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비트 토렌트에서 건강한 피어 선택 기반의 파일 다운로드 속도 향상

비트 토렌트에서 건강한 피어 선택 기반의 파일 다운로드 속도 향상

Current Clinical Practice Patterns of Self-Identified Interventional Radiologists.

The purpose of this study was to assess patterns of procedural, clinical evaluation and management (E/M), and diagnostic imaging services rendered by self-identified interventional radiologists (IRs) across the United States. Recent Medicare Physician and Other Supplier Public Use and Physician Compare national downloadable files were linked. IRs were defined as physicians self-identifying interventional radiology as their primary specialty on Medicare claims or as a specialty during Medicare enrollment. The primary outcome measure was percentage of work (in work relative value units [WRVU]) attributed to interventional services (both procedural and E/M) per IR. Secondary outcome measures included sociodemographic factors per interventional WRVU quartile and percentage of E/M service units per IR. Statistical analysis included chi-square and t tests and logistic regression. Overall, 3132 physicians nationally self-identified to Medicare as IRs. The distribution of WRVU attributed to interventional services was strongly bimodal. Procedures and E/M together accounted for ≥ 91% and ≤ 5% of total work for the most and least intervention-oriented quartiles, respectively, but were widely distributed in the middle two quartiles. The most intervention-oriented self-identified IRs were more likely out of medical school ≤ 30 years (odds ratio [OR], 2.5; p < 0.0001), men (OR, 2.2; p < 0.0001), and in academic practice (OR, 4.3; p < 0.0001). E/M accounted for only 1.4% of all billed services. Although most self-identified IRs perform both interventional and diagnostic imaging services, the subspecialty distribution is strongly bimodal, one-quarter each focusing ≤ 5% and ≥ 91% of work on interventional services. Despite ongoing emphasis on clinically focused interventional radiology, E/M services remain rarely reported.

비트토렌트에서 파일 다운로드 가용성 보장을 위한 S-트래커 설계 및 구현

비트토렌트에서 파일 다운로드 가용성 보장을 위한 S-트래커 설계 및 구현

The Mycology Collections Portal (MyCoPortal)

The Mycology Collections Portal (MyCoPortal) was established in 2011 to offer a simple, economic solution for institutions worldwide to maintain and serve their fungal collection data online. Although the MyCoPortal functions primarily as a web portal for collections to upload their specimen metadata and images, it also provides data packaging (e.g. checklists), visualization (mapping and timelines), educational material (identification keys, quizzes) and easy access to DwC formatted data sets as downloadable csv files. The MyCoPortal currently serves over 3.6M records from 84 institutions worldwide.

Intersections of History, Media, and Culture

Intersections of History, Media, and Culture

Feedback-Based Online Network Coding

Current approaches to the practical implementation of network coding are batch-based, and often do not use feedback, except possibly to signal completion of a file download. In this paper, the various benefits of using feedback in a network coded system are studied. It is shown that network coding can be performed in a completely online manner, without the need for batches or generations, and that such online operation does not affect the throughput. Although these ideas are presented in a single-hop packet erasure broadcast setting, they naturally extend to more general lossy networks, which employ network coding in the presence of feedback. The impact of feedback on sender-side queue size and receiver-side decoding delay is studied in an asymptotic sense as the traffic load approaches capacity. Different notions of decoding delay are considered, including an order-sensitive notion, which assumes that packets are useful only when delivered in order. Strategies for adaptive coding based on feedback are presented. Our scheme achieves throughput optimality and asymptotically optimal sender queue size and is conjectured to achieve asymptotically optimal in-order delivery delay for any number of receivers. This paper may be viewed as a natural extension of Automatic Repeat reQuest to coded networks.

