Real-Time and Data-Driven Operation Optimization and Knowledge Discovery for an Enterprise Information System

An enterprise information system (EIS) is an integrated data-applications platform characterized by diverse, heterogeneous, and distributed data sources. For many enterprises, a number of business processes still depend heavily on static rule-based methods and extensive human expertise. Enterprises are faced with the need for optimizing operation scheduling, improving resource utilization, discovering useful knowledge, and making data-driven decisions.

This thesis research is focused on real-time optimization and knowledge discovery that addresses workflow optimization, resource allocation, as well as data-driven predictions of process-execution times, order fulfillment, and enterprise service-level performance. In contrast to prior work on data analytics techniques for enterprise performance optimization, the emphasis here is on realizing scalable and real-time enterprise intelligence based on a combination of heterogeneous system simulation, combinatorial optimization, machine-learning algorithms, and statistical methods.

On-demand digital-print service is a representative enterprise requiring a powerful EIS.We use real-life data from Reischling Press, Inc. (RPI), a digit-print-service provider (PSP), to evaluate our optimization algorithms.

In order to handle the increase in volume and diversity of demands, we first present a high-performance, scalable, and real-time production scheduling algorithm for production automation based on an incremental genetic algorithm (IGA). The objective of this algorithm is to optimize the order dispatching sequence and balance resource utilization. Compared to prior work, this solution is scalable for a high volume of orders and it provides fast scheduling solutions for orders that require complex fulfillment procedures. Experimental results highlight its potential benefit in reducing production inefficiencies and enhancing the productivity of an enterprise.

We next discuss analysis and prediction of different attributes involved in hierarchical components of an enterprise. We start from a study of the fundamental processes related to real-time prediction. Our process-execution time and process status prediction models integrate statistical methods with machine-learning algorithms. In addition to improved prediction accuracy compared to stand-alone machine-learning algorithms, it also performs a probabilistic estimation of the predicted status. An order generally consists of multiple series and parallel processes. We next introduce an order-fulfillment prediction model that combines advantages of multiple classification models by incorporating flexible decision-integration mechanisms. Experimental results show that adopting due dates recommended by the model can significantly reduce enterprise late-delivery ratio. Finally, we investigate service-level attributes that reflect the overall performance of an enterprise. We analyze and decompose time-series data into different components according to their hierarchical periodic nature, perform correlation analysis,

and develop univariate prediction models for each component as well as multivariate models for correlated components. Predictions for the original time series are aggregated from the predictions of its components. In addition to a significant increase in mid-term prediction accuracy, this distributed modeling strategy also improves short-term time-series prediction accuracy.

In summary, this thesis research has led to a set of characterization, optimization, and prediction tools for an EIS to derive insightful knowledge from data and use them as guidance for production management. It is expected to provide solutions for enterprises to increase reconfigurability, accomplish more automated procedures, and obtain data-driven recommendations or effective decisions.

Towards Data Management Planning Support for Research Data

Görzig, H., Engel, F., Brocks, H., Vogel, T. & Hemmje, M. (2015, August). Towards Data Management Planning Support for Research Data. Paper presented at the ASE International Conference on Data Science, Stanford, United States of America.

D10.2 - Research Data Management Plan, version 1.0

This document is the first out of three iterations of the DMP that will be formally delivered during the project. Version 2 is due in month 24 and version 3 towards the end of the project. The DMP thus is not a fixed document; it evolves and gains more precision and substance during the lifespan of the project. In this first version we describe the planned research data sets related to the RAGE evaluation and validation activities, and the fifteen principles that will guide data management in RAGE. The former are described in the format of the EU data management template, and the latter in terms of their guiding principle, how we propose to implement them, and when they will be implemented. This document is thus first of all relevant to WP5 and WP8 members.

The Atlantic Meridional Transect (AMT) data management experience

As the UK's national marine data centre, a key responsibility of the British Oceanographic Data Centre (BODC) is to provide data management support for the scientific activities of complex multi-disciplinary long-term research programmes. Since the initial cruise in 1995, the NERC funded Atlantic Meridional Transect (AMT) project has undertaken 18 north–south transects of the Atlantic Ocean. As the project has evolved there has been a steady growth in the number of participants, the volume of data, its complexity and the demand for data. BODC became involved in AMT in 2002 at the beginning of phase II of this programme and since then has provided continuous support to the AMT and the wider scientific community through the rescue, quality control, processing and access to the data. The data management is carried out by a team of specialists using a sophisticated infrastructure and hardware to manage, integrate and serve physical, biological and chemical data. Here, we discuss the approach adopted, techniques applied and some guiding principles for management of large multi-disciplinary programmes.

