Sergio Davalos

Service-Oriented Software Reengineering: SoSR

Service-oriented computing (SOC) enables the development and design of loosely coupled software components for integration with other software system. Since most legacy system were not designed and developed with services components, current legacy software systems require modernization (reengineered) into a target system made up of a set of loosely coupled services. A methodology for service-oriented software reengineering (SoSR) is proposed for applying SOC to legacy systems. The SoSR methodology, a synthesis of best practices, is architecture-centric, service-oriented, role-specific, and model-driven. It is conceptualized from a three-service-participants model, 4+1 view model, and RACI chart. The SoSR methodology is applied in the modernization of a legacy system, a retail business information systems. The results show that this methodology can help software developers and system integrators in reengineering tightly coupled legacy information systems into service-oriented information systems. By including a business process engine for executing composite services with existing applications and database servers, SOC can affect future information system design, deployment, and integration

Computational personality recognition in social media

A variety of approaches have been recently proposed to automatically infer users’ personality from their user generated content in social media. Approaches differ in terms of the machine learning algorithms and the feature sets used, type of utilized footprint, and the social media environment used to collect the data. In this paper, we perform a comparative analysis of state-of-the-art computational personality recognition methods on a varied set of social media ground truth data from Facebook, Twitter and YouTube. We answer three questions: (1) Should personality prediction be treated as a multi-label prediction task (i.e., all personality traits of a given user are predicted at once), or should each trait be identified separately? (2) Which predictive features work well across different on-line environments? and (3) What is the decay in accuracy when porting models trained in one social media environment to another?

The Long-Term Performance and Failure Risk of Firms Cited in the US SEC's Accounting and Auditing Enforcement Releases

Abstract:  We investigate 239 firms cited in the SECs Accounting and Auditing Enforcement Releases (AAERs). We document significantly negative abnormal operating performance (measured using both cash-flow-based and earnings-based metrics) in the second and third years following AAERs. We also detect significantly negative abnormal stock returns in up to three years following AAERs. We further find that AAER firms are more likely to fail in the post-AAER period. Taken together, our findings suggest that the negative implications of an AAER citation resulting from egregious financial reporting violations can be long lasting and influence various facets of firm performance and survivability.

A Multivariate Regression Approach to Personality Impression Recognition of Vloggers

Research in psychology has suggested that behavior of individuals can be explained to a great extent by their underlying personality traits. In this paper, we focus on predicting how the personality of YouTube video bloggers is perceived by their viewers. Our approach to personality recognition is multimodal in the sense that we use audio-video features, as well as textual (emotional and linguistic) features extracted from the transcripts of vlogs. Based on these features, we predict the extent to which the video blogger is perceived to exhibit each of the traits of the Big Five personality model. In addition, we explore 5 multivariate regression techniques and contrast them with a single target approach for predicting personality impression scores. All 6 algorithms are able to outperform the average baseline model for all 5 personality traits on a dataset of 404 YouTube videos. This is interesting because previously published methods for the same dataset show an improvement over the baseline for the majority of personality traits, but not for all simultaneously.

Bankruptcy classification of firms investigated by the US Securities and Exchange Commission: an evolutionary adaptive ensemble model approach

This paper develops an adaptive, rule-based model for bankruptcy classification of firms subject to the SECs Accounting and Auditing Enforcement Release (AAER). In this paper, we use an evolutionary computing method, genetic algorithm (GA), to generate an optimal set of if-then (comprehensible) rules for bankruptcy classification of AAER firms. In particular, we use bagging to improve the models generalisation accuracy; and to develop a doubly controlled fitness function to guide the operations of the (GA) method. Our research contributes to the bankruptcy literature in several ways. First, it fills a gap in bankruptcy classification by developing a domain specific model for AAER firms. Secondly, the derived set of if-then rules used in an expert system adds to the bankruptcy knowledge base. Thirdly, we use bagging to improve generalisation of bankruptcy classification models. Finally, we demonstrate the key role of the fitness function in successful model performance.

