Narrow Results

The spatial and temporal locality of reference on which cache memory relies to minimize cache swaps, is exploited to design a new algorithm for finite automaton string recognition. It is shown that the algorithm, referred to as the Dynamic State Allocation algorithm outperforms the traditional table-driven algorithm for strings that tend to repeatedly access the same set of states, provided that the string is long enough to amortize the allocation cost. Further improvements on the algorithm result in even better performance.

The branch of coding theory that is based on formal languages has produced several methods for defining code properties, including word relations, dependence systems, implicational conditions, trajectories, and language inequations. Of those, the latter three can be viewed as formal methods in the sense that a certain formal expression can be used to denote a code property. Here we present a formal method which is based on transducers. Each transducer of a certain type defines/describes a desired code property. The method provides simple and uniform decision procedures for the basic questions of property satisfaction and maximality for regular languages. Our work includes statements about the hardness of deciding some of the problems involved. It turns out that maximality can be hard to decide even for "classical" code properties of finite languages. We also present an initial implementation of a LAnguage SERver capable of deciding the satisfaction problem for a given transducer code property and regular language.

The essential variables in a finite function f are defined as variables which occur in f and weigh with the values of that function. The number of essential variables is an important measure of complexity for discrete functions. When replacing some variables in a function with constants the resulting functions are called subfunctions, and when replacing all essential variables in a function with constants we obtain an implementation of this function. Such an implementation corresponds with a path in an ordered decision diagram (ODD) of the function which connects the root with a leaf of the diagram. The sets of essential variables in subfunctions of f are called separable in f. In this paper we study several properties of separable sets of variables in functions which directly affect the number of implementations and subfunctions in these functions.

We define equivalence relations which classify the functions of k-valued logic into classes with the same number of: (i) implementations; (ii) subfunctions; and (iii) separable sets. These relations induce three transformation groups which are compared with the lattice of all subgroups of restricted affine group (RAG). This allows us to solve several important computational and combinatorial problems.

We show how a non-local quantum CNOT with (N-1)-target operation can be implemented with unit fidelity and unit probability by using a N-qubit maximally entangled GHZ state as quantum channel. We also put forward two schemes for probabilistic implementing the operation with unit fidelity by employing a partially entangled pure GHZ state as quantum channel. The overall physical resources required for accomplishing these schemes are different, and the successful implementation probabilities are also different. We also point out the non-local CNOT with (N-1)-target operation can be used as a purification protocol to concentrate entanglement from an ensemble of partially entangled GHZ states into a subensemble of maximally entangled ones.

We present a systematic simple method for constructing non-local quantum conditional rotation with single target and multiple targets operations. We firstly show how a non-local conditional rotation with single target operation can be implemented with unit fidelity and unit probability by using a maximally entangled pair as quantum channel. We also put forward a scheme for probabilistically implementing the operation with unit fidelity by employing a partially entangled pair as quantum channel. The required physical resources for implementation of the non-local operation in these two cases are discussed. We further consider non-local conditional rotation with multiple targets operations on N spatially distributed systems, and show that the number of possible distinct operations increases here exponentially, with the available number of entangled pairs that are initially distributed between systems. We also point out that the non-local conditional rotation operation can be used to generate multiparticle entanglement between particles belonging to distant users in a communication network and distributed quantum computer.

Four operands Real Multiply Accumulation (4op-RMA) is a method to implement transversal circuits, direct form circuits and 2D type circuits with real coefficients by using a complex multiplier. Digital Signal Processors (DSPs) with 4op-RMA implement these circuits twice as fast as the conventional ones. Besides, we can simplify the programs on such DSPs. However 4op-RMA have not been applied to the lattice circuits yet because of their circuit structures. In this paper, we propose an implementation method for the lattice circuits by using 4op-RMA. The lattice part can be calculated by a 4op-RMA operation, which corresponds to a complex multiplication.

This paper presents a video transmission system for scalable High-Efficiency Video Coding (HEVC) videos using a 4G standard’s physical layer. SHVC, the scalable HEVC is used to compress the different layers of videos into binary files. The resultant binary files are easily transportable over any network thus solving many issues mainly related to videos with high resolutions. Three scenarios are studied and simulated at first, namely, Single Input Single Output (SISO), Multiple Input Single Output (MISO) and MIMO. Since the MIMO scenario offers the best results, it is considered in the implementation of the system on Field Programmable Gate Array (FPGA) using Xilinx System Generator (XSG). A Simulink model is developed under Matlab to simulate the video transmission scenarios using the WIMAX physical layer. Then, the MIMO system is implemented using a Zed-Board to co-simulate the video transmission in real-time and which allows a successful reception of the video sequences.