Wildlife tracking data management: a new vision

To date, the processing of wildlife location data has relied on a diversity of software and file formats. Data management and the following spatial and statistical analyses were undertaken in multiple steps, involving many time-consuming importing/exporting phases. Recent technological advancements in tracking systems have made large, continuous, high-frequency datasets of wildlife behavioral data available, such as those derived from the global positioning system (GPS) and other animal-attached sensor devices. These data can be further complemented by a wide range of other information about the animals’ environment. Management of these large and diverse datasets for modelling animal behaviour and ecology can prove challenging, slowing down analysis and increasing the probability of mistakes in data handling. We address these issues by critically evaluating the requirements for good management of GPS data for wildlife biology. We highlight that dedicated data management tools and expertise are needed. We explore current research in wildlife data management. We suggest a general direction of development, based on a modular software architecture with a spatial database at its core, where interoperability, data model design and integration with remote-sensing data sources play an important role in successful GPS data handling.

Prefetching and Cache Management using Task Lifetimes

Task-based dataflow programming models and runtimes emerge as promising candidates for programming multicore and manycore architectures. These programming models analyze dynamically task dependencies at runtime and schedule independent tasks concurrently to the processing elements. In such models, cache locality, which is critical for performance, becomes more challenging in the presence of fine-grain tasks, and in architectures with many simple cores.

This paper presents a combined hardware-software approach to improve cache locality and offer better performance is terms of execution time and energy in the memory system. We propose the explicit bulk prefetcher (EBP) and epoch-based cache management (ECM) to help runtimes prefetch task data and guide the replacement decisions in caches. The runtimem software can use this hardware support to expose its internal knowledge about the tasks to the architecture and achieve more efficient task-based execution. Our combined scheme outperforms HW-only prefetchers and state-of-the-art replacement policies, improves performance by an average of 17%, generates on average 26% fewer L2 misses, and consumes on average 28% less energy in the components of the memory system.

Dissidents with an innovation cause? Non-institutionalized actors ’ online social knowledge sharing, solution-finding tensions and technology management innovation

Purpose
– Traditionally, most studies focus on institutionalized management-driven actors to understand technology management innovation. The purpose of this paper is to argue that there is a need for research to study the nature and role of dissident non-institutionalized actors’ (i.e. outsourced web designers and rapid application software developers). The authors propose that through online social knowledge sharing, non-institutionalized actors’ solution-finding tensions enable technology management innovation.

Design/methodology/approach
– A synthesis of the literature and an analysis of the data (21 interviews) provided insights in three areas of solution-finding tensions enabling management innovation. The authors frame the analysis on the peripherally deviant work and the nature of the ways that dissident non-institutionalized actors deviate from their clients (understood as the firm) original contracted objectives.

Findings
– The findings provide insights into the productive role of solution-finding tensions in enabling opportunities for management service innovation. Furthermore, deviant practices that leverage non-institutionalized actors’ online social knowledge to fulfill customers’ requirements are not interpreted negatively, but as a positive willingness to proactively explore alternative paths.

Research limitations/implications
– The findings demonstrate the importance of dissident non-institutionalized actors in technology management innovation. However, this work is based on a single country (USA) and additional research is needed to validate and generalize the findings in other cultural and institutional settings.

Originality/value
– This paper provides new insights into the perceptions of dissident non-institutionalized actors in the practice of IT managerial decision making. The work departs from, but also extends, the previous literature, demonstrating that peripherally deviant work in solution-finding practice creates tensions, enabling management innovation between IT providers and users.

Exploiting evidence from unstructured data to enhance master data management

Master data management (MDM) integrates data from multiple
structured data sources and builds a consolidated 360-
degree view of business entities such as customers and products.
Today’s MDM systems are not prepared to integrate
information from unstructured data sources, such as news
reports, emails, call-center transcripts, and chat logs. However,
those unstructured data sources may contain valuable
information about the same entities known to MDM from
the structured data sources. Integrating information from
unstructured data into MDM is challenging as textual references
to existing MDM entities are often incomplete and
imprecise and the additional entity information extracted
from text should not impact the trustworthiness of MDM
data.
In this paper, we present an architecture for making MDM
text-aware and showcase its implementation as IBM InfoSphere
MDM Extension for Unstructured Text Correlation,
an add-on to IBM InfoSphere Master Data Management
Standard Edition. We highlight how MDM benefits from
additional evidence found in documents when doing entity
resolution and relationship discovery. We experimentally
demonstrate the feasibility of integrating information from
unstructured data sources into MDM.

