997 resultados para JavaScript Framework
Resumo:
We formulate and interpret several multi-modal registration methods in the context of a unified statistical and information theoretic framework. A unified interpretation clarifies the implicit assumptions of each method yielding a better understanding of their relative strengths and weaknesses. Additionally, we discuss a generative statistical model from which we derive a novel analysis tool, the "auto-information function", as a means of assessing and exploiting the common spatial dependencies inherent in multi-modal imagery. We analytically derive useful properties of the "auto-information" as well as verify them empirically on multi-modal imagery. Among the useful aspects of the "auto-information function" is that it can be computed from imaging modalities independently and it allows one to decompose the search space of registration problems.
Resumo:
Framework titanium in Ti-silicalite-1 (TS-1) zeolite was selectively identified by its resonance Raman bands using ultraviolet (W) Raman spectroscopy. Raman spectra of the TS-1 and silicalite-1 zeolites were obtained and compared using continuous wave laser lines at 244, 325, and 488 nm as the excitation sources. It was only with the excitation at 244 nm that resonance enhanced Raman bands at 490, 530, and 1125 cm(-1) appeared exclusively for the TS-1 zeolite. Furthermore, these bands increased in intensity with the crystallization time of the TS-1 zeolite. The Raman bands at 490, 530, and 1125 cm(-1) are identified as the framework titanium species because they only appeared when the laser excites the charge-transfer transition of the framework titanium species in the TS-1. No resonance Raman enhancement was detected for the bands of silicalite-1 zeolite and for the band at 960 cm(-1) of TS-1 with any of the excitation sources ranging from the visible tb UV regions. This approach can be applicable for the identification of other transition metal ions substituted in the framework of a zeolite or any other molecular sieve.
Resumo:
2007
Resumo:
Malicious software (malware) have significantly increased in terms of number and effectiveness during the past years. Until 2006, such software were mostly used to disrupt network infrastructures or to show coders’ skills. Nowadays, malware constitute a very important source of economical profit, and are very difficult to detect. Thousands of novel variants are released every day, and modern obfuscation techniques are used to ensure that signature-based anti-malware systems are not able to detect such threats. This tendency has also appeared on mobile devices, with Android being the most targeted platform. To counteract this phenomenon, a lot of approaches have been developed by the scientific community that attempt to increase the resilience of anti-malware systems. Most of these approaches rely on machine learning, and have become very popular also in commercial applications. However, attackers are now knowledgeable about these systems, and have started preparing their countermeasures. This has lead to an arms race between attackers and developers. Novel systems are progressively built to tackle the attacks that get more and more sophisticated. For this reason, a necessity grows for the developers to anticipate the attackers’ moves. This means that defense systems should be built proactively, i.e., by introducing some security design principles in their development. The main goal of this work is showing that such proactive approach can be employed on a number of case studies. To do so, I adopted a global methodology that can be divided in two steps. First, understanding what are the vulnerabilities of current state-of-the-art systems (this anticipates the attacker’s moves). Then, developing novel systems that are robust to these attacks, or suggesting research guidelines with which current systems can be improved. This work presents two main case studies, concerning the detection of PDF and Android malware. The idea is showing that a proactive approach can be applied both on the X86 and mobile world. The contributions provided on this two case studies are multifolded. With respect to PDF files, I first develop novel attacks that can empirically and optimally evade current state-of-the-art detectors. Then, I propose possible solutions with which it is possible to increase the robustness of such detectors against known and novel attacks. With respect to the Android case study, I first show how current signature-based tools and academically developed systems are weak against empirical obfuscation attacks, which can be easily employed without particular knowledge of the targeted systems. Then, I examine a possible strategy to build a machine learning detector that is robust against both empirical obfuscation and optimal attacks. Finally, I will show how proactive approaches can be also employed to develop systems that are not aimed at detecting malware, such as mobile fingerprinting systems. In particular, I propose a methodology to build a powerful mobile fingerprinting system, and examine possible attacks with which users might be able to evade it, thus preserving their privacy. To provide the aforementioned contributions, I co-developed (with the cooperation of the researchers at PRALab and Ruhr-Universität Bochum) various systems: a library to perform optimal attacks against machine learning systems (AdversariaLib), a framework for automatically obfuscating Android applications, a system to the robust detection of Javascript malware inside PDF files (LuxOR), a robust machine learning system to the detection of Android malware, and a system to fingerprint mobile devices. I also contributed to develop Android PRAGuard, a dataset containing a lot of empirical obfuscation attacks against the Android platform. Finally, I entirely developed Slayer NEO, an evolution of a previous system to the detection of PDF malware. The results attained by using the aforementioned tools show that it is possible to proactively build systems that predict possible evasion attacks. This suggests that a proactive approach is crucial to build systems that provide concrete security against general and evasion attacks.