Optimized device centric aggregation mechanisms for mobile devices with multiple wireless interfaces

Wireless broadband technologies and services are witnessing exponential growth to meet the demands of mobile users. State-of-the-art wireless networks are evolving with enhancements spanning all protocol layers and all network components from radio access to core network nodes. This has been coupled with a tremendous transformation of end user mobile devices towards multi-purpose smartphones and tablets with multi-core processing power, extendable memory storage, large battery capacity, and support for a wide range of wireless connectivity options. A standard smartphone currently can support short range Bluetooth and WiFi-Direct connectivity, local area WiFi connectivity, and long range 2G/3G/4G mobile connectivity. This naturally provides opportunities for data aggregation utilizing multiple wireless interfaces simultaneously to enhance device and network performance. In this work, we present the design, implementation, and testing of optimized device-centric data aggregation mechanisms for both file downloading and video streaming applications. The main novelty of the proposed mechanisms is their device-centric design, which makes them practical and feasible without any changes to wireless standards; moreover, they are scalable to support any number of wireless interfaces whereas previous related work has dealt with devices having two interfaces only. To demonstrate the effectiveness of the proposed mechanisms in terms of performance gains and practical feasibility, we develop an experimental testbed using Android devices and perform extensive testing for several network scenarios.

The effect of complement inhibition on erythrocyte destruction in AIHA

To determine differences in the provision of Medicare services based on physician gender in the United States.Participants included all 2013 Medicare fee-for-service physicians and their patients, a population that is predominantly older than 65 years. The 2013 Medicare Provider Utilization and Payment Data for services rendered between January 1, 2013, and December 31, 2013, were combined with the 2015 Physician Compare National Downloadable files and 2015 Berenson-Eggers Type of Service classification files. Total fee-for-service Medicare payments and Healthcare Common Procedure Coding System procedure codes for all fee-for-service beneficiaries were aggregated according to physician gender, specialty, years since medical school graduation, and type of service classifications.Excluding drug reimbursement, the mean total Medicare payments per female physician, compared with those for male physicians, were 41% in surgical specialties, 72% in hospital-based specialties, and 55% across all specialties (P<.001). The mean overall number of unique beneficiary visits per female physician was 59% of that for male physicians (P<.001). By using the Berenson-Eggers Type of Service classification, procedures and other services by female physicians were of 54% lower overall average intensity (allowed payments/number of unique patients) compared with those of male physicians. These differences persisted irrespective of years since medical school graduation (P<.001).Female physicians had smaller average total Medicare payments and fewer unique beneficiary visits than male physicians in the care of fee-for-service Medicare beneficiaries in 2013. The differences persisted across specialty types and years in practice. These data can identify variation but cannot determine causation or explain the reasons behind gender differences. These findings suggest, but do not prove, that female physician Medicare payments are lower due to different practice patterns, consisting of fewer patients cared for and lower intensity of care.

Reputation Management and Content Control: An Analysis of Radiation Oncologists' Digital Identities

Google is the most popular search engine in the United States, and patients are increasingly relying on online webpages to seek information about individual physicians. This study aims to characterize what patients find when they search for radiation oncologists online. The Centers for Medicare and Medicaid Services (CMS) Physician Comparable Downloadable File was used to identify all Medicare-participating radiation oncologists in the United States and Puerto Rico. Each radiation oncologist was characterized by medical school education, year of graduation, city of practice, gender, and affiliation with an academic institution. Using a custom Google-based search engine, up to the top 10 search results for each physician were extracted and categorized as relating to: (1) physician, hospital, or health care system; (2) third-party; (3) social media; (4) academic journal articles; or (5) other. Among all health care providers in the United States within CMS, 4443 self-identified as being radiation oncologists and yielded 40,764 search results. Of those, 1161 (26.1%) and 3282 (73.9%) were classified as academic and nonacademic radiation oncologists, respectively. At least 1 search result was obtained for 4398 physicians (99.0%). Physician, hospital, and health care-controlled websites (16,006; 39.3%) and third-party websites (10,494; 25.7%) were the 2 most often observed domain types. Social media platforms accounted for 2729 (6.7%) hits, and peer-reviewed academic journal websites accounted for 1397 (3.4%) results. About 6.8% and 6.7% of the top 10 links were social media websites for academic and nonacademic radiation oncologists, respectively. Most radiation oncologists lack self-controlled online content when patients search within the first page of Google search results. With the strong presence of third-party websites and lack of social media, opportunities exist for radiation oncologists to increase their online presence to improve patient-provider communication and better the image of the overall field. We discuss strategies to improve online visibility.

