Code of practice for learning analytics

Setting out the responsibilities of educational institutions to ensure that learning analytics is carried out responsibly, appropriately and effectively.

Code-switching, Metalinguistics, and Translation in a Bilingual/Bicultural Novel: Sandra Cisneros' Caramelo or Puro Cuento

Raquel Merino Álvarez, José Miguel Santamaría, Eterio Pajares (eds.)

Final Supplemental Environmental Document Pacific herring commercial fishing regulations (Sections 163, 163.1, and 164, Title 14, California Code of Regulations)

(PDF contains 63 pages.)

Code de Conduite pour une Peche Responsable

La pêche, y compris l'aquaculture, apporte une contribution fondamentale à l'alimentation, à l'emploi, aux loisirs, au commerce et au bien-être économique des populations du monde entier, qu'il s'agisse des générations présentes ou futures, et devrait, par conséquent, être conduite de manière responsable. Le présent Code définit des principes et des normes internationales de comportement pour garantir des pratiques responsables en vue d'assurer effectivement la conservation, la gestion et le développement des ressources bioaquatiques, dans le respect des écosystèmes et de la biodiversité. Le Code reconnaît l'importance nutritionnelle, économique, sociale, environnementale et culturelle de la pêche et les intérêts de tous ceux qui sont concernés par ce secteur. Le Code prend en considération les caractéristiques biologiques des ressources et de leur environnement, ainsi que les intérêts des consommateurs et autres utilisateurs. Les Etats et tous ceux impliqués dans le secteur de la pêche sont encouragés à appliquer ce Code de manière effective. (PDF contains 53 pages)

What is the Code of Conduct for Responsible Fisheries?

(PDF contains 17 pages)

Qu'est-ce que le Code de Conduite pour une Peche Responsable?

(PDF contains 19 pages)

Coding for information storage

Storage systems are widely used and have played a crucial rule in both consumer and industrial products, for example, personal computers, data centers, and embedded systems. However, such system suffers from issues of cost, restricted-lifetime, and reliability with the emergence of new systems and devices, such as distributed storage and flash memory, respectively. Information theory, on the other hand, provides fundamental bounds and solutions to fully utilize resources such as data density, information I/O and network bandwidth. This thesis bridges these two topics, and proposes to solve challenges in data storage using a variety of coding techniques, so that storage becomes faster, more affordable, and more reliable.

We consider the system level and study the integration of RAID schemes and distributed storage. Erasure-correcting codes are the basis of the ubiquitous RAID schemes for storage systems, where disks correspond to symbols in the code and are located in a (distributed) network. Specifically, RAID schemes are based on MDS (maximum distance separable) array codes that enable optimal storage and efficient encoding and decoding algorithms. With r redundancy symbols an MDS code can sustain r erasures. For example, consider an MDS code that can correct two erasures. It is clear that when two symbols are erased, one needs to access and transmit all the remaining information to rebuild the erasures. However, an interesting and practical question is: What is the smallest fraction of information that one needs to access and transmit in order to correct a single erasure? In Part I we will show that the lower bound of 1/2 is achievable and that the result can be generalized to codes with arbitrary number of parities and optimal rebuilding.

We consider the device level and study coding and modulation techniques for emerging non-volatile memories such as flash memory. In particular, rank modulation is a novel data representation scheme proposed by Jiang et al. for multi-level flash memory cells, in which a set of n cells stores information in the permutation induced by the different charge levels of the individual cells. It eliminates the need for discrete cell levels, as well as overshoot errors, when programming cells. In order to decrease the decoding complexity, we propose two variations of this scheme in Part II: bounded rank modulation where only small sliding windows of cells are sorted to generated permutations, and partial rank modulation where only part of the n cells are used to represent data. We study limits on the capacity of bounded rank modulation and propose encoding and decoding algorithms. We show that overlaps between windows will increase capacity. We present Gray codes spanning all possible partial-rank states and using only ``push-to-the-top'' operations. These Gray codes turn out to solve an open combinatorial problem called universal cycle, which is a sequence of integers generating all possible partial permutations.