173 research outputs found

    Artificial immune system agent model

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    The Artificial Immune Systems (AIS) is a biologically inspired techniques that emulates a natural system, in particular the vertebrate immune system, in order to develop computational tools for solving engineering problems.Immunity-based technique emerge as a new branch of artificial intelligence (AI).The human biological immune system has become the source of inspiration for developing intelligent problem-solving techniques.The powerful information processing capabilities of the human system, such as feature extraction, pattern extraction, learning, memory and its distributive nature provide rich metaphors for its artificial counterpart. Hence, the goal of this study is to develop an Artificial Immune System (AIS) model using agent approach for incremental learning.The main issue handled was how to integrate a multiagent system into an AIS application.This model proposed was simulated using cases for the performance measurement.The step by step activities performed in developing the agent based AIS model can be a guideline in developing an AIS application. Besides that, the simulation of the AIS model can be further enhanced to be used for teaching and learning purposes

    Domain-independent exception handling services that increase robustness in open multi-agent systems

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    Title from cover. "May 2000."Includes bibliographical references (p. 17-23).Mark Klein and Chrysanthos Dellarocas

    Injury By Algorithm: A Look Into Google\u27s Liability For Defamatory Autocompleted Search Suggestions

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    Google’s Autocomplete search feature has gained wide popularity as it allows users to perform search queries quickly by suggesting several search terms in real-time as users type a search request in the Google search bar. These generated suggestions change in an algorithmic manner with each additional letter that a user types into Google’s search bar while conducting a search. They are based in part upon predictions made from previous users’ searches as well as several other factors related to the popularity and volume of search queries. As a result, Google claims its lacks complete control over the Autocomplete search results and that it should not be held liable for the search results the algorithms generate while a user conducts a Google search. Google used this defense in several cases that surfaced globally after the search queries generated defamatory suggestions. Accordingly, as detailed in this Article, this point brings about troubling legal issues due to a lack of understanding who is actually responsible for the results generated by Google’s Autocomplete feature. Thus far, given the current state of Internet law, Google falls in a legal safe harbor in avoiding liability for defamatory suggestions. Nonetheless, a better legal framework must be established to determine Google’s true liability in generating defamatory search suggestions through its algorithmic based approach

    Proceedings of the 2nd International Workshop on Security in Mobile Multiagent Systems

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    This report contains the Proceedings of the Second Workshop on Security on Security of Mobile Multiagent Systems (SEMAS2002). The Workshop was held in Montreal, Canada as a satellite event to the 5th International Conference on Autonomous Agents in 2001. The far reaching influence of the Internet has resulted in an increased interest in agent technologies, which are poised to play a key role in the implementation of successful Internet and WWW-based applications in the future. While there is still considerable hype concerning agent technologies, there is also an increasing awareness of the problems involved. In particular, that these applications will not be successful unless security issues can be adequately handled. Although there is a large body of work on cryptographic techniques that provide basic building-blocks to solve specific security problems, relatively little work has been done in investigating security in the multiagent system context. Related problems are secure communication between agents, implementation of trust models/authentication procedures or even reflections of agents on security mechanisms. The introduction of mobile software agents significantly increases the risks involved in Internet and WWW-based applications. For example, if we allow agents to enter our hosts or private networks, we must offer the agents a platform so that they can execute correctly but at the same time ensure that they will not have deleterious effects on our hosts or any other agents / processes in our network. If we send out mobile agents, we should also be able to provide guarantees about specific aspects of their behaviour, i.e., we are not only interested in whether the agents carry out-out their intended task correctly. They must defend themselves against attacks initiated by other agents, and survive in potentially malicious environments. Agent technologies can also be used to support network security. For example in the context of intrusion detection, intelligent guardian agents may be used to analyse the behaviour of agents on a firewall or intelligent monitoring agents can be used to analyse the behaviour of agents migrating through a network. Part of the inspiration for such multi-agent systems comes from primitive animal behaviour, such as that of guardian ants protecting their hill or from biological immune systems

    Organ Transplantation Management

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    Organ transplantation is a widespread and effective technique to treat important diseases and can often make the difference between life and death of some patients. Given a donor, finding the best recipient for one of his organs means finding, in the shortest time possible, the patient in the waiting list that best represents the compromise between numerous constraints related to donor-recipient physical compatibility and logistical arrangements. Currently, this process is still done in a non-automated, non-coordinated way, often leading to a non-optimal choice of the eventual recipient. This project aims at easing the organ transplantation management by representing it into a multi-agent system and by completely delegating the operation of matchmaking to the agents in the system

    Suffolk Alumni Magazine, vol. 5, no. 3, 2010

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    https://dc.suffolk.edu/sam/1037/thumbnail.jp

    The Future of Reputation: Gossip, Rumor, and Privacy on the Internet

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    This is the complete text of Daniel J. Solove\u27s book, THE FUTURE OF REPUTATION: GOSSIP, RUMOR, AND PRIVACY ON THE INTERNET (Full Text) (Yale University Press, October 2007).Teeming with chatrooms, online discussion groups, and blogs, the Internet offers previously unimagined opportunities for personal expression and communication. But there\u27s a dark side to the story. A trail of information fragments about us is forever preserved on the Internet, instantly available in a Google search. A permanent chronicle of our private lives - often of dubious reliability and sometimes totally false - will follow us wherever we go, accessible to friends, strangers, dates, employers, neighbors, relatives, and anyone else who cares to look. This engrossing book, brimming with stories of gossip, slander, and rumor on the Internet, explores the profound implications of the online collision between free speech and privacy.Solove explores how the Internet is transforming gossip, the way we shame others, and our ability to protect our own reputations. Focusing on blogs, Internet communities, cyber mobs, and other current trends, he shows that, ironically, the unconstrained flow of information on the Internet may impede opportunities for self-development and freedom. Longstanding notions of privacy need review: unless we establish a balance among privacy, free speech, and anonymity, we may discover that the freedom of the Internet makes us less free

    Genetic determinants underlying rare diseases identified using next-generation sequencing technologies

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    Rare disorders affect less than one in 2000 individuals, placing a huge burden on individuals, families and the health care system. Gene discovery is the starting point in understanding the molecular mechanisms underlying these diseases. The advent of next-generation sequencing has accelerated discovery of disease-causing genetic variants and is showing numerous benefits for research and medicine. I describe the application of next-generation sequencing, namely LipidSeq™ ‒ a targeted resequencing panel for the identification of dyslipidemia-associated variants ‒ and whole-exome sequencing, to identify genetic determinants of several rare diseases. Utilization of next-generation sequencing plus associated bioinformatics led to the discovery of disease-associated variants for 71 patients with lipodystrophy, two with early-onset obesity, and families with brachydactyly, cerebral atrophy, microcephaly-ichthyosis, and widow’s peak syndrome. Understanding these variants and their contribution to disease can increase understanding of disease mechanisms and help with the development of therapeutic interventions in the future

    Clayborn v. Twitter

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    PETITION FOR EN BANC AND PANEL REHEARIN
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