BHL: A Source for Big Data Analysis

The Biodiversity Heritage Library (BHL) is a consortium of natural history and botanical libraries that cooperate to digitize taxonomic literature and to make that literature available to a global audience for open access and responsible use as a part of a global “biodiversity commons”. In partnership with the Internet Archive and through local digitization efforts, BHL has digitized more than 200,000 volumes of taxonomic literature. Using the Global Names Recognition and Discovery (GNRD) service, BHL has identified over 177 million instances of species names (including more than 29 million unique names) within the text. This content, which includes over 52 million pages of text, provides a rich unstructured source of biodiversity big data that is associated with taxonomic and bibliographic metadata. BHL allows users to search the collection, read the texts online, and download select pages or entire volumes as PDF files. More importantly, BHL makes the source data available for reuse and Big Data analysis via a number of different services. These services include direct downloads of data files and machine interfaces. This talk will describe the downloads and machine interfaces through which BHL source data is available. Each service will be introduced and described. Where feasible, the usage of each service will be demonstrated. Theoretical examples of how each service could be used to facilitate Big Data analysis will be provided.

Problematic internet use among high school students: Prevalence, associated factors and gender differences

This study aimed to measure the prevalence of Problematic Internet Use (PIU) among high school students and to identify factors associated with PIU underlining gender differences. The students filled a self-administered, anonymous questionnaire collecting information on demographic characteristics and patterns of Internet use. Multiple logistic regression analysis was performed to identify factors associated with PIU in the overall sample and by gender. Twenty-five schools and 2022 students participated in the survey. Prevalence of PIU was 14.2% among males and 10.1% among females. Males 15-year-olds and females 14-year-olds had the highest PIU prevalence that progressively lowered with age among females. Only 13.5% of pupils declared parents controlled their Internet use. The sensation of feeling lonely, the frequency of use, the number of hours of connection, and visiting pornographic websites were associated with the risk of PIU in both genders. Attending vocational schools, the activities of chatting and file downloading, and the location of use at Internet point among males, and younger age among females were associated with PIU, whilst information searching was protective among females. PIU could become a public health problem in the next years. The physical and mental health consequences should be studied.

Abstract 2587: VCF2CNA: a tool for efficiently detecting copy number alteration using VCF genotype data

