Design principles of semantic binary database management systems

The Semantic Binary Data Model (SBM) is a viable alternative to the now-dominant relational data model. SBM would be especially advantageous for applications dealing with complex interrelated networks of objects provided that a robust efficient implementation can be achieved. This dissertation presents an implementation design method for SBM, algorithms, and their analytical and empirical evaluation. Our method allows building a robust and flexible database engine with a wider applicability range and improved performance. ^ Extensions to SBM are introduced and an implementation of these extensions is proposed that allows the database engine to efficiently support applications with a predefined set of queries. A New Record data structure is proposed. Trade-offs of employing Fact, Record and Bitmap Data structures for storing information in a semantic database are analyzed. ^ A clustering ID distribution algorithm and an efficient algorithm for object ID encoding are proposed. Mapping to an XML data model is analyzed and a new XML-based XSDL language facilitating interoperability of the system is defined. Solutions to issues associated with making the database engine multi-platform are presented. An improvement to the atomic update algorithm suitable for certain scenarios of database recovery is proposed. ^ Specific guidelines are devised for implementing a robust and well-performing database engine based on the extended Semantic Data Model. ^

An incremental multilinear system for human face learning and recognition

This dissertation establishes a novel system for human face learning and recognition based on incremental multilinear Principal Component Analysis (PCA). Most of the existing face recognition systems need training data during the learning process. The system as proposed in this dissertation utilizes an unsupervised or weakly supervised learning approach, in which the learning phase requires a minimal amount of training data. It also overcomes the inability of traditional systems to adapt to the testing phase as the decision process for the newly acquired images continues to rely on that same old training data set. Consequently when a new training set is to be used, the traditional approach will require that the entire eigensystem will have to be generated again. However, as a means to speed up this computational process, the proposed method uses the eigensystem generated from the old training set together with the new images to generate more effectively the new eigensystem in a so-called incremental learning process. In the empirical evaluation phase, there are two key factors that are essential in evaluating the performance of the proposed method: (1) recognition accuracy and (2) computational complexity. In order to establish the most suitable algorithm for this research, a comparative analysis of the best performing methods has been carried out first. The results of the comparative analysis advocated for the initial utilization of the multilinear PCA in our research. As for the consideration of the issue of computational complexity for the subspace update procedure, a novel incremental algorithm, which combines the traditional sequential Karhunen-Loeve (SKL) algorithm with the newly developed incremental modified fast PCA algorithm, was established. In order to utilize the multilinear PCA in the incremental process, a new unfolding method was developed to affix the newly added data at the end of the previous data. The results of the incremental process based on these two methods were obtained to bear out these new theoretical improvements. Some object tracking results using video images are also provided as another challenging task to prove the soundness of this incremental multilinear learning method.

Dynamic image precompensation for improving visual performance of computer users with ocular aberrations

With the progress of computer technology, computers are expected to be more intelligent in the interaction with humans, presenting information according to the user's psychological and physiological characteristics. However, computer users with visual problems may encounter difficulties on the perception of icons, menus, and other graphical information displayed on the screen, limiting the efficiency of their interaction with computers. In this dissertation, a personalized and dynamic image precompensation method was developed to improve the visual performance of the computer users with ocular aberrations. The precompensation was applied on the graphical targets before presenting them on the screen, aiming to counteract the visual blurring caused by the ocular aberration of the user's eye. A complete and systematic modeling approach to describe the retinal image formation of the computer user was presented, taking advantage of modeling tools, such as Zernike polynomials, wavefront aberration, Point Spread Function and Modulation Transfer Function. The ocular aberration of the computer user was originally measured by a wavefront aberrometer, as a reference for the precompensation model. The dynamic precompensation was generated based on the resized aberration, with the real-time pupil diameter monitored. The potential visual benefit of the dynamic precompensation method was explored through software simulation, with the aberration data from a real human subject. An "artificial eye'' experiment was conducted by simulating the human eye with a high-definition camera, providing objective evaluation to the image quality after precompensation. In addition, an empirical evaluation with 20 human participants was also designed and implemented, involving image recognition tests performed under a more realistic viewing environment of computer use. The statistical analysis results of the empirical experiment confirmed the effectiveness of the dynamic precompensation method, by showing significant improvement on the recognition accuracy. The merit and necessity of the dynamic precompensation were also substantiated by comparing it with the static precompensation. The visual benefit of the dynamic precompensation was further confirmed by the subjective assessments collected from the evaluation participants.

