907 resultados para Automated Cryptanalysis


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Machines are increasingly becoming a substitute for human skills and intelligence in a number of fields where decisions that are crucial to group performance have to be taken under stringent constraints—for example, when an army contingent has to devise battlefield tactics or when a medical team has to diagnose and treat a life-threatening condition or illness. We hypothesize a scenario where similar machine-based intelligent technology is available to support, and even substitute human decision making in an organizational leadership context. We do not engage in any metaphysical debate on the plausibility of such a scenario. Rather, we contend that given what we observe in several other fields of human decision making, such a scenario may very well eventuate in the near future. We argue a number of “positives” that can be expected to emerge out of automated group and organizational leadership decision making. We also posit several anti-theses—“negatives” that can also potentially emerge from the hypothesized scenario and critically consider their implications. We aim to bring leadership and organization theorists, as well as researchers in machine intelligence, together at the discussion table for the first time and postulate that while leadership decision making in a group/organizational context could be effectively delegated to an artificial-intelligence (AI)-based decision system, this would need to be subject to the devising of crucial safeguarding conditions.

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Service virtualisation is a supporting tool for DevOps to generate interactive service models of dependency systems on which a system-under-test relies. These service models allow applications under development to be continuously tested against production-like conditions. Generating these virtual service models requires expert knowledge of the service protocol, which may not always be available. However, service models may be generated automatically from network traces. Previous work has used the Needleman-Wunsch algorithm to select a response from the service model to play back for a live request. We propose an extension of the Needleman-Wunsch algorithm, which uses entropy analysis to automatically detect the critical matching fields for selecting a response. Empirical tests against four enterprise protocols demonstrate that entropy weighted matching can improve response accuracy.

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This demo introduces an automated collaborative requirements engineering tool, called TestMEReq, which is used to promote effective communication and collaboration between client-stakeholders and requirements engineers for better requirements validation. Our tool is augmented with real time communication and collaboration support to allow multiple stakeholders to collaboratively validate the same set of requirements. We have conducted a user study focusing on validating requirements using TestMEReq with a few groups of requirements engineers and client stakeholders. The study shows that our automated tool support is able to assist requirements engineers to effectively communicate with client-stakeholders to better validate the requirements virtually in real time. (Demo video: https://www.youtube.com/watch?v=7sWLOx-N4Jo).

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This dissertation describes the development of a label-free, electrochemical immunosensing platform integrated into a low-cost microfluidic system for the sensitive, selective and accurate detection of cortisol, a steroid hormone co-related with many physiological disorders. Abnormal levels of cortisol is indicative of conditions such as Cushing’s syndrome, Addison’s disease, adrenal insufficiencies and more recently post-traumatic stress disorder (PTSD). Electrochemical detection of immuno-complex formation is utilized for the sensitive detection of Cortisol using Anti-Cortisol antibodies immobilized on sensing electrodes. Electrochemical detection techniques such as cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS) have been utilized for the characterization and sensing of the label-free detection of Cortisol. The utilization of nanomaterial’s as the immobilizing matrix for Anti-cortisol antibodies that leads to improved sensor response has been explored. A hybrid nano-composite of Polyanaline-Ag/AgO film has been fabricated onto Au substrate using electrophoretic deposition for the preparation of electrochemical immunosening of cortisol. Using a conventional 3-electrode electrochemical cell, a linear sensing range of 1pM to 1µM at a sensitivity of 66µA/M and detection limit of 0.64pg/mL has been demonstrated for detection of cortisol. Alternately, a self-assembled monolayer (SAM) of dithiobis(succinimidylpropionte) (DTSP) has been fabricated for the modification of sensing electrode to immobilize with Anti-Cortisol antibodies. To increase the sensitivity at lower detection limit and to develop a point-of-care sensing platform, the DTSP-SAM has been fabricated on micromachined interdigitated microelectrodes (µIDE). Detection of cortisol is demonstrated at a sensitivity of 20.7µA/M and detection limit of 10pg/mL for a linear sensing range of 10pM to 200nM using the µIDE’s. A simple, low-cost microfluidic system is designed using low-temperature co-fired ceramics (LTCC) technology for the integration of the electrochemical cortisol immunosensor and automation of the immunoassay. For the first time, the non-specific adsorption of analyte on LTCC has been characterized for microfluidic applications. The design, fabrication technique and fluidic characterization of the immunoassay are presented. The DTSP-SAM based electrochemical immunosensor on µIDE is integrated into the LTCC microfluidic system and cortisol detection is achieved in the microfluidic system in a fully automated assay. The fully automated microfluidic immunosensor hold great promise for accurate, sensitive detection of cortisol in point-of-care applications.

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An automated signal quality assessment method was proposed for the EEG signals, which will help in testing new BCI algorithms so that the testing can be made on high quality signals only. This research includes the development of novel feature extraction technique and a new clustering algorithm for EEG signals.