Abstract Whole genome sequencing (WGS) is increasingly used in both research and clinical settings. The Variant Call Format (VCF) specification is a widely adopted file format for genetic variation data exchange partially due to its smaller file size compared to raw WGS BAMs. Each variant in a typical VCF file contains its chromosome position, reference/alternative alleles and corresponding allele counts. This makes it possible to identify copy number alterations (CNAs). To this end, we developed VCF2CNA (http://vcf2cna.stjude.org), a web interface tool for CNA analysis from VCF files. A user of VCF2CNA, uploads a VCF file via the provided web interface. The entire analysis runs remotely with an average run time of 23 minutes. Results are emailed to the user as either a downloadable link or file attachments. VCF2CNA also accepts input in the Mutation Annotation Format (MAF) and the variant file format produced by the Bambino program. We analyzed 22 TCGA glioblastoma tumor/normal pairs by Illumina technology to evaluate VCF2CNA’s performance. It achieved high consistency (average F1-score: 0.952 ± 0.082) with CONSERTING, a tool that incorporated read-depth and SV data from raw BAMs for CNA detection. A segment-by-segment comparison between results from CONSERTING and VCF2CNA indicated that the latter was less sensitive to focal CNAs. This is expected because there is less information in the VCF input than in raw BAMs. Further analysis using samples with a “fractured genome” pattern revealed that VCF2CNA was more robust to library artifacts and produced relatively clean CNA profiles (on average 76.2-fold reduction compared to the number of segments reported by CONSERTING). Finally, we analyzed 137 pediatric neuroblastoma samples from the TARGET project, sequenced by Complete Genomics, Inc. (CGI) technology. MYCN amplification has been clinically validated in 33 samples. VCF2CNA identified high amplitude MYCN gains in 32 samples and the remaining sample carried a low-level broad gain covering MYCN. For comparison, CGI’s HMM-based method reported MYCN gains in only 15 out of the 33 samples. VCF2CNA further identified two additional MYCN amplifications among the remaining samples. Collectively, our analysis suggests that VCF2CNA is a platform-independent, efficient, robust and accurate tool for general WGS-based CNA analysis. It further complements CONSERTING, which produces more accurate result in focal CNAs at the cost of significantly higher computational burden. Citation Format: Daniel K. Putnam, Xiaotu Ma, Stephen V. Rice, Yu Liu, Jinghui Zhang, Xiang Chen. VCF2CNA: a tool for efficiently detecting copy number alteration using VCF genotype data [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 2587. doi:10.1158/1538-7445.AM2017-2587

Cloud-Assisted Cooperative Mechanism for File Download in Mobile Peer-to-Peer Networks

Cloud-Assisted Cooperative Mechanism for File Download in Mobile Peer-to-Peer Networks

A Primer to the Structure, Content and Linkage of the FDA's Manufacturer and User Facility Device Experience (MAUDE) Files.

Introduction and Background:The US Food and Drug Administration (FDA)’s Manufacturer and User Facility Device Experience (MAUDE) database is a publicly available resource providing over 4 million records relating to medical device safety. Using downloadable MAUDE files avoids limitations of the online MAUDE search interface. However, naive file usage can result in errors, while independent discovery of the nuances required to correctly work with the database can be time-consuming. Practical information is provided to shorten this learning curve and obtain accurate results when using the MAUDE database files.MAUDE File Descriptions:The MAUDE database consists of 135 fields in four primary (Master Event, Device, Patient, Text) and two supplemental (Device Problems and Problem Code Descriptions) file types. When combined, these six files provide a detailed account of an adverse event or product problem report. Website instructions for joining the files are incomplete. Comprehensive details are provided to enable precise file linking.Lessons Learned:MAUDE files have irregularities that must be understood to download and work with the data efficiently. Accurate results depend upon combining the files correctly and understanding the difference between report and event denominators. Appreciating data availability can facilitate successful MAUDE investigations.Conclusion:The MAUDE database can provide key insights about medical device safety. Detailed information is provided about the structure, content and interrelationships of the MAUDE database files to enable investigators to use this valuable resource more quickly and accurately.

