Actionable pattern analysis in computing and business intelligence systems

With advances in science and technology, computing and business intelligence (BI) systems are steadily becoming more complex with an increasing variety of heterogeneous software and hardware components. They are thus becoming progressively more difficult to monitor, manage and maintain. Traditional approaches to system management have largely relied on domain experts through a knowledge acquisition process that translates domain knowledge into operating rules and policies. It is widely acknowledged as a cumbersome, labor intensive, and error prone process, besides being difficult to keep up with the rapidly changing environments. In addition, many traditional business systems deliver primarily pre-defined historic metrics for a long-term strategic or mid-term tactical analysis, and lack the necessary flexibility to support evolving metrics or data collection for real-time operational analysis. There is thus a pressing need for automatic and efficient approaches to monitor and manage complex computing and BI systems. To realize the goal of autonomic management and enable self-management capabilities, we propose to mine system historical log data generated by computing and BI systems, and automatically extract actionable patterns from this data. This dissertation focuses on the development of different data mining techniques to extract actionable patterns from various types of log data in computing and BI systems. Four key problems—Log data categorization and event summarization, Leading indicator identification , Pattern prioritization by exploring the link structures , and Tensor model for three-way log data are studied. Case studies and comprehensive experiments on real application scenarios and datasets are conducted to show the effectiveness of our proposed approaches.

Dynamic modeling and analysis of single-stage boost inverters under normal and abnormal conditions

Inverters play key roles in connecting sustainable energy (SE) sources to the local loads and the ac grid. Although there has been a rapid expansion in the use of renewable sources in recent years, fundamental research, on the design of inverters that are specialized for use in these systems, is still needed. Recent advances in power electronics have led to proposing new topologies and switching patterns for single-stage power conversion, which are appropriate for SE sources and energy storage devices. The current source inverter (CSI) topology, along with a newly proposed switching pattern, is capable of converting the low dc voltage to the line ac in only one stage. Simple implementation and high reliability, together with the potential advantages of higher efficiency and lower cost, turns the so-called, single-stage boost inverter (SSBI), into a viable competitor to the existing SE-based power conversion technologies.^ The dynamic model is one of the most essential requirements for performance analysis and control design of any engineering system. Thus, in order to have satisfactory operation, it is necessary to derive a dynamic model for the SSBI system. However, because of the switching behavior and nonlinear elements involved, analysis of the SSBI is a complicated task.^ This research applies the state-space averaging technique to the SSBI to develop the state-space-averaged model of the SSBI under stand-alone and grid-connected modes of operation. Then, a small-signal model is derived by means of the perturbation and linearization method. An experimental hardware set-up, including a laboratory-scaled prototype SSBI, is built and the validity of the obtained models is verified through simulation and experiments. Finally, an eigenvalue sensitivity analysis is performed to investigate the stability and dynamic behavior of the SSBI system over a typical range of operation. ^

Integrated Ecological Modeling and Decision Analysis Within the Everglades Landscape

Planning for complex ecosystem restoration projects involves integrating ecological modeling with analysis of performance trade-offs among restoration alternatives. The authors used the Everglades Landscape Model and Multi-Criteria Decision Analysis to explore the effect of simulated ecosystem performance, risk preferences, and criteria weights on the ranking of three alternatives to restoring overland sheet flow in the Everglades. The ecological model outputs included both hydrologic and water quality criteria. Results were scored in the decision analysis framework, highlighting the trade-offs between hydrologic restoration and water quality constraints. Given equal weighting of performance measures, the alternative with more homogenous sheet flow was preferred over other alternatives, despite evidence of some localized eutrophication risk.

