe main ideas and demonstrate results of the research activities carried out by the authors in the field of design concepts of induction mass heating technology based on multiple-criteria optimization. The main goal of the studies is the application of different optimization methods and numerical finite element method (FEM) codes for field analysis to solve the multi-objective optimization problem that is mathematically formulated in terms of the most important optimization criteria, for example, maximum temperature uniformity, maximum energy efficiency and minimum scale formation.

Standard genetic algorithm (GA), non-dominated sorting genetic algorithm (NSGA) and alternance method of parametric optimization based on the optimal control theory are applied as effective tools for the practice-oriented problems for multiple-criteria optimization of induction heaters’ design based on non-linear coupled electromagnetic and temperature field analysis. Different approaches are used for combining FEM codes for interconnected field analysis and optimization algorithms into the automated optimization procedure.

Optimization procedures are tested and investigated for two- and three-criteria optimization problems solution on the examples of induction heating of a graphite disk, induction heating of aluminum and steel billets prior to hot forming.

Solved problems are based on the design of practical industrial applications. The developed optimization procedures are planned to be applied to the wide range of real-life problems of the optimal design and control of different electromagnetic devices and systems.

The paper describes main ideas and results of the research activities carried out by the authors during past years in the field of multiple-criteria optimization of induction heaters’ design based on numerical coupled electromagnetic and temperature field analysis. Implementing the automated procedure that combines a numerical FEM code for coupled field analysis with an optimization algorithm and its subsequent application for designing induction heaters makes the proposed approach specific and original. The paper also demonstrates that different optimization strategies used (standard GA, NSGA-II and the alternance method of optimal control theory) are effective for real-life industrial applications for multiple-criteria optimization of induction heaters design.

In this paper, with the goal of reducing the fuel consumption of UAV, the engine performance optimization is studied and on the basis of aircraft/engine integrated control, the minimum fuel consumption optimization method of engine given thrust is proposed. In the case of keeping the given thrust of the engine unchanged, the main fuel flow of the engine without being connected to the afterburner is optimally controlled so as to minimize the fuel consumption.

In this study, the reference model real-time optimization control method is adopted. The engine reference model uses a nonlinear real-time mathematical model of a certain engine component method. The quasi-Newton method is adopted in the optimization algorithm. According to the optimization variable nozzle area, the turbine drop-pressure ratio corresponding to the optimized nozzle area is calculated, which is superimposed with the difference of the drop-pressure ratio of the conventional control plan and output to the conventional nozzle controller of the engine. The nozzle area is controlled by the conventional nozzle controller.

The engine real-time minimum fuel consumption optimization control method studied in this study can significantly reduce the engine fuel consumption rate under a given thrust. At the work point, this is a low-altitude large Mach work point, which is relatively close to the edge of the flight envelope. Before turning on the optimization controller, the fuel consumption is 0.8124 kg/s. After turning on the optimization controller, you can see that the fuel supply has decreased by about 4%. At this time, the speed of the high-pressure rotor is about 94% and the temperature after the turbine can remain stable all the time.

The optimal control method of minimum fuel consumption for the given thrust of UAV is proposed in this paper and the optimal control is carried out for the nozzle area of the engine. At the same time, a method is proposed to indirectly control the nozzle area by changing the turbine pressure ratio. The relevant UAV and its power plant designers and developers may consider the results of this study to reach a feasible solution to reduce the fuel consumption of UAV.

Fuel consumption optimization can save fuel consumption during aircraft cruising, increase the economy of commercial aircraft and improve the combat radius of military aircraft. With the increasingly wide application of UAVs in military and civilian fields, the demand for energy-saving and emission reduction will promote the UAV industry to improve the awareness of environmental protection and reduce the cost of UAV use and operation.

The purpose of this paper is to define the process of analog circuit optimization on the basis of the control theory application. This approach produces many different strategies of optimization and determines the problem of searching of the best strategy in sense of minimal computer time. The determining of the best strategy of optimization and a searching of possible structure of this strategy with a minimal computer time is a principal aim of this work.

Different kinds of strategies for circuit optimization have been evaluated from the point of view of operations’ number. The generalized methodology for the optimization of analog circuit was formulated by means of the optimum control theory. The main equations for this methodology were elaborated. These equations include the special control functions that are introduced artificially. This approach generalizes the problem and generates an infinite number of different strategies of optimization. A problem of construction of the best algorithm of optimization is defined as a typical problem of the control theory. Numerical results show the possibility of application of this approach for optimization of electronic circuits and demonstrate the efficiency and perspective of the proposed methodology.

Examples show that the better optimization strategies that are appeared in limits of developed approach have a significant time gain with respect to the traditional strategy. The time gain increases when the size and the complexity of the optimized circuit are increasing. An additional acceleration effect was used to improve the properties of presented optimization process.

The obtained results show the perspectives of new approach for circuit optimization. A large set of various strategies of circuit optimization serves as a basis for searching the better strategies with a minimum computer time. The gain in processor time for the best strategy reaches till several thousands in comparison with traditional approach.