计量经济分析 = Econometric analysis

Advances in Experimental Social Psychology continues to be one of the most sought after and most often cited series in this field. Containing contributions of major empirical and theoretical interest, this series represents the best and the brightest in new research, theory, and practice in social psychology. This serial is part of the Social Sciences package on ScienceDirect. Visit info.sciencedirect.com for more information. Advances in Experimental Social Psychology is available online on ScienceDirect - full-text online of volume 32 onward. Elsevier book series on ScienceDirect gives multiple users throughout an institution simultaneous online access to an important complement to primary research. Digital delivery ensures users reliable, 24-hour access to the latest peer-reviewed content. The Elsevier book series are compiled and written by the most highly regarded authors in their fields and are selected from across the globe using Elsevier's extensive researcher network. For more information about the Elsevier Book Series on ScienceDirect Program, please visit store.elsevier.com. * One of the most sought after and most often cited series in this field* Contains contributions of major empirical and theoretical interest* Represents the best and the brightest in new research, theory, and practice in social psychology

/pdf/advances-in-experimental-social-psychology-1uimh1of8o.pdf

Advances in experimental social psychology

Preface. Automatic Train Operation System by Predictive Fuzzy Control (S. Yasunobu, S. Miyamoto). Application of Fuzzy Reasoning to the Water Purification Process (O. Yagashita, O. Itoh, M. Sugeno). The Application of a Fuzzy Controller to the Control of a Multi-Degree-of-Freedom Robot Arm (E.M. Scharf, N.J. Mandic). Optimizing Control of a Diesel Engine (Y. Murayama et al.). Development of Performance Adaptive Fuzzy Controllers with Application to Continuous Casting Plants (G. Bartolini et al.). A Fuzzy Logic Controller for Aircraft Flight Control (L.I. Larkin). Automobile Speed Control System Using a Fuzzy Logic Controller (S. Murakami, M. Maeda). An Experimental Study on Fuzzy Parking Control Using a Model Car (M. Sugeno, K. Murakami). A Fuzzy Controller in Turning Process Automation (Y. Sakai, K. Ohkusa). Design of Fuzzy Control Algorithms with the Aid of Fuzzy Models (W. Pedrycz). Human Operator's Fuzzy Model in Man-Machine System with a Nonlinear Controlled Object (K. Matsushima, H. Sugiyama). The Influence of Some Parameters on the Accuracy of a Fuzzy Model (J.B. Kiszka, M.E. Kochanska, D.S. Sliwinska). A Microprocessor Based Fuzzy Controller for Industrial Purposes (T. Yamazaki, M. Sugeno). The Application of Fuzzy and Artificial Intelligence Methods in the Building of a Blast Furnace Smelting Process Model (H. Zhao, M. Ma). An Annotated Bibliography of Fuzzy Control (R.M. Tong).

Industrial applications of fuzzy control

: A prior effort, State of Knowledge Relative to Intelligence Analysis, was initially motivated by the fact that seemingly little change had resulted from numerous studies of the intelligence community. Starting with Pearl Harbor, the U.S. intelligence community has often faced criticism for failing to predict or warn of future events. Though the criticisms have come from different groups, a certain commonality exists among the proposals for change in the intelligence community. The other noteworthy feature of these proposals is how little their content has changed over time. A thorough analysis of the intelligence literature was accomplished. This analysis provided an answer to the question of whether the existing literature on intelligence analysis contains the requisite knowledge to inform the development and application of both the mechanistic and cognitive activities to support doing intelligence analysis. A dominant finding was how little the practice of intelligence analysis had been informed by the findings in related scientific disciplines. The primary objective of this research effort was to understand the research findings in relevant scientific disciplines and to relate these findings to the practice of intelligence analysis. This research effort was based on the full text of over 5,800 documents consisting of nearly 172,000 pages. Our analysis of the current intelligence literature showed a continuation of previously observed trends. The number of publications dealing with intelligence analysis has decreased since 2007; in 2012 publication was at the level observed in 1996-1997. Also, we observed that the literature places less emphasis on the improvement of the quality of intelligence analysis. During the effort described in this report we conducted research syntheses for the topics of critical thinking, thinking dispositions, epistemological beliefs, practice based training, and various facets of cognition.

https://apps.dtic.mil/sti/pdfs/ADA595401.pdf

Advanced Analysis Cognition: Improving the Cognition of Intelligence Analysis

Psychology and life

This paper introduces a Bayesian network model for the motivation and psychology of the malicious insider. First, an initial model was developed based on results in the research literature, highlighting critical variables for the prediction of degree of interest in a potentially malicious insider. Second, a survey was conducted to measure these predictive variables in a common sample of normal participants. Third, a structural equation model was constructed based on the original model, updated based on a split-half sample of the empirical survey data and validated against the other half of the dataset. Fourth, the Bayesian network was adjusted in light of the results of the empirical analysis. Fifth, the updated model was used to develop an upper bound on the quality of model predictions of its own simulated data. When empirical data regarding psychological predictors were input to the model, predictions of counterproductive behavior approached the upper bound of model predictiveness.

