In a distributed model of intelligence, peer components need to communicate with one another. I present a system which enables two agents connected by a thick twisted bundle of wires to bootstrap a simple communication system from observations of a shared environment. The agents learn a large vocabulary of symbols, as well as inflections on those symbols which allow thematic role-frames to be transmitted. Language acquisition time is rapid and linear in the number of symbols and inflections. The final communication system is robust and performance degrades gradually in the face of problems.

When we looked at different issues in terrorism such as definitions, descriptions and motivations, groups and supporters, tactics, strategies, and victims of terrorists and terrorist activities, we see that terrorism is an issue that can occur at any time, and in any place, and it seems that the terrorism threat will still exist in the future. It is almost impossible to stop all terrorist activities all over the world, but it is possible to formulate an anti-terrorism policy that can keep terrorist activities at a minimum level and prevent planned terror activities by a well developed intelligence network. It seems that to establish a good intelligence collection system an approach in which HUMINT and TECHINT are interdependent with each other is necessary. By using a combination of human and technical intelligence collection methods, intelligence agencies can become more effective and efficient against terrorism.

This study investigates the viability of using Human Intelligence Tasks (HIT) in password categorization. To achieve this, this study constructs and performs a HIT experiment on the online crowdsourcing platform Amazon Mechanical Turks. The study performs the experiment on the site Amazon Mechanical Turks, and gathers data in the form of answers from the workers. A a mixed quantitative and qualitative analysis of the data is performed to investigate on the workers ability to derive the categories of passwords from different categories and difficulties. The study results indicate that HIT workers seem to be unable to reliable categorize more complex passwords correctly, compared to more common and simple passwords. With this result, the study concludes that the quality and reliability of HIT password categorization is lower than would be required to make HIT a valid method for password categorization. The study ends with a discussion on how and why this may be the case and briefly discuss on how the HIT task might be changed in future development to increase its viability.

In today's fast-paced, instant-gratification-oriented society, everyone is looking for quick fixes. We want it all and we want it now! This mindset is in conflict with the overall process of education and learning which requires time, reflection, and practice. More and more students are entering colleges and universities with weak academic preparation and deficient life skills. This often leads them to engage in unethical practices in order to compete, get ahead and survive academically. Declining academic integrity is a significant issue on almost all college campuses. The purpose of this study was to gain deeper insight into student nurses' perceptions of the concept of instant gratification in general and in nursing education in particular. The implications of the Trinity Paradigm of Intelligence in developing a culture of integrity were also explored. The emerged data supports the notion of "academic disintegrity" as a social problem with a long history of development.

The thesis aims to understand the motivation of sources in Human Intelligence gathering. Todo this, three autobiographies of three former sources are analyzed where they write about theirlives as sources. To understand the sources' motivation two theories are used, Abraham H.Maslow's hierarchy of needs and Harney's theory. Maslow's theory is based on Developmentalpsychology and Harneys on categorizations of types of police sources Harney encountered as afederal agent. Through the analysis, themes in motivation such as community and securityreappear. Motivation turns out to be about being appreciated for the work you do, belonging toa group, contributing to society, and financial stability. On the other hand, understanding thedifference in what the motive versus motivation can be for the sources seems to require a closerand deeper understanding of the sources' personalities.

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Matrices reasoning tests, which contain missing pieces in matrices that participants attempt to figure out, are one of the most popular types of tests to measure general intelligence. This thesis introduces several methods to develop matrices items, and presents them in different test forms to assess general intelligence. Part 1 introduces the development of a matrices test with reference to Carpenter’s five rules of Raven’s Progressive Matrices. The test items developed were administered together with the Standard Ravens’ Progressive Matrices (SPM). Results based on confirmatory factor analysis and inter-item correlation demonstrate good construct validity and reliability. Item characteristics are explored with Item-Response Theory (IRT) analyses. Part 2 introduces the development of a large item bank with multiple alternatives for each SPM item, with reference to the item components of the original SPM. Results showed satisfactory test validity and reliability when using the alternative items in a test. Findings also support the hypothesis that the combination of item components accounts for item difficulty. The work lays the foundation for the future development of computer adaptive versions of Raven’s Progressive Matrices. Part 3 introduces the development of an automatic matrix item generator and illustrates the results of the analyses of the items generated using the distribution-of-three rule. Psychometric properties of the items generated are explored to support the validity of the generator. Figural complexity, features, and the frequency at which certain rules were used are discussed to account for the difficulty of the items. Results of further analyses to explore the underlying factors of the difficulty of the generated items are presented and discussed. Results showed that the suggested factors explain a substantial amount of the variance of item difficulty, but are insufficient to predict the item difficulty. Adaptive on-the-fly item generation is yet to be possible for the test at this stage. Overall, the methods for creating matrices reasoning tests introduced in the dissertation provide a useful reference for research on abstract reasoning and fluid intelligence measurements. Implications for other areas of psychometric research are also discussed.