Formal modeling and analysis techniques for high level Petri nets

Petri Nets are a formal, graphical and executable modeling technique for the specification and analysis of concurrent and distributed systems and have been widely applied in computer science and many other engineering disciplines. Low level Petri nets are simple and useful for modeling control flows but not powerful enough to define data and system functionality. High level Petri nets (HLPNs) have been developed to support data and functionality definitions, such as using complex structured data as tokens and algebraic expressions as transition formulas. Compared to low level Petri nets, HLPNs result in compact system models that are easier to be understood. Therefore, HLPNs are more useful in modeling complex systems. ^ There are two issues in using HLPNs—modeling and analysis. Modeling concerns the abstracting and representing the systems under consideration using HLPNs, and analysis deals with effective ways study the behaviors and properties of the resulting HLPN models. In this dissertation, several modeling and analysis techniques for HLPNs are studied, which are integrated into a framework that is supported by a tool. ^ For modeling, this framework integrates two formal languages: a type of HLPNs called Predicate Transition Net (PrT Net) is used to model a system's behavior and a first-order linear time temporal logic (FOLTL) to specify the system's properties. The main contribution of this dissertation with regard to modeling is to develop a software tool to support the formal modeling capabilities in this framework. ^ For analysis, this framework combines three complementary techniques, simulation, explicit state model checking and bounded model checking (BMC). Simulation is a straightforward and speedy method, but only covers some execution paths in a HLPN model. Explicit state model checking covers all the execution paths but suffers from the state explosion problem. BMC is a tradeoff as it provides a certain level of coverage while more efficient than explicit state model checking. The main contribution of this dissertation with regard to analysis is adapting BMC to analyze HLPN models and integrating the three complementary analysis techniques in a software tool to support the formal analysis capabilities in this framework. ^ The SAMTools developed for this framework in this dissertation integrates three tools: PIPE+ for HLPNs behavioral modeling and simulation, SAMAT for hierarchical structural modeling and property specification, and PIPE+Verifier for behavioral verification.^

Formal Modeling and Analysis Techniques for High Level Petri Nets

Petri Nets are a formal, graphical and executable modeling technique for the specification and analysis of concurrent and distributed systems and have been widely applied in computer science and many other engineering disciplines. Low level Petri nets are simple and useful for modeling control flows but not powerful enough to define data and system functionality. High level Petri nets (HLPNs) have been developed to support data and functionality definitions, such as using complex structured data as tokens and algebraic expressions as transition formulas. Compared to low level Petri nets, HLPNs result in compact system models that are easier to be understood. Therefore, HLPNs are more useful in modeling complex systems. There are two issues in using HLPNs - modeling and analysis. Modeling concerns the abstracting and representing the systems under consideration using HLPNs, and analysis deals with effective ways study the behaviors and properties of the resulting HLPN models. In this dissertation, several modeling and analysis techniques for HLPNs are studied, which are integrated into a framework that is supported by a tool. For modeling, this framework integrates two formal languages: a type of HLPNs called Predicate Transition Net (PrT Net) is used to model a system's behavior and a first-order linear time temporal logic (FOLTL) to specify the system's properties. The main contribution of this dissertation with regard to modeling is to develop a software tool to support the formal modeling capabilities in this framework. For analysis, this framework combines three complementary techniques, simulation, explicit state model checking and bounded model checking (BMC). Simulation is a straightforward and speedy method, but only covers some execution paths in a HLPN model. Explicit state model checking covers all the execution paths but suffers from the state explosion problem. BMC is a tradeoff as it provides a certain level of coverage while more efficient than explicit state model checking. The main contribution of this dissertation with regard to analysis is adapting BMC to analyze HLPN models and integrating the three complementary analysis techniques in a software tool to support the formal analysis capabilities in this framework. The SAMTools developed for this framework in this dissertation integrates three tools: PIPE+ for HLPNs behavioral modeling and simulation, SAMAT for hierarchical structural modeling and property specification, and PIPE+Verifier for behavioral verification.

The effect of the use of computer assisted instruction (CAI) on attitudes and computational scores of developmental mathematics students at two inner city schools with predominantly Black enrollment

