IEEE / Institute of Electrical and Electronics Engineers Incorporated

IEEE / Institute of Electrical and Electronics Engineers Incorporated

IEEE / Institute of Electrical and Electronics Engineers Incorporated

IEEE / Institute of Electrical and Electronics Engineers Incorporated

IEEE / Institute of Electrical and Electronics Engineers Incorporated

IEEE / Institute of Electrical and Electronics Engineers Incorporated

IEEE Computer Society

IEEE / Institute of Electrical and Electronics Engineers Incorporated

IEEE Computer Society

IEEE Computer Society

IEEE / Institute of Electrical and Electronics Engineers Incorporated

It was developed with CSIR-National Aerospace Laboratories

Hackensack, NJ : World Scientific Publishing Co. Pte. Ltd., [2023]

Computing services notes - from Middle Managers 8/7/08

* All circ problems: aleph, print demons, notices, etc -- anybody/everybody just send a Grover http://www.uflib.ufl.edu/grover ticket. As Systems learns the quantity, frequency, and variety of problems reported, they'll learn how to how to base assignments.

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* New linking service - Serials Solutions 360 Linker - is being tested The "Find it@UF" icon will change slightly (substituting the SFX trademark swirly with an @) and we’ll need to know when to make the switch on all our handouts, web pages, etc.

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* phishing -- everyone remember to never give out any of your passwords to anybody. Not to Systems, not to CIRCA, not to UF. Requests for passwords (especially from email messages) are masquerades for phishing schemes. OK to give your logon, but never your password.

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* Active Directory -- public computers will begin conversion this week. Patrons will use Gatorlink to logon. We may create guest accounts (following procedures) valid for 14 days. Guest accounts cannot be renewed; patrons will have to select a new name (smith1, smith2, etc) every 2 weeks. The Peoplesoft folks have not yet committed to making longer-term, renewable guest accounts. These guest accounts are for computer use only; they do not govern borrowing privileges or remote access. (Patrons can log into to the Library Proxy with their Gatorlink, but it only connects if their Gatorlink account indicates an eligible status.)

*** We currently have 300 courtesy borrowers, and some of them may be eligible for real Gatorlinks (which they can create themselves). They should check with Jim Stevens. In the meantime, it may be easiest to create them a temp guest account on the spot and then (we or patron) contact Jim to see what else can be done. Stay tuned.

*** There are 1800 guest computer use accounts active today. 1800 accounts x every 2 weeks means a lot of work for staff and a lot of grief for patrons. We'll hope to succeed with requesting speedy establishment of longer-term, renewable guest Gatorlink accounts.

*** Small branches with only student assistants on the weekends might send guests to MSL for account creation.

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* Active Directory for staff computers -- might happen in mid-Fall. Huge implications for how we all manage our email; some aspects will be time-consuming and deadline-based.

*** Campus email only saves Inbox and Sent email for 30 days. Then it goes into Deleted folder. After 30 days, stuff in Deleted is irretrievable. We all must learn to put any items we want to save into our Retain Permanently folder.

*** Our new email address will be our Gatorlink. If you might be professionally embarrassed by your Gatorlink name, change it soon.

*** We'll all have to notify our discussion lists of our new (gatorlink) address. We should still receive mail directed to uflib, but we won't be able to post to lists that expect us to send from uflib. Feel free to start converting your discussion lists to gatorlink soon.

*** Will said he'll check the group email addresses (sciref, illoan, etc) to see how they can be addressed, managed, and accessed in the campus AD. Stay tuned.

*** We should receive recommendations and procedures on storing and backing up email on library vs. campus servers before we switch. Some gory details available at http://www.mail.ufl.edu/questionsandanswers.shtml and http://www.mail.ufl.edu/managemail.shtml.

* Office 2007 - if you really want Office 2007 on your staff computer now, please send a request via Grover. If you can wait til about mid-Sept, Systems will be able to push the software over the network rather then sending a staff member to enslave your computer for awhile.

Start-up wants to foster a quantum leap in molecular problem-solving

In a step that brings silicon-based quantum computers closer to reality, researchers at Princeton University have built a device in which a single electron can pass its quantum information to a particle of light. The particle of light, or photon, can then act as a messenger to carry the information to other electrons, creating connections that form the circuits of a quantum computer.

Edge computing is the way forward, but are we ready to surrender control to corporations.

Now, any developer could create an app and run it on Amazon, Microsoft or Google’s servers and make millions or billions in the process.

Cloud computing has become a platform for innovation. This paper looks at how the cloud changes the way computing is carried out, and evaluates the benefits, challenges and economic and environmental impacts. It discusses the policy issues raised and the role of governments and other stakeholders in addressing them.

