Management Driven Hybrid Multicast Framework for Content Aware Networks

The need for better adaptation of networks to transported flows has led to research on new approaches such as content aware networks and network aware applications. In parallel, recent developments of multimedia and content oriented services and applications such as IPTV, video streaming, video on demand, and Internet TV reinforced interest in multicast technologies. IP multicast has not been widely deployed due to interdomain and QoS support problems; therefore, alternative solutions have been investigated. This article proposes a management driven hybrid multicast solution that is multi-domain and media oriented, and combines overlay multicast, IP multicast, and P2P. The architecture is developed in a content aware network and network aware application environment, based on light network virtualization. The multicast trees can be seen as parallel virtual content aware networks, spanning a single or multiple IP domains, customized to the type of content to be transported while fulfilling the quality of service requirements of the service provider.

A hybrid simulation framework to assess the impact of renewable generators on a distribution network

With an increasing number of small-scale renewable generator installations, distribution network planners are faced with new technical challenges (intermittent load flows, network imbalances…). Then again, these decentralized generators (DGs) present opportunities regarding savings on network infrastructure if installed at strategic locations. How can we consider both of these aspects when building decision tools for planning future distribution networks? This paper presents a simulation framework which combines two modeling techniques: agent-based modeling (ABM) and particle swarm optimization (PSO). ABM is used to represent the different system units of the network accurately and dynamically, simulating over short time-periods. PSO is then used to find the most economical configuration of DGs over longer periods of time. The infrastructure of the framework is introduced, presenting the two modeling techniques and their integration. A case study of Townsville, Australia, is then used to illustrate the platform implementation and the outputs of a simulation.

Study of a geo-multicast framework for efficient message dissemination at unmanned level crossings

Collisions among trains and cars at road/rail level crossings (LXs) can have severe consequences such as high level of fatalities, injuries and significant financial losses. As communication and positioning technologies have significantly advanced, implementing vehicular ad hoc networks (VANETs) in the vicinity of unmanned LXs, generally LXs without barriers, is seen as an efficient and effective approach to mitigate or even eliminate collisions without imposing huge infrastructure costs. VANETs necessitate unique communication strategies, in which routing protocols take a prominent part in their scalability and overall performance, through finding optimised routes quickly and with low bandwidth overheads. This article studies a novel geo-multicast framework that incorporates a set of models for communication, message flow and geo-determination of endangered vehicles with a reliable receiver-based geo-multicast protocol to support cooperative level crossings (CLXs), which provide collision warnings to the endangered motorists facing road/rail LXs without barriers. This framework is designed and studied as part of a $5.5 m Government and industry funded project, entitled 'Intelligent-Transport-Systems to improve safety at road/rail crossings'. Combined simulation and experimental studies of the proposed geo-multicast framework have demonstrated promising outcomes as cooperative awareness messages provide actionable critical information to endangered drivers who are identified by CLXs.

A hybrid-parallel framework for the nonlinear seismic analysis of very tall buildings

FRAME3D, a program for the nonlinear seismic analysis of steel structures, has previously been used to study the collapse mechanisms of steel buildings up to 20 stories tall. The present thesis is inspired by the need to conduct similar analysis for much taller structures. It improves FRAME3D in two primary ways.

First, FRAME3D is revised to address specific nonlinear situations involving large displacement/rotation increments, the backup-subdivide algorithm, element failure, and extremely narrow joint hysteresis. The revisions result in superior convergence capabilities when modeling earthquake-induced collapse. The material model of a steel fiber is also modified to allow for post-rupture compressive strength.

Second, a parallel FRAME3D (PFRAME3D) is developed. The serial code is optimized and then parallelized. A distributed-memory divide-and-conquer approach is used for both the global direct solver and element-state updates. The result is an implicit finite-element hybrid-parallel program that takes advantage of the narrow-band nature of very tall buildings and uses nearest-neighbor-only communication patterns.