/pdf/a-bayesian-network-model-for-predicting-insider-threats-1mf113rlfn.pdf

A Bayesian Network Model for Predicting Insider Threats

Human behavioral factors are fundamental to understanding, detecting and mitigating insider threats, but to date insufficiently represented in a formal ontology. We report on the design and development of an ontology that emphasizes individual and organizational sociotechnical factors, and incorporates technical indicators from previous work. We compare our ontology with previous research and describe use cases to demonstrate how the ontology may be applied. Our work advances current efforts toward development of a comprehensive knowledge base to support advanced reasoning for insider threat mitigation. Keywords— insider threat; sociotechnical indicators ontology; domain knowledge representation; SME knowledge modeling; human behavioral modeling; domain knowledge sharing

/pdf/developing-an-ontology-for-individual-and-organizational-57t0gets18.pdf

Developing an Ontology for Individual and Organizational Sociotechnical Indicators of Insider Threat Risk.

Insider threats refer to actions by trusted individuals that directly or indirectly bring harm to the organization or expose the organization to external risks. Insider threat detection research and mitigation approaches have over-relied on technical solutions that tend to miss the human behavioral aspects of the problem. This paper focuses on approaches to assemble knowledge about insider threats and to apply this knowledge in support of insider threat assessment. This information can help organizations set up or improve existing insider threat mitigation programs by promoting a greater understanding of insider threat variables of concern; facilitating sharing of the knowledge base of insider threat indicators across organizations; raising awareness of the need to examine behavioral factors in addition to the more traditional focus on technical indicators; and discussing methods and challenges in acquiring and applying expert knowledge of insider threat indicators to facilitate decisions about responding to threat assessment alerts.

Positioning Your Organization to Respond to Insider Threats

: A model for the optimization of simulation-based training systems was developed using a systematic, top-down design procedure. The model consists of five tools that address the following problems: (a) determining which tasks should be trained by part-mission devices, full-mission simulators, or actual equipment; (b) specifying instructional features needed to train a set of tasks efficiently; (c) specifying the levels of fidelity that should be provided along several fidelity dimensions in order to meet task training requirements and satisfy cost limits; (d) determining the family of training devices that can train all required tasks at minimum cost; and (e) determining the optimal allocation of training time to training devices, given constraints on device use. The tools share common data on task requirements, training device features, and costs. A prototype decision support system was developed, and a formative evaluation was conducted. The model was demonstrated on Army rotary-wing aviation tasks, and specifications for application to armor maintenance were deployed. The report describes the model using the IDEFO (Integrated Computer- Aided Manufacturing Definition) system modeling language.

Optimization of Simulation-Based Training Systems: Model Description, Implementation, and Evaluation

We describe research on a comprehensive ontology of sociotechnical and organizational factors for insider threat (SOFIT) and results of an expert knowledge elicitation study. The study examined how alternative insider threat assessment models may reflect associations among constructs beyond the relationships defined in the hierarchical class structure. Results clearly indicate that individual indicators contribute differentially to expert judgments of insider threat risk. Further, models based on ontology class structure more accurately predict expert judgments. There is some (although weak) empirical evidence that other associations among constructs— such as the roles that indicators play in an insider threat exploit—may also contribute to expert judgments of insider threat risk. These findings contribute to ongoing research aimed at development of more effective insider threat decision support tools.

/pdf/modeling-expert-judgments-of-insider-threat-using-ontology-1o184fkc9y.pdf

Paul J. Sticha

Papers

A Bayesian Network Model for Predicting Insider Threats

Developing an Ontology for Individual and Organizational Sociotechnical Indicators of Insider Threat Risk.

Positioning Your Organization to Respond to Insider Threats

Optimization of Simulation-Based Training Systems: Model Description, Implementation, and Evaluation

Modeling Expert Judgments of Insider Threat Using Ontology Structure: Effects of Individual Indicator Threat Value and Class Membership