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This paper aims to reduce the worst-case crosstalk effects for resistance, inductance and capacitance (RLC) interconnects using the bus encoding technique. In current nanoscale technology, power dissipation, propagation delay and crosstalk performance of interconnects determine the overall performance of a chip. Signal integrity issues due to crosstalk in the form of voltage glitches, overshoots, undershoots, undesirable noise, propagation speed ups and downs, etc. are some of the major deterrents for high-performance RLC modelled (VLSI) interconnects. This research paper primarily proposes two novel encoding methods (I and II) for RLC modelled interconnects to reduce the effect of crosstalk, simultaneous switching noise (SSN) and power consumption.

The proposed methods are based on the bus encoding method that is effective and well-suited for the reduction of the crosstalk noise. This method encodes or transforms incoming data in a manner that encoded data contain minimum or no crosstalk effects. The proposed encoding method uses the bus invert (BI) method. The proposed encoding methods are able to avoid the worst-case crosstalks while consuming lesser power during transmission in VLSI interconnects.

It is observed that the proposed encoders reduced/eliminated the worst-case crosstalk by reducing SSN. The encoding method I also reduces Type 0 crosstalk by 100 per cent, while Type 1 crosstalk is reduced by 36.4 per cent and Type 2 is reduced by 16.8 per cent. The average simultaneous switching is reduced by 51.1 per cent. Similarly, encoding method II reduces switching activity by 10.3 per cent, whereas the coupling activity is reduced by 35.4 per cent. Furthermore, encoding method II also reduced Type 0, Type 1 and Type 2 crosstalk by 100, 36.9 and 27.1 per cent, respectively. Hence, the proposed encoding methods reduced the worst-case crosstalk completely.

In VLSI technology, the reduction in feature size and the increase in operating frequency are quite rapid. This leads to higher propagation delay, crosstalk and power dissipation through the interconnects. Most of the previously proposed encoders/decoders have turned out to be unsuitable for RLC modelled interconnects. Hence, the proposed encoder would be extremely useful for crosstalk reduction in newer operating conditions.

The encoding method I identifies the harsh crosstalks, that is Type 0 and Type 1, in the inverted and non-inverted forms of incoming data with respect to the previous data. The data having minimum crosstalk in the inverted and non-inverted forms are only sent through the transmission line. The encoding method I also removes the worst-case crosstalk and simultaneously reduces other mild crosstalks. The removal of worst-case crosstalk improves the overall performance of the interconnect. The encoding method II identifies Type 2 crosstalk along with Type 0 and Type 1 similar to encoding method I. Furthermore, the encoding method II exhibits an improvement over method I in terms of reduction in crosstalk and power dissipation.

This paper proposes a novel encoding method to reduce worst-case crosstalk effects that reduces SSN. The proposed encoding methods achieve their purpose of crosstalk reduction for several technology nodes.

Motivation significantly influences learning and memory. While a long history of research has focused on simple forms of associative learning, such as Pavlovian conditioning, recent research is beginning to characterize how motivation influences episodic memory. In this chapter we synthesize findings across behavioral, cognitive, and educational neuroscience to characterize motivation’s influence on memory. We provide evidence that neural systems underlying motivation, namely the mesolimbic dopamine system, interact with and facilitate activity within systems underlying episodic memory, centered on the medial temporal lobes. We focus on two mechanisms of episodic memory enhancement: encoding and consolidation. Together, the reviewed research supports an adaptive model of memory in which an individual’s motivational state (i.e., learning under states of reward or punishment) shapes the nature of memory representations in service of future goals. The impact of motivation on learning and memory, therefore, has very clear implications for and applications to educational settings.

This column aims to examine the role of text encoding, specifically Unicode, in modern digital library applications. It also seeks to examine the technical aspects of Unicode and how they impact those applications.

This column is simply exploratory, and examines issues regarding Unicode, text encoding in general, and what librarians should be aware of concerning technical aspects of the Unicode standard.

The paper finds that Unicode is the bedrock of all metadata in modern digital library applications. An awareness of how to identify and perform conversions on that data is critical to the support of these applications. Many aspects of functionality in forthcoming information resource tools will rely upon a familiarity with the technical aspects of Unicode.

This column explains the salient technical features of Unicode for those who may not be familiar with its inner workings. It also takes into account the impact text encoding has on the functionality of modern library applications.

In previous experiments where negotiators' fairness judgments have been found to be egocentrically biased, it is possible that the observed bias was caused largely by selective encoding of the background information given to negotiators. The extent to which egocentric fairness judgments were caused by selective encoding, however, cannot be determined from those experiments. In the present study, we tested for the effects of selective encoding by varying the point in time that negotiators learned their role in a simulated wage dispute. Results indicated that, while judgments of a fair settlement point were the most egocentric under conditions that allowed for selective encoding, these conditions were not necessary for the bias to occur; there was a significant degree of egocentric bias even when there was no possibility of selective encoding. Implications of these results for both research and practice are discussed.

The paper aims to describe an electronic text project involving a scholarly history journal, and to share findings related to the encoding of serials using the text encoding interchange (TEI) guidelines.