The city-based K7 Computing Pvt Ltd, provider of cyber security solutions, has topped the winners list for the Advanced+ Performance Award from AV-Com

The Python programming language, combined with the numerical computing library NumPy and the scientific computing library SciPy, has become the de facto standard for scientific computing in a variety of fields. This popularity is mainly due to the ease with which a Python program can be written and executed (easy syntax, dynamical typing, no compilation etc.), coupled with the existence of a large number of specialized third-party libraries that aim to lift all the limitations of the raw Python language. NumPy introduces vector programming, improving execution speeds, whereas SciPy brings a wealth of highly optimized and reliable scientific functions. There are cases, however, where vector programming alone is not sufficient to reach optimal performance. This issue is addressed with dedicated compilers that aim to translate Python code into native and statically typed code with support for the multi-core architectures of modern processors. In the present article it is shown how these approaches can be efficiently used to tackle different problems, with increasing complexity, that are relevant to crystallography: the 2D Laue function, scattering from a strained 2D crystal, scattering from 3D nanocrystals and, finally, diffraction from films and multilayers. For each case, detailed implementations and explanations of the functioning of the algorithms are provided. Different Python compilers (namely NumExpr, Numba, Pythran and Cython) are used to improve performance and are benchmarked against state-of-the-art NumPy implementations. All examples are also provided as commented and didactic Python (Jupyter) notebooks that can be used as starting points for crystallographers curious to enter the Python ecosystem or wishing to accelerate their existing codes.

The growing use of Information and Communication Technology (ICT) services is producing an increasing amount of greenhouse gas (GHG) emissions. New research has proposed a network model spanning Europe, USA and Canada that uses ‘cloud computing’ to supply renewable energy to IT data centres.

The growing use of Information and Communication Technology (ICT) services is producing an increasing amount of greenhouse gas (GHG) emissions. New research has proposed a network model spanning Europe, USA and Canada that uses ‘cloud computing’ to supply renewable energy to IT data centres.

It's time to quit multitasking. Plug in and sharpen your attention with these four meditative programs.

A growing number of businesses are moving to the cloud for everything from applications to data storage, but how secure is our data in the cloud?

Citation Twitter For more about this, go here. Find out more at this site. Keywords: Washington dc server hosting, Cloud solutions, It managed services, Dedicated managed hosting, Boston business phone system, Seattle server hosting. Graphics: Share This Image

The post The Three Most Prevalent Cloud Computing Myths Debunked appeared first on RSS News Feed.

For decades, organizations have tried to unlock the collective knowledge contained within their people and systems. And the challenge is getting harder, since every year, massive amounts of additional information are created for people to share. We've reached a point at which individuals are unable consume, understand, or even find half the information that is available to them.

The templates enable a holistic approach to analyzing data across marketing tools

We present results showing the capability of concrete-based information processing substrate in the signal classification task in accordance with in materio computing paradigm. As the Reservoir Computing is a suitable model for describing embedded in materio computation, we propose that this type of presented basic construction unit can be used as a source for "reservoir of states" necessary for simple tuning of the readout layer. In that perspective, buildings constructed from computing concrete could function as a highly parallel information processor for smart architecture. We present an electrical characterization of the set of samples with different additive concentrations followed by a dynamical analysis of selected specimens showing fingerprints of memfractive properties. Moreover, on the basis of obtained parameters, classification of the signal waveform shapes can be performed in scenarios explicitly tuned for a given device terminal.

Rescue vessels are the main actors in maritime safety and rescue operations. At the same time, aerial drones bring a significant advantage into this scenario. This paper presents the research directions of the AutoSOS project, where we work in the development of an autonomous multi-robot search and rescue assistance platform capable of sensor fusion and object detection in embedded devices using novel lightweight AI models. The platform is meant to perform reconnaissance missions for initial assessment of the environment using novel adaptive deep learning algorithms that efficiently use the available sensors and computational resources on drones and rescue vessel. When drones find potential objects, they will send their sensor data to the vessel to verity the findings with increased accuracy. The actual rescue and treatment operation are left as the responsibility of the rescue personnel. The drones will autonomously reconfigure their spatial distribution to enable multi-hop communication, when a direct connection between a drone transmitting information and the vessel is unavailable.

In this technical report we give an elementary introduction to Quantum Computing for non-physicists. In this introduction we describe in detail some of the foundational Quantum Algorithms including: the Deutsch-Jozsa Algorithm, Shor's Algorithm, Grocer Search, and Quantum Counting Algorithm and briefly the Harrow-Lloyd Algorithm. Additionally we give an introduction to Solomonoff Induction, a theoretically optimal method for prediction. We then attempt to use Quantum computing to find better algorithms for the approximation of Solomonoff Induction. This is done by using techniques from other Quantum computing algorithms to achieve a speedup in computing the speed prior, which is an approximation of Solomonoff's prior, a key part of Solomonoff Induction. The major limiting factors are that the probabilities being computed are often so small that without a sufficient (often large) amount of trials, the error may be larger than the result. If a substantial speedup in the computation of an approximation of Solomonoff Induction can be achieved through quantum computing, then this can be applied to the field of intelligent agents as a key part of an approximation of the agent AIXI.