Event mining for system and service management

Modern IT infrastructures are constructed by large scale computing systems and administered by IT service providers. Manually maintaining such large computing systems is costly and inefficient. Service providers often seek automatic or semi-automatic methodologies of detecting and resolving system issues to improve their service quality and efficiency. This dissertation investigates several data-driven approaches for assisting service providers in achieving this goal. The detailed problems studied by these approaches can be categorized into the three aspects in the service workflow: 1) preprocessing raw textual system logs to structural events; 2) refining monitoring configurations for eliminating false positives and false negatives; 3) improving the efficiency of system diagnosis on detected alerts. Solving these problems usually requires a huge amount of domain knowledge about the particular computing systems. The approaches investigated by this dissertation are developed based on event mining algorithms, which are able to automatically derive part of that knowledge from the historical system logs, events and tickets. ^ In particular, two textual clustering algorithms are developed for converting raw textual logs into system events. For refining the monitoring configuration, a rule based alert prediction algorithm is proposed for eliminating false alerts (false positives) without losing any real alert and a textual classification method is applied to identify the missing alerts (false negatives) from manual incident tickets. For system diagnosis, this dissertation presents an efficient algorithm for discovering the temporal dependencies between system events with corresponding time lags, which can help the administrators to determine the redundancies of deployed monitoring situations and dependencies of system components. To improve the efficiency of incident ticket resolving, several KNN-based algorithms that recommend relevant historical tickets with resolutions for incoming tickets are investigated. Finally, this dissertation offers a novel algorithm for searching similar textual event segments over large system logs that assists administrators to locate similar system behaviors in the logs. Extensive empirical evaluation on system logs, events and tickets from real IT infrastructures demonstrates the effectiveness and efficiency of the proposed approaches.^

Dynamic Image Precompensation for Improving Visual Performance of Computer Users with Ocular Aberrations

With the progress of computer technology, computers are expected to be more intelligent in the interaction with humans, presenting information according to the user's psychological and physiological characteristics. However, computer users with visual problems may encounter difficulties on the perception of icons, menus, and other graphical information displayed on the screen, limiting the efficiency of their interaction with computers. In this dissertation, a personalized and dynamic image precompensation method was developed to improve the visual performance of the computer users with ocular aberrations. The precompensation was applied on the graphical targets before presenting them on the screen, aiming to counteract the visual blurring caused by the ocular aberration of the user's eye. A complete and systematic modeling approach to describe the retinal image formation of the computer user was presented, taking advantage of modeling tools, such as Zernike polynomials, wavefront aberration, Point Spread Function and Modulation Transfer Function. The ocular aberration of the computer user was originally measured by a wavefront aberrometer, as a reference for the precompensation model. The dynamic precompensation was generated based on the resized aberration, with the real-time pupil diameter monitored. The potential visual benefit of the dynamic precompensation method was explored through software simulation, with the aberration data from a real human subject. An "artificial eye'' experiment was conducted by simulating the human eye with a high-definition camera, providing objective evaluation to the image quality after precompensation. In addition, an empirical evaluation with 20 human participants was also designed and implemented, involving image recognition tests performed under a more realistic viewing environment of computer use. The statistical analysis results of the empirical experiment confirmed the effectiveness of the dynamic precompensation method, by showing significant improvement on the recognition accuracy. The merit and necessity of the dynamic precompensation were also substantiated by comparing it with the static precompensation. The visual benefit of the dynamic precompensation was further confirmed by the subjective assessments collected from the evaluation participants.