Using three structures of varied sized, PFRAME3D is shown to compute reproducible results that agree with that of the optimized 1-core version (displacement time-history response root-mean-squared errors are ~〖10〗^(-5) m) with much less wall time (e.g., a dynamic time-history collapse simulation of a 60-story building is computed in 5.69 hrs with 128 cores—a speedup of 14.7 vs. the optimized 1-core version). The maximum speedups attained are shown to increase with building height (as the total number of cores used also increases), and the parallel framework can be expected to be suitable for buildings taller than the ones presented here.

PFRAME3D is used to analyze a hypothetical 60-story steel moment-frame tube building (fundamental period of 6.16 sec) designed according to the 1994 Uniform Building Code. Dynamic pushover and time-history analyses are conducted. Multi-story shear-band collapse mechanisms are observed around mid-height of the building. The use of closely-spaced columns and deep beams is found to contribute to the building's “somewhat brittle” behavior (ductility ratio ~2.0). Overall building strength is observed to be sensitive to whether a model is fracture-capable.

Proposing a hybrid-intelligent framework to secure e-government web applications

One of the essential needs to implement a successful e-Government web application is security. Web application firewalls (WAF) are the most important tool to secure web applications against the increasing number of web application attacks nowadays. WAFs work in different modes depending on the web traffic filtering approach used, such as positive security mode, negative security mode, session-based mode, or mixed modes. The proposed WAF, which is called (HiWAF), is a web application firewall that works in three modes: positive, negative and session based security modes. The new approach that distinguishes this WAF among other WAFs is that it utilizes the concepts of Artificial Intelligence (AI) instead of regular expressions or other traditional pattern matching techniques as its filtering engine. Both artificial neural networks and fuzzy logic concepts will be used to implement a hybrid intelligent web application firewall that works in three security modes.

Deployment of a Hybrid Multicast Switch in Energy-Aware Data Center Network: A Case of Fat-Tree Topology

Recently, energy efficiency or green IT has become a hot issue for many IT infrastructures as they attempt to utilize energy-efficient strategies in their enterprise IT systems in order to minimize operational costs. Networking devices are shared resources connecting important IT infrastructures, especially in a data center network they are always operated 24/7 which consume a huge amount of energy, and it has been obviously shown that this energy consumption is largely independent of the traffic through the devices. As a result, power consumption in networking devices is becoming more and more a critical problem, which is of interest for both research community and general public. Multicast benefits group communications in saving link bandwidth and improving application throughput, both of which are important for green data center. In this paper, we study the deployment strategy of multicast switches in hybrid mode in energy-aware data center network: a case of famous fat-tree topology. The objective is to find the best location to deploy multicast switch not only to achieve optimal bandwidth utilization but also to minimize power consumption. We show that it is possible to easily achieve nearly 50% of energy consumption after applying our proposed algorithm.

Coordination polymers and hybrid networks of different dimensionalities formed by metal sulfites

In our effort to explore the use of the sulfite ion to design hybrid and open-framework materials, we have been able to prepare, under hydrothermal conditions, zero-dimensional [Zn(C12H8N2)(SO3)]center dot 2H(2)O, I (a = 7.5737(5) angstrom, b = 10.3969(6) angstrom, c = 10.3986(6) angstrom, alpha = 64.172(1)degrees, beta = 69.395(1)degrees, gamma = 79.333(1)degrees, Z = 2, and space group P (1) over bar), one-dimensional [Zn-2(C12H8N2)(SO3)(2)(H2O)], II (a = 8.0247(3) angstrom, b = 9.4962(3) angstrom, c = 10.2740(2) A, alpha = 81.070(1)degrees, beta = 80.438(1)degrees, gamma = 75.66(5)degrees, Z = 2, and space group P (1) over bar), two-dimensional [Zn-2(C10H8N2)(SO3)(2)]center dot H2O, III (a = 16.6062(1) angstrom, b = 4.7935(1) angstrom, c = 19.2721(5) angstrom, beta = 100.674(2)degrees, Z = 4, and space group C2/c), and three-dimensional [Zn-4(C6H12N2)(SO3)(4)(H2O)(4)], IV (a = 11.0793(3) angstrom, c = 8.8246(3) angstrom, Z = 2, and space group P42nm), of which the last three are coordination polymers. A hybrid open-framework sulfite-sulfate of the composition [C2H10N2][Nd(SO3)(SO4)(H2O)](2), V (a = 9.0880(3) angstrom, b = 6.9429(2) angstrom, c = 13.0805(5) A, beta = 91.551(2)degrees, Z = 2, and space group P2(1)/c), with a layered structure containing metal-oxygen-metal bonds has also been described.

