Codeship: Financing growth: Case study and Teaching note

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics

Heterogeneous computing with an algorithmic skeleton framework

The Graphics Processing Unit (GPU) is present in almost every modern day personal computer. Despite its specific purpose design, they have been increasingly used for general computations with very good results. Hence, there is a growing effort from the community to seamlessly integrate this kind of devices in everyday computing. However, to fully exploit the potential of a system comprising GPUs and CPUs, these devices should be presented to the programmer as a single platform. The efficient combination of the power of CPU and GPU devices is highly dependent on each device’s characteristics, resulting in platform specific applications that cannot be ported to different systems. Also, the most efficient work balance among devices is highly dependable on the computations to be performed and respective data sizes. In this work, we propose a solution for heterogeneous environments based on the abstraction level provided by algorithmic skeletons. Our goal is to take full advantage of the power of all CPU and GPU devices present in a system, without the need for different kernel implementations nor explicit work-distribution.To that end, we extended Marrow, an algorithmic skeleton framework for multi-GPUs, to support CPU computations and efficiently balance the work-load between devices. Our approach is based on an offline training execution that identifies the ideal work balance and platform configurations for a given application and input data size. The evaluation of this work shows that the combination of CPU and GPU devices can significantly boost the performance of our benchmarks in the tested environments, when compared to GPU-only executions.

Interactive spatial decision support for sustainable agroforestry management: a case study in East Kalimantan, Indonesia

Forest managers, stakeholders and investors want to be able to evaluate economic, environmental and social benefits in order to improve the outcomes of their decisions and enhance sustainable forest management. This research developed a spatial decision support system that provides: (1) an approach to identify the most beneficial locations for agroforestry projects based on the biophysical properties and evaluate its economic, social and environmental impact; (2) a tool to inform prospective investors and stakeholders of the potential and opportunities for integrated agroforestry management; (3) a simulation environment that enables evaluation via a dashboard with the opportunity to perform interactive sensitivity analysis for key parameters of the project; (4) a 3D interactive geographic visualization of the economic, environmental and social outcomes, which facilitate understanding and eases planning. Although the tool and methodology presented are generic, a case study was performed in East Kalimantan, Indonesia. For the whole study area, it was simulated the most suitable location for three different plantation schemes: monoculture of timber, a specific recipe (cassava, banana and sugar palm) and different recipes per geographic unit. The results indicate that a mixed cropping plantation scheme, with different recipes applied to the most suitable location returns higher economic, environmental and social benefits.

Development of an integrative approach for the characterization of ecological risk on marine transition ecosystems: the Sado Estuary as a case study

Estuaries and other transitional waters are complex ecosystems critically important as nursery and shelter areas for organisms. Also, humans depend on estuaries for multiple socio-economical activities such as urbanism, tourism, heavy industry, (taking advantage of shipping), fisheries and aquaculture, the development of which led to strong historical pressures, with emphasis on pollution. The degradation of estuarine environmental quality implies ecologic, economic and social prejudice, hence the importance of evaluating environmental quality through the identification of stressors and impacts. The Sado Estuary (SW Portugal) holds the characteristics of industrialized estuaries, which results in multiple adverse impacts. Still, it has recently been considered moderately contaminated. In fact, many studies were conducted in the past few years, albeit scattered due to the absence of true biomonitoring programmes. As such, there is a need to integrate the information, in order to obtain a holistic perspective of the area able to assist management and decision-making. As such, a geographical information system (GIS) was created based on sediment contamination and biomarker data collected from a decade-long time-series of publications. Four impacted and a reference areas were identified, characterized by distinct sediment contamination patterns related to different hot spots and diffuse sources of toxicants. The potential risk of sediment-bound toxicants was determined by contrasting the levels of pollutants with available sediment quality guidelines, followed by their integration through the Sediment Quality guideline Quotient (SQG-Q). The SQG-Q estimates per toxicant or class was then subjected to georreferencing and statistical analyses between the five distinct areas and seasons. Biomarker responses were integrated through the Biomarkers Consistency Indice and georreferenced as well through GIS. Overall, in spite of the multiple biological traits surveyed, the biomarker data (from several organisms) are accordant with sediment contamination. The most impacted areas were the shipyard area and adjacent industrial belt, followed by urban and agricultural grounds. It is evident that the estuary, although globally moderately impacted, is very heterogeneous and affected by a cocktail of contaminants, especially metals and polycyclic aromatic hydrocarbon. Although elements (like copper, zinc and even arsenic) may originate from the geology of the hydrographic basin of the Sado River, the majority of the remaining contaminants results from human activities. The present work revealed that the estuary should be divided into distinct biogeographic units, in order to implement effective measures to safeguard environmental quality.

