Background: The reason for conducting this master thesis within the field of knowledge management derived from the realization that there was a need for an increased understanding of the socio-cultural dynamics of the integration and transfer of knowledge in cross-functional new product development projects. Research advocates that organizations with organic project-based environments with fluid team boundaries may aggravate routine-based work and organizational memory, which in turn may lead to an organizations’ inability of capturing and storing existing personalized knowledge for internal storage and future transfer (Koskinen, 2004). For this reason, the conversion of knowledge for re-use between and within projects in an organization is not supported in a natural way (Lindner and Wald, 2011). To this end, organizational culture is critically important in facilitating a knowledge transfer culture within an organization that supports such knowledge conversion processes (Davenport and Prusak, 1998a). Thus, an increased understanding of the socio-cultural dynamics of knowledge integration and transfer in cross-functional projects is viewed as an opportunity to contribute with findings with interest in both industry and academia. Increasing the understanding of organizational culture’s role in knowledge conversion facilitation is particularly seen as an important research area in existing knowledge management research. The study aimed to produce a deeper understanding of these social processes by exploring and interpreting them in their real-life social contexts. Research question: How does organizational culture and knowledge management strategies support as well as hinder knowledge integration and transfer between cross-functional product development teams and specialists in a project-based organization? Purpose: To increase the understanding of the socio-cultural dynamics of knowledge integration and transfer in cross-functional projects. In order to study the socio-cultural elements, a case study in a global Swedish company engaged in new product development was conducted during the spring of 2016. Method: The research design of the study was case study. The empirical data was collected through face-to-face interviews, observations and studying of internal steering documentations. The author found it necessary to adopt an interpretivist epistemological position with a qualitative focus in alignment with employing abductive reasoning in order to understand the collected data and to explore the posed research question. Quality measures with respect to qualitative research studies were cautiously considered. Conclusion: This study found that an organization with a network-based knowledge culture and a standardized process with standards and routines for effective knowledge conversion processes are two sides of the same coin that can support the knowledge integration and transfer between cross-functional product development teams and specialists in a project-based organization. Further, both a single dominant organizational culture and multiple local cultures within an organization can both support and hinder the integration and transfer of knowledge. In extension to this finding, inconsistencies in the knowledge integration and transfer processes may evolve across these different cultural interpretations which may further support or hinder the social dynamics in an organization. Moreover, my study suggests that a network-based knowledge culture can interact with a standardized process in order to enable effective knowledge integration and transfer routines.

When a network packet is formed by a computer's protocol stack, there are many components (e.g., Memory, CPU, etc.) of the computer that are involved in the process. The objective of this research is to identify, characterize and analyze the effects of the various components of a device (e.g., Memory, CPU, etc.) on the device's network traffic by measuring the changes in its network traffic with changes in its components. We also show how this characterization can be used to effectively perform counterfeit detection of devices which have counterfeit components (e.g., Memory, CPU, etc.). To obtain this characterization, we measure and apply statistical analyses like probability distribution fucntions (PDFs) on the interarrival times (IATs) of the device's network packets (e.g., ICMP, UDP, TCP, etc.). The device is then modified by changing just one component (e.g., Memory, CPU, etc.) at a time while holding the rest constant and acquiring the IATs again. This, over many such iterations provides an understanding of the effect of each component on the overall device IAT statistics. Such statistics are captured for devices (e.g., field-programmable gate arrays (FPGAs) and personal computers (PCs)) of different types. Some of these statistics remain stable across different IAT captures for the same device and differ for different devices (completely different devices or even the same device with its components changed). Hence, these statistical variations can be used to detect changes in a device's composition, which lends itself well to counterfeit detection. Counterfeit devices are abundant in today's world and cause billions of dollars of loss in revenue. Device components are substituted with inferior quality components or are replaced by lower capacity components. Armed with our understanding of the effects of various device components on the device's network traffic, we show how such substitutions or alterations of legitimate device components can be detected and hence perform effective counterfeit detection by statistically analyzing the deviation of the device's IATs from that of the original legitimate device. We perform such counterfeit detection experiments on various types of device configurations (e.g., PC with changed CPU, RAM, etc.) to prove the technique's efficacy. Since this technique is a fully network-based solution, it is also a non-destructive technique which can quickly, inexpensively and easily verify the device's legitimacy. This research also discusses the limitations of network-based counterfeit detection.

