Stored Data Values Research Articles

AgYields - a national database for collation of past, present and future pasture and crop yield data

The New Zealand agricultural sector has a rich heritage of measuring yield and growth rates for pastures and crops. Historically these datasets were collected by Government departments, Crown research institutes, Universities and more latterly seed companies and private research providers as well as on-farm. These data are expensive to collect, spatially and temporally patchy, and stored in a range of electronic and physical platforms. Meanwhile the potential value of such data is increasing with the ability to create meta-analyses and simulation modelling to create resilience in crop and pasture systems to meet the needs of the changing regulatory and climate environment. A challenge of data collection is the different priorities and skill sets of those undertaking the task. Thus, there is a need to provide guidelines for the collection, collation and publication of such data to standardize best practice and maximize the value gained from increasingly scarce resources available for pasture and crop research to support the primary industries. In addition, declining funding for field research, means there is an urgent need to draw together existing and future data into a publicly accessible industry good resource. This paper outlines the development of the AgYields web-based repository for pasture and crop growth rate and yield data. It describes the rationale for the database and the need for standardization of data collection to maximize the value of stored data in common formats. The intent is to provide a resource to enhance livestock and crop production systems throughout New Zealand and provide guidelines for future data collection.

Задача выбора вычислительных процессов, обеспечивающих защиту информации, для серверов распределенной системы и алгоритмы ее решения

Purpose: providing information security on servers of various destinations of an automated system based on the formulation of an optimization task setting for selecting auxiliary processes for information protection, developing and researching algorithms for solving this problem. Method: To solve the problem, the authors propose two exact algorithms for incomplete search with exponential computational complexity, based on the ideas of the Balash method. One algorithm starts with a solution consisting of all ones, and the second algorithm starts with a solution consisting of all zeros. Also proposed are two approximate algorithms with polynomial complexity, based on the ideas of the “greedy” algorithm, one algorithm starts the search from a zero solution, the other from all-one solution. Result: Mathematical model and algorithms for solving the problem of selecting processes to protect information in conditions of limited computing resources of servers. The process selection model is a Boolean programming problem with a non-linear quality indicator and linear constraints. The indicator provides an estimate of the damage prevented when using the selected processes, taking into account the probability or possibility of various attacks on servers, the value of stored data, and the probability of protection from attacks using processes. During the experiments, recommendations were developed for choosing one of two algorithms (search starting from the zero solution and search starting from all-one solution) among pairs of exact and approximate algorithms depending on the availability of resources in order to reduce the time to solve the problem.

Reasoning about integrity constraints for tree-structured data

We study a class of integrity constraints for tree-structured data modelled as data trees, whose nodes have a label from a finite alphabet and store a data value from an infinite data domain. The constraints require each tuple of nodes selected by a conjunctive query (using navigational axes and labels) to satisfy a positive combination of equalities and a positive combination of inequalities over the stored data values. Such constraints are instances of the general framework of XML-to-relational constraints proposed recently by Niewerth and Schwentick. They cover some common classes of constraints, including W3C XML Schema key and unique constraints, as well as domain restrictions and denial constraints, but cannot express inclusion constraints, such as reference keys. Our main result is that consistency of such integrity constraints with respect to a given schema (modelled as a tree automaton) is decidable. An easy extension gives decidability for the entailment problem. Equivalently, we show that validity and containment of unions of conjunctive queries using navigational axes, labels, data equalities and inequalities is decidable, as long as none of the conjunctive queries uses both equalities and inequalities; without this restriction, both problems are known to be undecidable. In the context of XML data exchange, our result can be used to establish decidability for a consistency problem for XML schema mappings. All the decision procedures are doubly exponential, with matching lower bounds. The complexity may be lowered to singly exponential, when conjunctive queries are replaced by tree patterns, and the number of data comparisons is bounded.

Verification of heap manipulating programs with ordered data by extended forest automata

We present a general framework for verifying programs with complex dynamic linked data structures whose correctness depends on ordering relations between stored data values. The underlying formalism of our framework is that of forest automata (FA), which has previously been developed for verification of heap-manipulating programs. We extend FA with constraints between data elements associated with nodes of the heaps represented by FA, and we present extended versions of all operations needed for using the extended FA in a fully-automated verification approach, based on abstract interpretation. We have implemented our approach as an extension of the Forester tool and successfully applied it to a number of programs dealing with data structures such as various forms of singly- and doubly-linked lists, binary search trees, as well as skip lists.