An empirical study of Kirkpatrick's evaluation model in the hospitality industry

This study examined Kirkpatrick’s training evaluation model (Kirkpatrick & Kirkpatrick, 2006) by assessing a sales training program conducted at an organization in the hospitality industry. The study assessed the employees’ training outcomes of knowledge and skills, job performance, and the impact of the training upon the organization. By assessing these training outcomes and their relationships, the study demonstrated whether Kirkpatrick’s theories are supported and the lower evaluation levels can be used to predict organizational impact. The population for this study was a group of reservations sales agents from a leading luxury hotel chain’s reservations center. During the study period from January 2005 to May 2007, there were 335 reservations sales agents employed in this Global Reservations Center (GRC). The number of reservations sales agents who had completed a sales training program/intervention during this period and had data available for at least two months pre and post training composed the sample for this study. The number of agents was 69 ( N = 69). Four hypotheses were tested through paired-samples t tests, correlation, and hierarchical regression analytic procedures. Results from the analyses supported the hypotheses in this study. The significant improvement in the call score supported hypothesis one that the reservations sales agents who completed the training improved their knowledge of content and required skills in handling calls (Level 2). Hypothesis two was accepted in part as there was significant improvement in call conversion, but there was no significant improvement of time usage. The significant improvement in the sales per call supported hypothesis three that the reservations agents who completed the training contributed to increased organizational impact (Level 4), i.e., made significantly more sales. Last, findings supported hypothesis four that Level 2 and Level 3 variables can be used for predicting Level 4 organizational impact. The findings supported the theory of Kirkpatrick’s evaluation model that in order to expect organizational results, a positive change in behavior (job performance) and learning must occur. The examinations of Levels 2 and 3 helped to partially explain and predict Level 4 results.

Design and evaluation of a consulting system for database design

Database design is a difficult problem for non-expert designers. It is desirable to assist such designers during the problem solving process by means of a knowledge based (KB) system. A number of prototype KB systems have been proposed, however there are many shortcomings. Few have incorporated sufficient expertise in modeling relationships, particularly higher order relationships. There has been no empirical study that experimentally tested the effectiveness of any of these KB tools. Problem solving behavior of non-experts, whom the systems were intended to assist, has not been one of the bases for system design. In this project a consulting system for conceptual database design that addresses the above short comings was developed and empirically validated.^ The system incorporates (a) findings on why non-experts commit errors and (b) heuristics for modeling relationships. Two approaches to knowledge base implementation--system restrictiveness and decisional guidance--were used and compared in this project. The Restrictive approach is proscriptive and limits the designer's choices at various design phases by forcing him/her to follow a specific design path. The Guidance system approach which is less restrictive, provides context specific, informative and suggestive guidance throughout the design process. The main objectives of the study are to evaluate (1) whether the knowledge-based system is more effective than a system without the knowledge-base and (2) which knowledge implementation--restrictive or guidance--strategy is more effective. To evaluate the effectiveness of the knowledge base itself, the two systems were compared with a system that does not incorporate the expertise (Control).^ The experimental procedure involved the student subjects solving a task without using the system (pre-treatment task) and another task using one of the three systems (experimental task). The experimental task scores of those subjects who performed satisfactorily in the pre-treatment task were analyzed. Results are (1) The knowledge based approach to database design support lead to more accurate solutions than the control system; (2) No significant difference between the two KB approaches; (3) Guidance approach led to best performance; and (4) The subjects perceived the Restrictive system easier to use than the Guidance system. ^

An evaluation of coping ability as a guide to the treatment of persons diagnosed with schizophrenia and substance abuse

This dissertation introduced substance abuse to the Dynamic Vulnerability Formulation (DVF) and the social competence model to determine if the relationship between schizophrenic symptomatology and coping ability in the DVF applied also to the dually diagnosed schizophrenic or if these variables needed to be modified. It compared the coping abilities of dually and singly diagnosed clients in day treatment and identified, examined, and assessed the relative influence of relevant mediating variables on two dimensions of coping ability of the dually diagnosed: coping skills and coping effort. These variables were: presence of negative and nonnegative symptoms, duration of mental illness, type of substance used, and age of first substance use.^ A priori effect sizes based on previous empirical research were used to interpret the results related to the comparison of demographic, socioeconomic, and treatment characteristics between the singly and dually diagnosed study samples. The data suggested that the singly diagnosed group had higher coping skills than the dually diagnosed group, particularly in the areas of housing stability, work affect, and total social adjustment. The dually diagnosed group had lower scores on one aspect of coping effort--agency or self-efficacy. The data supported the presence of an inverse relationship between symptom severity and coping skills, particularly for the dually diagnosed group. The data did not support the presence of an inverse relationship between symptom severity and coping effort, but did suggest a positive relationship between symptom severity and one measure of coping effort, agency, for the dually diagnosed group. Regression equations using each summary measure of coping skill--social adjustment and role functioning--yielded statistically significant F-ratios. Thirty-six percent of the variance in social adjustment and thirty-one percent of the variance in role functioning were explained by the relative influence of the relevant variables. Both negative and non-negative symptoms were the only significant predictors of social adjustment. The non-negative symptoms variable was the sole significant predictor of role functioning. The results of this study provided partial support for the use of the Dynamic Vulnerability Formulation (DVF) with the dually diagnosed. ^