Governance structures and performance management systems in universities: a comparative study between the UK and Portugal

À semelhança do que aconteceu em muitas instituições públicas, as universidades têm enfrentado pressões crescentes para mudar, tendo de repensar as suas formas de governança e de gestão, dando mais ênfase à implementação de sistemas de gestão do desempenho (SGD). Apesar de existirem vários estudos sobre o desempenho, estes têm ignorado o uso dado à informação recolhida. Além disso, e apesar de terem ocorrido várias reformas na governança destas instituições, existem ainda poucos estudos que relacionam a governança e o desempenho. Assim, esta pesquisa visa explorar a forma como as universidades medem, reportam e gerem o desempenho e como as estruturas de governança se relacionam com estas práticas. Para alcançar o objetivo proposto, um estudo comparativo entre universidades britânicas e portuguesas foi realizado. Os dados foram recolhidos através da utilização de uma metodologia qualitativa, sendo os métodos utilizados a análise documental e entrevistas semi-estruturadas a membros dos órgãos de governo e gestão de cada instituição. A análise dos dados mostrou a inexistência de um sistema completamente integrado de gestão de desempenho (SGD) em ambas as instituições, essencialmente devido à falta de práticas de gestão de desempenho. De facto, apesar de alguns dos entrevistados terem reportado o "uso positivo" de dados sobre o desempenho, alguns relataram o "não uso" desses dados, principalmente em relação ao desempenho individual, e outros o "mau uso" dessa informação, tendo sido reportadas práticas de gaming e deturpação dos resultados. Como forma de ultrapassar alguns destes problemas, verificou-se a co-existência de duas estruturas de governança: uma 'formal', da qual fazem parte todos os órgão de governo, com um valor mais 'simbólico'; e uma estrutura 'paralela', constituída por órgãos mais ágeis, que gerem a universidade no dia a dia. Verificou-se terem sido vários os fatores a afetarem, negativa e positivamente, os SGD em ambas as instituições, tendo sido rotulados de "inibidores" e "determinantes", respetivamente. A pesquisa mostrou que, apesar de as estruturas de governança serem importantes para a implementação e funcionamento de um SGD, há outros fatores que precisam de ser levados em consideração, nomeadamente, o nível de comunicação e o nível de envolvimento dos atores no processo. Estes dois fatores são considerados relevantes para a integração bem sucedida de práticas de medição, reporte e gestão de desempenho. Esta integração, juntamente com outras mudanças que ocorreram em termos de governança, contribuirá certamente para que se passe de um sistema em que se governa o desempenho para um sistema em que se governa para o desempenho.

Communication between nodes for autonomic and distributed management

Over the last decade, the most widespread approaches for traditional management were based on the Simple Network Management Protocol (SNMP) or Common Management Information Protocol (CMIP). However, they both have several problems in terms of scalability, due to their centralization characteristics. Although the distributed management approaches exhibit better performance in terms of scalability, they still underperform regarding communication costs, autonomy, extensibility, exibility, robustness, and cooperation between network nodes. The cooperation between network nodes normally requires excessive overheads for synchronization and dissemination of management information in the network. For emerging dynamic and large-scale networking environments, as envisioned in Next Generation Networks (NGNs), exponential growth in the number of network devices and mobile communications and application demands is expected. Thus, a high degree of management automation is an important requirement, along with new mechanisms that promote it optimally and e ciently, taking into account the need for high cooperation between the nodes. Current approaches for self and autonomic management allow the network administrator to manage large areas, performing fast reaction and e ciently facing unexpected problems. The management functionalities should be delegated to a self-organized plane operating within the network, that decrease the network complexity and the control information ow, as opposed to centralized or external servers. This Thesis aims to propose and develop a communication framework for distributed network management which integrates a set of mechanisms for initial communication, exchange of management information, network (re) organization and data dissemination, attempting to meet the autonomic and distributed management requirements posed by NGNs. The mechanisms are lightweight and portable, and they can operate in di erent hardware architectures and include all the requirements to maintain the basis for an e cient communication between nodes in order to ensure autonomic network management. Moreover, those mechanisms were explored in diverse network conditions and events, such as device and link errors, di erent tra c/network loads and requirements. The results obtained through simulation and real experimentation show that the proposed mechanisms provide a lower convergence time, smaller overhead impact in the network, faster dissemination of management information, increase stability and quality of the nodes associations, and enable the support for e cient data information delivery in comparison to the base mechanisms analyzed. Finally, all mechanisms for communication between nodes proposed in this Thesis, that support and distribute the management information and network control functionalities, were devised and developed to operate in completely decentralized scenarios.

