Entire File Research Articles

BD5: An open HDF5-based data format to represent quantitative biological dynamics data.

BD5 is a new binary data format based on HDF5 (hierarchical data format version 5). It can be used for representing quantitative biological dynamics data obtained from bioimage informatics techniques and mechanobiological simulations. Biological Dynamics Markup Language (BDML) is an XML (Extensible Markup Language)-based open format that is also used to represent such data; however, it becomes difficult to access quantitative data in BDML files when the file size is large because parsing XML-based files requires large computational resources to first read the whole file sequentially into computer memory. BD5 enables fast random (i.e., direct) access to quantitative data on disk without parsing the entire file. Therefore, it allows practical reuse of data for understanding biological mechanisms underlying the dynamics.

Secure Proof of Ownership Using Merkle Tree for Deduplicated Storage

In cloud services, deduplication is a widely used data reduction technique to minimize storage and communication overhead. Nonetheless, deduplication introduces a serious security risk: a malicious client can obtain access to a file on storage by learning just a piece of information about the file. Proof of ownership schemes provides protection against this security risk as it enables the server to check whether the client actually owns a particular file in its entirety. However, a malicious client may misuse proof of ownership procedure to waste resources at the server. For that, she sends a large number of upload requests and tries to keep the server busy in computing challenges and verifying responses. In this paper, we propose a secure proof of ownership scheme using Merkle tree. In this approach, cloud server precomputes the challenges-responses to avoid computational overhead during subsequent upload. Moreover, cloud server does not need to retain resources until the response is received since our approach is a stateless protocol. Security analysis demonstrates that a malicious client without having entire file cannot prove herself as an owner of the file. As a proof of concept, we implement our approach in a realistic environment and demonstrate that it outperforms the existing proof of ownership schemes in terms of challenge generation, communication, and response verification cost.

The disintegration of event files over time: Decay or interference?

When facing particular combinations of stimuli and responses, people create temporary event files integrating the corresponding stimulus and response features. Repeating one or more of these features retrieves the entire event file, which impairs performance if not all features repeat (partial-repetition costs). We studied how durable event files are over time and how sensitive they are to intervening objects or stimulus-response events. After-effects of relevant and irrelevant stimulus-response bindings were assessed after intervals of 1 to 5 s between creation and retrieval of the binding that were either unfilled (Experiment 1A), filled with 0, 2, or 4 presentations of the same neutral stimulus (1B), or of changing stimuli (1C), or filled with 0, 2, or 4 task-unrelated stimulus-response combinations (2A) or the same number of repetitions of the binding-inducing stimulus-response combination (2B). Taken altogether, the findings show a strong impact on the duration of the interval but no systematic effect of the type and number of intervening events. This suggests that event files disintegrate over time, as a function of spontaneous decay, but not due to interference from other bindings.

Lossless data transmission for Internet of things application over wireless multimedia sensor networks using enhanced and optimal path scheduling approach to maximizing the quality of service

AbstractThe congestion of packet forwarding between a source and destination is challenging on downlink transmission in the entire file (ex. Audio and Video). Whenever file is been uploaded to the server, a user requests for file where server transmits it without knowledge of user's bandwidth, which is a major, cause of packet loss or time duration in the receiver end. To accumulate the better solution, Enhanced and Optimal Path Scheduling Approach (EOPSA) designs to find optimal path scheduling for multimedia data transmission in multimedia sensor network over cloud server using IoT devices. EOPSA studied the multisource video‐on‐demand streaming in multimedia sensor networks. The method introduced a heuristic distributed protocol to find optimal route for multimedia data transmissions. Efficient way to identify the bandwidth before the transmission ensures link establishment between sender and receiver. Here, the capture of bandwidth helps to check user's system capability to forward requested media data. Based on experiment evaluation, EOPSA improves 0.20 packet delivery ratio, 130 throughput, 0.20 second average delay and 14 communication overhead for 15, 25, 50, 75, and 100 nodes compared than conventional methods.

