Online Storage Research Articles

MWSTAT: A MODULATED WEB-BASED STATISTICAL SYSTEM

In this paper we present the development of a modulated web based statistical system, hereafter MWStat, which shifts the statistical paradigm of analyzing data into a real time structure. The MWStat system is useful for both online storage data and questionnaires analysis, as well as to provide real time disposal of results from analysis related to several statistical methodologies in a customizable fashion. Overall, it can be seem as a useful technical solution that can be applied to a large range of statistical applications, which needs of a scheme of devolution of real time results, accessible to anyone with internet access. We display here the step-by-step instructions for implementing the system. The structure is accessible, built with an easily interpretable language and it can be strategically applied to online statistical applications. We rely on the relationship of several free languages, namely, PHP, R, MySQL database and an Apache HTTP server, and on the use of software tools such as phpMyAdmin. We expose three didactical examples of the MWStat system on institutional evaluation, statistical quality control and multivariate analysis. The methodology is also illustrated in a real example on institutional evaluation.

Spike-driven threshold-based learning with memristive synapses and neuromorphic silicon neurons

Biologically plausible neuromorphic computing systems are attracting considerable attention due to their low latency, massively parallel information processing abilities, and their high energy efficiency. To achieve these features neuromorphic silicon neuron circuits need to be integrated with plastic synapse circuits capable of on-line learning and storage of synaptic weights. Within this context, memristive devices play a key role thanks to their non-volatility, scalability, and compatibility with the complementary metal–oxide–semiconductor fabrication process. However, neuro-memristive systems are still facing difficult challenges for implementing efficient learning protocols. Here, we propose and demonstrate in hardware a spike-driven threshold-based learning rule which goes beyond conventional spike-timing dependent plasticity mechanisms, by also taking into account the neuron membrane potential and its firing rate. The mixed memristive–neuromorphic system we demonstrate comprises an oxide-based memristive synapse device placed between two silicon neurons implemented on a neuromorphic chip that comprises the proper interfacing and spike-based learning circuits designed to drive the memristive elements. We show how the system is able to emulate in real-time weight dependent post-synaptic activity and drive synaptic weight updates at the memristive synapse level following the spike-driven learning rule presented. We validate this spike-based learning mechanism with experimental results and quantify the system performance with basic learning experiments.

Central Controller Framework for Mobile Cloud Computing and Security Issues

Cloud Computing is an on demand service where resources like online office software and on-line storage are made available as per the users requirement. The word cloud in cloud computing is used as a symbol for internet since it offers various computing services as well as resources like storage, servers, platforms and applications are provided to devices over the internet. Mobile cloud computing joins the cloud computing with mobile computing and giving the shopper with limitless pool of useful resource from cloud without hampering mobility of consumer. The mobile cloud computing generation is developing rapidly many of the customers and at the equal time it introduces the early protection threats inside. A mobile user storing data on the cloud can be read by the cloud service provider or hacked by man-in-middle attack, thus affecting consumer privateers and integrity. So information saved on the cloud have to be encrypted, disallowing unauthorized user to access saved records. Mobile devices are resource constrained since they are battery powered, have less processing power and have less storage space. Any set of rules or technique used for securing mobile users statistics have to don't forget above constraints for powerful makes use of cloud for portable clients. Most of the mobile devices have nearly equal functionalities, so mobile devices will face some problems associated with security and third parties, by this paper we have given a review of different techniques for secure storage of mobile user’s data in the cloud, their merits and demerits for mobile environment.

User requirements for national research and education networks for research in West and Central Africa

National research and education networks (NRENs) play a critical role in the development of communication network infrastructure and networked services for researchers and educators. They help close ‘digital divides’ between and within countries and are an essential factor for national and international development. In collaboration with the West and Central African Research and Education Network (WACREN), the TANDEM project has developed a roadmap for the development of NRENs in the region. This was based on the results of a survey that was conducted to investigate user requirements of networked services. The analysis of the 561 responses to a three-part questionnaire divided into 11 education, 22 research and 2 technical management questions identified key educational and research service needs. This article reports on the results of the survey with respect to research services. Highlights include respondents wanting regular access to online conference and academic articles (89%), a range of research services including online library resources, video conferencing, collaboration tools, online data access and storage, online library resources and inter-university login (>87%), access to remote computing facilities (80%) and high performance computing facilities (77%). A desire to share data with others online (74%) was also identified. Respondents also indicated that they would like to access research services through a range of device types–Laptops (96%), Fixed PC (86%) and Mobile Devices (81%). Poor network connectivity was consistently identified as being a major barrier to research in the region.