Acquisition and data analysis related to changes in some forest soils properties after prescribed fire action

Controlled fires in forest areas are frequently used in most Mediterranean countries as a preventive technique to avoid severe wildfires in summer season. In Portugal, this forest management method of fuel mass availability is also used and has shown to be beneficial as annual statistical reports confirm that the decrease of wildfires occurrence have a direct relationship with the controlled fire practice. However prescribed fire can have serious side effects in some forest soil properties. This work shows the changes that occurred in some forest soils properties after a prescribed fire action. The experiments were carried out in soil cover over a natural site of Andaluzitic schist, in Gramelas, Caminha, Portugal, that had not been burn for four years. The composed soil samples were collected from five plots at three different layers (0-3cm, 3-6cm and 6-18cm) during a three-year monitoring period after the prescribed burning. Principal Component Analysis was used to reach the presented conclusions.

Acqusition and data analysis of the eco-efficiency for the establishment of indicators parameters for industrial environmental sustainability

The industrial activity is inevitably associated with a certain degradation of the environmental quality, because is not possible to guarantee that a manufacturing process can be totally innocuous. The eco-efficiency concept is globally accepted as a philosophy of entreprise management, that encourages the companies to become more competitive, innovative and environmentally responsible by promoting the link between its companies objectives for excellence and its objectives of environmental excellence issues. This link imposes the creation of an organizational methodology where the performance of the company is concordant with the sustainable development. The main propose of this project is to apply the concept of eco-efficiency to the particular case of the metallurgical and metal workshop industries through the development of the particular indicators needed and to produce a manual of procedures for implementation of the accurate solution.

A Communication and Resources Management Scheme to Support the Smart Grid Integration of Multiplayers Access to Resources Information

The increasing and intensive integration of distributed energy resources into distribution systems requires adequate methodologies to ensure a secure operation according to the smart grid paradigm. In this context, SCADA (Supervisory Control and Data Acquisition) systems are an essential infrastructure. This paper presents a conceptual design of a communication and resources management scheme based on an intelligent SCADA with a decentralized, flexible, and intelligent approach, adaptive to the context (context awareness). The methodology is used to support the energy resource management considering all the involved costs, power flows, and electricity prices leading to the network reconfiguration. The methodology also addresses the definition of the information access permissions of each player to each resource. The paper includes a 33-bus network used in a case study that considers an intensive use of distributed energy resources in five distinct implemented operation contexts.

Adhésion thérapeutique aux traitements oncologiques oraux et prise en charge interdisciplinaire [Therapeutic adherence to oral cancer therapy and interdisciplinary management].

Medication adherence is a well-known risk factor in internal medicine. However in oncology this dimension is emerging due to the increasing number of oral formulations. First results in the oral oncology literature suggest that patients' ability to cope with medical prescription decreases with time. This might preclude patients from reaching clinical outcomes. Factors impacting on medication adherence to oral oncology treatments have not been yet extensively described neither strategies to address them and support patient's needs. Oncologists and pharmacists in our University outpatient settings performed a pilot study which aimed at measuring and facilitating adherence to oral oncology treatments and at understanding determinants of patient's adherence. The ultimate purpose of such a patient-centered and interdisciplinary collaboration would be to promote patient self-management and complement the standard medical follow-up.

Relating leadership, thinking styles, self-concept, motivation and stress management in education

Seventy-five principals and vice-.wincipals from public elementary and secondary schools in Hamilton, Ontario, Canada participated in this study. Participants provided ,information concerning their thinking styles, motivations, and the physical effects of stress. This information was examined to find out how satisfaction-oriented, and how security-oriented the thinking styles of the participants were. Second, the data were analysed to see how the thinking style orientations related to life style habits and the effects of stress. The satisfaction-oriented thinking styles scored higher than all of the security-oriented thinking styles by a wide margin with a small preference for the satisfaction-people-oriented styles labelled humanistic-helpful, and affiliative as opposed to the satisfaction-task-oriented styles labeled achievement, and self-actualizing. Although all eight of the security-oriented thinking styles scored well below all of the satisfaction-oriented thinking styles on the Life Styles Inventory, the perfectionistic style scored higher than all of the security-oriented styles by an impressive margin. The next highest scores were recorded by a cluster of three passive-defensive people-oriented thinking styles labeled approval, conventional, and dependent. The competitive style scored lower, and the styles labeled avoidance, oppositional, and power scored the lowest of all the defensive-security-oriented styles. These findings suggest that principals and vice-principals see themselves as relaxed, flexible, and satisfied with their ability to adapt to the stress levels they experience in their lives; however, there was some support for medical research findings that suggest that specific security-oriented thinking styles are associated with emotional stresses that contribute to the development of specific lifestyle habits, physical symptoms, and illnesses. Although the number of females in this study provides very limited generalizability, the findings of this study suggest that high achieving females tend to develop satisfaction-growth styles to a higher level than males, and they tend to use security-oriented styles to a lesser degree than males.