Testing and validating a coherence-based model for decision-making and search

Recently, Jekel et al. (2018) proposed the integrated coherence-based decision and search model (iCodes), which predicts decision-making and information search in multi-cue decision tasks. This model assumes that decision-makers strive for coherence-maximization and that this pursuit is represented by an iterative spread of activation through a network that represents all relevant information of the current decision. The goal of my thesis is to evaluate iCodes as a general theory of decision-making and information search, to test its predictions by employing experimental methods, computational modeling and process tracing, and finally to critically discuss its merits in the field of judgment and decision-making research (JDM) as a whole. A unique contribution of iCodes compared to other theories in JDM is its prediction that people show a tendency to search for information on the option that is currently supported by the available evidence, also referred to as the attraction search effect. In the first manuscript, we could show that the attraction search effect is a robust finding and generalizes to a variety of different tasks. This finding supported a broad range of applicability for iCodes’ predictions for information search. In the second manuscript, we could show that iCodes can account for the effect of a theoretically motivated moderator of the attraction search effect, namely that rating the attractiveness of options before search increases the tendency to search for information on the attractive option. We further validated the assumed, underlying information-search process by showing that a model-inherent parameter can account for the effect of attractiveness ratings. The third manuscript showed that iCodes is not only able to predict behavioral information search but is also able to predict gaze behavior in decision-making. It further highlighted the role of coherence for attention allocation in decision tasks. In sum, my thesis contributes to the theoretical advancement of research in JDM and emphasizes the importance of formalized theories

CSP with Synthesisable SystemC TM and OSSS

Abstract C. Hoare's Communicating Sequential Processes (CSP) notatio

Paint: PA instruction set interpreter

Journal ArticleThis document describes Paint, an instruction set simulator based on Mint[3]. Paint interprets the PA-RISC instruction set, and has been extended to support the Avalanche Scalable Computing Project[2]. These extensions include a new process model that allows multiple programs to be run on each processor and the ability to model both kernel and user code on each processor. In addition, a new address space model more accurately detects when a program is accessing an illegal virtual address, allows a program's virtual address space to grow dynamically, and does lazy allocation of physical pages as programs need them. Note that this document is intended to be an addendum to the original Mint technical report, which the reader should consult for an overview of the Mint simulation environment and terminology

Jack Voltaic 3.0 Cyber Research Report

The Jack Voltaic (JV) Cyber Research project is an innovative, bottom-up approach to critical infrastructure resilience that informs our understanding of existing cybersecurity capabilities and identifies gaps. JV 3.0 contributed to a repeatable framework cities and municipalities nationwide can use to prepare. This report on JV 3.0 provides findings and recommendations for the military, federal agencies, and policy makers

Improving Maritime Prepositioning Force (MPF) offloads using modeling and simulation

The Marine Corps' Maritime Prepositioning Force (MPF) marries fly-in troops to their gear in an expeditionary environment. The arrival and assembly operation underneath this larger umbrella of MPF Operations proves itself a somewhat chaotic, definitively complex and dynamic logistics operation. From the moment the offload of the ship or ships begins when equipment and rolling stock exit the ships, until it ends as using units sign for their intended equipment, all personnel involved in this process--drivers, assistant drivers, heavy equipment handlers, crane operators, equipment managers--and all equipment involved present a flurry of activity that must be effectively managed, tracked, and optimized. Modeling, Virtual Environments, and Simulation, or MOVES, tools, aid in providing such capability. The creation of a Discrete Event Simulation (DES) using the open-source tool Viskit enables MPF planning, training, and analysis in its ability to portray the effects that size, amount of personnel support, and time have on the operation. Scenario Authoring and Visualization for Advanced Graphical Environments (Savage) comprises an archive of extensible three dimensional (3D) models that, when tied to the DES in an Extensible 3D (X3D) Graphics environment, enable the animation of the simulation, and when connected to real-world tracking data of the offload, allow for real-time visual tracking of this logistics process, creating a Common Operating Picture (COP) for the Arrival and Assembly Operations Group (AAOG).http://archive.org/details/improvingmaritim109453731US Marina Corps (USMC) author.Approved for public release; distribution is unlimited

C Language Compiler Back-End for PicoBlaze-6

Tato práce řeší konstrukci zadní části kompilátoru jazyka C pro soft-core procesor PicoBlaze-6 od firmy Xilinx. K řešení tohoto problému bylo zvoleno užití projektu Small Device C Compiler coby přední části překladače. Vytvořené řešení poskytuje podporu volání ukazatelů na funkce a užití struktur. Hlavním přínosem této práce je přenesení pokročilých konstrukcí jazyka C na procesor PicoBlaze.The goal of this thesis is to construct a C compiler back-end for the soft-core processor PicoBlaze-6 by Xilinx, Inc. The construction itself was done by use of the Small Device C Compiler as the front-end. The resulting application offers the ability to compile function pointer calling and structure usage. The main benefit of this thesis is bringing some of advanced C language constructs to the PicoBlaze processor.