Space-Time Adaptive Processing (STAP) can harness the efficacy of interference and clutter significantly. Calculations of the STAP weights involve solving linear equations which require very intensive computations. In this paper, the QR decomposition (QRD) using the modified gram-schmidt (MGS) algorithm is parameterized with vector size to create a trade-off between the hardware resources utilization and computation time. To achieve an efficient floating point structure, the proposed architecture of QRD-MGS algorithm is simulated and implemented in two modes: single-vector and multi-vector. Results show that the multi-vector method can lead to a high-performance design with higher operating frequency, lower power consumption, and less resource utilization than the single-vector method. For example, Modelism simulations show that the decomposition of a $12\times 51$ matrix with vector size of 17 takes 7.86$\mu$s with the maximum clock frequency of 282MHz, for implementation on the Arria10 FPGA. In real STAP applications, the matrix sizes are too large to be fit on FPGAs and the update rate of the weights are high. Therefore, this method can fit any matrix in the contemporary FPGAs with an acceptable update rate.

In this study, a second-generation positive current conveyor (CCII+)-based analog circuit is proposed for the electronic implementation of a different dynamical system which is an adaptation of the chaotic Lorenz differential equation set. The proposed circuit is more cost-effective and contains less active and passive elements than the circuit obtained by applying the classical parallel synthesis method with opamps. Mathematical analyses and SPICE simulations are performed for chaotic phase portraits and bifurcation diagrams. The proposed dynamical circuit is implemented on the board by using commercially available active and passive elements on the market and an experimental study is conducted. In order to demonstrate the usability of this proposed circuit in secure communication studies, three different synchronization methods are applied and one of them is implemented. The obtained experimental results are in good agreement with the mathematical analysis and simulation results.

The Security policy of a software system is a set of actions that the system should or should not do in given conditions. These actions can be considered as critical properties in many applications which require high level of safety, such as the military, bank or stock software systems. Security policy must be specified clearly in software requirements and then be followed strictly and correctly in implementations. User permission policy is one of the most important aspects in software security policy. This paper proposes an approach for checking the conformance between user permissions of an implementation and their given specifications. In this approach, the source code of a program is represented at an abstraction level called Abstract Syntax Tree, which are then checked against specification of user permissions expressed using Role-Based Access Control (RBAC). A checking tool has been developed and verified using several common examples.

We present fast implementations of a hybrid algorithm for reporting box and cube intersections. Our algorithm initially takes a divide-and-conquer approach and switches to simpler algorithms for low numbers of boxes. We use our implementations as engines to solve problems about geometric primitives. We look at two such problems in the category of quality analysis of surface triangulations.

This paper presents an implementation for Delaunay triangulations of three-dimensional point sets. The code uses a variant of the randomized incremental flip algorithm and employs symbolic perturbation to achieve robustness. The algorithm's theoretical time complexity is quadratic in n, the number of input points, and this is optimal in the worst case. However, empirical running times are proportional to the number of triangles in the final triangulation, which is typically linear in n. Even though the symbolic perturbation scheme relies on exact arithmetic, the resulting code is efficient in practice. This is due to a careful implementation of the geometric primitives and the arithmetic module. The source code is available on the Internet.

Let $p$ be a prime and let $ℂ$ be the complex field. We explicitly classify the finite solvable irreducible monomial subgroups of $\mathrm{\text{GL}}(p,ℂ)$ up to conjugacy. That is, we give a complete and irredundant list of $\mathrm{\text{GL}}(p,ℂ)$-conjugacy class representatives as generating sets of monomial matrices. Copious structural information about non-solvable finite irreducible monomial subgroups of $\mathrm{\text{GL}}(p,ℂ)$ is also proved, enabling a classification of all such groups bar one family. We explain the obstacles in that exceptional case. For $p\le 3$, we classify all finite irreducible subgroups of $\mathrm{\text{GL}}(p,ℂ)$. Our classifications are available publicly in MAGMA.

