BUILDING EFFICIENT AND COST-EFFECTIVE CLOUD-BASED BIG DATA MANAGEMENT SYSTEMS

In today’s big data world, data is being produced in massive volumes, at great velocity and from a variety of different sources such as mobile devices, sensors, a plethora of small devices hooked to the internet (Internet of Things), social networks, communication networks and many others. Interactive querying and large-scale analytics are being increasingly used to derive value out of this big data. A large portion of this data is being stored and processed in the Cloud due the several advantages provided by the Cloud such as scalability, elasticity, availability, low cost of ownership and the overall economies of scale. There is thus, a growing need for large-scale cloud-based data management systems that can support real-time ingest, storage and processing of large volumes of heterogeneous data. However, in the pay-as-you-go Cloud environment, the cost of analytics can grow linearly with the time and resources required. Reducing the cost of data analytics in the Cloud thus remains a primary challenge. In my dissertation research, I have focused on building efficient and cost-effective cloud-based data management systems for different application domains that are predominant in cloud computing environments. In the first part of my dissertation, I address the problem of reducing the cost of transactional workloads on relational databases to support database-as-a-service in the Cloud. The primary challenges in supporting such workloads include choosing how to partition the data across a large number of machines, minimizing the number of distributed transactions, providing high data availability, and tolerating failures gracefully. I have designed, built and evaluated SWORD, an end-to-end scalable online transaction processing system, that utilizes workload-aware data placement and replication to minimize the number of distributed transactions that incorporates a suite of novel techniques to significantly reduce the overheads incurred both during the initial placement of data, and during query execution at runtime. In the second part of my dissertation, I focus on sampling-based progressive analytics as a means to reduce the cost of data analytics in the relational domain. Sampling has been traditionally used by data scientists to get progressive answers to complex analytical tasks over large volumes of data. Typically, this involves manually extracting samples of increasing data size (progressive samples) for exploratory querying. This provides the data scientists with user control, repeatable semantics, and result provenance. However, such solutions result in tedious workflows that preclude the reuse of work across samples. On the other hand, existing approximate query processing systems report early results, but do not offer the above benefits for complex ad-hoc queries. I propose a new progressive data-parallel computation framework, NOW!, that provides support for progressive analytics over big data. In particular, NOW! enables progressive relational (SQL) query support in the Cloud using unique progress semantics that allow efficient and deterministic query processing over samples providing meaningful early results and provenance to data scientists. NOW! enables the provision of early results using significantly fewer resources thereby enabling a substantial reduction in the cost incurred during such analytics. Finally, I propose NSCALE, a system for efficient and cost-effective complex analytics on large-scale graph-structured data in the Cloud. The system is based on the key observation that a wide range of complex analysis tasks over graph data require processing and reasoning about a large number of multi-hop neighborhoods or subgraphs in the graph; examples include ego network analysis, motif counting in biological networks, finding social circles in social networks, personalized recommendations, link prediction, etc. These tasks are not well served by existing vertex-centric graph processing frameworks whose computation and execution models limit the user program to directly access the state of a single vertex, resulting in high execution overheads. Further, the lack of support for extracting the relevant portions of the graph that are of interest to an analysis task and loading it onto distributed memory leads to poor scalability. NSCALE allows users to write programs at the level of neighborhoods or subgraphs rather than at the level of vertices, and to declaratively specify the subgraphs of interest. It enables the efficient distributed execution of these neighborhood-centric complex analysis tasks over largescale graphs, while minimizing resource consumption and communication cost, thereby substantially reducing the overall cost of graph data analytics in the Cloud. The results of our extensive experimental evaluation of these prototypes with several real-world data sets and applications validate the effectiveness of our techniques which provide orders-of-magnitude reductions in the overheads of distributed data querying and analysis in the Cloud.

Learning Management Systems (LMS) and e-learning management: an integrative review and research agenda

Information Technology (IT) can be an important component for innovation since enabling e-learning it can provide conditions to which the organization can work with new business and improved processes. In this regard, the Learning Management Systems (LMS) allows communication and interaction between teachers and students in virtual spaces. However the literature indicates that there are gaps in the researches, especially concerning the use of IT for the management of e-learning. The purpose of this paper is to analyze the available literature about the application of LMS for the e-learning management, seeking to present possibilities for researches in the field. An integrative literature review was performed considering the Web of Science, Scopus, Ebsco and Scielo databases, where 78 references were found, of which 25 were full papers. This analysis derives interesting characteristics from scientific studies, highlighting gaps and guidelines for future research.