Synthesis, structure, transformation studies and catalytic properties of open-framework cadmium thiosulfate compounds

Five new thiosulfate based inorganic-organic hybrid open-framework compounds have been synthesized employing mild reaction conditions. Of the five compounds, [Na-2(H2O)(8)][Cd(C10H8N2)( S2O3)(2)]center dot 2H(2)O, I and [Cd-2(C10H8N2)(2)(HS2O3)(2)(S2O3)(2)][(C10H9N2)(2)(C10H8N2)(2)]center dot 8H(2)O, II have one-dimensional (1D) structures and [Cd(C10H8N2)(H2O)(2)(S2O3)]center dot 2H(2)O, III, [Cd-2(C10H8N2)(3)(S2O3)(2)], IV and [Cd-2(C10H8N2)(2.5)(S2O3)(2)], V have three- dimensional (3D) structures. The 1D structures are somewhat related, formed by the bonding between tetrahedral Cd centers (CdN2S2) and 4,4'-bipyridine (bpy) units. The inter-chain spaces are occupied by the hanging thiosulfate units in both the cases along with Na(H2O)(6) chains in I and free bpy units in II. The three 3D structures have one-dimensional cadmium thiosulfate chains linked by bpy units. Interpenetration has been observed in all the 3D structures. The 3D structures appear to be related and can be derived from fgs net. Transformation studies on the 1D compound, [Na-2(H2O)(8)][Cd(C10H8N2)(S2O3)(2)]center dot 2H(2)O, I, indicated a facile formation of [Cd(C10H8N2)(H2O)(2)(S2O3)]center dot 2H(2)O, III. Prolonged heating of I gave rise to a 3D cadmium sulfate phase, [Cd-2(C10H8N2)(2)(H2O)(3)(SO4)(2)]center dot 2H(2)O, VI. Compound VI has one-dimensional cadmium sulfate chains formed by six-membered rings connected by bpy units to form a 3D structure, which appears to resemble the topological arrangement of III. Transformation studies of III indicates the formation of IV and V, and at a higher temperature a new 3D cadmium sulfate, [Cd(C10H8N2)(SO4)], VII. Compound VII has a 4 x 4 grid cadmium sulfate layers pillared by bpy units. All the compounds were characterized by PXRD, TGA, IR and UV-visible studies. Preliminary studies on the possible use of the 3D compounds (III-VII) in heterogeneous cyanosilylation of imines appear to be promising.