An evaluation of functional impairment among children with anxiety disorders

Despite a considerable progress in developing and testing psychosocial treatments to reduce youth anxiety disorders, much remains to learn about the relation between anxiety symptom reduction and change in youth functional impairment. The specific aims of this dissertation thus were to examine: (1) the relation between different levels of anxiety and youth functional impairment ratings; (2) incremental validity of the Children Global Assessment Scale (CGAS); (3) the mediating role of anxiety symptom reduction on youth functional impairment ratings; (4) the directionality of change between anxiety symptom reduction and youth functional impairment; (5) the moderating effects of youth age, sex, and ethnicity on the mediated relation between youth anxiety symptom reduction and change in functional impairment; and (6) an agreement (or lack thereof) between youths and their parents in their views of change in youth functional impairment vis-à-vis anxiety symptom reduction. ^ The results were analyzed using archival data set acquired from 183 youths and their mothers. Research questions were tested using SPSS and structural equation modeling techniques in Mplus. ^ The results supported the efficacy of psychosocial treatments to reduce the severity of youth anxiety symptoms and its associated functional impairment. Moreover, the results revealed that at posttreatment, youths who scored either low or medium on anxiety levels scored significantly lower on impairment, than youths who scored high on anxiety levels. Incremental validity of the CGAS was also revealed across all assessment points and informants in my sample. In addition, the results indicated the mediating role of anxiety symptom reduction with respect to change in youth functional impairment at posttest, regardless of the youth’s age, sex, and ethnicity. No significant findings were observed with regard to the bidirectionality and an informant disagreement vis-à-vis the relation between anxiety symptom reduction and change in functional impairment. ^ The study’s main contributions and potential implications on theoretical, empirical, and clinical levels are further discussed. The emphasis is on the need to enhance existing evidence-based treatments and develop innovative treatment models that will not only reduce youth’s symptoms (such anxiety) but also evoke genuine and palpable improvements in lives of youths and their families.^

An energy based nanomechnical properties evaluation method for cementitious materials

Advances in multiscale material modeling of structural concrete have created an upsurge of interest in the accurate evaluation of mechanical properties and volume fractions of its nano constituents. The task is accomplished by analyzing the response of a material to indentation, obtained as an outcome of a nanoindentation experiment, using a procedure called the Oliver and Pharr (OP) method. Despite its widespread use, the accuracy of this method is often questioned when it is applied to the data from heterogeneous materials or from the materials that show pile-up and sink-in during indentation, which necessitates the development of an alternative method. ^ In this study, a model is developed within the framework defined by contact mechanics to compute the nanomechanical properties of a material from its indentation response. Unlike the OP method, indentation energies are employed in the form of dimensionless constants to evaluate model parameters. Analysis of the load-displacement data pertaining to a wide range of materials revealed that the energy constants may be used to determine the indenter tip bluntness, hardness and initial unloading stiffness of the material. The proposed model has two main advantages: (1) it does not require the computation of the contact area, a source of error in the existing method; and (2) it incorporates the effect of peak indentation load, dwelling period and indenter tip bluntness on the measured mechanical properties explicitly. ^ Indentation tests are also carried out on samples from cement paste to validate the energy based model developed herein by determining the elastic modulus and hardness of different phases of the paste. As a consequence, it has been found that the model computes the mechanical properties in close agreement with that obtained by the OP method; a discrepancy, though insignificant, is observed more in the case of C-S-H than in the anhydrous phase. Nevertheless, the proposed method is computationally efficient, and thus it is highly suitable when the grid indentation technique is required to be performed. In addition, several empirical relations are developed that are found to be crucial in understanding the nanomechanical behavior of cementitious materials.^