Resumo:
Purpose –The research examines the sales process practised by SMEs, and barriers and enablers that hinder and support effective selling practices from the selling organisation’s perspective in Scottish-based Food and Drink firms. Design/methodology approach - – The paper adopts an interpretivist perspective with qualitative data gathered through face-to-face semi-structured interviews. 20 people involved in selling activities were interviewed from 15 SMEs across Scotland. Thematic analysis established key findings regarding the sales process practice. Findings – Five themes emerged that affect the operationalisation of the selling process: the owner manager has considerable involvement in the sales process, SMEs with some degree of sales knowledge take a more systematic approach, SMEs lack awareness of how CRM technology can assist them, power is tipped in favour of the buyer and, the geographic location of the SME places constraints on how SMEs conduct business Research limitation/implication – Thematic analysis was chosen over other more traditional methods due to the lack of relevant quantitative data. The phenomenon of the research and research methodology means that it will not be possible to repeat this study and replicate its findings. However, the process that has been adopted does provide a basis for future research. Originality/value - The paper identifies areas where future research is required in the field alongside suggestions where policy makers and government business agencies might focus intervention to assist SMEs improve delivery of the sales process and selling effectiveness
Resumo:
The creative industries sector faces a constantly changing context characterised by the speed of the development and deployment of digital information systems and Information Communications Technologies (ICT) on a global scale. This continuous digital disruption has had significant impact on the whole value chain of the sector: creation and production; discovery and distribution; and consumption of cultural goods and services. As a result, creative enterprises must evolve business and operational models and practices to be sustainable. Enterprises of all scales, type, and operational model are affected, and all sectors face ongoing digital disruption. Management consultancy practitioners and business strategy academics have called for new strategy development frameworks and toolkits, fit for a continuously changing world. This thesis investigates a novel approach to organisational change appropriate to the digital age, in the context of the creative sector in Scotland. A set of concepts, methods, tools, and processes to generate theoretical learning and practical knowing was created to support enterprises to digitally adapt through undertaking journeys of change and organisational development. The framework is called The AmbITion Approach. It was developed by blending participatory action research (PAR) methods and modern management consultancy, design, and creative practices. Empirical work also introduced to the framework Coghlan and Rashford’s change categories. These enabled the definition and description of the extent to which organisations developed: whether they experienced first order (change), second order (adaptation) or third order (transformation) change. Digital research tools for inquiry were tested by a pilot study, and then embedded in a longitudinal study over two years of twentyone participant organisations from Scotland’s creative sector. The author applied and investigated the novel approach in a national digital development programme for Scotland’s creative industries. The programme was designed and delivered by the author and ran nationally between 2012-14. Detailed grounded thematic analysis of the data corpus was undertaken, along with analysis of rich media case studies produced by the organisations about their change journeys. The results of studies on participants, and validation criteria applied to the results, demonstrated that the framework triggers second (adaptation) and third order change (transformation) in creative industry enterprises. The AmbITion Approach framework is suitable for the continuing landscape of digital disruption within the creative sector. The thesis contributes to practice the concepts, methods, tools, and processes of The AmbITion Approach, which have been empirically tested in the field, and validated as a new framework for business transformation in a digital age. The thesis contributes to knowledge a theoretical and conceptual framework with a specific set of constructs and criteria that define first, second, and third order change in creative enterprises, and a robust research and action framework for the analysis of the quality, validity and change achieved by action research based development programmes. The thesis additionally contributes to the practice of research, adding to our understanding of the value of PAR and design thinking approaches and creative practices as methods for change.
Resumo:
R. Daly and Q. Shen. A Framework for the Scoring of Operators on the Search Space of Equivalence Classes of Bayesian Network Structures. Proceedings of the 2005 UK Workshop on Computational Intelligence, pages 67-74.
Resumo:
Oliver, A., Freixenet, J., Marti, R., Pont, J., Perez, E., Denton, E. R. E., Zwiggelaar, R. (2008). A novel breast tissue density classification framework. IEEE Transactions on Information Technology in BioMedicine, 12 (1), 55-65
Resumo:
We describe and evaluate options for providing anonymous IP service, argue for the further investigation of local anonymity, and sketch a framework for the implementation of locally anonymous networks.
