data transfer/storage requirements

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Safeguards Needed in Transfer of Patient Data

Safeguards Needed in Transfer of Patient Data

the privacy of the patient is further protected, be- cause the storage and transfer of patient information must meet security and confidentiality requirements specified by state and fede[r]

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Big data architecture evolution : 2014 and beyond

Big data architecture evolution : 2014 and beyond

Since our healthcare concern is already an established organization and using a complete Information System as standard MIS, at the time of the change to Big Data system, there will be a grave requirement to “Extract” current data, which is in the form of Master, Transactional, and Referential entities. The Big Data Architecture must categorize data transfer requirements and also deliver pointers within the Data Ingestion Strategy as to the level of “Transformation” (which should include data cleansing and storing garbage data for any future testing purposes) that will be required to store data in a format (Schemas suited to NoSQL indexing) that meets the requirements (data storage in HDFS – Hadoop Distributed File System and constraints of the target application to extract data using either Mahout or some other machine learning application, designed and developed).
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Research Data Storage, Sharing, and Transfer Options

Research Data Storage, Sharing, and Transfer Options

Principal investigators should establish a research data management system for their projects including procedures for storing “working data” collected during the conduct of the research. The PI should communicate these procedures to all group members. The procedures should ensure that the PI is able to access all data produced by the research group and must meet all applicable security requirements. Below is a list of options for the storage, sharing, and transfer of digital research data. A glossary of the terms used in the summary is located at the end of this document.
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Data storage, collaboration, backup, transfer and encryption

Data storage, collaboration, backup, transfer and encryption

• Encrypt data – especially when sensitive or transmitting and sharing • Know data retention policies that apply: funder, publisher, home. institution[r]

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OPTION TERMS AND CONDITIONS OF ELECTRONIC TENDER HELD BY RWE GAS STORAGE CZ, S.R.O. FOR YEARLY GAS STORAGE CAPACITY

OPTION TERMS AND CONDITIONS OF ELECTRONIC TENDER HELD BY RWE GAS STORAGE CZ, S.R.O. FOR YEARLY GAS STORAGE CAPACITY

The difference between amount of Fixed storage Capacity and amount of booked storage capacity is Non-fixed storage capacity for which the contractual fee specified in the Auction Parameters Table is applied. This fee will be invoiced as a one-time payment based on the invoice issued by the Storage Operator no later than 10 days from the date specified in the Auction Parameters Table with a maturity of 14 days.

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QoS Based Framework for Effective Web Services in Cloud Computing

QoS Based Framework for Effective Web Services in Cloud Computing

In general, there exist two different techniques for ac- cessing web services: using SOAP (Simple Object Ac- cess Protocol) and the REST (Representational State Transfer) approach. SOAP provides the mechanism that allows access to objects across the heterogeneous net- work. SOAP defines the XML-based information which can be used for exchanging ordered and typed informa- tion in a decentralized distributed environment between peers, including Web Services and UDDI registries that represent service brokers through which Providers adver- tise their services [16]. The Service Provider supplies a Service proxy to the Service Consumer. SOAP Request and SOAP Response are the ways through which SOAP files are bound to send request and get response. The route of Web Service invocation initiates, when the cli- ent-side proxy hush-up the user’s request (method call) into a SOAP message and sends it to the service, which extracts the call from the received message, and then executes the call to produce the relative results, wraps the results into a SOAP message, and sends it to the client. Upon receiving the message, the same proxy extracts the results and hands them over to the calling client applica- tion. The Service Consumer executes the request by call- ing an API function on the proxy. The service proxy, shown in Figure 8, finds a contract and a reference to the Service Provider in the registry. It then formats the re- quest message and executes the request on behalf of the consumer. The service proxy is a convenience entity for the Service Consumer. It is not mandatory; the Service Consumer developer could write the necessary software for accessing the service directly. The service proxy can enhance performance by caching remote references and data. When a proxy caches a remote reference, subse- quent service calls will not require additional registry calls. By storing service contracts locally, the consumer reduces the number of network hops required to execute the service. In addition, proxiescan improve performance by eliminating network calls altogetherby performing some functions locally.
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University of California Berkeley Davis Irvine Los Angeles Merced Riverside San Diego San Francisco Santa Barbara Santa Cruz. Answers for Transfers

University of California Berkeley Davis Irvine Los Angeles Merced Riverside San Diego San Francisco Santa Barbara Santa Cruz. Answers for Transfers