SILS MRAT: A Multi-Agent Decision-Support System for Shipboard Integration of Logistics Systems

This report describes work performed by CDM Technologies Inc. on subcontract to ManTech Advanced Systems International, Inc. (Fairmont, West Virginia), and under sponsorship of the Office of Naval Research (ONR). The principal aim of the SILS (Shipboard Integration of Logistics Systems) project is to provide a decision-support capability for Navy ships that integrates shipboard logistical and tactical systems within a near real-time, automated, computer-based shipboard readiness and situation awareness facility. Specifically, SILS is intended to provide the captain of a ship and his staff with an accurate evaluation of the current condition of the ship, based on the ability of all of its equipment, services and personnel to perform their intended functions. The SILS software system consists of two main subsystems, namely: the SILS IE (Interface Engine) subsystem for information interchange with heterogeneous external applications, developed by ManTech Advanced Systems International; and, the SILS MRAT (Mission Readiness Analysis Toolkit) subsystem for intelligent decision-support with collaborative software agents, developed by CDM Technologies. This report is focused specifically on the technical aspects of the SILS MRAT subsystem. The automated reasoning capabilities of SILS MRAT are supported by a knowledge management architecture that is based on information-centric principles. Such an architecture utilizes a virtual model of the real world problem situation, consisting of data objects with characteristics and a rich set of relationships. Commonly referred to as an ontology, this internal information model provides a common vocabulary and context for software agents with reasoning capabilities. The concurrent need for incremental capability increases implies a steadily increasing data load from diverse operational (dynamic) and historical (static) data sources, ranging from free text messages and Web content to highly structured data contained in consolidated operational data stores, Data Warehouses, and Data Marts. In order to provide useful high-level capabilities the architecture is required to support the transformation of these data flows into information and knowledge relevant to the concerns and operational context of individual shipboard users. Accordingly, the system must be capable of not only storing data but also the relationships and higher level concepts that place the data into context. For this reason, to manage an increasing number of relationships and concepts over time, the SILS MRAT subsystem was designed to employ a formalized ontological framework. There were four additional considerations in the selection of the overall SILS architecture. First, utility to support a useful level of automated information management (i.e., the ability to collaboratively analyze data, monitor dynamic operational context, formulate warnings and alerts, and generate recommendations). Second, flexibility to accommodate contributions from multiple team members that may employ differing technologies and implementation paradigms. Third, scalability to allow a progressive increase in the breadth and diversity of the data sources, the volume of data processed, the number of validated components, and the intelligence of the tools (i.e., agents). Fourth, adaptability to facilitate the tailoring of the information management capabilities to different data sources and existing data environments. The current SILS architecture addresses these desirable characteristics by partitioning the system into a lower-level data collection and integration layer, a higher-level information management layer (SILS MRAT), and a translation facility that is capable of mapping the data schema of the lower layer to the information representation (i.e., ontology) of the upper layer (SILS IE). The higher-level information management layer provides a collaborative, distributed communication facility that supports the development of semi-autonomous modules of capability referred to as agents. The agents employ the formalized ontology supported by the communication facility to collaborate with each other and the human users in a meaningful manner

Development of New Computational Tools for Analyzing Hi-C Data and Predicting Three-Dimensional Genome Organization

Background: The development of Hi-C (and related methods) has allowed for unprecedented sequence-level investigations into the structure-function relationship of the genome. There has been extensive effort in developing new tools to analyze this data in order to better understand the relationship between 3D genomic structure and function. While useful, the existing tools are far from maturity and (in some cases) lack the generalizability that would be required for application in a diverse set of organisms. This is problematic since the research community has proposed many cross-species "hallmarks" of 3D genome organization without confirming their existence in a variety of organisms. Research Objective: Develop new, generalizable computational tools for Hi-C analysis and 3D genome prediction. Results: Three new computational tools were developed for Hi-C analysis or 3D genome prediction: GrapHi-C (visualization), GeneRHi-C (3D prediction) and StoHi-C (3D prediction). Each tool has the potential to be used for 3D genome analysis in both model and non-model organisms since the underlying algorithms do not rely on any organism-specific constraints. A brief description of each tool follows. GrapHi-C is a graph-based visualization of Hi-C data. Unlike existing visualization methods, GrapHi-C allows for a more intuitive structural visualization of the underlying data. GeneRHi-C and StoHi-C are tools that can be used to predict 3D genome organizations from Hi-C data (the 3D-genome reconstruction problem). GeneRHi-C uses a combination of mixed integer programming and network layout algorithms to generate 3D coordinates from a ploidy-dependent subset of the Hi-C data. Alternatively, StoHi-C uses t-stochastic neighbour embedding with the complete set of Hi-C data to generate 3D coordinates of the genome. Each tool was applied to multiple, independent existing Hi-C datasets from fission yeast to demonstrate their utility. This is the first time 3D genome prediction has been successfully applied to these datasets. Overall, the tools developed here more clearly recapitulated documented features of fission yeast genomic organization when compared to existing techniques. Future work will focus on extending and applying these tools to analyze Hi-C datasets from other organisms. Additional Information: This thesis contains a collection of papers pertaining to the development of new tools for analyzing Hi-C data and predicting 3D genome organization. Each paper's publication status (as of January 2020) has been provided at the beginning of the corresponding chapter. For published papers, reprint permission was obtained and is available in the appendix

The COMPLEX reference framework for HW/SW co-design and power management supporting platform-based design-space exploration

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