SQMS – A prototype for a supplier quality management system

Within the supply chain, the customer does not simply buy parts or services from suppliers, but also buys supplier capabilities, which results in quality products and services. Having a tool that handles the Inspection as well as the Nonconformance, Complaint, Corrective Action and Concession processes is key to successfully track the supplier performance. Taking as a case study a Supplier Quality Management (SQM) currently in operation in an Original Equipment Manufacturer (OEM) for automotive industry, this paper presents a platform to support a Supplier Quality Management System (SQMS), that fits the technical specification ISO/TS 16949 requirements. This prototype is composed by a web platform and a mobile App, having flexibility and mobility as key main characteristics.

Standardized environmental management systems as an internal management tool

In a principal-agent model we analyze the firm’s decision to adopt an informal or a standardized Environmental Management System (EMS). Our results are consistent with empirical evidence in several respects. A standardized EMS increases the internal control at the cost of introducing some degree of rigidity that entails an endogenous setup cost. Standardized systems are more prone to be adopted by big and well established firms and under tougher environmental policies. Firms with standardized EMS tend to devote more effort to abatement although this effort results in lower pollution only if public incentives are strong enough, suggesting a complementarity relationship between standardized EMS and public policies. Emission charges have both a marginal effect on abatement and a qualitative effect on the adoption decision that may induce a conflict between private and public interests. As a result of the combination of these two effects it can be optimal for the government to distort the tax in a specific way in order to push the firm to choose the socially optimal EMS. The introduction of standardized systems can result in win-win situations where firms, society and the environment get better off.

Entrepreneurship in project management systems: proposal of a model and preliminary empirical evidence

This study analyzes the manifestation of the dimensions of Entrepreneurial Orientation (EO) and Project Management Systems (PMS). We used a qualitative approach to conduct exploratory research through a study in literature and a pilot case in a software company. Data was collected from semi structured interviews, documents, and records on file, then triangulated and treated with content analysis. The model proposed for the relationship between the types of PMS (ad hoc, Classic PM, innovation, entrepreneurship/intrapreneurship) and the dimensions of EO (innovativeness, risk-taking, proactiveness, competitive aggressiveness, and autonomy), was partially corroborated by empirical studies. New studies are suggested to validate the applicability and setup of the model.

The exploration of potato-associated bacteria in the Central Andean Highlands and their application in integrated crop management systems

Potato is the most important food crop after wheat and rice. A changing climate, coupled with a heightened consumer awareness of how food is produced and legislative changes governing the usage of agrochemicals, means that alternative more integrated and sustainable approaches are needed for crop management practices. Bioprospecting in the Central Andean Highlands resulted in the isolation and in vitro screening of 600 bacterial isolates. The best performing isolates, under in vitro conditions, were field trialled in their home countries. Six of the isolates, Pseudomonas sp. R41805 (Bolivia), Pseudomonas palleroniana R43631 (Peru), Bacillus sp. R47065, R47131, Paenibacillus sp. B3a R49541, and Bacillus simplex M3-4 R49538 (Ecuador), showed significant increase in the yield of potato. Using – omic technologies (i.e. volatilomic, transcriptomic, proteomic and metabolomic), the influence of microbial isolates on plant defence responses was determined. Volatile organic compounds of bacterial isolates were identified using GC/MS. RT-qPCR analysis revealed the significant expression of Ethylene Response Factor 3 (ERF3) and the results of this study suggest that the dual inoculation of potato with Pseudomonas sp. R41805 and Rhizophagus irregularis MUCL 41833 may play a part in the activation of plant defence system via ERF3. The proteomic analysis by 2-DE study has shown that priming by Pseudomonas sp. R41805 can induce the expression of proteins related to photosynthesis and protein folding in in vitro potato plantlets. The metabolomics study has shown that the total glycoalkaloid (TGA) content of greenhouse-grown potato tubers following inoculation with Pseudomonas sp. R41805 did not exceed the acceptable safety limit (200 mg kg-1 FW). As a result of this study, a number of bacteria have been identified with commercial potential that may offer sustainable alternatives in both Andean and European agricultural settings.