This study examined the effects of computer assisted instruction (CAI) 1 hour per week for 18 weeks on changes in computational scores and attitudes of developmental mathematics students at schools with predominantly Black enrollment. Comparisons were made between students using CAI with differing software--PLATO, CSR or both together--and students using traditional instruction (TI) only.^ This study was conducted in the Dade County Public School System from February through June 1991, at two senior high schools. The dependent variables, the State Student Assessment Test (SSAT), and the School Subjects Attitude Scales (SSAS), measured students' computational scores and attitudes toward mathematics in 3 categories: interest, usefulness, and difficulty, respectively.^ Univariate analyses of variance were performed on the least squares mean differences from pretest to posttest for testing main effects and interactions. A t-test measured significant main effects and interactions. Results were interpreted at the.01 level of significance.^ Null hypotheses 1, 2, and 3 compared versions of CAI with the control group, for changes in mathematical computation scores measured with the SSAT. It could not be concluded that changes in standardized mathematics test scores of students using CAI with differing software 1 hour per week for 18 class hours combined with TI were significantly higher than changes in test scores for students receiving TI only.^ Null hypotheses 4, 5, and 6 tested the effects of CAI for attitudes toward mathematics for experimental groups against control groups measured with the SSAS. Changes in attitudes toward mathematics of students using CAI with differing software 1 hour per week for 18 class hours combined with TI were not significantly higher than attitude changes for students receiving TI only.^ Teacher effect on students' computational scores was a more influential variable than CAI. No interaction was found between gender and learning method on standardized mathematics test scores (null hypothesis 7). ^

A methodology for formally modeling and analyzing software architecture of mobile agent systems

A methodology for formally modeling and analyzing software architecture of mobile agent systems provides a solid basis to develop high quality mobile agent systems, and the methodology is helpful to study other distributed and concurrent systems as well. However, it is a challenge to provide the methodology because of the agent mobility in mobile agent systems.^ The methodology was defined from two essential parts of software architecture: a formalism to define the architectural models and an analysis method to formally verify system properties. The formalism is two-layer Predicate/Transition (PrT) nets extended with dynamic channels, and the analysis method is a hierarchical approach to verify models on different levels. The two-layer modeling formalism smoothly transforms physical models of mobile agent systems into their architectural models. Dynamic channels facilitate the synchronous communication between nets, and they naturally capture the dynamic architecture configuration and agent mobility of mobile agent systems. Component properties are verified based on transformed individual components, system properties are checked in a simplified system model, and interaction properties are analyzed on models composing from involved nets. Based on the formalism and the analysis method, this researcher formally modeled and analyzed a software architecture of mobile agent systems, and designed an architectural model of a medical information processing system based on mobile agents. The model checking tool SPIN was used to verify system properties such as reachability, concurrency and safety of the medical information processing system. ^ From successful modeling and analyzing the software architecture of mobile agent systems, the conclusion is that PrT nets extended with channels are a powerful tool to model mobile agent systems, and the hierarchical analysis method provides a rigorous foundation for the modeling tool. The hierarchical analysis method not only reduces the complexity of the analysis, but also expands the application scope of model checking techniques. The results of formally modeling and analyzing the software architecture of the medical information processing system show that model checking is an effective and an efficient way to verify software architecture. Moreover, this system shows a high level of flexibility, efficiency and low cost of mobile agent technologies. ^

Customer relationship management: A content analysis of issues and best practices

This dissertation is a study of customer relationship management theory and practice. Customer Relationship Management (CRM) is a business strategy whereby companies build strong relationships with existing and prospective customers with the goal of increasing organizational profitability. It is also a learning process involving managing change in processes, people, and technology. CRM implementation and its ramifications are also not completely understood as evidenced by the high number of failures in CRM implementation in organizations and the resulting disappointments. ^ The goal of this dissertation is to study emerging issues and trends in CRM, including the effect of computer software and the accompanying new management processes on organizations, and the dynamics of the alignment of marketing, sales and services, and all other functions responsible for delivering customers a satisfying experience. ^ In order to understand CRM better a content analysis of more than a hundred articles and documents from academic and industry sources was undertaken using a new methodological twist to the traditional method. An Internet domain name (http://crm.fiu.edu) was created for the purpose of this research by uploading an initial one hundred plus abstracts of articles and documents onto it to form a knowledge database. Once the database was formed a search engine was developed to enable the search of abstracts using relevant CRM keywords to reveal emergent dominant CRM topics. The ultimate aim of this website is to serve as an information hub for CRM research, as well as a search engine where interested parties can enter CRM-relevant keywords or phrases to access abstracts, as well as submit abstracts to enrich the knowledge hub. ^ Research questions were investigated and answered by content analyzing the interpretation and discussion of dominant CRM topics and then amalgamating the findings. This was supported by comparisons within and across individual, paired, and sets-of-three occurrences of CRM keywords in the article abstracts. ^ Results show that there is a lack of holistic thinking and discussion of CRM in both academics and industry which is required to understand how the people, process, and technology in CRM impact each other to affect successful implementation. Industry has to get their heads around CRM and holistically understand how these important dimensions affect each other. Only then will organizational learning occur, and overtime result in superior processes leading to strong profitable customer relationships and a hard to imitate competitive advantage. ^

