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In this paper, we develop a new bi-objective model for dynamic weapon-target assignment problem. We consider that the initial weapon assignment plan of defense is disrupted during engagement because of a destroyed air target, breakdown of a weapon system or a new incoming air target. The objective functions are defined as the maximization of probability of no-leaker and the maximization of stability in engagement order of weapon systems. Stability is defined as assigning same air target in sequence in engagement order of a weapon system so that reacquisition and re-tracking of air target are not required by sensors. We propose a new solution procedure to generate updated assignment plans by maximizing efficiency of defense while maximizing stability through swapping weapon engagement orders. The proposed solution procedure generates non-dominated solutions from which defense can quickly choose the most-favored course of action. We solve a set of representative problems with different sizes and present computational results to evaluate effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

With the continuous advancement of science and technology, the social network based on the Internet has gradually penetrated into people's daily lives. The image data shared on social media using platforms such as mobile phones has exploded, and hundreds of millions of dollars are generated every day with picture information. In the past, the traditional ways of expressing textual information that people are familiar with have begun to be gradually replaced by image information that is not subject to regional culture such as language and script. In modern warfare, with the continuous development and equipment of highly sophisticated weapons and equipment, the amount of information that the entire combat system needs to process will also increase. In particular, the air defense system needs to quickly and accurately identify the aircraft targets that are coming. It mainly uses computer to extract the feature information of the acquired image and converts the content in the image into a feature expression that can be processed by the computer. After the appropriate classification algorithm, the image is the target object is classified by category. In this paper, we propose a complex image recognition algorithm based on immune random forest model. The experimental results show that the proposed algorithm has high recognition efficiency and higher robustness. [ABSTRACT FROM AUTHOR]

This paper examines how South Korea might be able to deter the growing threat from North Korea’s nuclear weapons and missile programs. North Korea’s six nuclear weapons experiments with various types of missile test fires using solid fuel and new technology pose a security threat to South Korea and the USA. The credibility of the North’s WMD capability and the military balance of two Koreas are critically analyzed. South Korea’s superior conventional weapons system, supported by U.S. strategic weapons and intelligence systems, could fend off North Korean nuclear weapons and missile attacks. However, it is imperative that the U.S.-ROK alliance continues to develop a stringent nuclear deterrence strategy and deploy a series of countermeasures, including preemptive strikes and a multilayered missile defense system, such as Kill Chain, KAMD, and THAAD, all to guard against a potential nuclear weapon attack from North Korea. [ABSTRACT FROM AUTHOR]

This paper applies a distributed theory of situation awareness based upon the analysis of interactions between agents (both human and non-human) in an Airborne Warning and Control System (Boeing E3D Sentry). The basic tenet of this approach is that agents within a system each hold their own component(s) of situation awareness, which may be very different from, but compatible with, other agent’s view of the situation. However, it is argued that it is not always necessary to have complete sharing of this awareness, as different system agents have different purposes. Situation awareness is regarded as a dynamic and collaborative process that binds agents together on tasks on a moment-by-moment basis. Situation awareness is conceptualised as residing at a system, not an individual level. Data were collected from crew-members in theE3D during a series of simulated air battles. These data pertained to task structure, communications between the crew and the collection and analysis of crew actions at critical decision points. All phases of operations were considered. From these data propositional networks were developed in which key knowledge objects were identified. Analysis of these networks clearly shows how the location and nature of distributed situation awareness changes across agents with regard to the phase of operation/air battle. [ABSTRACT FROM AUTHOR]