A new MDA-SOA based framework for intercloud interoperability

Cloud computing has been one of the most important topics in Information Technology which aims to assure scalable and reliable on-demand services over the Internet. The expansion of the application scope of cloud services would require cooperation between clouds from different providers that have heterogeneous functionalities. This collaboration between different cloud vendors can provide better Quality of Services (QoS) at the lower price. However, current cloud systems have been developed without concerns of seamless cloud interconnection, and actually they do not support intercloud interoperability to enable collaboration between cloud service providers. Hence, the PhD work is motivated to address interoperability issue between cloud providers as a challenging research objective. This thesis proposes a new framework which supports inter-cloud interoperability in a heterogeneous computing resource cloud environment with the goal of dispatching the workload to the most effective clouds available at runtime. Analysing different methodologies that have been applied to resolve various problem scenarios related to interoperability lead us to exploit Model Driven Architecture (MDA) and Service Oriented Architecture (SOA) methods as appropriate approaches for our inter-cloud framework. Moreover, since distributing the operations in a cloud-based environment is a nondeterministic polynomial time (NP-complete) problem, a Genetic Algorithm (GA) based job scheduler proposed as a part of interoperability framework, offering workload migration with the best performance at the least cost. A new Agent Based Simulation (ABS) approach is proposed to model the inter-cloud environment with three types of agents: Cloud Subscriber agent, Cloud Provider agent, and Job agent. The ABS model is proposed to evaluate the proposed framework.

Analysis of temporal and spatial variations of forest. A case of study in notheastern Armenia

The forest has a crucial ecological role and the continuous forest loss can cause colossal effects on the environment. As Armenia is one of the low forest covered countries in the world, this problem is more critical. Continuous forest disturbances mainly caused by illegal logging started from the early 1990s had a huge damage on the forest ecosystem by decreasing the forest productivity and making more areas vulnerable to erosion. Another aspect of the Armenian forest is the lack of continuous monitoring and absence of accurate estimation of the level of cuts in some years. In order to have insight about the forest and the disturbances in the long period of time we used Landsat TM/ETM + images. Google Earth Engine JavaScript API was used, which is an online tool enabling the access and analysis of a great amount of satellite imagery. To overcome the data availability problem caused by the gap in the Landsat series in 1988- 1998, extensive cloud cover in the study area and the missing scan lines, we used pixel based compositing for the temporal window of leaf on vegetation (June-late September). Subsequently, pixel based linear regression analyses were performed. Vegetation indices derived from the 10 biannual composites for the years 1984-2014 were used for trend analysis. In order to derive the disturbances only in forests, forest cover layer was aggregated and the original composites were masked. It has been found, that around 23% of forests were disturbed during the study period.

Agent-based parking occupancy simulation

The existing parking simulations, as most simulations, are intended to gain insights of a system or to make predictions. The knowledge they have provided has built up over the years, and several research works have devised detailed parking system models. This thesis work describes the use of an agent-based parking simulation in the context of a bigger parking system development. It focuses more on flexibility than on fidelity, showing the case where it is relevant for a parking simulation to consume dynamically changing GIS data from external, online sources and how to address this case. The simulation generates the parking occupancy information that sensing technologies should eventually produce and supplies it to the bigger parking system. It is built as a Java application based on the MASON toolkit and consumes GIS data from an ArcGis Server. The application context of the implemented parking simulation is a university campus with free, on-street parking places.

José Mourinho, The special one: A pedagogical case

The purpose of this work is to create a case to reflect about the leadership role of José Mourinho in Real Madrid CF, considering his successful background experiences in FC Porto, Chelsea FC and FC Inter. The case is based on the failure of the Special One in Real Madrid CF. This paper is mainly focused in the leadership process, charismatic leadership and contingency theory of leadership. Moreover it is intended to introduce concepts about the influence of leaders in the organizational culture, the management of human resources, and the role of a leader adapting to a different context.

Attractiveness of European masters under Bologna constraints: The South American case

This paper studies strategies to attract students from outside Europe to European preexperience masters. We characterize the value added by such masters through interviews with key players at the universities and multinational recruiting corporations. We considered a strategy for segmenting international students in the US and extended it to the European market. We have analyzed data from international applications to Nova SBE as a proxy for applications in European institutions. Based on that analysis we conclude with recommendations to attract suitable candidates from outside Europe. In particular we also provided three different solutions to attract students from the southern hemisphere: we conclude that European institutions should (a) increase the spring semester intake, (b) provide bridging courses for some students, or (c) could place some accepted candidates in internships before starting classes.