Epi Archive: automated data collection of notifiable disease data

ObjectiveLANL has built a software program that automatically collectsglobal notifiable disease data—particularly data stored in files—andmakes it available and shareable within the Biosurveillance Ecosystem(BSVE) as a new data source. This will improve the prediction andearly warning of disease events and other applications.IntroductionMost countries do not report national notifiable disease data in amachine-readable format. Data are often in the form of a file thatcontains text, tables and graphs summarizing weekly or monthlydisease counts. This presents a problem when information is neededfor more data intensive approaches to epidemiology, biosurveillanceand public health as exemplified by the Biosurveillance Ecosystem(BSVE).While most nations do likely store their data in a machine-readableformat, the governments are often hesitant to share data openly fora variety of reasons that include technical, political, economic, andmotivational issues [1]. For example, an attempt by LANL to obtaina weekly version of openly available monthly data, reported by theAustralian government, resulted in an onerous bureaucratic reply. Theobstacles to obtaining data included: paperwork to request data fromeach of the Australian states and territories, a long delay to obtaindata (up to 3 months) and extensive limitations on the data’s use thatprohibit collaboration and sharing. This type of experience whenattempting to contact public health departments or ministries of healthfor data is not uncommon.A survey conducted by LANL of notifiable disease data reportingin 52 countries identified only 10 as being machine-readable and42 being reported in pdf files on a regular basis. Within the 42 nationsthat report in pdf files, 32 report in a structured, tabular format and10 in a non-structured way.As a result, LANL has developed a tool-Epi Archive (formerlyknown as EPIC)-to automatically and continuously collect globalnotifiable disease data and make it readily accesible.MethodsWe conducted a survey of the national notifiable disease reportingsystems notating how the data is reported in two important dimensions:date standards and case definitions.The development of software to regularly ingests notifiabledisease data frand makes this data available involved four main stepsscraping, extracting, parsing and persisting.For scraping: we would examine website designs and determinereporting mechanisms for each country/website as well as what variesacross the reporting mechanisms. We then designed and wrote codeto automate the downloading of report pdf files, for each country.We stored report pdfs along with appropriate metadata for extractingand parsing.For extracting: we developed software that can extract notifiabledisease data presented in tabular form from a pdf file. We combinedthe methodology of figure placement detection with the in-housedeveloped table extraction and annotation heuristics.For parsing: we determined what to extract from each pdf dataset from the survey conducted. We then parsed the extracted datainto uniform data structures correctly accommodating the dimensionssurveyed and the various human languages. This task involvedingesting notifiable disease data in many disparate formats extractedfrom pdf files and coalescing the data into a standardized format.For persisting: We then store the data in the Epi ArchivePostgreSQL database and make it available through the BSVE.ResultsThe EpiArchive tool currently contains subnational notifiabledisease data from 10 nations. When a user accesses the EpiArchivesite, they are prompted with four fields: country, region, disease,and date duration. These fields allow the user to specify the location(down to the state level), the disease of interest, and the durationof interest. Upon form submission, a time series is generated fromthe users’ specifications. The generated time series can then bedownloaded into a csv file if a user is interested in performingpersonal analysis. Additionally, the data from EpiArchive can bereached through an API.ConclusionsLANL as part of a currently funded DTRA effort so that it willautomatically and continuously collect global notifiable diseasedata—particularly data stored in pdf files—and make it available andshareable within the Biosurveillance Ecosystem (BSVE) as a newdata source. This will provide data to analytics and users that willimprove the prediction and early warning of disease events and otherapplications.

PUBLIC INTEGRITY AUDITING FOR SHARED DYNAMIC CLOUD DATA WITH GROUP USER REVOCATION

Cloud computing is the protracted revelation of computing as effectiveness, where data owners can remotely store their data. The essential service presents by the Cloud is Data Storage. On the other hand, it is a tricky task for sharing data in multi-owner manner anywhere group admin and all group members can store and alter data while protecting data and identity privacy from an untrusted cloud server, due to the frequent change of the membership. So secure multi-owner data sharing scheme for dynamic groups in the cloud computing have been projected which absorb addition of group signature and broadcast encryption techniques. However this system also recognized some boundaries in terms of competence and security. since multi-owner data storing and sharing in a dynamic surroundings dumps enormous amount of data files in the cloud, which leftovers in cloud for imprecise period of time. The confidential information stored may changed by service providers. To maintain cloud file’s security and privacy regular elimination of unwanted files is needed. To determine this drawback we propose new framework which is Reliable and Scalable Secure Method to Store and Share Secrete Data for groups in Cloud i.e MONA that remove unnecessary files automatically when the predefined time period for sharing specified by data owner has been run out which improve performance of the system in terms of security and efficiency. Also this method decreases the overhead at the time of upload and download file in the cloud. At last proposed method by name Multi Owner Data Sharing Over Cloud (MODOC) declares required efficiency and most importantly security. We apply a working prototype of the MODOC method and assess its performance based on the time addicted during various operations The results give you an idea about that MODOC has the prospective to be effectively used for secure data sharing in the cloud.