An analysis of student and instructor perceptions of students' writing skills at the university level

This study examined university students' writing skills as perceived by university students and their English instructors. The goal of the study was to provide English instructors with objective, quantified information about writing perceptions from both the students' and instructors' viewpoints. ^ A survey instrument was developed based on a survey instrument created by Newkirk, Cameron, and Selfe (1977) to identify instructors' perceived knowledge of student writing skills. The present study used a descriptive statistical design. It examined five writing skill areas: attitude, content, grammar and mechanics, literary considerations, and the writing process through a questionnaire completed by a convenience sample of summer and fall admitted freshmen who were enrolled in Essay Writing and Freshman Composition courses and English Department instructors at a large South Florida public university. ^ The study consisted of five phases. The first phase was modifying of the Newkirk, Cameron, and Selfe (1977) questionnaire. Two versions of the revised survey were developed - one for instructors and one for students. The second phase was pilot testing the questionnaire for evaluation of administration and scoring. The third phase was administering the questionnaire to 1,280 students and 48 instructors. The fourth phase was analyzing the data. The study found a significant difference in the perceptions of students and instructors in all areas of writing skills examined by the survey. Responses to 29 of 30 questions showed that students felt they had better attitudes toward writing and better writing skills than instructors thought. ^ The final phase was developing recommendations for practice. Based on findings and theory and empirical evidence drawn from the fields of adult education and composition research, learner-centered, self-directed curriculum guidelines are offered. ^ By objectively quantifying student and instructor perceptions of students' writing skills, this study contributes to a growing body of literature that: (a) encourages instructors to acknowledge the perception disparities between instructors and students; (b) gives instructors a better understanding of how to communicate with students; and (c) recommends the development of new curriculum, placement tests, and courses that meet the needs of students and enables English instructors to provide meaningful instruction. ^

The construction and optimization of an ion mobility spectrometer for the analysis of explosives and drugs

Today, over 15,000 Ion Mobility Spectrometry (IMS) analyzers are employed at worldwide security checkpoints to detect explosives and illicit drugs. Current portal IMS instruments and other electronic nose technologies detect explosives and drugs by analyzing samples containing the headspace air and loose particles residing on a surface. Canines can outperform these systems at sampling and detecting the low vapor pressure explosives and drugs, such as RDX, PETN, cocaine, and MDMA, because these biological detectors target the volatile signature compounds available in the headspace rather than the non-volatile parent compounds of explosives and drugs.^ In this dissertation research volatile signature compounds available in the headspace over explosive and drug samples were detected using SPME as a headspace sampling tool coupled to an IMS analyzer. A Genetic Algorithm (GA) technique was developed to optimize the operating conditions of a commercial IMS (GE Itemizer 2), leading to the successful detection of plastic explosives (Detasheet, Semtex H, and C-4) and illicit drugs (cocaine, MDMA, and marijuana). Short sampling times (between 10 sec to 5 min) were adequate to extract and preconcentrate sufficient analytes (> 20 ng) representing the volatile signatures in the headspace of a 15 mL glass vial or a quart-sized can containing ≤ 1 g of the bulk explosive or drug.^ Furthermore, a research grade IMS with flexibility for changing operating conditions and physical configurations was designed and fabricated to accommodate future research into different analytes or physical configurations. The design and construction of the FIU-IMS were facilitated by computer modeling and simulation of ion’s behavior within an IMS. The simulation method developed uses SIMION/SDS and was evaluated with experimental data collected using a commercial IMS (PCP Phemto Chem 110). The FIU-IMS instrument has comparable performance to the GE Itemizer 2 (average resolving power of 14, resolution of 3 between two drugs and two explosives, and LODs range from 0.7 to 9 ng). ^ The results from this dissertation further advance the concept of targeting volatile components to presumptively detect the presence of concealed bulk explosives and drugs by SPME-IMS, and the new FIU-IMS provides a flexible platform for future IMS research projects.^