Homomorphic encryption (HE) allows direct computations on encrypted data. Despite numerous research efforts, the practicality of HE schemes remains to be demonstrated. In this regard, the enormous size of ciphertexts involved in HE computations degrades computational efficiency. Near-memory Processing (NMP) and Computing-in-memory (CiM) - paradigms where computation is done within the memory boundaries - represent architectural solutions for reducing latency and energy associated with data transfers in data-intensive applications such as HE. This paper introduces CiM-HE, a Computing-in-memory (CiM) architecture that can support operations for the B/FV scheme, a somewhat homomorphic encryption scheme for general computation. CiM-HE hardware consists of customized peripherals such as sense amplifiers, adders, bit-shifters, and sequencing circuits. The peripherals are based on CMOS technology, and could support computations with memory cells of different technologies. Circuit-level simulations are used to evaluate our CiM-HE framework assuming a 6T-SRAM memory. We compare our CiM-HE implementation against (i) two optimized CPU HE implementations, and (ii) an FPGA-based HE accelerator implementation. When compared to a CPU solution, CiM-HE obtains speedups between 4.6x and 9.1x, and energy savings between 266.4x and 532.8x for homomorphic multiplications (the most expensive HE operation). Also, a set of four end-to-end tasks, i.e., mean, variance, linear regression, and inference are up to 1.1x, 7.7x, 7.1x, and 7.5x faster (and 301.1x, 404.6x, 532.3x, and 532.8x more energy efficient). Compared to CPU-based HE in a previous work, CiM-HE obtain 14.3x speed-up and >2600x energy savings. Finally, our design offers 2.2x speed-up with 88.1x energy savings compared to a state-of-the-art FPGA-based accelerator.

A method for computer-implemented unit-conversion method, the method comprising identifying a first numerical value in a first system of units displayed on a computing device, converting the first numerical value in the first system of units into a second numerical value, and displaying the second numerical value and the second system of units on the computing device.

A system (200) and a method (100) of operating a computing device to perform memoization are disclosed. The method includes determining whether a result of a function is stored in a cache and, if so, retrieving the result from the cache and, if not, calculating the result and storing it in the cache. The method (100) includes transforming (104) by the computing device at least one selected from the input parameters and the output parameters of the function, the transforming being based on an analysis of the function and its input arguments to establish whether or not there is a possible relationship reflecting redundancy among the input parameters and output parameters of the function. The transforming may include at least one of: use of symmetry, scaling, linear shift, interchanging of variables, inversion, polynomial and/or trigonometric transformations, spectral or logical transformations, fuzzy transformations, and systematic arrangement of parameters.

A portable or mobile computing device, such as a smart phone or portable media player, can be used to control one or more electronic devices over an appropriate wireless channel. In one example, a user can utilize a smart phone as a mouse for a notebook computer or Internet-capable television. The user can move the portable device on a surface and press appropriate selectable elements on the portable device, as if the user is using a wireless mouse. The portable device can send the commands over the wireless channel to the electronic device, which can provide inputs and/or control signals to the electronic device. In some embodiments, the user can take advantage of the processing capability of the portable device to work directly with elements such as a wireless keyboard and wireless monitor, without the need for a notebook or other such computing element therebetween.

In one embodiment, the invention provides a method of managing a computing job based on a job priority and a submitter quota.

A cloud system may create physical resource tags to store relationships between cloud computing offerings, such as computing service offerings, storage offerings, and network offerings, and the specific physical resources in the cloud computing environment. Cloud computing offerings may be presented to cloud customers, the offerings corresponding to various combinations of computing services, storage, networking, and other hardware or software resources. After a customer selects one or more cloud computing offerings, a cloud resource manager or other component within the cloud infrastructure may retrieve a set of tags and determine a set of physical hardware resources associated with the selected offerings. The physical hardware resources associated with the selected offerings may be subsequently used to provision and create the new virtual machine and its operating environment.

A computing section is provided with a plurality of computing units and correlatively stores entries of configuration information that describes configurations of the plurality of computing units with physical configuration numbers that represent the entries of configuration information and executes a computation in a configuration corresponding to a designated physical configuration number. A status management section designates a physical configuration number corresponding to a status to which the computing section needs to advance the next time for the computing section and outputs the status to which the computing section needs to advance the next time as a logical status number that uniquely identifies the status to which the computing section needs to advance the next time in an object code. A determination section determines whether or not the computing section has stored an entry of configuration information corresponding to the status to which the computing section needs to advance the next time based on the logical status number that is output from the status management section. A rewriting section correlatively stores the entry of the configuration information and a physical configuration number corresponding to the entry of the configuration information in the computing section when the determination section determines that the computing section has not stored the entry of configuration information corresponding to the status to which the computing section needs to advance the next time.