Neighbor-cell assisted error correction for MLC NAND flash memories

Continued scaling of NAND flash memory to smaller process technology nodes decreases its reliability, necessitating more sophisticated mechanisms to correctly read stored data values. To distinguish between different potential stored values, conventional techniques to read data from flash memory employ a single set of reference voltage values, which are determined based on the overall threshold voltage distribution of flash cells. Unfortunately, the phenomenon of program interference, in which a cell's threshold voltage unintentionally changes when a neighboring cell is programmed, makes this conventional approach increasingly inaccurate in determining the values of cells. This paper makes the new empirical observation that identifying the value stored in the immediate-neighbor cell makes it easier to determine the data value stored in the cell that is being read. We provide a detailed statistical and experimental characterization of threshold voltage distribution of flash memory cells conditional upon the immediate-neighbor cell values, and show that such conditional distributions can be used to determine a set of read reference voltages that lead to error rates much lower than when a single set of reference voltage values based on the overall distribution are used. Based on our analyses, we propose a new method for correcting errors in a flash memory page, neighbor-cell assisted correction (NAC). The key idea is to re-read a flash memory page that fails error correction codes (ECC) with the set of read reference voltage values corresponding to the conditional threshold voltage distribution assuming a neighbor cell value and use the re-read values to correct the cells that have neighbors with that value. Our simulations show that NAC effectively improves flash memory lifetime by 33% while having no (at nominal lifetime) or very modest (less than 5% at extended lifetime) performance overhead.

Low Power Spin-Transfer Magnetoresistive Random Access Memory Writing Scheme with Selective Word Line Bootstrap

We describe a new writing scheme with a selective word line bootstrap for spin-transfer magnetoresistive random access memory (MRAM). Applying spin-transfer switching to MRAM, its writing power consumption decreases and its memory cell area is also reduced. However, during write operation, the required bit line cramp voltage for stored data switching depends on the value of stored data, magnetic tunnel junction (MTJ) characteristics, and switching current direction. Therefore, the bit line voltage must be optimized to minimize the power consumption. With the proposed scheme, word line voltage is varied according to the value of writing data in order to decrease the threshold bit line voltage. Furthermore, the spin-transfer MRAM resistance model with reading and writing operations was successfully implemented for the circuit simulation. From the simulation results, it was found that writing threshold bit line bias during writing operation can decrease from 17 to 28% with the proposed selective bootstrap. Also, more than 25% of the cell transistor gate width can be decreased. This result shows that the proposed writing scheme is effective in reducing power consumption, and can also reduce the MRAM cell area.

Silent stores and store value locality

Value locality, a recently discovered program attribute that describes the likelihood of the recurrence of previously seen program values, has been studied enthusiastically in the recent published literature. Much of the energy has focused on refining the initial efforts at predicting load instruction outcomes, with the balance of the effort examining the value locality of either all register-writing instructions or a focused subset of them. Surprisingly, there has been very little published characterization of or effort to exploit the value locality of data words stored to memory by computer programs. This paper presents such a characterization, including detailed source-level analysis of the causes of silent stores, proposes both memory-centric (based on message passing) and producer-centric (based on program structure) prediction mechanisms for stored data values, introduces the concept of silent stores and new definitions of multiprocessor false sharing based on these observations, and suggests new techniques for aligning cache coherence protocols and microarchitectural store handling techniques to exploit the value locality of stores. We find that realistic implementations of these techniques can significantly reduce multiprocessor data bus traffic and are more effective at reducing address bus traffic than the addition of Exclusive state to a MS I coherence protocol. We also show that squashing of silent stores can provide uniprocessor speedups greater than the addition of store-to-load forwarding.

On the value locality of store instructions

Value locality, a recently discovered program attribute that describes the likelihood of the recurrence of previously-seen program values, has been studied enthusiastically in the recent published literature. Much of the energy has focused on refining the initial efforts at predicting load instruction outcomes, with the balance of the effort examining the value locality of either all register-writing instructions, or a focused subset of them. Surprisingly, there has been very little published characterization of or effort to exploit the value locality of data words stored to memory by computer programs. This paper presents such a characterization, proposes both memory-centric (based on message passing) and producer-centric (based on program structure) prediction mechanisms for stored data values, introduces the concept of silent stores and new definitions of multiprocessor false sharing based on these observations, and suggests new techniques for aligning cache coherence protocols and microarchitectural store handling techniques to exploit the value locality of stores. We find that realistic implementations of these techniques can significantly reduce multiprocessor data bus traffic and are more effective at reducing address bus traffic than the addition of Exclusive state to a MSI coherence protocol. We also show that squashing of silent stores can provide uniprocessor speedups greater than the addition of store-to-load forwarding.

Typed query languages for databases containing queries

This paper introduces and studies the relational meta algebra, a statically typed extension of the relational algebra to allow for meta programming in databases. In this meta algebra one can manipulate database relations involving not only stored data values (as in classical relational databases) but also stored relational algebra expressions. Topics discussed include modeling of advanced database applications involving “procedural data” ; desirability as well as limitations of a strict typing discipline in this context; equivalence with a first-order calculus; and global expressive power and non-redundancy of the proposed formalism.

Apparatus and method for equalizing a soundfield

Apparatus for equalizing a soundfield comprises an amplifier and a gain control circuit for selectively adjusting the gain of the amplifier as a function of frequency in response to data values received by the gain control circuit. The apparatus has power supply terminals for supplying operating current from an external power source to the amplifier and the gain control circuit. In addition, the apparatus comprises an electronic storage device for storing data values and applying those data values to the gain control circuit. The stored data values are maintained in the apparatus upon interruption of the supply of operating current to the power supply terminals. The apparatus has an input port for applying data values to the storage device, and does not have manually actuable controls for selectively adjusting the stored data values.