Decision-making is a complex assignment, especially in situations of conflict. One way to deal with such problematic situations is game theory application. The purpose of this paper is to present the theoretical and practical application of game theory with emphasis on matrix games and linear programming application. The paper presents an overview of a developed software tool that simplifies solving problems for the user with help of simplex algorithm. Practical starting point on game theory efficiency is provided by demonstrating the application on a real problem.
This paper describes the research and experiment efforts of the NATO STO group IST-149-RTG capability concept demonstrator for interoperability within unmanned ground systems and C2 and the NAAG team of experts on UGV. The main purpose of the group was to investigate possible standards for controlling UGVs and tests them in a real world scenario. The efforts have been two folded, where the first effort was two NATO groups having an experiment demonstrating interoperability between the UGVs and OCUs available within the group. The Belgium contribution is done in the EU project ICARUS. Both efforts used the Joint Architecture for Unmanned Systems (JAUS) with the interoperability profile (IOP) to successfully enable interoperability between the systems. The trials showed that it is possible to extend the systems quite easily and achieve compliance with parts of the standard in a relatively short time.
Any program that exhibit furtive demonstrations against the interests of the PC client can be considered as a malware. These baleful programs can play out varieties of different capacities, for example, taking, encoding, or erasing dainty information, changing or commandeering centre processing capacities, and examining clients' computer action without their consent. Today, malware is utilised by both governments and black hat hackers, to take individual, financial, or business data. In this paper, put forward a strategy for arranging malware utilising profound learning procedures. Malware binaries are pictured as greyscale pictures, with the perception that for some malware families, the pictures having a place with a similar family show up fundamentally the same as in surface and design. A standard picture highlights grouping strategy is proposed. The exploratory outcomes give 97.45% arrangement classification on a malware database of 9,339 examples with 25 diverse malware families.
A low power area reduced clock pulse generator and a modified clock sense pulse latch is proposed for conventional shift register. The proposed clock pulse generator basically based on the inverted inverter delay circuit and a pass transistor logic AND gate circuit. This clock pulse generator and modified clock sense pulse latch consumes low power and low area than other conventional clock pulse generator. Here the clock pulse generator consist of five number of back to back cascaded clock pulse circuit. The pulse generated from the proposed clock pulse generator helps to increase the speed, reduces the area and power of conventional shift register. The clock pulse generator and the modified clock sense pulse latch is designed and tested by the Cadence Virtuoso 180 nm technology. The power consumption for 16-bit shift register is 0.705 mW at 500 MHz clock frequency and 0.395 mW at 100 MHz frequency. The proposed shift register saved 12% area and 19.50% power rather than other conventional shift register.
The recent first principles review (FPR) has clearly highlighted further need for improvements in defence capability management. Moreover, improved data management and decision support tools are essential to achieving the efficiencies and realising the opportunities presented. Program viewer is one such tool that leverages and aggregates actual stakeholder data to support force posture planning and capability acquisition prioritisation. Key contributions from this paper include: 1) fusing disparate and unexploited defence enterprise data for analysis; 2) producing a range of tailorable and informative views of cost, schedule and capability from actual defence data; 3) enabling impact analysis on what-if scenarios. Incorporating numerous stakeholder requested features, program viewer offers a new approach to aggregating and analysing defence capabilities, and has been used to support the current and previous force structure reviews (FSRs). This paper's target audience includes ADO and international military systems architects.
The application programming interface (API) as a means of communication to establish a connection with the cloud, which allows storing the vast amounts of heterogeneous data. Data has been steadily growing over the past several years. Software developers can use different data from cloud as convenient ecosystems for developing, deploying, testing and maintaining their software. API provides the archival solution and storing the data in the cloud. This platform also plays an essential role in managing them effectively with improved transfer rates. API is becoming increasingly dynamic and complex day by day. One of the significant challenges faced by us is to develop appropriate individual API and extensible mechanisms for managing and storing the data in the cloud. The objective of this paper is to utilize the storage efficiently based on API capability and analysis of (extreme amounts of) raw heterogeneous data.