Knowledge-based management systems for the police force

Knowledge-Based Management Systems enable new ways to process and analyse knowledge to gain better insights to solve a problem and aid in decision making. In the police force such systems provide a solution for enhancing operations and improving client administration in terms of knowledge management. The main objectives of every police officer is to ensure the security of life and property, promote lawfulness, and avert and distinguish wrongdoing. The administration of knowledge and information is an essential part of policing, and the police ought to be proactive in directing both explicit and implicit knowledge, whilst adding to their abilities in knowledge sharing. In this paper the potential for a knowledge based system for the Mauritius police was analysed, and recommendations were also made, based on requirements captured from interviews with several long standing officers, and surveying of previous works in the area.

Quality Management

The purpose of this chapter is to enable registered health and social care prac - titioners to assume a clinical and/or a professional leadership role in quality management in the health and social care sectors. The contents in this chap - ter will strengthen the management competences of practitioners working in these sectors, including critical thinking, critical reflection, problem solving and decision -making, thus improving the quality in health and social care services.

Total Quality Management and Corporate Social Responsibility. Literature review. The case of Nabeiro Delta Cafés Group

The relationship between the themes of Total Quality Management (TQM) and Social Responsibility (CSR) through the concepts, approaches and models of excellence is a reality of sustainable and stable companies. Being organizations, people, act correctly and rightly do in society go through a quality management and social responsibility thereof. It is based on these two philosophies (Total Quality Management and Corporate Social Responsibility), which developed this literature review work, essentially based on a relational analysis in two papers, namely: "TQM and CSR Nexus" by Ghobadian et al. (2007) and "The Corporate Social Responsibility Audit Within the Quality Management Framework," de Kok et al. (2001) and applied to an organizational situation in concrete: the Nabeiro Delta Cafés Group - SGPS, SA.

AgroDB - integration of database management systems with crop models.

2016

Physical soil attributes of Conilon coffee (Coffea canephora) under organic and conventional management systems.

Coffea sp. is cultivated in large areas, using both conventional and organic management. However, information about the sustainability of these two management systems is still deficient. The objective of the present study was to evaluate the physical properties of soil cultivated with Conilon coffee (C. canephora) under organic and conventional management. Two areas cultivated with Conilon coffee (under organic and conventional management) and a fragment of Atlantic forest, used as a reference, were selected for the experiment. Soil granulometry, hydraulic conductivity, water retention curve, resistance to penetration, porosity, optimal hydric interval, and other physical characteristics were measured at depths of 0 to 10 and 10 to 20 cm. The data was submitted to multivariate and descriptive statistical analyses. Higher similarity was observed between the soil cultivated with Conilon coffee under organic management and the Atlantic forest soil. Soil resistance to penetration at 10, 30, 100, 500 and 1500 kPa, macro porosity, density and total porosity were the main physical properties that differentiated both management systems studied. The non-use of agricultural machinery and the addition of organic matter may be the main reasons for higher soil sustainability observed under organic management when compared with the conventional system.

Soil management systems for sustainable melon cropping in the Submedian of the São Francisco Valley.

Changes in soils management systems, including the application of green manure, are able to increase crop productivity. The aim of this study was to propose a soil management system with the use of green manure to improve the nutritional status and melon productivity in the submedian of the São Francisco Valley. The experiment was installed in Typic Plinthustalf and conducted in split plot. There were two soil tillage systems, tillage (T) and no tillage (NT), and three types of green manure (two vegetal cocktails: VC1- 75% legumes (L) + 25% non-legumes (NL); VC2- 25% L+ 75% NL and spontaneous vegetation (SV)). The experimental design was a randomised block with four replications. Fourteen species of legumes, grasses and oilseeds were used for the composition of the plant cocktails. We evaluated production of the dry shoot and root biomass and carbon and nutrient accumulation by green manures and melon plant. Data were subjected to analysis of variance and the treatment means were compared by Tukey´s test (P<0.05). Shoot biomass production and carbon and nutrient accumulation were higher in plant mixtures compared to spontaneous vegetation. The root system of the plant cocktails added larger quantities of biomass and nutrients to the soil to a depth of 0.60 m when compared to the spontaneous vegetation. The cultivation of plant cocktails with soil tillage, regardless of their composition, is a viable alternative for adding biomass and nutrients to the soil in melon crops in semi-arid conditions, providing productivity increases.

Land quality monitoring systems that integrate local and technical knowledge contribute to sustainability valuation in agricultural landscapes.

2008