Guanxi plays an important role in Chinese entrepreneurial networking activities, especially for micro entrepreneurial firms in China. Due to limited information and resources available to micro firms, micro firms are more dependent on entrepreneurs’ guanxi networks to get access to the necessary resources. Previous literatures have particularly discussed the impacts of guanxi networks for foreigners successfully doing business in China. Nevertheless, there are scant literatures that study on the role of the guanxi in Chinese entrepreneurship. The purpose of this study is to provide a better understanding of the role of guanxi in Chinese entrepreneurship. This study employs the relevant guanxi concepts, Western social capital theory, and network-based entrepreneurship as the main conceptual framework to examine how Chinese entrepreneurs utilize their guanxi networks during the development of micro firms. Furthermore, this study is based on ten case studies in China. Empirical Data are collected from semi-structured interviews with ten Chinese entrepreneurs in micro firms. The results show that guanxi networks are highly important for Chinese entrepreneurs to develop their business. Firstly, Chinese entrepreneurs make use of different guanxi governance mechanisms--qinqing, renqing and jiaoqing to acquire different information and resources for the development of their firms. The obtained information and resources constitute the social capital, which can be used to complement insufficient capital within the firms. Secondly, Chinese entrepreneurs intentionally enlarge their guanxi network size to obtain more resources. Moreover, Chinese entrepreneurs benefit from strong guanxi ties and closure network structures to obtain the cohesive social capital. While Chinese entrepreneurs gain greater benefits from weak guanxi ties and spare network structures for acquiring additional information, resources and business opportunities. Thirdly, guanxi-networking activities are different from Western social networking activities, as guanxi-networking activities put more emphasize on keeping harmony and mutual reciprocity. Furthermore, Chinese entrepreneurs are proactive to build and maintain guanxi networks through various approaches for their business development. Lastly, even though guanxi networks play important roles in the development of micro entrepreneurial firms, they cannot be sustainable competitive advantage in the long term. Indeed, the core competences such as high quality of products and services, advanced technologies and marketing channels could be sustainable competitive advantages for the entrepreneurial firms in today’s increasingly fierce competitive market.

Interpersonal relationship and recommendation are the important relation and popular mechanism. Living in the information-overloading age, the original information searching mechanisms, which require the specification of keywords, are ineffective and impractical. Moreover, a variety of recommendation techniques have been proposed and many of them have been implemented in real systems, especially in online stores. Among different recommendation techniques proposed in the literature, the content-based and collaborative filtering approaches have been broadly adopted by membership stores that maintain users¡¦ long term interest. For short-term interest, by far the content-based approach is the most popular one for recommendation. However, most of the proposed recommendation approaches do not take the social information as an important factor. In this study, we proposed several social network-based recommendation approaches that take into account the similarities of items with respect to their social closeness for meeting users¡¦ short term interests. Our experiment evaluation results show that social network-based approaches perform better than the content-based counterpart, if the user¡¦s short term interest profile contains articles of similar content. Nonetheless, content-based approach becomes better when articles in the profile are diversified in their content. Besides, contrast to content-based approach, social network-based approach is less likely to recommend articles which readers do not value. Finally, the desired articles recommended by content-based approach are very different from those by social network-based approach. This suggests the development of some hybrid recommendation method that utilizes both content and social network when making recommendations.

Performance of neural network based restoration of optical networks is evaluated and a few possible improvements are proposed. Neural network based restoration is simulated with optical link capacities assigned by a new method. Two new improvement methods are developed to reduce the neural network size and the restoration time of severed optical connections. Cycle based restoration is suggested, which reduces the neural network structure by restoring the severed connections for each optical node, iteratively. Additionally, to reduce the restoration time, the necessary waiting time before the neuron outputs fire for the propagation delay over the network is computed and embedded in the control structure of the neural network. The improvement methods are evaluated by simulations in terms of restorability, restoration time, network redundancy and average length of restoration paths for different failure cases and different security requirements.