The concept of virtualisation along with the physical objects and IP address for internet connectivity may be a big challenge in the present society. It may refer to the numerous physical devices around the world connected with internet for collecting and sharing data. Specifically, the technology associated with internet of things (IoT) may be viewed as the network of physical objects embedded along with connectivity to share and exchange data linked among the physical and cyber space. Sometimes also it may create opportunities for direct integration between the physical world and computer- based systems and leads to economic benefits. It may be thought of connected devices to transfer data among one another in order to optimise the performance automatically and quite a major challenge. It has been proposed to analyse the opportunities and performance associated with virtualised data to simplify and strengthen human activities as well as expertise.
This study focuses on face recognition under uncontrolled conditions as a second biometric factor in order to multi factor authenticate(MFA) in online assessment. Obtained results of this project indicate reasonable accuracy to address the issue of occlusion using AR, MUCT and UMB Datasets, utilizing deep learning and the previous approach based on feature extraction (shallow method). The shallow method accuracy improvement includes HOG by 4%, in comparison to Gabor Sparse Representation based Classification (GSRC) method and by 9% using Gabor. Shallow method can handle occlusion issue in the lack of occlusion dictionaries and sufficient training sample. Modified ResNet as a deep learning method is used to be able to improve accuracy comparing the best member of the SRC family, Structured Sparse Representation based Classification(SSRC) by 3% on average.
Weapon effect modelling has many applications, but in this paper we focus on how advanced computer models can be used to assess the effectiveness of blast shielding structures and materials, for example to improve the safety of weapons production. Safety laws are changing from prescriptive, solution-based regulations to a risk-management-based approach, so being able to estimate the performance of protective measures allows us to produce directly-relevant safety evidence. Such an approach can be used to show that risks are reduced so far as is reasonably practicable (SFAIRP) in order to demonstrate compliance with the WHS Act, 2011. This paper first describes how a variety of computer-based models for the prediction of the development and propagation of blast pressures can be used to provide a detailed assessment of the risks associated with explosions in complex environments, with particular reference to injury assessment - something that is sometimes impractical with simpler techniques. We then show how some of these techniques have been used in two real-world examples to successfully support safety case development. Finally, we extrapolate from the examples, showing how these techniques could be applied to assess weapons safety in different environments, or for risk assessment in defensive or offensive scenarios.
Research on cognitive ability of human brain can be seen now in literature that substantiates research scope and future directions in the field of human brain and its cognitive ability. This paper studies on research articles and work that highlighted various studies; surveys; and comparison on human brain research and its impact on cognitive ability for various artificial intelligence (AI) based applications. The research studies result several important questions on machine learning and impact of cognitive ability.
The rise of piracy in the Gulf of Aden and off the coast of Somalia prompted several nations to direct their navies to conduct counter-piracy operations in that region of the world. A major challenge with such operations is the sheer size of the area to patrol. One way to address this problem is by noting that pirates are more likely to operate under favourable environmental conditions and to focus patrols in areas where such conditions prevail by generating maps of piracy risk based on environmental forecast. This contribution presents a system that invokes a multi-objective optimiser with each new forecast to help the decision makers plan operations over the course of days, weeks or months. Implemented using web-based technologies to mitigate for potential resource limitations at the client site, the resulting decision support system is demonstrated for a counter-piracy operation conducted off the coast of Somalia.
Ideas by Statistical Mechanics (ISM) is a generic program to model evolution and propagation of ideas/patterns throughout populations subjected to endogenous and exogenous interactions. The program is based on the author's work in Statistical Mechanics of Neocortical Interactions (SMNI). This product can be used for decision support for projects ranging from diplomatic, information, military, and economic (DIME) factors of propagation/evolution of ideas, to commercial sales, trading indicators across sectors of financial markets, advertising and political campaigns, etc. It seems appropriate to base an approach for propagation of ideas on the only system so far demonstrated to develop and nurture ideas, i.e., the neocortical brain. The issue here is whether such biological intelligence is a valid application to military intelligence, or is it simply a metaphor?