For many years, the non-montonic reasoning community has focussed on highly expressive logics. Such logics have turned out to be computationally expensive, and have given little support to the practical use of non-monotonic reasoning. In this work we discuss defeasible logic, a less-expressive but more efficient non-monotonic logic. We report on two new implemented systems for defeasible logic: a query answering system employing a backward-chaining approach, and a forward-chaining implementation that computes all conclusions. Our experimental evaluation demonstrates that the systems can deal with large theories (up to hundreds of thousands of rules). We show that defeasible logic has linear complexity, which contrasts markedly with most other non-monotonic logics and helps to explain the impressive experimental results. We believe that defeasible logic, with its efficiency and simplicity, is a good candidate to be used as a modeling language for practical applications, including modelling of regulations and business rules.

In this paper we present a new method that uses data-flow coherence constraints in definite logic program generation. We outline three main advantages of these constraints supported by our results: i) drastically pruning the search space (around 90%), ii) reducing the set of positive examples and reducing or even removing the need for the set of negative examples, and iii) allowing the induction of predicates that are difficult or even impossible to generate by other methods. Besides these constraints, the approach takes into consideration the program termination condition for recursive predicates. The paper outlines some theoretical issues and implementation aspects of our system for automatic logic program induction.

The Lexicographic Path Ordering (LPO) poses an interesting problem to the implementor: How to achieve a version that is both efficient and correct? The method of program transformation helps us to develop an efficient version step-by-step, making clear the essential ideas, while retaining correctness. By theoretical analysis we show that the worst-case behavior is thereby changed from exponential to polynomial. Detailed measurements show the practical improvements of the different variants. They allow us to assess experimentally various optimizations suggested for LPO.

Substantial research exists on quality management practices in context to large organisations with plethora of studies in manufacturing organisations while exiguously aiming service sector SMEs. As more and more organisations strive to remain competitive, the concepts and practices of quality management have received increased attention by Indian industry. The contribution of service sector in Indian economy has increased at a faster rate in comparison with other sectors. Considering the pressing need this research explores the literature for a near exhaustive list of practices in quality management by deploying qualitative and descriptive approach. Thereafter, twenty service organizations were surveyed for comprehending their adoption of the type of quality management practices. On the basis of their prioritization or apportioning weight to those practices, a descriptive pattern analysis has been deployed to detect perceived level of adoption/implementation of quality management practices. The findings represent that out of twenty one quality management practices; thirteen practices substantially have been ranked on priority while others require phenomenal acclimatization towards implementation in the Indian scenario. Analysis also reflects that the strength of service SMEs lies with customer focus, management leadership and customer feedback. Further with the integration of contextual factors, as supported by theory, a conceptual framework has been proposed exhibiting relationship between quality management practices with performance and growth. The methodological approach led to the emergence of unique dimensions culminating into new findings with both managerial and entrepreneurial implications. Directions for future scope of research and suggestions for improvement have also been recommended.

In this article we describe what a credit spread option (CSO) is and show a tree algorithm to price it. The tree algorithm we have opted for is a two factor model composed by a Hull and White (HW) one factor for the interest rate process and a Black-Karazinsky (BK) one factor for the default intensity. As opposed to the tree model of Schonbucher 1999 the intensity process cannot become negative. Having as input the risk free yield curve and market implied default probability curve the model by construction will price correctly the associated defaultable bond. We then use Market data to calibrate the model to price an at the money (ATM) CSO call and then test it to price an out of the money (OTM) Bermudan CSO call on a CDS. Furthermore the discussions in this paper show in practice the difficulties and challenges faced by financial institutions in marking to market those instruments.

Knowledge management (KM) is a business discipline that is currently dominated by large businesses. SMEs are generally trailing behind them in terms of applying KM principles. Various frameworks have been developed and reported in the literature, but they possess drawbacks. The characteristics, features and needs of SMEs are often not reflected in them. This paper introduces a framework for implementing KM in the SME sector, which is centred on six major themes: the types of knowledge to be managed, the socio-technical perspective of KM, the formation of a KM coordinating group, the initiatives to be implemented, a guide to deploying these initiatives, and the tools and techniques to support them. A pilot study involving a small group of academics and practitioners in the KM field was used to make a preliminary assessment of it prior to testing it in SMEs. Overall, their evaluation indicated a positive view towards the framework.

This study tested the influences of change novelty, participation and goal setting on organisational learning. The study was conducted following the strategic reorientation of a large telecommunication firm. Major findings were: (1) Participation in strategic change is positively related to organisational learning; (2) the use of goal setting as part of the implementation process enhances organisational learning; and (3) medium and high levels of change novelty is associated with higher levels of learning than low levels of change novelty.