Foresight exercises as a tool for decision-making: the example of two case studies in health

Based on the report for the unit “Foresight Methods Analysis” of the PhD programme on Technology Assessment at the Universidade Nova de Lisboa, under the supervision of Prof. Dr. António B. Moniz

Zara: Marketing in Fast Fashion: A case-study

Zara was founded in 1975 by Amancio Ortega Gaona, soon becoming the largest and most successful chain of the Galician group Inditex (Industria de Diseño Textil) and a pioneer of the rising fashion category of Fast Fashion. Its innovative vertically-integrated strategies, combined with its emphasis on quality and demand-based offer have shaped the world of fashion and brought forth many questions on its future sustainability and growth. Zara has always relied on its store network for advertising its product offer; allowing its garments to “speak for themselves”. With the continued pressure felt in the industry, management has pressed some concerns about future company growth and creative, innovating solutions must be implemented to guarantee Zara’s future growth. The case-study narrative focuses on these issues and leaves readers with an open question regarding what decision to implement.

How can clusters help in the product type choice? The case of a specialized retail store

This work project (WP) is a study about a clustering strategy for Sport Zone. The general cluster study’s objective is to create groups such that within each group the individuals are similar to each other, but should be different among groups. The clusters creation is a mix of common sense, trial and error and some statistical supporting techniques. Our particular objective is to support category managers to better define the product type to be displayed in the stores’ shelves by doing store clusters. This research was carried out for Sport Zone, and comprises an objective definition, a literature review, the clustering activity itself, some factor analysis and a discriminant analysis to better frame our work. Together with this quantitative part, a survey addressed to category managers to better understand their key drivers, for choosing the type of product of each store, was carried out. Based in a non-random sample of 65 stores with data referring to 2013, the final result was the choice of 6 store clusters (Figure 1) which were individually characterized as the main outcome of this work. In what relates to our selected variables, all were important for the distinction between clusters, which proves the adequacy of their choice. The interpretation of the results gives category managers a tool to understand which products best fit the clustered stores. Furthermore, as a side finding thanks to the clusterization, a STP (Segmentation, Targeting and Positioning) was initiated, being this WP the first steps of a continuous process.

DYNAMOD – A dynamic agent based modelling framework for digital businesses

Digital Businesses have become a major driver for economic growth and have seen an explosion of new startups. At the same time, it also includes mature enterprises that have become global giants in a relatively short period of time. Digital Businesses have unique characteristics that make the running and management of a Digital Business much different from traditional offline businesses. Digital businesses respond to online users who are highly interconnected and networked. This enables a rapid flow of word of mouth, at a pace far greater than ever envisioned when dealing with traditional products and services. The relatively low cost of incremental user addition has led to a variety of innovation in pricing of digital products, including various forms of free and freemium pricing models. This thesis explores the unique characteristics and complexities of Digital Businesses and its implications on the design of Digital Business Models and Revenue Models. The thesis proposes an Agent Based Modeling Framework that can be used to develop Simulation Models that simulate the complex dynamics of Digital Businesses and the user interactions between users of a digital product. Such Simulation models can be used for a variety of purposes such as simple forecasting, analysing the impact of market disturbances, analysing the impact of changes in pricing models and optimising the pricing for maximum revenue generation or a balance between growth in usage and revenue generation. These models can be developed for a mature enterprise with a large historical record of user growth rate as well as for early stage enterprises without much historical data. Through three case studies, the thesis demonstrates the applicability of the Framework and its potential applications.

Towards an integrated technology management across the rail supply chain extended to society: building the case study on high-speed trains

The present paper was prepared for the course “Project III”, with the supervision of Prof. António Moniz, reporting on the author speaking notes at the Winter School on Technology Assessment, 6-7 December 2010, as part of the Doctoral Programme on Technology Assessment at FCT-UNL.

Knowledge management framework based on brain models and human physiology

The life of humans and most living beings depend on sensation and perception for the best assessment of the surrounding world. Sensorial organs acquire a variety of stimuli that are interpreted and integrated in our brain for immediate use or stored in memory for later recall. Among the reasoning aspects, a person has to decide what to do with available information. Emotions are classifiers of collected information, assigning a personal meaning to objects, events and individuals, making part of our own identity. Emotions play a decisive role in cognitive processes as reasoning, decision and memory by assigning relevance to collected information. The access to pervasive computing devices, empowered by the ability to sense and perceive the world, provides new forms of acquiring and integrating information. But prior to data assessment on its usefulness, systems must capture and ensure that data is properly managed for diverse possible goals. Portable and wearable devices are now able to gather and store information, from the environment and from our body, using cloud based services and Internet connections. Systems limitations in handling sensorial data, compared with our sensorial capabilities constitute an identified problem. Another problem is the lack of interoperability between humans and devices, as they do not properly understand human’s emotional states and human needs. Addressing those problems is a motivation for the present research work. The mission hereby assumed is to include sensorial and physiological data into a Framework that will be able to manage collected data towards human cognitive functions, supported by a new data model. By learning from selected human functional and behavioural models and reasoning over collected data, the Framework aims at providing evaluation on a person’s emotional state, for empowering human centric applications, along with the capability of storing episodic information on a person’s life with physiologic indicators on emotional states to be used by new generation applications.