transfer applicants from any of the 103 par- ticipating California community colleges: Allan Hancock College, American River College, Antelope Valley College, Bakersfi eld College, Barstow College, Berkeley City Col- lege, Butte Community College, Cabrillo College, Cañada College, Cerritos College, Cerro Coso Community College, Chabot College, Chaffey Community College, Citrus College, City College of San Francisco, Col- lege of Alameda, College of Marin, College of San Mateo, College of the Canyons, Col- lege of the Desert, College of the Redwoods, College of the Sequoias, College of the Sis- kiyous, Columbia College, Contra Costa Community College, Copper Mountain College, Cosumnes River College, Cuesta College, Cuyamaca College, Cypress College, De Anza College, Diablo Valley College, East Los Angeles College, El Camino Community College, Evergreen Valley College, Feather River College, Folsom Lake College, Foothill College, Fresno City College, Fullerton Col- lege, Gavilan College, Glendale Community College, Golden West College, Grossmont College, Hartnell College, Imperial Valley College, Irvine Valley College, Lake Tahoe Community College, Laney College, Las Positas College, Lassen Community Col- lege, Los Angeles City College, Los Angeles Harbor College, Los Angeles Mission Col- lege, Los Angeles Pierce College, Los Angeles Trade-Technical College, Los Angeles Valley College, Los Medanos College, Mendocino College, Merced College, Merritt College, MiraCosta Community College, Mission College, Modesto Junior College, Monterey Peninsula College, Moorpark College, Mount San Antonio College, Mount San Jacinto Community College, Napa Valley College,
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Data migration from Operetta High Content Imaging System to Columbus Image Data Storage and Analysis System

Data migration from Operetta High Content Imaging System to Columbus Image Data Storage and Analysis System

Images acquired on the Operetta ® High Content Imaging System are stored as TIF files in the Operetta Database (ODA). The ODA also contains all image-related metadata as well as image analysis sequences and results that have been generated with the Harmony ® High Content Imaging and Analysis Software. There are two ways to migrate images and the associated metadata from the Harmony software to the Columbus™ Image Data Storage and Analysis System, either by using the Columbus Transfer function or via the export of images and metadata. Here, we provide detailed step-by-step instructions for both methods.
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REQUEST FOR PROPOSALS UPDATE AND CONVERSION TO WEB-BASED GEOGRAPHIC INFORMATION SYSTEM (GIS)

REQUEST FOR PROPOSALS UPDATE AND CONVERSION TO WEB-BASED GEOGRAPHIC INFORMATION SYSTEM (GIS)

Bixby implemented GIS in 2003; however, the System has not been updated much since then. Some data was compiled but never included in the final GIS. The Consultant is responsible for assessing the existing GIS and incorporating existing and new data as required by the City. It may be necessary to construct new layers and change exiting layers as part of updating the GIS.

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A Survey of Issues in Multimedia Databases

A Survey of Issues in Multimedia Databases

In the recent world everyone is dealing with multimedia everywhere. We have multimedia around us everywhere. Due to the evolution of information technology the importance of multimedia has enhanced. So, this is the reason that we have to structure the multimedia information in a structured order so that we may have information access whenever we require. The multimedia data is not protected from unauthorized access. So, to cater for these security issues possible measures should been taken e.g. Data Analysis, Storage Management and Data Integrity should be checked to see how much the data in multimedia database is secure. While doing Data Analysis, Meta data management has to be done in order to do pattern matching. For Storage Management, the issues to be handled are access criteria for multimedia data types, and special index development. Data integrity checking includes maintenance of data by sustaining data quality, controlling concurrency, and multimedia updates recovery.
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DOWNLOAD THE VCIA CONFERENCE APP!

DOWNLOAD THE VCIA CONFERENCE APP!

Self-Storage Customers Commercial Market Premium 100% Transfer Self-Storage Customers Premium 100% Transfer Self-Storage Captive Insurance Company Quota-share Reinsurance Commercial M[r]

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1965 11 #27 Part 2 pdf

1965 11 #27 Part 2 pdf

To satisfy these requirements, the system should include dynamic memory allocation, alternate forms of data structure, and a data management and transfer mechanism so that the same data [r]

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Cloud Storage: Key to Future of IT Infrastructure. Anil Vasudeva President & Chief Analyst

Cloud Storage: Key to Future of IT Infrastructure. Anil Vasudeva President & Chief Analyst

Customer/member data Transactional data from applications Application Logs Other Types of Event Data Network Monitoring/Network Traffic Online Retail Transactions Other Log Files Call Data Records Web Logs Text data from social media and online Search logs Trade/quote data Intelligence/defense data Multimedia (audio/video/images) Weather Smartmeter data Other (please specify)

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Survey on File Security Using Encryption Technique over Public Cloud Environment

Survey on File Security Using Encryption Technique over Public Cloud Environment

ABSTRACT: In the world of computing, security and privacy issues are a major concern and cloud computing is no exception to these issues. In this paper we outline a security protocol called as Security as a Service (SasS). We provide a mechanism for achieving maximum security by leveraging the capabilities of a processor called a cryptographic coprocessor. Further we enhance the security of the encrypted data by distributing the data within the cloud, i.e. we divide the user data into pieces called as chunks. SasS protocol gives the user a chance to define the security of their data, by leaving the option of dividing the data into chunks in the user's hand. Based on the user requirement data will be made into chunks. Each chunk after encryption will be stored in a separate database. In this way we provide the maximum security to a user data. To our best knowledge, for the first time security is offered as a service to the user.
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An Approach to Decision Support System Usage for Data Storage Configuration Variant Selection

An Approach to Decision Support System Usage for Data Storage Configuration Variant Selection