Living in an information-overloading age, the original information searching mechanisms are ineffective and impractical. As the e-commerce is more and more popular, using information technology to discover the latent demand of customers becomes an important issue. Hence, a variety of recommendation techniques have been proposed and many of them have been implemented in real systems, mostly in online stores. Among the techniques, the content-based and collaborative filtering approaches are the ones broadly adopted and proved to be successful. Recently, social network-based recommendation approach has been proposed that takes into account the similarities of items with respect to their social closeness. The social network-based approach performs better than content-based approach in some scenarios and it can also avoid recommending articles that have high content similarity to a user¡¦s favorite articles but low quality. Therefore, we propose three hybrid approaches, Switching, Proportional, and Fusion that combine content-based and social network-based approaches in order to achieve a better performance. Our experimental result shows that even though the proposed approaches have pros and cons under different scenarios, in general they achieve better performance than individual approaches. Besides, we generate some synthetic articles that have close content similarities to articles in our collection to evaluate the fidelity of each approach. The experimental results show that approaches incorporating social network information have lower chance to recommend these faked articles.

Buffer overflow vulnerabilities continue to prevail and the sophistication of attacks targeting these vulnerabilities is continuously increasing. As a successful attack of this type has the potential to completely compromise the integrity of the targeted host, early detection is vital. This thesis examines generic approaches for detecting executable payload attacks, without prior knowledge of the implementation of the attack, in such a way that new and previously unseen attacks are detectable. Executable payloads are analysed in detail for attacks targeting the Linux and Windows operating systems executing on an Intel IA-32 architecture. The execution flow of attack payloads are analysed and a generic model of execution is examined. A novel classification scheme for executable attack payloads is presented which allows for characterisation of executable payloads and facilitates vulnerability and threat assessments, and intrusion detection capability assessments for intrusion detection systems. An intrusion detection capability assessment may be utilised to determine whether or not a deployed system is able to detect a specific attack and to identify requirements for intrusion detection functionality for the development of new detection methods. Two novel detection methods are presented capable of detecting new and previously unseen executable attack payloads. The detection methods are capable of identifying and enumerating the executable payload’s interactions with the operating system on the targeted host at the time of compromise. The detection methods are further validated using real world data including executable payload attacks.

<p>System integration, interoperability, just in time delivery, window of opportunity, and dust-to-dust optimization are all keywords of our computerized future. Survivability is an important concept that together with dependability and quality of service are key issues in the systems of the future, i.e. infrastructural systems, business applications, and everyday desktop applications. The importance of dependable systems and the widely spread usage of dependable system together with the complexity of those systems makes middleware and frameworks for survivability imperative to the system builder of the future. This thesis presents a simulation approach to investigate the effect on data survival when the defending system uses knowledge of the current situation to protect the data. The results show the importance of situation awareness to avoid wasting recourses. A number of characteristics of the situational information provided and how this information may be used to optimize the system.</p>