An efficient binary storage format for IFC building models using HDF5 hierarchical data format

The Industry Foundation Classes (IFC) are a prevalent data model in which Building Information Models can be exchanged, typically with a file-based nature. Processing the full extent of these models can be time-consuming. Considering the multi-disciplinary nature of the construction industry, stakeholders will typically only be interested in a small subset, depending on the purpose of the exchange. Therefore, the retrieval of relevant subsets, whether spatially, based on discipline, or others, is necessary to effectively consume such datasets in downstream applications.Prevalent encoding forms of IFC models are text-based and do not facilitate random-access seeking within the file and do not impose an ordering on the definition of elements within the file. Therefore, typically, the entire file needs to be read in order to find the data of interest. Furthermore, text-based data is slower to parse in comparison to binary data.This paper assesses a binary serialization format originating from the family of EXPRESS standards. It is based on an existing open, binary, hierarchical data format called HDF5 that allows random access to specific instances and therefore efficient retrieval of relevant subsets. The block-level, transparent compression yields a reduction of file sizes as compared to traditional serializations. Fully specified datatypes embedded in the exchange guarantee interoperable use.In this paper, several serialization profiles are introduced that cater to specific use cases by governing storage settings. Advanced functionality from the HDF5 library is applied to offer novel paradigms for fine-grained access rights, varying level of detail, revision management and aggregation of aspect models.

Do Pirated Video Streams Crowd Out Non-Pirated Video Streams? Evidence from Online Activity

Does watching more pirated streaming video mean spending less time watching non-pirated streaming video? This study measures whether, and how much, time spent watching pirated video crowds out time spent on streaming video apps. While prior studies have estimated the impact of piracy on sales revenues, our study measures the impact of piracy on time spent on free and paid streaming apps. We combine big data tools with standard econometric techniques, including a two-stage least squares model, to analyze 5.25 terabytes of online activity data from 19,764 American households and their 468,612 devices from 2016 to 2017. The analysis suggests that every minute spent engaged with pirated video sites crowded out about 3.5 minutes of time spent streaming video. Because pirated video files are generally more compressed than non-pirated video files and because they are frequently downloaded as entire files rather than streamed, as with non-pirate sites like Netflix and Amazon, we conclude that our results exhibit closer to a 1-to-1 crowding out effect of piracy on over-the-top streaming video services.

Ransomware Evasion with its Behaviors

Ransomware is a malware, where entire system is encrypted as soon as it gets into the system. Presently it is very hot topic in the IT news as a money making scheme. Since Ransomware is evolving rapidly the studies on it becomes outdated very soon and also cybercriminals who works on Ransomware have created their own bionetwork where they always come up with new techniques like Trojans, bots, coins etc. which will penetrate inside the systems by detouring the antivirus tools. User system can free from attack either by maintaining the system with proper updates and good anti Ransomware tools like Acronics, Trend Micro and many. Companies and domestic users are the ones who are mainly affected by the Ransomware and will be under financial loss. To recognize and to get rid of Ransomware safely by making use of various countermeasures users must know the behavior and variants of Ransomware. There are various articles that gives the information about the different families of Ransomware like Crypto Ransomware, a kind of Ransomware that deletes the actual data of user and encrypts entire files present in the user’s system, Wannacry is other variant that actually targets the windows operating system and encrypts the files and Cryptolocker, Locky etc. are different variants that are present which are unique in their own way. But then this article focuses on the Evasion of Ransomware with special characteristics like unbreakable encryption, giving extensions to files and its capacity lies in encrypting all kinds of data, the Evasion Method includes complete prevention of Ransomware which assists the organization and also domestic user.

Reversible fingerprinting for genomic information

New genome sequencing technologies have simplified the generation of genomic data, making them more common but in turn a likely target of attack. Security strategies have been devised such as restricting the amount of information that can be queried or using new encryption techniques. These solutions might not be enough if the entire file has to be shared, as the recipient might leak the accessible information. This contribution addresses this issue using watermarking. Each read in a genomic file is modified depending on its content and a secret key. This allows generating different watermarked instances of the original file. Each watermark acts as a fingerprint: if a leak occurs, the unique modifications of the instance points to who originated the unauthorized publication. Using the key, the modifications can be undone. This allows sharing a leak-discouraging version with which the relevance of a file can be assessed, and can be reversed to the original if needed.