Hybrid mathematical and informational modeling of beam-to-column connections

The analysis of steel and composite frames has traditionally been carried out by idealizing beam-to-column connections as either rigid or pinned. Although some advanced analysis methods have been proposed to account for semi-rigid connections, the performance of these methods strongly depends on the proper modeling of connection behavior. The primary challenge of modeling beam-to-column connections is their inelastic response and continuously varying stiffness, strength, and ductility. In this dissertation, two distinct approaches—mathematical models and informational models—are proposed to account for the complex hysteretic behavior of beam-to-column connections. The performance of the two approaches is examined and is then followed by a discussion of their merits and deficiencies. To capitalize on the merits of both mathematical and informational representations, a new approach, a hybrid modeling framework, is developed and demonstrated through modeling beam-to-column connections. Component-based modeling is a compromise spanning two extremes in the field of mathematical modeling: simplified global models and finite element models. In the component-based modeling of angle connections, the five critical components of excessive deformation are identified. Constitutive relationships of angles, column panel zones, and contact between angles and column flanges, are derived by using only material and geometric properties and theoretical mechanics considerations. Those of slip and bolt hole ovalization are simplified by empirically-suggested mathematical representation and expert opinions. A mathematical model is then assembled as a macro-element by combining rigid bars and springs that represent the constitutive relationship of components. Lastly, the moment-rotation curves of the mathematical models are compared with those of experimental tests. In the case of a top-and-seat angle connection with double web angles, a pinched hysteretic response is predicted quite well by complete mechanical models, which take advantage of only material and geometric properties. On the other hand, to exhibit the highly pinched behavior of a top-and-seat angle connection without web angles, a mathematical model requires components of slip and bolt hole ovalization, which are more amenable to informational modeling. An alternative method is informational modeling, which constitutes a fundamental shift from mathematical equations to data that contain the required information about underlying mechanics. The information is extracted from observed data and stored in neural networks. Two different training data sets, analytically-generated and experimental data, are tested to examine the performance of informational models. Both informational models show acceptable agreement with the moment-rotation curves of the experiments. Adding a degradation parameter improves the informational models when modeling highly pinched hysteretic behavior. However, informational models cannot represent the contribution of individual components and therefore do not provide an insight into the underlying mechanics of components. In this study, a new hybrid modeling framework is proposed. In the hybrid framework, a conventional mathematical model is complemented by the informational methods. The basic premise of the proposed hybrid methodology is that not all features of system response are amenable to mathematical modeling, hence considering informational alternatives. This may be because (i) the underlying theory is not available or not sufficiently developed, or (ii) the existing theory is too complex and therefore not suitable for modeling within building frame analysis. The role of informational methods is to model aspects that the mathematical model leaves out. Autoprogressive algorithm and self-learning simulation extract the missing aspects from a system response. In a hybrid framework, experimental data is an integral part of modeling, rather than being used strictly for validation processes. The potential of the hybrid methodology is illustrated through modeling complex hysteretic behavior of beam-to-column connections. Mechanics-based components of deformation such as angles, flange-plates, and column panel zone, are idealized to a mathematical model by using a complete mechanical approach. Although the mathematical model represents envelope curves in terms of initial stiffness and yielding strength, it is not capable of capturing the pinching effects. Pinching is caused mainly by separation between angles and column flanges as well as slip between angles/flange-plates and beam flanges. These components of deformation are suitable for informational modeling. Finally, the moment-rotation curves of the hybrid models are validated with those of the experimental tests. The comparison shows that the hybrid models are capable of representing the highly pinched hysteretic behavior of beam-to-column connections. In addition, the developed hybrid model is successfully used to predict the behavior of a newly-designed connection.

Building knowledge capabilities : an organisational learning approach

The communal nature of knowledge production predicts the importance of creating learning organisations where knowledge arises out of processes that are personal, social, situated and active. It follows that workplaces must provide both formal and informal learning opportunities for interaction with ideas and among individuals. This grounded theory for developing contemporary learning organisations harvests insights from the knowledge management, systems sciences, and educational learning literatures. The resultant hybrid theoretical framework informs practical application, as reported in a case study that harnesses the accelerated information exchange possibilities enabled through web 2.0 social networking and peer production technologies. Through complementary organisational processes, 'meaning making' is negotiated in formal face-to-face meetings supplemented by informal 'boundary spanning' dialogue. The organisational capacity building potential of this participatory and inclusive approach is illustrated through the example of the Dr. Martin Luther King, Jr. Library in San Jose, California, USA. As an outcome of the strategic planning process at this joint city-university library, communication, decision-making, and planning structures, processes, and systems were re-invented. An enterprise- level redesign is presented, which fosters contextualising information interactions for knowledge sharing and community building. Knowledge management within this context envisions organisations as communities where knowledge, identity, and learning are situated. This framework acknowledges the social context of learning - i.e., that knowledge is acquired and understood through action, interaction, and sharing with others. It follows that social networks provide peer-to-peer enculturation through intentional exchange of tacit information made explicit. This, in turn, enables a dynamic process experienced as a continuous spiral that perpetually elevates collective understanding and enables knowledge creation.