A survey on trade-off between storage and repair traffic in distributed storage systems

Distributed storage systems give dependable access to information through excess spread over independently unreliable hubs. Application scenarios incorporate server farms, distributed capacity frameworks, and capacity in remote systems. This paper gives a study on the cloud storage model of networked online storage where data is stored in virtualized pools of storage which are generally hosted by third parties. Hosting companies operate large data centersand people who require their data to be encouraged buy or lease accumulating limit from them. The server cultivate overseers, outside of anyone's ability to see, virtualize the advantages according to the necessities of the customer and reveal them as limit pools, which the customers would themselves have the capacity to use to store records or data objects. . The data is stored across various locations, when the user wants to retrieve them, it could be done by any of the encryption methods. At last, in view of existing procedures, promising future research bearings are recommended.

Combining Static and Dynamic Storage Management for Data Intensive Scientific Workflows

Workflow management systems are widely used to express and execute highly parallel applications. For data-intensive workflows, storage can be the constraining resource: The number of tasks running at once must be artificially limited to not overflow the space available in the filesystem. It is all too easy for a user to dispatch a workflow which consumes all available storage and disrupts all system users. To address these issues, we present a three-tiered approach to workflow storage management: (1) A static analysis algorithm which analyzes the storage needs of a workflow before execution, giving a realistic prediction of success or failure. (2) An online storage management algorithm which accounts for the storage needed by future tasks to avoid deadlock at runtime. (3) A task containment system which limits storage consumption of individual tasks, enabling the strong guarantees of the static analysis and dynamic management algorithms. We demonstrate the application of these techniques on three complex workflows.

TOXsIgN: a cross-species repository for toxicogenomic signatures.

At the same time that toxicologists express increasing concern about reproducibility in this field, the development of dedicated databases has already smoothed the path toward improving the storage and exchange of raw toxicogenomic data. Nevertheless, none provides access to analyzed and interpreted data as originally reported in scientific publications. Given the increasing demand for access to this information, we developed TOXsIgN, a repository for TOXicogenomic sIgNatures. The TOXsIgN repository provides a flexible environment that facilitates online submission, storage and retrieval of toxicogenomic signatures by the scientific community. It currently hosts 754 projects that describe more than 450 distinct chemicals and their 8491 associated signatures. It also provides users with a working environment containing a powerful search engine as well as bioinformatics/biostatistics modules that enable signature comparisons or enrichment analyses. The TOXsIgN repository is freely accessible at http://toxsign.genouest.org. Website implemented in Python, JavaScript and MongoDB, with all major browsers supported. Supplementary data are available at Bioinformatics online.

Electronic Database of Variation

The paper is an overview of the Repository of Variationist Research (https://vastry.ru/), an online storage and interactive plotting tool for quantitative sociolinguistic data. The paper describes a number of sociolinguistic experiments from which the data come and outlines the Repository and the toolkit it provides to its users.

Futuristic Correlation of Big Data & Cloud Computing in the New Millennium

Exchange a few words by using information technology in a variety of ways manufacture big amounts of data. Such data requires dealing out and storage. The cloud is an online storage space model where data is stored on multiple virtual servers. Big data processing represents a new face up to in computing, particularly in cloud computing. Data processing involves data acquirement, storage and analysis. In this respect, there are many questions including, what is the connection between big data and cloud computing? And how is big data processed in cloud computing? The answer to these difficulties will be talk about in this paper, where the big data and cloud computing will be studied, in adding up to receiving acquainted with the relationship between them in terms of safety and challenges. It recommends a period for big data, and a model that illustrates the relationship between big data and cloud computing.