A comparative analysis of non­reference assessment methods

A comparative analysis of functions to assess image quality in the absence of a sample: no-reference (NR) measure or NR-type methods. The availability of NR-methods is very important for assessing the quality of streaming video such as television, game streaming, online conferences, web-chatting, etc. (because on the side of the recipient of the video there is no standard for quality comparison) and assessing the results of transformations aimed at improving video, and choosing the parameters of these transformations (brightness change, semitone and others). The human visual system (HVS) is able to visually assessing video quality, but If required to visually assess the quality of dozens or hundreds of videos or ranking them by quality level it will be needed a huge amount of time. Six types of experiments were performed to analyze the correlation of calculated quantitative estimates with visual assessments of the quality of the tested video files. Three of them are fundamentally new: comparing video after gamma correction and changing the contrast with different parameters, as well as blurring, which may be the result of defocusing the camcorder. A hybrid method (or reduced-reference (RR) measure) and a full-reference (FR) measure or FR-type method were also added for comparison. It has been experimentally shown that none of the studied non-reference methods of image quality assessment is universal, and the calculated assessment cannot be converted into a quality scale without taking into account the factors influencing the distortion of image quality. Moreover, all NR-type methods could not cope with the experiment of changing the contrast, believing that the best result is the most contrasting image but the original. Instead, the reference methods showed an excellent result (except one, which showed partial ineffectiveness). Also, it has been shown performance comparison between methods. It is shown that most of the studied methods calculate local estimates for each frame, and their arithmetic mean value is an estimate of the quality of the entire video file. If the video is dominated by large areas of uniform evaluation, methods of this type may give incorrect quality evaluations that do not coincide with the visual evaluations.

Альтернативный подход к определению нормы стока неизученных рек (на примере бассейна реки Амур в пределах Забайкальского края)

The article presents an approach to determining the flow rate of unexplored rivers depending on their order according to A. Scheidegger and the corresponding zoning. It is shown that the use of a single dependence of the flow rate on the river order gives significant errors for small streams. This is because of the fact that approximation function of the entire data file actually reflects regularities only for hydrological stations with great values of the runoff norm.For the territory of the Amur Basin within the Transbaikal cray, five regions have been identified, within which the dependences of the flow rate of small and medium rivers have values of the correlation coefficient from 0.95 to 0.97. An additional zoning scheme for the area under consideration has also been developed, which makes it possible to simplify the determination of the order of the river.The proposed scheme of flow rate determination includes the following operations: determination of the area according to the additional scheme – calculation of the river order – determination of the area according to the main scheme – calculation of the flow rate.

Rendering Optimization for Mobile Web 3D Based on Animation Data Separation and On-Demand Loading

Based on advances in image processing technology and Web-enabling technologies for mobile devices, mobile Augmented Reality (AR) and Virtual Reality (VR) has developed rapidly. The rendering and interaction of 3D models is an important part of AR and VR applications and is closely related to user experience. However, since the existing WebGL 3D JavaScript libraries for Web-based mobile 3D (represented by three.js and babylon.js) load the entire model file at once, large-size 3D models with complex interactions cannot be rendered smoothly due to limited data transmission, the weak computation capabilities of mobile Web browsers, and the latency of 3D model rendering. In this paper, we first propose model-animation data separation and an on-demand loading mechanism to improve the data request and loading process of Web 3D models. The main mechanisms are the following: (1) The model data are segmented into topological data and animation data sequences, and only the necessary data of the model are loaded when the Web-based mobile 3D model is first rendered. (2) The 3D model animation data sequence is semantically decomposed, and a multigranular model animation data service is established to provide continuous animation data support. (3) An asynchronous request-response mechanism is used to optimize the loading method of the model data. The model rendering mechanism uses an on-demand request and rendering method to transform the centralized loading process of the 3D model into a decentralized process. According to the testing and verification results, this optimization method can reduce the latency of mobile Web 3D in model data transmission and rendering by 24.72% for the experiment models. The interaction experience of Web-based mobile AR and VR is substantially improved relative to existing Web 3D rendering engines and rendering mechanisms, especially in complex interactive service scenarios.

DC-Patch: A Microarchitectural Fault Patching Technique for GPU Register Files

The ever-increasing parallelism demand of General-Purpose Graphics Processing Unit (GPGPU) applications pushes toward larger and more energy-hungry register files in successive GPU generations. Reducing the supply voltage beyond its safe limit is an effective way to improve the energy efficiency of register files. However, at these operating voltages, the reliability of the circuit is compromised. This work aims to tolerate permanent faults from process variations in large GPU register files operating below the safe supply voltage limit. To do so, this paper proposes a microarchitectural patching technique, DC-Patch, exploiting the inherent data redundancy of applications to compress registers at run-time with neither compiler assistance nor instruction set modifications. Instead of disabling an entire faulty register file entry, DC-Patch leverages the reliable cells within a faulty entry to store compressed register values. Experimental results show that, with more than a third of faulty register entries, DC-Patch ensures a reliable operation of the register file and reduces the energy consumption by 47% with respect to a conventional register file working at nominal supply voltage. The energy savings are 21% compared to a voltage noise smoothing scheme operating at the safe supply voltage limit. These benefits are obtained with less than 2 and 6% impact on the system performance and area, respectively.