Abstract. Electronic record management systems (including archives and libraries) should meet a large set of requirements, which can be described by tangible and intangible criteria. If digital data storage is needed for a library/archive, its configuration should be clearly defined at preliminary development stages. Tangible criteria can be represented quantitatively, by specific values of certain parameters. Intangible ones (reflecting, for instance, non-functional requirements) should be described by expert estimates, since there are usually no quantitative values to describe them. The paper suggests an approach to data storage configuration selection using multi-criteria decision making (MCDM) support methods, based on MoReq requirements and hierarchical storage management concept. MCDM support technology used allows selecting optimal data storage configuration, meeting both tangible and intangible requirements, in every specific case.
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Solar Energy Systems

Solar Energy Systems

collectors. However, this is not possible in many designs because the collectors are usually mounted on the building’s roof, and the structure would not be capable of supporting the tank and its contents. Therefore, the second best location for the thermal storage tank is usually the building’s basement or another heated area, with protection against moisture and cold, as close as possible to any existing service water heating components and the point of ultimate use. Thermal storage tanks should not be located in areas where flammable materials are stored.

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A Survey on De-duplication of Distributed Cloud Storage by Improving Confidentiality, Integrity and Reliability

A Survey on De-duplication of Distributed Cloud Storage by Improving Confidentiality, Integrity and Reliability

reliability, especially in archival storage systems where data are critical and should be preserved over long time periods. This requires that the de-duplication storage systems provide reliability comparable to other high-available systems. Furthermore, the challenge for data privacy also arises as more and more sensitive data are being outsourced by users to cloud. Encryption mechanisms have usually been utilized to protect the confidentiality before outsourcing data into cloud. Most commercial storage service provider are reluctant to apply encryption over the data because it makes de-duplication impossible. The reason is that the traditional encryption mechanisms, including public key encryption and symmetric key encryption, require different users to encrypt their data with their own keys. As a result, identical data copies of different users will lead to different cipher texts. To solve the problems of confidentiality and de-duplication, the notion of convergent encryption [4] has been proposed and widely adopted to enforce data confidentiality while realizing de-duplication. However, these systems achieved confidentiality of outsourced data at the cost of decreased error resilience. Therefore, how to protect both confidentiality and reliability while achieving de- duplication in a cloud storage system is still a challenge.
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HIGH LEVEL COMPLIANCE REVIEW ELECTRONIC DATA STORAGE DEVICES

HIGH LEVEL COMPLIANCE REVIEW ELECTRONIC DATA STORAGE DEVICES

Further issues of concern to the reviewer were the extent to which information about relevant policy and required procedures for electronic data storage device contents disposal is accessible for Victoria Police employees and whether education and training efforts were sufficient to ensure employees are given the best possible opportunity to be familiar with the required standards and procedures. Lack of easy access to clear policy direction was evident from the observation that the policies and instructions relating to data disposal are contained in varying degrees of detail in a number of standards, policy and procedural documents. Also, documents containing significant information such as the Records Disposal Guide, are not referred to in the VPM. The lack of central leadership and coordination places the onus on local stations or areas of Victoria Police to locate and bring these documents together and develop local procedural documents. This was done well in some areas and not at all in others. This approach is inherently inefficient and results in duplication of effort without quality assurance.
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Industrial Energy Monitoring System based on the Internet of Things (IoT)

Industrial Energy Monitoring System based on the Internet of Things (IoT)

This IC provides the digital signal processing core for acquiring signals from voltage and current transducers and calculating various power quality parameters. It also provides the function to monitor the calculated parameters and cause an interrupt when a value crosses a preset threshold value. The reading from the IC conforms with IEC 61000-4-7 Class I and Class II specifications. The readings provided by the IC are active, reactive and apparent powers; power factor; total harmonic distortion and harmonics within the 2.8 kHz pass band in all phases. The IC incorporates second- order-sigma-delta Analog to Digital converters (ADCs) for high accuracy and contains a digital integrator on the phase and neutral current data paths. The harmonics engine that analyzes one phase at a time can analyze up to the 63rd harmonic and provides data for up to three harmonics. These values are updated at a rate of 8000 samples per second.
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An Adaptive Biomedical Data Managing Scheme Based on Blockchain Technique Ahmed Faeq Hussein 1, *, Abbas K. ALZubaidi 2,Qais Ahmed Habash1 ,and Mustafa Musa Jaber 3

An Adaptive Biomedical Data Managing Scheme Based on Blockchain Technique Ahmed Faeq Hussein 1, *, Abbas K. ALZubaidi 2,Qais Ahmed Habash1 ,and Mustafa Musa Jaber 3

In this study, a new scheme for managing a biomedical data is presented. Two blockchains are employed to improve the system security and increase the overall stability. Besides, the combining between various data types contributes to reduce the overall system costs and improve searching and processing time as well. Moreover, for the blockchains, the conformance proof can be well-defined and planned as an accord mechanism wherein authenticated blocks are constructed. With regards to the blockchains, public key encryption with keyword search is employed to put forward the records sharing protocol. After receiving hatches from the patient, authorisation of the physician is done to explore and access the desirable history biomedical records to enhance diagnosis. The acceptable obtained results indicate that the scheme is fast and good enough to use it within large hospitals where it has the ability to fit and work under dense payload environments.
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