Paperless Distribution of Educational Materials Using QR Codes and Online Storage Services

今回我々はクラウド上のオンラインストレージに置いたファイルのURLリンクをQRコード®化し，教育現場において配布資料をペーパーレス化する試みを行なった。受講者がスマートデバイス（スマートフォンなど）でQRコード®を読みとり，配布資料を電子媒体で受け取るしくみを構築した。受講者側に事前に十分な説明をし，準備をすると，受講者は円滑に電子媒体で資料を受け取ることが可能となった。この方法は簡便・安価で有用な情報共有手段となることがわかった。

The TOTEM DAQ based on the Scalable Readout System (SRS)

The TOTEM (TOTal cross section, Elastic scattering and diffraction dissociation Measurement at the LHC) experiment at LHC, has been designed to measure the total proton-proton cross-section and study the elastic and diffractive scattering at the LHC energies. In order to cope with the increased machine luminosity and the higher statistic required by the extension of the TOTEM physics program, approved for the LHC’s Run Two phase, the previous VME based data acquisition system has been replaced with a new one based on the Scalable Readout System. The system features an aggregated data throughput of 2GB / s towards the online storage system. This makes it possible to sustain a maximum trigger rate of ∼ 24kHz, to be compared with the 1KHz rate of the previous system. The trigger rate is further improved by implementing zero-suppression and second-level hardware algorithms in the Scalable Readout System. The new system fulfils the requirements for an increased efficiency, providing higher bandwidth, and increasing the purity of the data recorded. Moreover full compatibility has been guaranteed with the legacy front-end hardware, as well as with the DAQ interface of the CMS experiment and with the LHC’s Timing, Trigger and Control distribution system. In this contribution we describe in detail the architecture of full system and its performance measured during the commissioning phase at the LHC Interaction Point.

Dynamic Signal Strength Mapping and Analysis by Means of Mobile Geographic Information System

AbstractBluetooth beacons are becoming increasingly popular for various applications such as marketing or indoor navigation. However, designing a proper beacon installation requires knowledge of the possible sources of interference in the target environment. While theoretically beacon signal strength should decay linearly with log distance, on-site measurements usually reveal that noise from objects such as Wi-Fi networks operating in the vicinity significantly alters the expected signal range. The paper presents a novel mobile Geographic Information System for measurement, mapping and local as well as online storage of Bluetooth beacon signal strength in semireal time. For the purpose of on-site geovisual analysis of the signal, the application integrates a dedicated interpolation algorithm optimized for low-power devices. The paper discusses the performance and quality of the mapping algorithms in several different test environments.

PYM: a new, affordable, image-based method using a Raspberry Pi to phenotype plant leaf area in a wide diversity of environments

BackgroundPlant science uses increasing amounts of phenotypic data to unravel the complex interactions between biological systems and their variable environments. Originally, phenotyping approaches were limited by manual, often destructive operations, causing large errors. Plant imaging emerged as a viable alternative allowing non-invasive and automated data acquisition. Several procedures based on image analysis were developed to monitor leaf growth as a major phenotyping target. However, in most proposals, a time-consuming parameterization of the analysis pipeline is required to handle variable conditions between images, particularly in the field due to unstable light and interferences with soil surface or weeds. To cope with these difficulties, we developed a low-cost, 2D imaging method, hereafter called PYM. The method is based on plant leaf ability to absorb blue light while reflecting infrared wavelengths. PYM consists of a Raspberry Pi computer equipped with an infrared camera and a blue filter and is associated with scripts that compute projected leaf area. This new method was tested on diverse species placed in contrasting conditions. Application to field conditions was evaluated on lettuces grown under photovoltaic panels. The objective was to look for possible acclimation of leaf expansion under photovoltaic panels to optimise the use of solar radiation per unit soil area.ResultsThe new PYM device proved to be efficient and accurate for screening leaf area of various species in wide ranges of environments. In the most challenging conditions that we tested, error on plant leaf area was reduced to 5% using PYM compared to 100% when using a recently published method. A high-throughput phenotyping cart, holding 6 chained PYM devices, was designed to capture up to 2000 pictures of field-grown lettuce plants in less than 2 h. Automated analysis of image stacks of individual plants over their growth cycles revealed unexpected differences in leaf expansion rate between lettuces rows depending on their position below or between the photovoltaic panels.ConclusionsThe imaging device described here has several benefits, such as affordability, low cost, reliability and flexibility for online analysis and storage. It should be easily appropriated and customized to meet the needs of various users.