Track Conditions: Upon Revisiting How Superstition Won and Science Lost

Track Conditions: Upon Revisiting <i>How Superstition Won and Science Lost</i>

Forgery Detection Mechanism with Abnormal Structure Analysis on Office Open XML based MS-Word File

We examine the weaknesses of the existing OOXML-based MS-Word file structure, and analyze how data concealment and forgery are performed in MS-Word digital documents. In case of forgery by including hidden information in MS-Word digital document, there is no difference in opening the file with the MS-Word Processor. However, the computer system may be malfunctioned by malware or shell code hidden in the digital document. If a malicious image file or ZIP file is hidden in the document by using the structural vulnerability of the MS-Word document, it may be infected by ransomware that encrypts the entire file on the disk even if the MS-Word file is normally executed. Therefore, it is necessary to analyze forgery and alteration of digital document through internal structure analysis of MS-Word file. In this paper, we designed and implemented a mechanism to detect this efficiently and automatic detection software, and presented a method to proactively respond to attacks such as ransomware exploiting MS-Word security vulnerabilities.

MySeq: privacy-protecting browser-based personal Genome analysis for genomics education and exploration

BackgroundThe complexity of genome informatics is a recurring challenge for genome exploration and analysis by students and other non-experts. This complexity creates a barrier to wider implementation of experiential genomics education, even in settings with substantial computational resources and expertise. Reducing the need for specialized software tools will increase access to hands-on genomics pedagogy.ResultsMySeq is a React.js single-page web application for privacy-protecting interactive personal genome analysis. All analyses are performed entirely in the user’s web browser eliminating the need to install and use specialized software tools or to upload sensitive data to an external web service. MySeq leverages Tabix-indexing to efficiently query whole genome-scale variant call format (VCF) files stored locally or available remotely via HTTP(s) without loading the entire file. MySeq currently implements variant querying and annotation, physical trait prediction, pharmacogenomic, polygenic disease risk and ancestry analyses to provide representative pedagogical examples; and can be readily extended with new analysis or visualization components.ConclusionsMySeq supports multiple pedagogical approaches including independent exploration and interactive online tutorials. MySeq has been successfully employed in an undergraduate human genome analysis course where it reduced the barriers-to-entry for hands-on human genome analysis.

Efficient dynamic multi-keyword fuzzy search over encrypted cloud data

Multi-keyword search of encrypted cloud data has attracted extensive attention worldwide in the recent years due to the increasing concern for data security and privacy in Cloud Computing. Fault-tolerance is important for multi-keyword fuzzy search which can provide accurate results even with the presence of minor spelling and typographical errors in the search keywords. But, existing fuzzy search schemes lack efficiency due to their high computational overhead and do not support file dynamic updates. This paper proposes an efficient dynamic multi-keyword fuzzy search scheme for encrypted cloud data to support dynamic file updates. Locality sensitive hashing (LSH) and Bloom filters are employed to generate index vectors and query vectors. Based on the generated vectors, a balanced binary tree is constructed as the index for the entire file set, and a Top-k search algorithm is developed to search k files that are most relevant to a given query with the help of the index tree. Extensive experiments conducted on real-world datasets demonstrate that our scheme is more efficient than existing similar schemes.

Completeness of informed consent in supporting national standard accreditation of patient and family rights 5 hospitals at Ropanasuri surgical special hospital in Padang