Thesis (MSc)--Stellenbosch University, 2014. / ENGLISH ABSTRACT: This thesis explores the use of networks as a means to visualise, interpret and mine MS-based proteomics data. A network-based approach was applied to a quantitative, cross-species LCMS/ MS dataset derived from two yeast species, namely Saccharomyces cere- visiae strain VIN13 and Saccharomyces paradoxus strain RO88. In order to identify and quantify proteins from the mass spectra, a workflow consisting of both custom-built and existing programs was assembled. Networks which place the identifed proteins in several biological contexts were then constructed. The contexts included sequence similarity to other proteins, ontological descriptions, proteins-protein interactions, metabolic pathways and cellular location. The contextual, network-based representations of the proteins proved effective for identifying trends and patterns in the data that may otherwise have been obscured. Moreover, by bringing the experimentally derived data together with multiple, extant biological resources, the networks represented the data in a manner that better represents the interconnected biological system from which the samples were derived. Both existing and new hypotheses based on proteins relating to the yeast cell wall and proteins of putative oenological potential were investigated. These proteins were investigated in light of their differential expression between the two yeast species. Examples of proteins that were investigated included cell wall proteins such as GGP1 and SCW4. Proteins with putative oenological potential included haze protection factor proteins such as HPF2. Furthermore, differences in capacity for maloethanolic fermentation between the two strains were also investigated in light of the protein data. The network-based representations also allowed new hypotheses to be formed around proteins that were identified in the dataset, but were of unknown function. / AFRIKAANSE OPSOMMING: Hierdie studie verken die gebruik van netwerke om proteonomiese data te visualiseer, te interpreteer en te ontgin. 'n Netwerkgebaseerde benadering is gevolg ter ontleding van 'n kwantitatiewe LC-MS/MS datastel wat afkomstig was van twee gis-spesies nl, Saccharomyces cerevisiae ras VIN1 en Saccharomyces paradoxus ras RO88. Die massaspektra is met bestaande en selfgeskrewe rekenaarprogramme verwerk om 'n werkvloei saam te stel ter identifisering en kwantifisering van die betrokke proteïene. Hierdie proteïene is dan aan bestaande biologiese databasisse gekoppel om die proteïene in biologiese konteks te plaas. Die gekontekstualiseerde is dan gebruik om biologiese netwerke van die data te bou. Die kontekste beskou onder meer lokalisering van selaktiwiteite, ontologiese beskrywings, ooreenkomste in aminosuur-volgordes en interaksies met bekende proteïene asook assosiasie en verbintenisse met metaboliese paaie. Hierdie kontekstuele, netwerk-gebaseerde voorstelling van die betrokke prote- ïene het effektief duidelike data-tendense en patrone opgelewer wat andersins nie opmerkbaar sou wees nie. Daarby het die kombinering van eksperimentele data en bestaande biologiese bronne 'n beter perspektief aan die data-analise verleen. Beide bestaande en nuwe hipoteses tov gis-selwandproteïene en prote ïene met moontlike wynkundige potensiaal is ondersoek in die lig van hul differensiële uitdrukking in die twee gis-spesies. Voorbeelde wat ondersoek is sluit in selwandproteïene soos GGP1 en SCW4 asook waasbeskermingsfaktorproteïen HPF2. Verskille tov kapasiteit mbt malo-etanoliese gisting is ook gevind. Die netwerk-gebaseerde voorstellings het ook aanleiding gegee tot die formulering van nuwe hipoteses mbt datastel-proteïene waarvan die funksies tans onbekend is.

220 f. / Submitted by Suelen Reis (suziy.ellen@gmail.com) on 2013-04-29T14:08:17Z No. of bitstreams: 1 Clarissa Braga.pdf: 830557 bytes, checksum: 3d0ca4aced5d0c4298844a1738cbdd2a (MD5) / Approved for entry into archive by Maria Auxiliadora Lopes(silopes@ufba.br) on 2013-06-11T13:41:26Z (GMT) No. of bitstreams: 1 Clarissa Braga.pdf: 830557 bytes, checksum: 3d0ca4aced5d0c4298844a1738cbdd2a (MD5) / Made available in DSpace on 2013-06-11T13:41:26Z (GMT). No. of bitstreams: 1 Clarissa Braga.pdf: 830557 bytes, checksum: 3d0ca4aced5d0c4298844a1738cbdd2a (MD5) Previous issue date: 2006 / As possibilidades educativas dos ambientes informais de aprendizagem da rede, quando aplicadas aos ambientes formais de aprendizagem, geram uma dicotomia entre o discurso e a prática pedagógica. Esta é a tese desenvolvida nos capítulos a seguir. As formas de interação em rede, de acesso ao conhecimento e as possibilidades de trocas de informação entre os internautas em um ambiente virtual informal sofrem alterações quando há a formalização dos cursos. Isto porque, o currículo traz condicionantes de tempo (carga horária, necessidade de avaliação em determinados períodos) e espaço (ambiente virtual do curso restrito aos inscritos, ferramentas de interação com moderadores) que irão impactar na sociabilidade do ambiente virtual formal. Para o desenvolvimento desta tese, foram analisadas três experiências pioneiras de utilização da rede nem um contexto educativo. A estratégia de análise foi a comparação entre o discurso e a prática pedagógica destas três experiências. A metodologia utilizada foi a abordagem dialética e a pesquisa de campo foi feita através de entrevistas com autores e executores dos cursos analisados. / Salvador