Current military doctrine is primarily hierarchical in nature with respect to power and authority. The "Functional Concept of Battlespace Awareness" (FCBA) is a military sensor methodology that employs a hierarchical command structure to test emerging technologies. Asymmetric warfare, however, demands a faster and more adaptive warfighting mentality that distributes power and responsibility across more of our forces; particularly those that are at the frontlines of the battlefield. "Power to the Edge" is a warfighting methodology that emphasizes a departure from traditional military hierarchies and a transition into a configuration that empowers "Edge" actors with information and authority. This thesis will prove that "Power to the Edge" doctrine is a more effective way to fight the enemies we will likely face in the Information Age. By analyzing and interpreting data collected at the Extended Awareness II and Extended Awareness IIB experiments, this thesis will show that transition in our current command and control methodology will be necessary to keep up with a changing enemy.

The performance of IEEE 802.11g wireless local area network (WLAN) standard receivers when the signal is transmitted over a frequency-selective, slowly fading Nakagami channel in a pulse-noise interference environment when errors-and-erasures Viterbi decoding is used is examined. The different combinations of modulation (both binary and non-binary) and convolutional code rate specified by the WLAN standard are examined. The performance obtained with errors-and-erasures decoding (EED) is compared with the performance obtained with errors-only hard decision Viterbi decoding (HHD) as well as that obtained with soft decision Viterbi decoding (SDD) for binary modulation, while for non-binary modulation, EED performance is compared with HDD performance. It was found that EED can significantly improve performance under some conditions when pulse-noise interference is present.

The desire for more intelligence in the battlefield has given rise to the idea of routing video images over wireless sensor networks. This would apprise combat decision makers with actual images of battlefield developments and allow them to make sound decisions. To achieve this objective, the characteristics of video traffic must be studied and understood. This thesis focuses on evaluating the possibility of routing video images over a wireless sensor network. Video traffic is modeled and simulations are performed via the use of the Sun Small Programmable Object Technology (Sun SPOT) Java development kits configured in three different network topologies: the star topology, binary tree topology and chain topology. It is known that video traffic is self similar and can be obtained by aggregating a large number of On-Off message sources. Hence, an On-Off model using Pareto distribution function is used to model video traffic over the network. In this thesis four self-similar shaping parameters, i.e., alpha(On) = 1.2, 1.4, 1.7 and 1.9 are used in the simulations. The performance of each topology is evaluated based on parameters like mean throughput, mean interarrival time, mean packet drop, and mean delay. / Singapore Armed Forces author.

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The purpose of this thesis will be to examine the decision-making process in crisis situations, defined as those presenting a high threat and short decisional time. Crisis situations in the area of foreign policy have become more acute and dangerous since the end of World War II and the rise of nuclear weapon delivery capabilities.

Decision makers require the right information at the right time, in the right place and in the right format so that they can make good decisions. Although business intelligence (BI) has the potential to improve decision making, there is little empirical evidence of how well this has been achieved. The purpose of this dissertation is to examine the quality of decisions made using BI. The research question it addresses is what are the key antecedents of decision quality for users of business intelligence systems? The theoretical support for the model is developed based on the literature review that draws on decision support systems (DSS), group decision support systems (GDSS), and BI. Grounded on this literature review, the antecedents of decision quality are operationalized in this dissertation through independent variables such as the problem space complexity, the level of BI usage, the BI user experience, and information quality. The dependent variable is operationalized as decision quality and it captures the self-satisfaction with a decision made by users in a BI environment. The research model was tested using a survey of BI users whose names were provided by a marketing company. This research suggests that BI user experience is a more complex construct than has been initially thought.

Allen J. Lichtman and Daniel M. Rohrer write that "Unfortunately, formal debate theory tends to lag behind the actual practice of competitive debate" (70). This statement accurately describes the current controversy surrounding the counter-system counterplans and how they may affect traditional debate theory. These counterplans are increasingly employed by negative teams in intercollegiate debate, but so far, there is no contemporary attempt to explain how they fit into current debate theory. This study will analyze this new genre of counterplans by answering the following questions.

Social networking sites usage has shown a meteoric rise over the past decade. Social networking sites survive and thrive based on the information that users disclose. The willingness of users to disclose their information lies at the core and is the driving force of the economies of these sites. This study proposed and tested an integrated theoretical framework for self-disclosure on social networking sites. Drawing from three different theoretical perspectives viz. self-congruency theory, privacy calculus theory, and extension of unified theory of acceptance and use of technology (UTAUT2), a research model was formulated. The model was tested using survey data of 380 university students. Facebook was used as a prototype for this research. This study examined the effects of the variables emanating from the three different theoretical perspectives mentioned above on the attitudinal, intentional, and behavioral aspects of self-disclosure on social networking sites. Further, the effects of self-congruency and perceived control on trust in social networking sites and its members were evaluated. The contributions to theory and practical implications of the findings are discussed.

The extraordinary conditions of a disaster, require the mobilisation of all available resources, inducing the rush of humanitarian partners into the affected area. This phenomenon called the proliferation of actors, causes serious problems during the disaster response phase including the oversupply, duplicated efforts, lack of planning. The aim of this research is to provide a solution to reduce the partner proliferation problem. To that end the main research question is put forward as “How to reduce the proliferation of partners in a disaster response”? Panel analysis of the historic record of 4,252 natural onset disasters between 1980 to 2013 via regression analysis, MA and AHP gives rise to the formation of a predictive decision-making platform called PREDIS. It is capable of predicting the human impact of the disaster (fatality, injured, homeless) of up to 3% of errors and enables the decision makers to estimate the required needs for each disaster and prioritises them based on the disaster type and socio-economics of the affected country. It further renders it possible to rank and optimise the desired partners based on the decision maker’s preferences. Verification of the PREDIS through a simulation game design using a sample group of decision makers, show that this technique enables the user to decide within one hour after the disaster strike using the widely available data at the time of the disaster. It also enables non-experts to decide almost identically to experts in terms of the similarity of the choices and the speed of the decision. The lack of an extensive database for the potential humanitarian partners from which to choose, is the limitation of this research in addition to the lack of standardised set of minimum requirements for the suitable partners. The model is also as strong as its data feed which is inconsistent in various humanitarian sources.

We study a dynamic channel selection framework for cognitive radio networks (CRNs) which support both delay sensitive and best effort services. Unlike existing works in the literature, we consider the effect of heterogeneous radio frequency characteristics and heterogeneous primary user activities on channel selection in multi-channel CRNs. Optimal spectrum decision policies are obtained to achieve minimum delay using dynamic programming techniques, such as Markov decision process (MDP) and reinforcement learning, under different assumptions. To address the computational complexity issue in the MDP solutions, a myopic scheme is proposed based on the estimated packet sojourn time. / October 2016