Background: Completeness of informed consent is one indicator in supporting the accreditation of national hospital standards through the assessment of patient and family rights (PFR) assessment standards 5. In the health service process, informed consent can also be used as evidence and has a strong legal value in the form of a sheet of paper containing the doctor’s explanation about the diagnosis of the disease and the actions that will be performed on the patient.Methods: This research uses descriptive method with a qualitative approach. The population used was the entire patient medical record file in 2018, which was 3.093 medical record files. Sampling was done by random sampling using a formula according to Notoatmodjo for the calculation of the number of samples and obtained 355 files of medical records. Data processing using Microsoft Excel computer programs. For observing the completeness of the standard rights of patients and families using national standards for hospital accreditation.Results: Based on the analysis of 355 medical record files at Ropanasuri specialty hospital it is known that 296 pieces of informed consent were filled in with a percentage of 83.38%, 59 sheets of informed consent were incomplete with a percentage of 16.62%. The results showed the greatest incompleteness found in filling the informed consent items of witness signatures of 2.81%, providing information on the completeness of filling the doctor's identity by 2.54% and the name of the witness 1.70% on filling the authentication.Conclusions: 296 pieces of informed consent were filled in with a percentage of 83.38%, 59 sheets of informed consent were incomplete with a percentage of 16.62%.

A New Stable Peer-to-Peer Protocol With Non-Persistent Peers: The Group Suppression Protocol

Recent studies have suggested that the stability of peer-to-peer networks may rely on persistent peers , who dwell on the network after they obtain the entire file. In the absence of such peers, one piece becomes extremely rare in the network, which leads to instability. Technological developments, however, are poised to reduce the incidence of persistent peers, giving rise to a need for a protocol that guarantees stability with non-persistent peers. We propose a novel peer-to-peer protocol, the group suppression protocol , to ensure the stability of peer-to-peer networks under the scenario that all the peers adopt non-persistent behavior. Using a suitable Lyapunov potential function, the group suppression protocol is proven to be stable when the file is broken into two pieces, and detailed experiments demonstrate the stability of the protocol for arbitrary number of pieces. We define and simulate a decentralized version of this protocol for practical applications. Straightforward incorporation of the group suppression protocol into BitTorrent while retaining most of BitTorrent’s core mechanisms is also presented. Subsequent simulations show that under certain assumptions, BitTorrent with the official protocol cannot escape from the missing piece syndrome, but BitTorrent with group suppression does.

Cache-Aided Non-Orthogonal Multiple Access for 5G-Enabled Vehicular Networks

The increasing demand for rich multimedia services and the emergence of the Internet of Things (IoT) pose challenging requirements for the next-generation vehicular networks. Such challenges are largely related to high spectral efficiency and low latency requirements in the context of massive content delivery and increased connectivity. In this respect, caching and non-orthogonal multiple access (NOMA) paradigms have been recently proposed as potential solutions to effectively address some of these key challenges. In this paper, we introduce cache-aided NOMA as an enabling technology for vehicular networks. In this context, we first consider the full file caching case, where each vehicle caches and requests entire files using the NOMA principle. Without loss of generality, we consider a two-user vehicular network communication scenario under double Nakagami $\text{-}m$ fading conditions and propose an optimum power allocation policy. To this end, an optimization problem that maximizes the overall probability of successful decoding of files at each vehicle is formulated and solved. Furthermore, we consider the case of split file caching, where each file is divided into two parts. A joint power allocation optimization problem is formulated, where power allocation across vehicles and cached split files is investigated. The offered analytic results are corroborated by extensive results from computer simulations and interesting insights are developed. Indicatively, it is shown that the proposed caching-aided NOMA outperforms the conventional NOMA technique.

MassComp, a lossless compressor for mass spectrometry data

BackgroundMass Spectrometry (MS) is a widely used technique in biology research, and has become key in proteomics and metabolomics analyses. As a result, the amount of MS data has significantly increased in recent years. For example, the MS repository MassIVE contains more than 123TB of data. Somehow surprisingly, these data are stored uncompressed, hence incurring a significant storage cost. Efficient representation of these data is therefore paramount to lessen the burden of storage and facilitate its dissemination.ResultsWe present MassComp, a lossless compressor optimized for the numerical (m/z)-intensity pairs that account for most of the MS data. We tested MassComp on several MS data and show that it delivers on average a 46% reduction on the size of the numerical data, and up to 89%. These results correspond to an average improvement of more than 27% when compared to the general compressor gzip and of 40% when compared to the state-of-the-art numerical compressor FPC. When tested on entire files retrieved from the MassIVE repository, MassComp achieves on average a 59% size reduction. MassComp is written in C++ and freely available at https://github.com/iochoa/MassComp.ConclusionsThe compression performance of MassComp demonstrates its potential to significantly reduce the footprint of MS data, and shows the benefits of designing specialized compression algorithms tailored to MS data. MassComp is an addition to the family of omics compression algorithms designed to lessen the storage burden and facilitate the exchange and dissemination of omics data.