170,177 research outputs found

    Text books untuk mata kuliah pemrograman web

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    .HTML.And.Web.Design.Tips.And.Techniques.Jan.2002.ISBN.0072228253.pd

    Machine Learning Playground

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    Machine learning is a science that “learns” about the data by finding unique patterns and relations in the data. There are a lot of libraries or tools available for processing machine learning datasets. You can upload your dataset in seconds and quickly start using these tools to get prediction results in a few minutes. However, generating an optimal model is a time consuming and tedious task. The tunable parameters (hyper-parameters) of any machine learning model may greatly affect the accuracy metrics. While most of the tools have models with default parameter setting to provide good results, they can often fail to provide optimal results for reallife datasets. This project will be to develop a GUI application where a user could upload a dataset and dynamically visualize accuracy results based on the selected algorithm and its hyperparameters

    SOAP Services with Clarens: Guide for Developers and Administrators

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    The Clarens application server enables secure, asynchronous SOAP services to run on a Grid cluster such as one of those of the TeraGrid. There is a Client, who wants to use the service and understands the application domain enough to form a reasonable service request; a Developer, who is a power-user of the TeraGrid, who understands both Clarens and the application domain, and creates and deploys a service on a TeraGrid head node; and there is a Root system administrator, who controls the Clarens installation and the cluster on which it runs. The purpose of this document is to provide all of the information a service developer needs to know in order to deploy a Clarens service, with information also provided for the system administrator of the Clarens installation. First we discuss how each of the three roles see the service

    CLICKTHROUGH MECHANISM FOR KEYWORD SEARCH IN MOBILES

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    Within our design, the customer collects and stores in your area the click through data to safeguard privacy, whereas heavy tasks for example concept extraction, training, and reranking are carried out in the PMSE server. Because of the need for location information in mobile search, PMSE classifies these concepts into content concepts and placement concepts. Additionally, users’ locations are utilized to supplement the place concepts in PMSE. We advise a customized mobile internet search engine that captures the users’ preferences by means of concepts by mining their click on data. The consumer preferences are organized within an ontology-based, multifaceted account, which are utilized to adapt a customized ranking function for rank adaptation of future search engine results. In line with the client-server model, we present an in depth architecture and style for implementation of PMSE. To characterize the variety from the concepts connected having a query as well as their relevance’s towards the user’s need; four entropies are brought to balance the weights between your content and placement facets. Experimental results reveal that PMSE considerably increases the precision evaluating towards the baseline. Furthermore, we address the privacy issue by restricting the data within the account uncovered towards the PMSE server with two privacy parameters. We prototype PMSE around the Android Os platform

    Securing library information system: Vulnerabilities and threats

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    Threats and vulnerabilities in computers and networks are common nowadays since computers are widely used by the public. The risks of computer threats and vulnerabilities are high since most computers are connected to the internet. Library Information Systems is also vulnerable to attack since it is a public access institution. Majority of users are naive when it comes to computer and network securities. Some breaches in Library Information System are intentional and some are unintentional. Risks analysis should be done to find the threats and risks in designing the Library Information System. Threats are made possible due to lack of proper procedures, software flaws and policies. The administrators should anticipate all the possible attacks and their mitigation techniques. In this paper, we will try to address various issues arise from this vulnerabilities and threats. We will also describe how we can reduce and overcome this vulnerabilities and threats

    UKC ANSAware Survival Guide (for Modula-3)

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    The ANSAware platform is a suite of libraries and tools which facilitate the building of distributed applications. The documentation with the release forms little more that a reference manual to the language and does not aid the first time user. This document provides a simple introduction to distributed systems concepts and, through the use of an example, demonstrates how to build applications with ANSAware

    Database of audio records

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    Diplomka a prakticky castDiplome with partical part

    Serverification of Molecular Modeling Applications: the Rosetta Online Server that Includes Everyone (ROSIE)

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    The Rosetta molecular modeling software package provides experimentally tested and rapidly evolving tools for the 3D structure prediction and high-resolution design of proteins, nucleic acids, and a growing number of non-natural polymers. Despite its free availability to academic users and improving documentation, use of Rosetta has largely remained confined to developers and their immediate collaborators due to the code's difficulty of use, the requirement for large computational resources, and the unavailability of servers for most of the Rosetta applications. Here, we present a unified web framework for Rosetta applications called ROSIE (Rosetta Online Server that Includes Everyone). ROSIE provides (a) a common user interface for Rosetta protocols, (b) a stable application programming interface for developers to add additional protocols, (c) a flexible back-end to allow leveraging of computer cluster resources shared by RosettaCommons member institutions, and (d) centralized administration by the RosettaCommons to ensure continuous maintenance. This paper describes the ROSIE server infrastructure, a step-by-step 'serverification' protocol for use by Rosetta developers, and the deployment of the first nine ROSIE applications by six separate developer teams: Docking, RNA de novo, ERRASER, Antibody, Sequence Tolerance, Supercharge, Beta peptide design, NCBB design, and VIP redesign. As illustrated by the number and diversity of these applications, ROSIE offers a general and speedy paradigm for serverification of Rosetta applications that incurs negligible cost to developers and lowers barriers to Rosetta use for the broader biological community. ROSIE is available at http://rosie.rosettacommons.org
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