Menu Analysis: Review and Evaluation

In the article - Menu Analysis: Review and Evaluation - by Lendal H. Kotschevar, Distinguished Professor School of Hospitality Management, Florida International University, Kotschevar’s initial statement reads: “Various methods are used to evaluate menus. Some have quite different approaches and give different information. Even those using quite similar methods vary in the information they give. The author attempts to describe the most frequently used methods and to indicate their value. A correlation calculation is made to see how well certain of these methods agree in the information they give.” There is more than one way to look at the word menu. The culinary selections decided upon by the head chef or owner of a restaurant, which ultimately define the type of restaurant is one way. The physical outline of the food, which a patron actually holds in his or her hand, is another. These descriptions are most common to the word, menu. The author primarily concentrates on the latter description, and uses the act of counting the number of items sold on a menu to measure the popularity of any particular item. This, along with a formula, allows Kotschevar to arrive at a specific value per item. Menu analysis would appear a difficult subject to broach. How does a person approach a menu analysis, how do you qualify and quantify a menu; it seems such a subjective exercise. The author offers methods and outlines on approaching menu analysis from empirical perspectives. “Menus are often examined visually through the evaluation of various factors. It is a subjective method but has the advantage of allowing scrutiny of a wide range of factors which other methods do not,” says Distinguished Professor, Kotschevar. “The method is also highly flexible. Factors can be given a score value and scores summed to give a total for a menu. This allows comparison between menus. If the one making the evaluations knows menu values, it is a good method of judgment,” he further offers. The author wants you to know that assigning values is fundamental to a pragmatic menu analysis; it is how the reviewer keeps score, so to speak. Value merit provides reliable criteria from which to gauge a particular menu item. In the final analysis, menu evaluation provides the mechanism for either keeping or rejecting selected items on a menu. Kotschevar provides at least three different matrix evaluation methods; they are defined as the Miller method, the Smith and Kasavana method, and the Pavesic method. He offers illustrated examples of each via a table format. These are helpful tools since trying to explain the theories behind the tables would be difficult at best. Kotschevar also references examples of analysis methods which aren’t matrix based. The Hayes and Huffman - Goal Value Analysis - is one such method. The author sees no one method better than another, and suggests that combining two or more of the methods to be a benefit.

Design and evaluation of a consulting system for database design

Database design is a difficult problem for non-expert designers. It is desirable to assist such designers during the problem solving process by means of a knowledge based (KB) system. Although a number of prototype KB systems have been proposed, there are many shortcomings. Firstly, few have incorporated sufficient expertise in modeling relationships, particularly higher order relationships. Secondly, there does not seem to be any published empirical study that experimentally tested the effectiveness of any of these KB tools. Thirdly, problem solving behavior of non-experts, whom the systems were intended to assist, has not been one of the bases for system design. In this project, a consulting system, called CODA, for conceptual database design that addresses the above short comings was developed and empirically validated. More specifically, the CODA system incorporates (a) findings on why non-experts commit errors and (b) heuristics for modeling relationships. Two approaches to knowledge base implementation were used and compared in this project, namely system restrictiveness and decisional guidance (Silver 1990). The Restrictive system uses a proscriptive approach and limits the designer's choices at various design phases by forcing him/her to follow a specific design path. The Guidance system approach, which is less restrictive, involves providing context specific, informative and suggestive guidance throughout the design process. Both the approaches would prevent erroneous design decisions. The main objectives of the study are to evaluate (1) whether the knowledge-based system is more effective than the system without a knowledge-base and (2) which approach to knowledge implementation - whether Restrictive or Guidance - is more effective. To evaluate the effectiveness of the knowledge base itself, the systems were compared with a system that does not incorporate the expertise (Control). An experimental procedure using student subjects was used to test the effectiveness of the systems. The subjects solved a task without using the system (pre-treatment task) and another task using one of the three systems, viz. Control, Guidance or Restrictive (experimental task). Analysis of experimental task scores of those subjects who performed satisfactorily in the pre-treatment task revealed that the knowledge based approach to database design support lead to more accurate solutions than the control system. Among the two KB approaches, Guidance approach was found to lead to better performance when compared to the Control system. It was found that the subjects perceived the Restrictive system easier to use than the Guidance system.