A nested Petri net framework for modeling and analyzing multi-agent systems

In the past two decades, multi-agent systems (MAS) have emerged as a new paradigm for conceptualizing large and complex distributed software systems. A multi-agent system view provides a natural abstraction for both the structure and the behavior of modern-day software systems. Although there were many conceptual frameworks for using multi-agent systems, there was no well established and widely accepted method for modeling multi-agent systems. This dissertation research addressed the representation and analysis of multi-agent systems based on model-oriented formal methods. The objective was to provide a systematic approach for studying MAS at an early stage of system development to ensure the quality of design. ^ Given that there was no well-defined formal model directly supporting agent-oriented modeling, this study was centered on three main topics: (1) adapting a well-known formal model, predicate transition nets (PrT nets), to support MAS modeling; (2) formulating a modeling methodology to ease the construction of formal MAS models; and (3) developing a technique to support machine analysis of formal MAS models using model checking technology. PrT nets were extended to include the notions of dynamic structure, agent communication and coordination to support agent-oriented modeling. An aspect-oriented technique was developed to address the modularity of agent models and compositionality of incremental analysis. A set of translation rules were defined to systematically translate formal MAS models to concrete models that can be verified through the model checker SPIN (Simple Promela Interpreter). ^ This dissertation presents the framework developed for modeling and analyzing MAS, including a well-defined process model based on nested PrT nets, and a comprehensive methodology to guide the construction and analysis of formal MAS models.^

Nuclear magnetic resonance spectroscopic and computational investigations of chloroperoxidase catalyzed regio- and enantio-selective transformations

Chloroperoxidase (CPO) is the most versatile heme-containing enzyme that catalyzes a broad spectrum of reactions. The remarkable feature of this enzyme is the high regio- and enantio-selectivity exhibited in CPO-catalyzed oxidation reactions. The aim of this dissertation is to elucidate the structural basis for regio- and enantio-selective transformations and investigate the application of CPO in biodegradation of synthetic dyes. ^ To unravel the mechanism of CPO-catalyzed regioselective oxidation of indole, the dissertation explored the structure of CPO-indole complex using paramagnetic relaxation and molecular modeling. The distances between the protons of indole and the heme iron revealed that the pyrrole ring of indole is oriented toward the heme with its 2-H pointing directly at the heme iron. This provides the first experimental and theoretical explanation for the "unexpected" regioselectivity of CPO-catalyzed indole oxidation. Furthermore, the residues including Leu 70, Phe 103, Ile 179, Val 182, Glu 183, and Phe 186 were found essential to the substrate binding to CPO. These results will serve as a lighthouse in guiding the design of CPO mutants with tailor-made activities for biotechnological applications. ^ To understand the origin of the enantioselectivity of CPO-catalyzed oxidation reactions, the interactions of CPO with substrates such as 2-(methylthio)thiophene were investigated by nuclear magnetic resonance spectroscopy (NMR) and computational techniques. In particular, the enantioselectivity is partly explained by the binding orientation of substrates. In third facet of this dissertation, a green and efficient system for degradation of synthetic dyes was developed. Several commercial dyes such as orange G were tested in the CPO-H2O 2-Cl- system, where degradation of these dyes was found very efficient. The presence of halide ions and acidic pH were found necessary to the decomposition of dyes. Significantly, the results revealed that this degradation of azo dyes involves a ferric hypochlorite intermediate of CPO (Fe-OCl), compound X.^

``This is your brain on drugs'': The public policy of anti -drug programming. An exploratory analysis of media and other sources of drug information for adolescents