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Social networks are often inferred from spatial associations, but other parameters like acoustic communication are likely to play a central role in within group interactions. However, it is currently difficult to determine which individual initiates vocalizations, or who responds to whom. To this aim, we designed a method that allows analyzing group vocal network while controlling for spatial networks, by positioning each group member in equidistant individual cages and analyzing continuous vocal interactions semi-automatically. We applied this method to two types of zebra finch groups, composed of either two adult females and two juveniles, or four young adults (juveniles from the first groups). Young often co-occur in the same social group as adults but are likely to have a different social role, which may be reflected in their vocal interactions. Therefore, we tested the hypothesis that the social structure of the group influences the parameters of the group vocal network. We found that groups including juveniles presented periods with higher level of activity than groups composed of young adults. Using two types of analyses (Markov analysis and cross-correlation), we showed that juveniles as well as adults were more likely to respond to individuals of their own age-class (i.e. to call one after another, in terms of turn-taking, and within a short time-window, in terms of time delay). When juveniles turned into adulthood, they showed adult characteristics of vocal patterns. Together our results suggest that vocal behavior changes during ontogeny, and individuals are more strongly connected with individuals of the same age-class within acoustic networks.

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One of the main unresolved questions in science is how non-living matter became alive in a process known as abiognesis, which aims to explain how from a primordial soup scenario containing simple molecules, by following a ``bottom up'' approach, complex biomolecules emerged forming the first living system, known as a protocell. A protocell is defined by the interplay of three sub-systems which are considered requirements for life: information molecules, metabolism, and compartmentalization. This thesis investigates the role of compartmentalization during the emergence of life, and how simple membrane aggregates could evolve into entities that were able to develop ``life-like'' behaviours, and in particular how such evolution could happen without the presence of information molecules. Our ultimate objective is to create an autonomous evolvable system, and in order tp do so we will try to engineer life following a ``top-down'' approach, where an initial platform capable of evolving chemistry will be constructed, but the chemistry being dependent on the robotic adjunct, and how then this platform can be de-constructed in iterative operations until it is fully disconnected from the evolvable system, the system then being inherently autonomous. The first project of this thesis describes how the initial platform was designed and built. The platform was based on the model of a standard liquid handling robot, with the main difference with respect to other similar robots being that we used a 3D-printer in order to prototype the robot and build its main equipment, like a liquid dispensing system, tool movement mechanism, and washing procedures. The robot was able to mix different components and create populations of droplets in a Petri dish filled with aqueous phase. The Petri dish was then observed by a camera, which analysed the behaviours described by the droplets and fed this information back to the robot. Using this loop, the robot was then able to implement an evolutionary algorithm, where populations of droplets were evolved towards defined life-like behaviours. The second project of this thesis aimed to remove as many mechanical parts as possible from the robot while keeping the evolvable chemistry intact. In order to do so, we encapsulated the functionalities of the previous liquid handling robot into a single monolithic 3D-printed device. This device was able to mix different components, generate populations of droplets in an aqueous phase, and was also equipped with a camera in order to analyse the experiments. Moreover, because the full fabrication process of the devices happened in a 3D-printer, we were also able to alter its experimental arena by adding different obstacles where to evolve the droplets, enabling us to study how environmental changes can shape evolution. By doing so, we were able to embody evolutionary characteristics into our device, removing constraints from the physical platform, and taking one step forward to a possible autonomous evolvable system.

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The ability of agents and services to automatically locate and interact with unknown partners is a goal for both the semantic web and web services. This, \serendipitous interoperability", is hindered by the lack of an explicit means of describing what services (or agents) are able to do, that is, their capabilities. At present, informal descriptions of what services can do are found in \documentation" elements; or they are somehow encoded in operation names and signatures. We show, by ref- erence to existing service examples, how ambiguous and imprecise capa- bility descriptions hamper the attainment of automated interoperability goals in the open, global web environment. In this paper we propose a structured, machine readable description of capabilities, which may help to increase the recall and precision of service discovery mechanisms. Our capability description draws on previous work in capability and process modeling and allows the incorporation of external classi¯cation schemes. The capability description is presented as a conceptual meta model. The model supports conceptual queries and can be used as an extension to the DAML-S Service Pro¯le.

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The next phase envisioned for the World Wide Web is automated ad-hoc interaction between intelligent agents, web services, databases and semantic web enabled applications. Although at present this appears to be a distant objective, there are practical steps that can be taken to advance the vision. We propose an extension to classical conceptual models to allow the definition of application components in terms of public standards and explicit semantics, thus building into web-based applications, the foundation for shared understanding and interoperability. The use of external definitions and the need to store outsourced type information internally, brings to light the issue of object identity in a global environment, where object instances may be identified by multiple externally controlled identification schemes. We illustrate how traditional conceptual models may be augmented to recognise and deal with multiple identities.

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This research investigates the prevalence of sports-related terms among the Web sites of the world’s leading companies, the Fortune Global 500. An automated process copied about four gigabytes of textual data, around 70 million words, from their sites. The subsequent analysis revealed regional and industry differences in the distribution of sports-related terms, the popularity of tennis stars and few references to sports stars, especially in Asia.