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Ever since the birth of coding theory almost 60 years ago, researchers have been pursuing the elusive goal of constructing the "best codes," whose encoding introduces the minimum possible redundancy for the level of noise they can correct. In this article, we survey recent progress in list decoding that has led to efficient error-correction schemes with an optimal amount of redundancy, even against worst-case errors caused by a potentially malicious channel. To correct a proportion ρ (say 20%) of worst-case errors, these codes only need close to a proportion ρ of redundant symbols. The redundancy cannot possibly be any lower information theoretically. This new method holds the promise of correcting a factor of two more errors compared to the conventional algorithms currently in use in diverse everyday applications. [ABSTRACT FROM AUTHOR]

The article focuses on storing data inside the volume of the recording medium, rather than on its surface, as in conventional optical and magnetic approaches. These systems deliver much higher data-transfer rates and access based on partial information. Holographic data storage records information in the form of volumetric gratings within the volume of the recording medium. In digital holographic storage, information is typically encoded in the form of 2-dimension pixelated images that include 2-dimension modulation coding, data shuffling and error correction. A multitude of holograms can be recorded in virtually the same volume through angular, wavelength or shift-and-correlation multiplexing techniques. Unlike conventional storage techniques, holographic data storage uses the entire volume, rather than just the surface, of the recording medium, greatly increasing potential data density. The page organization of such memory provides tremendous parallelism, resulting in far greater data-transfer rates than in conventional optical or magnetic storage.

The article describes Computer Science Unplugged, an activity program designed to teach introductory computer science concepts including parity and error detection, computational thinking, and data compression to children.

This article focuses on the problem of levels in error-message generation in interactive software systems. Most computer users are not familiar with how their systems work beyond a certain level of operations. Consequently, there is often a problem with error-message generation in interactive software systems. Such problems of file creation error often occur at a program execution level unknown to the user. Many computer users have probably experienced these kinds of error messages. The problem with these messages is that, among many other things, they are signaled by a lower level operation that has been invoked by the user command without the user being aware of it. The difficulties in error-message generation in such cases arise because a lower level operation can be invoked by many different user commands that serve radically different user intentions. An error message signaled at any level is designed with the assumption that the receiver is the caller of that operation. There is, of course, nothing wrong with this assumption if the command is activated by the user. The trouble occurs when the user is not the caller of that operation.

Examines the detection of combined occurrences for a large number of changes of values of variables. Description of the two efficient solutions for the combined occurrences; Properties of the methods; Error analysis for the second method.

Evaluates the propagation of variance technique of the sensitivity of time-varying systems on initial condition and parameter error. Determination of system-dependent partial derivatives matrices; Use of Wengert differentiation technique; Application of the method on trajectory estimation.

This article examines the code structure used for preventing errors during identification of partition symbols which separate one character from another. Variability in item length occur under two circumstances: first, when an item contains a variable number of characters with each character consisting of a fixed number of bits and when an item contains a variable or fixed number of characters with each character being made up of a variable number of bits. Since present day computers are designed for manipulation of fixed-length characters, the first scheme is the most popular. When items vary in size, additional information must be provided that specifies either the dimensions of the items or their starting addresses in the memory. There exist a number of ways to provide this control information, the most popular are the partitioned representation, the grid-matrix representation and the chained representation. Since any error in the control information makes the identification of subsequent items either impossible or very expensive, a method of reinforcing the control information against errors is proposed. The method is illustrated for the partitioned representation, with obvious extension for the other schemes.

The article presents the error that occurred in the codes of an algorithm in an experiment. The algorithm B is considered to have the greatest potential for error. The process of selecting the bit codes used in the activity is also seen as a way to reduce the possibility of error. Careful choosing of bit codes is believed to reduce the error instead of randomly choosing it. Moreover, large number of computer words are regarded to be useful in the activity. A part of a well-developed theory of error-correcting codes is also planned to be applied.

Secondary clustering as a cause of hash code inefficiency is discussed, and a new hashing method based on its elimination is presented. Comparisons with previous methods are made both analytically and empirically. [ABSTRACT FROM AUTHOR]

The article discusses another article in the issue which presents the results of research in the area of error-correcting codes built on Reed-Solomon codes. Error-correcting codes are tools used to compensate for interference in communication, the author states, as well as being essential for accuracy in digital data storage.