Resumo:
An appearance-based framework for 3D hand shape classification and simultaneous camera viewpoint estimation is presented. Given an input image of a segmented hand, the most similar matches from a large database of synthetic hand images are retrieved. The ground truth labels of those matches, containing hand shape and camera viewpoint information, are returned by the system as estimates for the input image. Database retrieval is done hierarchically, by first quickly rejecting the vast majority of all database views, and then ranking the remaining candidates in order of similarity to the input. Four different similarity measures are employed, based on edge location, edge orientation, finger location and geometric moments.
Resumo:
We consider a mobile sensor network monitoring a spatio-temporal field. Given limited cache sizes at the sensor nodes, the goal is to develop a distributed cache management algorithm to efficiently answer queries with a known probability distribution over the spatial dimension. First, we propose a novel distributed information theoretic approach in which the nodes locally update their caches based on full knowledge of the space-time distribution of the monitored phenomenon. At each time instant, local decisions are made at the mobile nodes concerning which samples to keep and whether or not a new sample should be acquired at the current location. These decisions account for minimizing an entropic utility function that captures the average amount of uncertainty in queries given the probability distribution of query locations. Second, we propose a different correlation-based technique, which only requires knowledge of the second-order statistics, thus relaxing the stringent constraint of having a priori knowledge of the query distribution, while significantly reducing the computational overhead. It is shown that the proposed approaches considerably improve the average field estimation error by maintaining efficient cache content. It is further shown that the correlation-based technique is robust to model mismatch in case of imperfect knowledge of the underlying generative correlation structure.
Resumo:
The advent of virtualization and cloud computing technologies necessitates the development of effective mechanisms for the estimation and reservation of resources needed by content providers to deliver large numbers of video-on-demand (VOD) streams through the cloud. Unfortunately, capacity planning for the QoS-constrained delivery of a large number of VOD streams is inherently difficult as VBR encoding schemes exhibit significant bandwidth variability. In this paper, we present a novel resource management scheme to make such allocation decisions using a mixture of per-stream reservations and an aggregate reservation, shared across all streams to accommodate peak demands. The shared reservation provides capacity slack that enables statistical multiplexing of peak rates, while assuring analytically bounded frame-drop probabilities, which can be adjusted by trading off buffer space (and consequently delay) and bandwidth. Our two-tiered bandwidth allocation scheme enables the delivery of any set of streams with less bandwidth (or equivalently with higher link utilization) than state-of-the-art deterministic smoothing approaches. The algorithm underlying our proposed frame-work uses three per-stream parameters and is linear in the number of servers, making it particularly well suited for use in an on-line setting. We present results from extensive trace-driven simulations, which confirm the efficiency of our scheme especially for small buffer sizes and delay bounds, and which underscore the significant realizable bandwidth savings, typically yielding losses that are an order of magnitude or more below our analytically derived bounds.
Resumo:
NetSketch is a tool for the specification of constrained-flow applications and the certification of desirable safety properties imposed thereon. NetSketch is conceived to assist system integrators in two types of activities: modeling and design. As a modeling tool, it enables the abstraction of an existing system while retaining sufficient information about it to carry out future analysis of safety properties. As a design tool, NetSketch enables the exploration of alternative safe designs as well as the identification of minimal requirements for outsourced subsystems. NetSketch embodies a lightweight formal verification philosophy, whereby the power (but not the heavy machinery) of a rigorous formalism is made accessible to users via a friendly interface. NetSketch does so by exposing tradeoffs between exactness of analysis and scalability, and by combining traditional whole-system analysis with a more flexible compositional analysis. The compositional analysis is based on a strongly-typed Domain-Specific Language (DSL) for describing and reasoning about constrained-flow networks at various levels of sketchiness along with invariants that need to be enforced thereupon. In this paper, we define the formal system underlying the operation of NetSketch, in particular the DSL behind NetSketch's user-interface when used in "sketch mode", and prove its soundness relative to appropriately-defined notions of validity. In a companion paper [6], we overview NetSketch, highlight its salient features, and illustrate how it could be used in two applications: the management/shaping of traffic flows in a vehicular network (as a proxy for CPS applications) and in a streaming media network (as a proxy for Internet applications).