PENGEMBANGAN MODEL BLENDED LEARNING BERBASIS LEARNING MANAGEMENT SYSTEM DI MTS. MUHAMMADIYAH SANINGBAKAR SOLOK

Blended learning is one of model for integration of pedagogic and information and communication technology (ICT) skill of teacher. The community service program aims are to develop an integrated learning environment using Learning Management Sytem and incraasing teacher skill on utilize of ICT as a supporting tool to quality improvement of teaching and learning process at MTs. Muhammadiyah Saningbakar. The ICT skill as well as define on National Curriculum Nasional 2013 become an integrated skill for every teacher. In this programme, two focus activity are defined, first activity is redesign ICT training for teaching and second is development an online learning environment based-on learning management system (LMS) as delivery medium on blended learning. Redesign ICT training including some of main competencies are 1) Course material development, 2) Word Processing, 3) Presentation design, 4) content development, 5) online learning and 6) applied strategic of blended learning. Those skill is needed to fullfill of successfullness requirement of blended learning. Development an online learning management system is using most popular open source course LMS named by Moodle. To achieve development goal some activity is applied as folows : 1) Define an domain name system for MTs. Muhammadiyah Saningbakar, 2) Get a hosting services as online storage for online environment, 3) LMS installation and Configiration, 4) User management, 5) Course and teacher settings and 6) Content uploading and delivery using LMS. Blended learning environment is developed based on MTs. M curriculum, and defined on course setting of LMS into 3 catagories : Islamic, Adaptive, and Subtantive. And each category containing some course which are available on LMS and accessed by student using networking.
 Keyword: Blended Learning, ICT Skill, Integrated Learning Environment, LMS, Online Learning

Online & Offline data storage and data processing at the European XFEL facility

For the upcoming experiments at the European XFEL light source facility, a new online and offline data processing and storage infrastructure is currently being built and verified. Based on the experience of the system being developed for the Petra III light source at DESY, presented at the last CHEP conference, we further develop the system to cope with the much higher volumes and rates ( 50GB/sec) together with a more complex data analysis and infrastructure conditions (i.e. long range InfiniBand connections). This work will be carried out in collaboration of DESY/IT, European XFEL and technology support from IBM/Research. This presentation will shortly wrap up the experience of 1 year runtime of the PetraIII ([3]) system, continue with a short description of the challenges for the European XFEL ([2]) experiments and the main section, showing the proposed system for online and offline with initial result from real implementation (HW & SW). This will cover the selected cluster filesystem GPFS ([5]) including Quality of Service (QOS), extensive use of flash based subsystems and other new and unique features this architecture will benefit from.

Delay-Optimized File Retrieval under LT-Based Cloud Storage

Fountain-code based cloud storage system provides reliable online storage solution through placing unlabeled content blocks into multiple storage nodes. Luby Transform (LT) code is one of the popular fountain codes for storage systems due to its efficient recovery. However, to ensure high success decoding of fountain codes based storage, retrieval of additional fragments is required, and this requirement could introduce additional delay. In this paper, we show that multiple stage retrieval of fragments is effective to reduce the file-retrieval delay. We first develop a delay model for various multiple stage retrieval schemes applicable to our considered system. With the developed model, we study optimal retrieval schemes given requirements on success decodability. Our numerical results suggest a fundamental tradeoff between the file-retrieval delay and the target probability of successful file decoding, and that the file-retrieval delay can be significantly reduced by optimally scheduling packet requests in a multi-stage fashion.