DSRC versus 4G-LTE for Connected Vehicle Applications: A Study on Field Experiments of Vehicular Communication Performance

Dedicated short-range communication (DSRC) and 4G-LTE are two widely used candidate schemes for Connected Vehicle (CV) applications. It is thus of great necessity to compare these two most viable communication standards and clarify which one can meet the requirements of most V2X scenarios with respect to road safety, traffic efficiency, and infotainment. To the best of our knowledge, almost all the existing studies on comparing the feasibility of DRSC or LTE in V2X applications use software-based simulations, which may not represent realistic constraints. In this paper, a Connected Vehicle test-bed is established, which integrates the DSRC roadside units, 4G-LTE cellular communication stations, and vehicular on-board terminals. Three Connected Vehicle application scenarios are set as Collision Avoidance, Traffic Text Message Broadcast, and Multimedia File Download, respectively. A software tool is developed to record GPS positions/velocities of the test vehicles and record certain wireless communication performance indicators. The experiments have been carried out under different conditions. According to our results, 4G-LTE is more preferred for the nonsafety applications, such as traffic information transmission, file download, or Internet accessing, which does not necessarily require the high-speed real-time communication, while for the safety applications, such as Collision Avoidance or electronic traffic sign, DSRC outperforms the 4G-LTE.

Demographic factors contributing to online movie piracy of Hindi films produced in Mumbai

The aim of this paper is to investigate the demographic factors contributing to online movie piracy. Does the age play any role, or is it occupation that drives people to resort at online piracy through downloading movies or file sharing? Is there any difference between the piracy behaviour of males and females? These three demographic factors have been taken to examine their impact on piracy behaviour of individuals. The primary data collected administering a questionnaire on 515 respondents between the ages of 16 to 60 years with the aim to identify the factors namely age, occupation, and gender. The respondents were moviegoers. Using chi-square test and Yule's coefficient of association we are able to predict the factors responsible for online movie piracy.

A smart storage optimisation technique on the cloud

This paper is an extension to a recent work on enhancing load balancing and optimising storage consumption on the cloud. Our methodology, called ssCloud (Smart Storage Cloud), is based on methods designed to enhance the load balancing in concurrent file download techniques on the cloud using a collaborative dual direction technique. In this paper, we show how ssCloud operates in both the upload and download phases for providing Data as a Service (DaaS) on the cloud. Our goal is to reduce the amount of storage consumed on the cloud while providing a fast and efficient download time for the cloud clients. This is done by having two separate cloud interfaces, one for download requests (load balancing module) and another for upload requests, which involves partitioning and saving files on the available cloud servers (FileController). We also provide an analysis of ssCloud performance and compare it to other reviewed storage optimisation techniques on the cloud by simulating the cloud environment and comparing service times.

A smart storage optimisation technique on the cloud

This paper is an extension to a recent work on enhancing load balancing and optimising storage consumption on the cloud. Our methodology, called ssCloud (Smart Storage Cloud), is based on methods designed to enhance the load balancing in concurrent file download techniques on the cloud using a collaborative dual direction technique. In this paper, we show how ssCloud operates in both the upload and download phases for providing Data as a Service (DaaS) on the cloud. Our goal is to reduce the amount of storage consumed on the cloud while providing a fast and efficient download time for the cloud clients. This is done by having two separate cloud interfaces, one for download requests (load balancing module) and another for upload requests, which involves partitioning and saving files on the available cloud servers (FileController). We also provide an analysis of ssCloud performance and compare it to other reviewed storage optimisation techniques on the cloud by simulating the cloud environment and comparing service times.