Localization and delocalization errors in density functional theory and implications for band-gap prediction

The band-gap problem and other systematic failures of approximate functionals are explained from an analysis of total energy for fractional charges. The deviation from the correct intrinsic linear behavior in finite systems leads to delocalization and localization errors in large or bulk systems. Functionals whose energy is convex for fractional charges such as LDA display an incorrect apparent linearity in the bulk limit, due to the delocalization error. Concave functionals also have an incorrect apparent linearity in the bulk calculation, due to the localization error and imposed symmetry. This resolves an important paradox and opens the possibility to obtain accurate band-gaps from DFT.Comment: 4 pages 4 figure

Evolutionary Algorithm Aided Interleaver Design for Serially Concatenated Codes

In this paper, we propose an algorithm for designing the interleavers of Serially Concatenated Codes (SCCs), in order to increase the Minimum Hamming Distance (MHD) between the legitimate permutations of the encoded bit sequence and hence to improve the corresponding error floor. Unlike previous so-called Code Matched Interleaver (CMI) designs, our approach is capable of creating interleavers for serial concatenations of both irregular and non-linear codes, as well as achieving MHDs that are arbitrarily close to the maximum possible, provided that a sufficiently high off-line complexity is affordable. However, owing to the efficiency of the proposed approach, only a relatively low number of algorithm generations are required to achieve significant improvements to the error floor of low-delay wireless sensor network, speech and audio schemes, for example. Indeed, we demonstrate that our interleavers are capable of completely eradicating the error floors that would otherwise be apparent, if classic random or S-random interleavers were employed

Procedural error monitoring and smart checklists

Human beings make and usually detect errors routinely. The same mental processes that allow humans to cope with novel problems can also lead to error. Bill Rouse has argued that errors are not inherently bad but their consequences may be. He proposes the development of error-tolerant systems that detect errors and take steps to prevent the consequences of the error from occurring. Research should be done on self and automatic detection of random and unanticipated errors. For self detection, displays should be developed that make the consequences of errors immediately apparent. For example, electronic map displays graphically show the consequences of horizontal flight plan entry errors. Vertical profile displays should be developed to make apparent vertical flight planning errors. Other concepts such as energy circles could also help the crew detect gross flight planning errors. For automatic detection, systems should be developed that can track pilot activity, infer pilot intent and inform the crew of potential errors before their consequences are realized. Systems that perform a reasonableness check on flight plan modifications by checking route length and magnitude of course changes are simple examples. Another example would be a system that checked the aircraft's planned altitude against a data base of world terrain elevations. Information is given in viewgraph form

Programming Safety Tips: Why You Should Use Immutable Objects or How to create programs with bugs that can never be found or fixed.

Program safety deals with how to make programs as error free as possible. The hardest errors in a program for a programmer to find are often errors in using memory. There are two reasons for this. The first is that errors in accessing memory almost never show problems in the proximate area of the program where the error is made. The error has no apparent impact when it is made, but often causes catastrophic results to occur much later in the program, in areas of the program unrelated to memory error that caused it. The second reason memory errors are so difficult to find is that the working of memory is often poorly understood by most novice, and many professional, programmers. This makes it difficult for many programmers to even understand why an action causes the error. This article will show an example of a program error that can easily occur when memory access is poorly understood. This leads to program errors that are very easy to fix when they are found, but extremely difficult to find. The article will then explain how many memory errors can be easily avoided by following the very simple rule, “Make all object immutable unless there is a good reason to make them mutable”, and why immutable objects are an essential tool in good, safe programming practice

Improved rotor position estimation in extended back-EMF based sensorless PM brushless AC drives with magnetic saliency

An improved extended back-EMF based sensorless control method is proposed for a brushless AC motor equipped with an interior permanent magnet rotor. It accounts for dq-axis cross-coupling magnetic saturation by introducing an apparent mutual winding inductance. The error which results in the estimated rotor position when the influence of cross-coupling magnetic saturation is neglected is analyzed analytically, predicted by finite element analysis, and confirmed experimentally, for various d- and q-axis currents. It is shown that a significant improvement in the accuracy of the rotor position estimation can be achieved by the proposed method, as confirmed by measurements