In the 1980s, government agencies sought to utilize research on drug use prevention to design media campaigns. Enlisting the assistance of the national media, several campaigns were designed and initiated to bring anti-drug use messages to adolescents in the form of public service advertising. This research explores the sources of information selected by adolescents in grades 7 through 12 and how the selection of media and other sources of information relate to drug use behavior and attitudes and perceptions related to risk/harm and disapproval of friends' drug-using activities.^ Data collected from 1989 to 1992 in the Miami Coalition School Survey provided a random selection of secondary school studies. The responses of these students were analyzed using multivariate statistical techniques.^ Although many of the students selected media as the source for most of their information on the effects of drugs on the people who use them, the selection of media was found to be positively related to alcohol use and negatively related to marijuana use. The selection of friends, brothers, or sisters was a statistically significant source for adolescents who smoke cigarettes, use alcohol or marijuana.^ The results indicate that the anti-drug use messages received by students may be canceled out by media messages perceived to advocate substance use and that a more persuasive source of information for adolescents may be friends and siblings. As federal reports suggest that the economic costs of drug abuse will reach an estimated $150 billion by 1997 if current trends continue, prevention policy that addresses the glamorization of substance use remains a national priority. Additionally, programs that advocate prevention within the peer cluster must be supported, as peers are an influential source for both inspiring and possibly preventing drug use behavior. ^

Methods for modeling and analyzing concurrent software

Concurrent software executes multiple threads or processes to achieve high performance. However, concurrency results in a huge number of different system behaviors that are difficult to test and verify. The aim of this dissertation is to develop new methods and tools for modeling and analyzing concurrent software systems at design and code levels. This dissertation consists of several related results. First, a formal model of Mondex, an electronic purse system, is built using Petri nets from user requirements, which is formally verified using model checking. Second, Petri nets models are automatically mined from the event traces generated from scientific workflows. Third, partial order models are automatically extracted from some instrumented concurrent program execution, and potential atomicity violation bugs are automatically verified based on the partial order models using model checking. Our formal specification and verification of Mondex have contributed to the world wide effort in developing a verified software repository. Our method to mine Petri net models automatically from provenance offers a new approach to build scientific workflows. Our dynamic prediction tool, named McPatom, can predict several known bugs in real world systems including one that evades several other existing tools. McPatom is efficient and scalable as it takes advantage of the nature of atomicity violations and considers only a pair of threads and accesses to a single shared variable at one time. However, predictive tools need to consider the tradeoffs between precision and coverage. Based on McPatom, this dissertation presents two methods for improving the coverage and precision of atomicity violation predictions: 1) a post-prediction analysis method to increase coverage while ensuring precision; 2) a follow-up replaying method to further increase coverage. Both methods are implemented in a completely automatic tool.

Two-bit pattern analysis for quantitative information flow

Protecting confidential information from improper disclosure is a fundamental security goal. While encryption and access control are important tools for ensuring confidentiality, they cannot prevent an authorized system from leaking confidential information to its publicly observable outputs, whether inadvertently or maliciously. Hence, secure information flow aims to provide end-to-end control of information flow. Unfortunately, the traditionally-adopted policy of noninterference, which forbids all improper leakage, is often too restrictive. Theories of quantitative information flow address this issue by quantifying the amount of confidential information leaked by a system, with the goal of showing that it is intuitively "small" enough to be tolerated. Given such a theory, it is crucial to develop automated techniques for calculating the leakage in a system. ^ This dissertation is concerned with program analysis for calculating the maximum leakage, or capacity, of confidential information in the context of deterministic systems and under three proposed entropy measures of information leakage: Shannon entropy leakage, min-entropy leakage, and g-leakage. In this context, it turns out that calculating the maximum leakage of a program reduces to counting the number of possible outputs that it can produce. ^ The new approach introduced in this dissertation is to determine two-bit patterns, the relationships among pairs of bits in the output; for instance we might determine that two bits must be unequal. By counting the number of solutions to the two-bit patterns, we obtain an upper bound on the number of possible outputs. Hence, the maximum leakage can be bounded. We first describe a straightforward computation of the two-bit patterns using an automated prover. We then show a more efficient implementation that uses an implication graph to represent the two- bit patterns. It efficiently constructs the graph through the use of an automated prover, random executions, STP counterexamples, and deductive closure. The effectiveness of our techniques, both in terms of efficiency and accuracy, is shown through a number of case studies found in recent literature. ^