Semi-explicit MPC based on subspace clustering

This paper presents a new strategy of simplifying the online computations in linear model predictive control (MPC). Employing a specific type of state dependent parameterization for the optimization variable in MPC, advantages of explicit MPC are combined with those of online optimization based MPC into an efficient MPC scheme. The parameterization is computed offline applying a tailored subspace clustering algorithm to training data consisting of states and corresponding solutions to the MPC optimization problem. It is then refined to guarantee feasibility of the parameterized optimization. During the offline design phase, complexity of the parameterization can be adjusted and control performance can be traded off against online computational effort and storage requirements. Numerical examples evaluate the presented methods and illustrate their benefits.

High-Speed Counter-Current Chromatography with an Online Storage Technique for the Preparative Isolation and Purification of Dihydroflavonoids from Sophora alopecuroides L.

High-speed counter-current chromatography (HSCCC) is an efficient and non-absorption separation technique, but limitations still exist in simultaneous isolation of complex structures of natural products. Moreover, particular methods are various for different kinds of natural products. A novel HSCCC strategy combined with an online storage recycling elution (OSR-CCC) technique was developed for the quick separation of naturally occurring dihydroflavonoids from the extract of the herb Sophora alopecuroides L. In the separation procedure, a storage loop and two six-port valves were connected to a HSCCC system. Effluent A was subjected to an online storage loop and then to recycling separation three times after effluent B was collected in head-to-tail mode. After completion of the recycling separation of effluent A, the elution was switched to tail-to-head mode to collect effluent C. A biphasic solvent system of n-hexane/ethyl acetate/methanol/water (9:6:6:8, v/v/v/v) was used as the separation solvent during the whole elution. Six constituents were isolated simultaneously from the extract (200mg) of S. alopecuroides by running HSCCC non-stop, and their purities were higher than 95.0%. Their structures were determined as the pterocarpan glycoside sophoratonkin (1) (10.0mg) and five dihydroflavonoids, alopecurone F (2) (5.4mg), lehmannin (3) (11.0mg), alopecurone A (4) (35.0mg), sophoraflavanone G (5) (21.0mg), alopecurone B (6) (31.0mg). This recycling HSCCC method combined with an online storage technique could be a rapid, effective and simple approach to isolate stilbene-dihydroflavonoids from herbs of the Sophora genus simultaneously. Copyright © 2017 John Wiley & Sons, Ltd.

Practical Network Coding for the Update Problem in Cloud Storage Systems

Cloud storage systems are emerging as the primary solution for online storage and information sharing. As the demand for such a service is increasing at a phenomenal rate, the cost for maintaining and delivering content concerns the cloud providers and ISPs. As in other distributed systems, e.g. , file sharing and multimedia streaming, network coding can significantly simplify the process for content distribution and retrieval. However, it also raises difficulties in updating portions of a file, as any change in the file will impact all coded content in the system. In this paper, we present the differential update model and its optimization for updating coded blocks by delivering only the changes in a file. We complete the design with an update algorithm and a communication protocol among all participants in the system. Our experimental results verify that our design makes network coding practical for file updates in cloud storage systems. The proposed update model leads to bandwidth saving, compared to conventional update mechanisms, with minimal computational costs.

UNDANGAN PAPERLESS BERBASIS CLOUD COMPUTING DENGAN MEMANFAATKAN CLOUDINARY

Paperless is an attempt to reduce the use of paper media in the filing process, a use of paperless office technology, paperless office technology will be applied using cloud computing technology. Cloud computing is a service that provides synchronized online storage media, which can be accessed through a variety of devices such as Android smartphones. Cloud services applications built on these systems is a data storage service to take advantage of the cloudinary storage media. Cloudinary is a service that provides cloud services for image, download and CDN (Content Delivery Network). This can certainly provide convenience in the process of registering and sending out invitations electronically using paperless invitations. In addition, there is a process of checking the read (read) status will be performed by the MySQL database system to use the webservice. Paperless invitations applications can be run if the user has an e-mail account, the paperless invitations test system that have been made show the menu each function can be executed according to its input.