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A dial box is a computer peripheral for direct 3D manipulation e.g. to interactively input the rotation and torsion angles of a model displayed on a computer screen. Dial boxes were common input tools in the first years of interactive 3D graphics and they were available for Silicon Graphics (SGI) or Sun Microsystems and sold with their workstations. Currently they have been replaced by standard computer mouse interaction techniques.

Standard dial box has 8 dials mounted on a plate. The plate is set upright with the help of a stand and usually located next to the computer screen for convenient access. The connection to a computer is made via the serial port (RS-232).

One of the fields of application for dial boxes was molecular graphics.

Bubble memory is a type of non-volatile computer memory that uses a thin film of a magnetic material to hold small magnetized areas, known as bubbles or domains, each storing one bit of data. The material is arranged to form a series of parallel tracks that the bubbles can move along under the action of an external magnetic field. The bubbles are read by moving them to the edge of the material, where they can be read by a conventional magnetic pickup, and then rewritten on the far edge to keep the memory cycling through the material. In operation, bubble memories are similar to delay-line memory systems.

Bubble memory started out as a promising technology in the 1970s, offering performance similar to core memory, memory density similar to hard drives, and no moving parts. This led many to consider it a contender for a "universal memory" that could be used for all storage needs. The introduction of dramatically faster semiconductor memory chips in the early 1970s pushed bubble into the slow end of the scale and it began to be considered mostly as a replacement for disks. The equally dramatic improvements in hard-drive capacity through the early 1980s made it uncompetitive in price terms for mass storage.

Bubble memory was used for some time in the 1970s and 1980s in applications where its non-moving nature was desirable for maintenance or shock-proofing reasons. The introduction of flash storage and similar technologies rendered even this niche uncompetitive, and bubble disappeared entirely by the late 1980s.

Rambus DRAM (RDRAM), and its successors Concurrent Rambus DRAM (CRDRAM) and Direct Rambus DRAM (DRDRAM), are types of synchronous dynamic random-access memory (SDRAM) developed by Rambus from the 1990s through to the early 2000s. The third-generation of Rambus DRAM, DRDRAM was replaced by XDR DRAM. Rambus DRAM was developed for high-bandwidth applications and was positioned by Rambus as replacement for various types of contemporary memories, such as SDRAM. RDRAM is a serial memory bus.

DRDRAM was initially expected to become the standard in PC memory, especially after Intel agreed to license the Rambus technology for use with its future chipsets. Further, DRDRAM was expected to become a standard for graphics memory. However, RDRAM got embroiled in a standards war with an alternative technology—DDR SDRAM—and quickly lost out on grounds of price and, later, performance. By around 2003, DRDRAM was no longer supported in new personal computers.

Holographic data storage is a potential technology in the area of high-capacity data storage. While magnetic and optical data storage devices rely on individual bits being stored as distinct magnetic or optical changes on the surface of the recording medium, holographic data storage records information throughout the volume of the medium and is capable of recording multiple images in the same area utilizing light at different angles.

Additionally, whereas magnetic and optical data storage records information a bit at a time in a linear fashion, holographic storage is capable of recording and reading millions of bits in parallel, enabling data transfer rates greater than those attained by traditional optical storage.

The syntax of the Python programming language is the set of rules that defines how a Python program will be written and interpreted (by both the runtime system and by human readers). The Python language has many similarities to Perl, C, and Java. However, there are some definite differences between the languages.

The floppy disk is a data storage and transfer medium that was ubiquitous from the mid-1970s well into the 2000s. Besides the 3½-inch and 5¼-inch formats used in IBM PC compatible systems, or the 8-inch format that preceded them, many proprietary floppy disk formats were developed, either using a different disk design or special layout and encoding methods for the data held on the disk.

Design rule for Camera File system (DCF) is a JEITA specification (number CP-3461) which defines a file system for digital cameras, including the directory structure, file naming method, character set, file format, and metadata format. It is currently the de facto industry standard for digital still cameras. The file format of DCF conforms to the Exif specification, but the DCF specification also allows use of any other file formats.

The latest version of the standard is 2.0 (2010 edition).

The UNIX-HATERS Handbook is a semi-humorous edited compilation of messages to the UNIX-HATERS mailing list. The book was edited by Simson Garfinkel, Daniel Weise and Steven Strassmann and published in 1994.

Project Looking Glass is a now inactive free software project under the GPL to create an innovative 3D desktop environment for Linux, Solaris, and Windows. It was sponsored by Sun Microsystems.

Looking Glass is programmed in the Java language using the Java 3D system to remain platform independent. Despite the use of graphics acceleration features, the desktop explores the use of 3D windowing capabilities for both existing application programs and ones specifically designed for Looking Glass.

There is a Live CD available from Project Looking Glass. The Looking Glass environment is also included on a Live DVD (FunWorks 2007 edition) from the Granular Linux project.

In computational complexity and optimization the no free lunch theorem is a result that states that for certain types of mathematical problems, the computational cost of finding a solution, averaged over all problems in the class, is the same for any solution method. The name alludes to the saying "no such thing as a free lunch", that is, no method offers a "short cut". This is under the assumption that the search space is a probability density function. It does not apply to the case where the search space has underlying structure (e.g., is a differentiable function) that can be exploited more efficiently (e.g., Newton's method in optimization) than random search or even has closed-form solutions (e.g., the extrema of a quadratic polynomial) that can be determined without search at all. For such probabilistic assumptions, the outputs of all procedures solving a particular type of problem are statistically identical. A colourful way of describing such a circumstance, introduced by David Wolpert and William G. Macready in connection with the problems of search and optimization, is to say that there is no free lunch. Wolpert had previously derived no free lunch theorems for machine learning (statistical inference). Before Wolpert's article was published, Cullen Schaffer independently proved a restricted version of one of Wolpert's theorems and used it to critique the current state of machine learning research on the problem of induction.

In the "no free lunch" metaphor, each "restaurant" (problem-solving procedure) has a "menu" associating each "lunch plate" (problem) with a "price" (the performance of the procedure in solving the problem). The menus of restaurants are identical except in one regard – the prices are shuffled from one restaurant to the next. For an omnivore who is as likely to order each plate as any other, the average cost of lunch does not depend on the choice of restaurant. But a vegan who goes to lunch regularly with a carnivore who seeks economy might pay a high average cost for lunch. To methodically reduce the average cost, one must use advance knowledge of a) what one will order and b) what the order will cost at various restaurants. That is, improvement of performance in problem-solving hinges on using prior information to match procedures to problems.

In formal terms, there is no free lunch when the probability distribution on problem instances is such that all problem solvers have identically distributed results. In the case of search, a problem instance in this context is a particular objective function, and a result is a sequence of values obtained in evaluation of candidate solutions in the domain of the function. For typical interpretations of results, search is an optimization process. There is no free lunch in search if and only if the distribution on objective functions is invariant under permutation of the space of candidate solutions. This condition does not hold precisely in practice, but an "(almost) no free lunch" theorem suggests that it holds approximately.