Dressing up Tinderella: Interrogating authenticity claims on the mobile dating app Tinder

Mobile dating applications (‘apps’) have increased in popularity over recent years, with Tinder among the first to break into the mainstream heterosexual market. Since mobile dating intensifies the need to confirm that potential dates are not misrepresenting themselves and are safe to meet in person, Tinder’s success indicates that it has allayed these concerns regarding the authenticity of its users. This article combines Giddens’ conceptualization of authenticity, as the ability to reference a coherent biographical narrative, with Callon’s sociology of translation to investigate Tinder’s framing of authenticity within mobile dating. Applying a walkthrough method that interrogates Tinder’s technological architecture, promotional materials, and related media, this hybrid theoretical framework is used to identify how Tinder configures an actor-network that establishes its app as the solution to users’ concerns, enrols individuals in using its features in authenticity claims, and popularizes Tinder’s framing across public discourse. This network of human and non-human actors frames authenticity as being established through one’s Facebook profile and adherence to normative standards relating to age, gender, ethnicity, and socioeconomic status. However, user discourses on other social media identify and challenge negative outcomes of this framing, with normativity fostering discrimination and Facebook verification failing to prevent abusive behavior. This case study of Tinder paves the way for future investigation into user responses to its framing. Further, it demonstrates the efficacy and broader applicability of this theoretical approach for identifying both human and technological influences on the construction of authenticity with digital media.

Modeling and optimization of extracellular polysaccharides production by Enterobacter A47

Polysaccharides are gaining increasing attention as potential environmental friendly and sustainable building blocks in many fields of the (bio)chemical industry. The microbial production of polysaccharides is envisioned as a promising path, since higher biomass growth rates are possible and therefore higher productivities may be achieved compared to vegetable or animal polysaccharides sources. This Ph.D. thesis focuses on the modeling and optimization of a particular microbial polysaccharide, namely the production of extracellular polysaccharides (EPS) by the bacterial strain Enterobacter A47. Enterobacter A47 was found to be a metabolically versatile organism in terms of its adaptability to complex media, notably capable of achieving high growth rates in media containing glycerol byproduct from the biodiesel industry. However, the industrial implementation of this production process is still hampered due to a largely unoptimized process. Kinetic rates from the bioreactor operation are heavily dependent on operational parameters such as temperature, pH, stirring and aeration rate. The increase of culture broth viscosity is a common feature of this culture and has a major impact on the overall performance. This fact complicates the mathematical modeling of the process, limiting the possibility to understand, control and optimize productivity. In order to tackle this difficulty, data-driven mathematical methodologies such as Artificial Neural Networks can be employed to incorporate additional process data to complement the known mathematical description of the fermentation kinetics. In this Ph.D. thesis, we have adopted such an hybrid modeling framework that enabled the incorporation of temperature, pH and viscosity effects on the fermentation kinetics in order to improve the dynamical modeling and optimization of the process. A model-based optimization method was implemented that enabled to design bioreactor optimal control strategies in the sense of EPS productivity maximization. It is also critical to understand EPS synthesis at the level of the bacterial metabolism, since the production of EPS is a tightly regulated process. Methods of pathway analysis provide a means to unravel the fundamental pathways and their controls in bioprocesses. In the present Ph.D. thesis, a novel methodology called Principal Elementary Mode Analysis (PEMA) was developed and implemented that enabled to identify which cellular fluxes are activated under different conditions of temperature and pH. It is shown that differences in these two parameters affect the chemical composition of EPS, hence they are critical for the regulation of the product synthesis. In future studies, the knowledge provided by PEMA could foster the development of metabolically meaningful control strategies that target the EPS sugar content and oder product quality parameters.