Time critical vehicle routings, such as with unmanned aerial vehicle (UAV) routing, are considered as integrated location routing problems where the objective is to simultaneously optimise the location and the routing. Although computer systems are good at providing solutions for optimised routing, they may not have the expert knowledge as that of human operators. Human operators play an important role in ensuring the safety and in achieving operational effectiveness in such systems. Problems such as increased human error, lack of situational awareness, and opacity from poorly automated systems remain; particularly in scenarios where human operators must make decisions in time-pressured planning. Hence, we study joint cognitive problem solving for a class of problems related to supervisory control of integrated vehicle routing. Results indicate that the graphical representation of the routing alternatives led to quicker evaluation time by the operator than tabular representation.
In this paper, a static weapon target assignment problem is studied by optimising the conflicting criteria like shooting failure and number of weapons used to destroy the targets. The inherent intractability and conflicting objectives of this problem motivated us to use multi-objective particle swarm optimisation (MOPSO) to uncover the true Pareto front. We first employ the MOPSO to uncover the Pareto front. Secondly, a ranking method called techniques for order preference by similarity to ideal solution (TOPSIS) is used to sort the non-dominated solutions by the preference of decision maker (DM). A numerical experiment on two test cases has been conducted to realise the efficacy of the method. The experimental work is offering large number of solutions in the Pareto front, which may create problem to DM for effective decision. Therefore, by TOPSIS a prioritised set of non-dominated solutions is provided to DM, which fits the preference under different situations.
The Coalition Attack Guidance Experiment (CAGE) aims to assess potential joint fires capabilities and operational impacts, which can be effective to meet challenges from new and evolving threats. An important objective is digital targeting focusing on target development and timely prosecution. The need to coordinate geographically distributed assets and personnel throughout a theatre of combat is constantly in tension with the need to prosecute quickly. This study provides an empirical comparison of digital targeting using baseline and potential future Command and Control (C2) systems as two experimental conditions. While CAGE IIIA demonstrated the benefits of a coalition human-in-the-loop experiment across multiple sites, we learned valuable lessons to improve this scientific endeavour. Technical failures and confounding factors have threatened the validity of this complex experiment, inevitably weakening our understanding of potential capabilities. For future work, we identify the need to consider the human dimension and extant processes for effective system integration.
Traditional missile guidance laws are designed against fighter aircraft, with a much lower velocity (600–800 m/s) than ballistic missiles. To see whether intercepting a theatre ballistic missile inside the atmosphere is difficult in terms of missile guidance, trajectories of two different re-entry vehicles and the terminal phase of their interception, while the interceptor is guided by its own sensors, are simulated using MATLAB/Simulink. The interception is always successful if the inherent delay of the missile guidance system is small (below 0.5 seconds). The re-entry vehicles follow weaving trajectories, but the amplitude of the weave is small and does not pose problems for the interceptor. Neither does the high velocity of the missile (2,600 m/s), provided that the interceptor is near the inverse trajectory at the start of the terminal phase. Consequently, current missile guidance technology seems to be sufficient against aerodynamically stable missiles, but early detection and tracking are essential for success.
Sensor fusion is the notion of combining the data from two or more sensors in order to enhance performance compared with that of individual sensors. The most common method for fusing sensors is through Bayesian methods. However, these cannot easily take into account unknown uncertainty or imprecision. A relatively new method is subjective logic. Although similar to Dempster-Shafer theory, it is unique in that it allows us to collapse the frame of discernment into a binary frame, thereby reducing the complexity. In this paper, we show two novel methods for employing subjective logic: 1) it can be used for target identification (and we show some examples for surveillance in the airborne environment); 2) given some knowledge about the performance of a suite of sensors, we might be able to select the best sensor for a given task. This is achieved through the use of the expected decision formula.