隨著中小企業（Small and Medium Enterprises，SMEs）在台灣這個國家數量的提升，建立一個能夠運作至水準的團隊以確保公司維持具競爭力的型態已變得重要。為了維持競爭力，這些中小企業會找尋新穎、具創意的方法，為要能夠從同業當中脫穎而出。創新源自於兩處，藉由打造一項服務或是產品。在本篇研究當中，服務和產品皆被用來作為調查研究。要有具創意的想法，對於一個團隊就有其需要將想法付諸行動。然而，團隊的打造是一個長久的過程。團隊成長的過程會有第一次開會、相互瞭解、然後能夠作為一個單位去運作。在這個過程中，會有衝突和困惑的障礙。因此，本篇研究提出一項新的競爭情報─人力情報（Human Intelligence，HI）─以協助成長中的公司快速地建立一個團隊。 HI的目的是去建立一個讓公司可以更為快速建立團隊的程序。HI的架構遵循計畫與方向、資料蒐集、分析與傳播之競爭情報架構的原則。藉由三家有創新服務或產品的台灣中小企業之研究，本篇研究使用質性研究蒐集資料並且能夠為著分析從訪談、網路研究、和所在地觀察當中挖掘資料。在團隊效能上採用基礎實際理論，HI能夠告知一家公司建立中的團隊是處在哪一個階段。一旦建立中的團隊所處階段被確認了，人力資源實務就能針對公司給予建議，進而完成競爭情報架構的過程。 人力情報架構的結果能夠給目前的團隊情況給予見解並且提供回饋或是建議，這使得成長中的公司能夠有效地打造一個團隊。 / With small and medium enterprises (SMEs) raising all over the country of Taiwan, thus forming a team that can perform up to standard to ensure the company stay in competitive form has become crucial. To stay competitive these SMEs find new innovative ways to be able to differentiate themselves from peers. Innovation can come from two sources, either by creating a service or product. In this paper, both service and product are used as sample studies. To have an innovative idea, there is a need for a team to carry the idea to action. However, team building is a long process. This process of team performance went through meeting for the first time, understanding each other and then being able to perform as one unit. During this process, there are bounds to be conflicts and confusions. Thus this paper brings about a new competitive intelligence, “Human Intelligence” (HI), to help growing companies to build a team rapidly. HI’s aim is to create a process that allows companies to build teams faster. HI’s framework follows the principle of competitive intelligence process framework of planning and direction, collection of data, analysis and dissemination. Through the study of 3 Taiwanese SMEs that have innovation of either product or service. This paper uses qualitative study to collect data and is able to mine data from interview, internet research and on-site observation for analysis. Using basic practical theories on team performance, HI is able to determine which stage of team forming a company is in. Once the stage of team forming is determined, human resource practices give recommendation for the company, thus completing the process of competitive intelligence framework. The result of the Human Intelligence framework was able to provide insight to current team situation and offer a feedback or recommendation. This allows growing companies to form a team efficiently.

The interest in crisis management is increasing for some decades now, since researchers and organizations have realized that crises can endanger them severely and that all kinds of organization are potentially under the constant threat of crises. Artificial intelligence (AI) is also in the heart of the attention as some tasks, traditionally occupied by humans, are already replaced by AI agents, and the fast development achieves more and more promising results. As the core of AI, decision-making has been identified, which itself can also completely change the outcome of a crisis. Thus, the idea to explore the junction of these two fields in the light of decision-making processes appeared to be highly inter-esting. Therefore, the purpose of this paper is: first, to find out what is really important in deci-sion-making processes in crisis management, second, to figure out abilities and limita-tions for human and artificial intelligences, and lastly, how artificial intelligence can af-fect important characteristics of decision-making processes in a foreseeable period of time. Putting all together led to the research question: How artificial intelligence can affect decision-making processes in crisis management? To guide these efforts, a qualitative method with an interpretivist approach has been cho-sen. Therefore, crisis experts (managers and consultants) and AI experts (researchers and developers) were interviewed. Also, notes were taken from a conference about artificial intelligence. As a result, it has been found out that speed and comprehensiveness are two crucial fac-tors when making decisions in crisis situations. Additionally, empirical findings figured out that this approach needs to be extended by the two decision parameters short- and long-term effect as it is not just about decision-making itself, but also about the feasibility and future consequences of decisions made. A model for ‘successful decision-making in crisis situations’ could be developed and the roles of intuition and rationality as well as abilities and limitations were clarified for both, human and artificial intelligence. Based on this understanding, artificial and human intelligence could have been placed within our model, showing the complement nature of them. Finally, an exploratory an-swer to the research question could be derived, presented as short-, medium-, and long-term perspectives. Even though crisis management can be expected to be one of the last organizational fields invested by AI, the results show that there are great benefits of ap-plying AI in crisis management, leading in a high potential that AI will change the picture dramatically.

With the ever expanding usage of social media websites such as Twitter, it is possible to use statistical inquires to form a geographic location of a person using solely the content of their tweets. According to a study done in 2010, Zhiyuan Cheng, was able to detect a location of a Twitter user within 100 miles of their actual location 51% of the time. While this may seem like an already significant find, this study was done while Twitter was still finding its ground to stand on. In 2010, Twitter had 75 million unique users registered, as of March 2013, Twitter has around 500 million unique users. In this thesis, my own dataset was collected and using Excel macros, a comparison of my results to that of Cheng’s will see if the results have changed over the three years since his study. If found to be that Cheng’s 51% can be shown more efficiently using a simpler methodology, this could have a significant impact on Homeland Security and cyber security measures.