DESIGNING AN IF-THEN RULES-BASED ENSEMBLE OF HETEROGENEOUS BANKRUPTCY CLASSIFIERS: A GENETIC ALGORITHM APPROACH

This paper proposes a framework for an ensemble bankruptcy classifier that uses if-then rules to combine the outputs from a heterogeneous set of classifiers. A genetic algorithm GA induces the rules using an asymmetric, cost-sensitive fitness function that includes accuracy and misclassification costs. The GA-based ensemble classifier outperforms individual classifiers and ensemble classifiers generated by other methods. The results of the classifier are in the form of if-then rules. We apply the approach to a balanced dataset and an imbalanced dataset. Both are composed of firms subject to financial distress and cited in the US Securities and Exchange Commissions Accounting and Auditing Enforcement Releases. Copyright

Legacy to web migration: service-oriented software reengineering methodology

In this paper, a Service-Oriented Software Reengineering (SOSR) methodology is proposed for reengineering a legacy system into a service-oriented system. Although Service-Oriented Computing (SOC) enables a software developer to design loosely coupled software components and integrate them with other software systems, most components in a legacy system were not developed as services. The SOSR methodology is based on a set of best practices that are architecture-centric, service-oriented, role-specific and model-driven. The SOSR methodology is demonstrated by the modernisation of two different legacy systems – a Business-to-Business (B2B) system and the other is a Business-to-Consumer (B2C) System. The resulting service-oriented systems and the evaluation of the methodology in terms of non-functional system requirements such as interoperability, etc. show that this methodology can be used by software developers and system integrators to reengineer tightly coupled legacy information systems into the loosely coupled, agile, service-oriented information systems.

A UML model-driven business process development methodology for a Virtual Enterprise using SOA & ESB

The purpose of this paper is to demonstrate how a Virtual Enterprise Integration (VEI) project using Service-Oriented Architecture (SOA) and Enterprise Service Bus (ESB) can be effectively conducted by a virtual team of service brokers. Currently, VEI is accomplished through SOA and ESB using web services and business process engines that execute WSDL and WS-BPEL. To reengineer a Virtual Enterprise (VE) based on one or more legacy components, referred to as a legacy VE, the abstract and concrete parts of the relevant business processes of the VE need to be reverse engineered to a high level of abstraction. To develop new business processes, business process requirements need to be forward engineered into business processes in BPEL. However, service brokers need guidelines for comprehending the operations of the legacy VEs or for understanding the business process requirement. In order to provide clear communication of this information, we propose a UML model driven Business Process Development Methodology (BPDM) called mBPDM. We demonstrate its applicability and capabilities by applying it to two case studies: a loan application process system which involves reverse engineering and Washington State Patrols Drug Recognition Evaluation system which involves forward engineering. Based upon the results of reverse and forward engineering of two virtual enterprise cases, the guidelines, which use UML as a blueprint with multi-architectural views, help service brokers understand the underlying process architecture and organization of a virtual enterprise that has been built using the SOA concept and the contemporary ESB.

A Special Web Service Mechanism: Asynchronous .NET Web Services

The purpose of this paper is to propose an asynchronous service-oriented approach for B2B applications integration for web services. Currently, most web services are synchronous since their interaction protocol SOAP is based upon a synchronous transport protocol HTTP. However, synchronous web services presents limitations for integrating applications across businesses if one of the applications fails or the application needs longer interaction time due to its business requirements. For the asynchronous service-oriented approach, an asynchronous web service message handling middleware using existing email servers and .NET web services is developed since the existing email servers are ubiquitous and have a natural queuing mechanism and an asynchronous mechanism for .NET web services are not available contrary to the open source web service engine, AXIS. Creating such a middleware allows service providers to deploy asynchronous web services with as much easy as synchronous web services.

Using Big Data to Study Psychological Constructs: Nostalgia on Facebook

Nostalgia, reflecting on the past, has many aspects. At times, we refer to it as a state of mind as in, I’m nostalgic. At times, as a feeling – I’m feeling nostalgic. We sometimes use nostalgia as a way to deal with “in the present” emotions or feelings. For instance, we reminisce about past holidays to feel better about the present [1]. Nostalgia can be internally or externally activated. Internally, an individual can evoke feelings of nostalgia. On the other hand, external stimuli can evoke nostalgia, such as a song, an ad, or a brand [2-5].