Hybridity in contemporary commercial organizations: implications for employee trust

This study advances the concept of organizational hybridity (OH). By doing so, it takes into account the individual level of analysis often neglected in organizational theory. More specifically, it aims to understand the implications of organizational hybridity for employees’ trust in contemporary commercial organizations. Informed and guided by current literature, this study argues that the current literature on organizational hybridity fails to adequately address the consequences of hybridity for employees' behaviour. The empirical study was conducted in 2014 using data collected via semi-structured interviews and document analysis. The study was based on a comparison of two case studies in Nigeria: Alter Securities Limited and Barak Petroleum Limited. A total of forty (40) interviews were conducted; twenty (20) from each organization. The data were analysed using thematic analysis. The main findings are that organizational hybridity in this study produced tensions that resulted in negative behavioural responses and employees’ distrust in the commercial hybrid organizations. However, employees’ identification with non-market orientated institutional logics such as family, philanthropic and religious logics is seen to facilitate their commitment, honesty, and trust in the organizations. Nevertheless, caution is required here as religious logics may also lead to an acceptance of unethical behaviour by employees. Overall, this study contributes to the literature on organizational hybridity by extending on Battilana and Lee’s (2014) framework, which highlights governance, leadership, organizational culture and intra-organizational relationships as core organizational attributes in the context of which issues may arise in commercial hybrid organizations. Furthermore, it addresses a gap in Besharov and Smith’s (2014) hybrid typology framework by providing an alternative line of argument focused on understanding how tensions manifest within commercial hybrid organizations. The key recommendations of this research underscore the need for commercial hybrid organizations to invest in mechanisms for improving employees’ trust so as to reap the benefits associated with trust. This could be achieved by involving employees in the decision-making process and clearly communicating the organizations’ values, so as to minimise the misinterpretation of the embodied institutional logics by employees.

Shadows : Re-visualising the shark. Developing a framework for hybrid photography in the illumination of nonhuman animal and ecological perspectives at Heron Island and Gladstone, Great Barrier Reef

This study investigated how and to what degree “hybrid photography”—the simultaneous use of indexical and fictional properties and strategies— innovates the representation of animals within animalcentric, ecocentric frameworks. Design theory structured this project’s Practice-led, Visual research methodology framework. Grounded theory processes articulated emerging categories of hybrid photography through systematically and comparatively treating animal photography works for reflexive analysis. Design theory then applied and clarified categories, developing practice that re-visualised shark perspectives as new ecological discourse. Shadows, a creative practice installation, realised a full-scale photographic investigation into shark and marine animal realities of a specific environment—Heron Island and Gladstone, Great Barrier Reef—facing ecological crisis from dredging and development at Gladstone Harbour. Works rendered and explored hybrid photography’s capacity for illuminating nonhuman animals, in particular, sharks, and comprise 65% of this project’s weighting. This exegetical paper offers a definition, strategies and evaluation of hybrid photography in unsettling animal perspectives as effective ecological discourse, and comprises 35%.

A Hybrid Queue-based Bayesian Network Framework for passenger facilitation modelling

This paper presents a novel framework for the modelling of passenger facilitation in a complex environment. The research is motivated by the challenges in the airport complex system, where there are multiple stakeholders, differing operational objectives and complex interactions and interdependencies between different parts of the airport system. Traditional methods for airport terminal modelling do not explicitly address the need for understanding causal relationships in a dynamic environment. Additionally, existing Bayesian Network (BN) models, which provide a means for capturing causal relationships, only present a static snapshot of a system. A method to integrate a BN complex systems model with stochastic queuing theory is developed based on the properties of the Poisson and Exponential distributions. The resultant Hybrid Queue-based Bayesian Network (HQBN) framework enables the simulation of arbitrary factors, their relationships, and their effects on passenger flow and vice versa. A case study implementation of the framework is demonstrated on the inbound passenger facilitation process at Brisbane International Airport. The predicted outputs of the model, in terms of cumulative passenger flow at intermediary and end points in the inbound process, are found to have an $R^2$ goodness of fit of 0.9994 and 0.9982 respectively over a 10 hour test period. The utility of the framework is demonstrated on a number of usage scenarios including real time monitoring and `what-if' analysis. This framework provides the ability to analyse and simulate a dynamic complex system, and can be applied to other socio-technical systems such as hospitals.