The project was completed using a combination of in‐house and outsourced digitization and encoding, employing a variety of methods for quality control and encoding guidelines creation.

Evidence is provided that certain types of encoding should be done in‐house, and describes a variety of mechanisms for capturing granular metadata in serials projects.

The paper covers a number of areas, including serials encoding using the TEI and granular metadata capture, which have not been explored elsewhere in the literature. It also provides guidance for others undertaking similar electronic text projects.

The genetic algorithm (GA) technique is widely used for the optimization of stiffened composite panels. It is based on sequential execution of a number of specific operators, including the encoding of particular design variables. For instance, in the case of a stiffened composite panel, the design variables that need to be encoded are: the number of plies and their stacking sequences in the panel skin and stiffeners. This paper aims to present a novel, implicit, heuristic approach for encoding composite laminates and, through its use, demonstrates an improvement in the optimization process.

The stiffened panel optimization has been formulated as a constrained discrete minimum-weight design problem. GAs, which use both new encoding schemes and those previously described in the literature, have been used to find near-optimal solutions to the formulated problem. The influence of the new encoding scheme on the searching capabilities of the GA has been investigated using comparative analysis of the optimization results.

The new encoding scheme allows the definition of stacking sequences in composites using shorter symbolic representations as compared with standard encoding operators and, as a result of this, a reduction in the problem design space. According to numerical experiments performed in this work, this feature enables GA to obtain near-optimal designs using smaller population sizes than those required if standard encoding schemes are used.

The approach to encoding laminates presented in this paper is based on the original heuristics. In the context of GA-based optimization of stiffened composite panels, the use of the new approach rather than the standard encoding technique can lead to a significant reduction in computational time employed.

The purpose of this case study is to describe a multi-year text encoding initiative (TEI) project that took place in the McGill University Library, Rare Books and Special Collections.

Early nineteenth century English language chapbooks from the collection were digitized, and the proofed text files were encoded in TEI, following Best Practices for TEI in Libraries (2011).

The project coordinator describes the TEI file structure and customizations for the project to support a distinct subject classification of the chapbooks and the encoding of the woodcut illustrations using the Iconclass classification.

The authors focus on procedures, use of TEI data elements and encoding challenges.

This paper documents the project workflow and provides a possible model for future digital humanities projects.

The graduate students who participated in the TEI encoding learned a new suite of skills involving extensible markup language (XML) file structure and the application of a markup language that requires interpretation.

The McGill Library Chapbook Project Web site, launched in 2013 now provides access to 933 full-text works.

Presents some basic features for encoding spoken texts with the TEI (text encoding initiative) scheme. Highlights the reasons for encoding spoken texts and gives a brief history of text encoding development. An example is used to demonstrate how to encode a simple transcription using the TEI scheme. Pros and cons of text encoding are also discussed. Creating TEI‐conformant transcriptions with XML provides the possibility for researchers to retrieve original recordings via hyper‐textual pages to look for specific (or partial) features that were not included in the transcription.

In this paper, a set of safe adaptive genetic algorithms (sGAs) is proposed based on the Splicing/Decomposable encoding scheme and the efficient speed‐up strategies developed by Xu et al.. The proposed algorithms implement the self‐adaptation of the problem representation, selection and recombination operators at the levels of population, individual and component which commendably balance the conflicts between “reliability” and “efficiency”, as well as “exploitation” and “exploration” existed in the evolutionary algorithms. It is shown that the algorithms converge to the optimum solution in probability one. The proposed sGAs are experimentally compared with the classical genetic algorithm (CGA), non‐uniform genetic algorithm (nGA) proposed by Michalewicz, forking genetic algorithm (FGA) proposed by Tsutsui et al. and the classical evolution programming (CEP). The experiments indicate that the new algorithms perform much more efficiently than CGA and FGA do, comparable with the real‐coded GAs — nGA and CEP. All the algorithms are further evaluated through an application to a difficult real‐life application problem: the inverse problem of fractal encoding related to fractal image compression technique. The results for the sGA is better than those of CGA and FGA, and has the same, sometimes better performance compared to those of nGA and CEP.

The aim of this paper is to describe the Rosarium Project which is currently curating nonfiction materials about the genus Rosa written at the turn of the twentieth century and published in popular American periodicals. This is achieved by encoding the texts following the guidelines set forth by the Text Encoding Initiative Consortium (TEI).

This paper explains what text encoding is and why following the guidelines set forth by the TEI Consortium was the best choice for the Rosarium Project. It then goes on to outline the workflow and choices made by the principal researcher which are needed to move the project steadily forward.

The principal researcher on the Rosarium Project has found that encoding with the TEI was easy to learn and fun to do, as well as intellectually stimulating. Librarians should find text-encoding projects of their own specialist subjects equally doable.

The Rosarium Project is unique, in that it is curating early twentieth century articles on the subject of roses that appeared in popular magazines. These materials are hidden away in online repositories and libraries worldwide. This project is of value, in that it provides primary sources to researchers in areas of popular culture, horticulture and garden history and also acts as an example of what librarians can contribute to the Digital Humanities.