OpenRaiser/Intern-Atlas huggingface dataset:
A High-Level Reconfigurable Computing Platform Software Frameworks
Venue: arXiv cs.AR 2004
Year: 2004

Reconfigurable computing refers to the use of processors, such as Field Programmable Gate Arrays (FPGAs), that can be modified at the hardware level to take on different processing tasks. A reconfigurable computing platform describes the hardware and software base on top of which modular extensions can be created, depending on the desired application. Such reconfigurable computing platforms can take on varied designs and implementations, according to the constraints imposed and features desired by the scope of applications. This paper introduces a PC-based reconfigurable computing platform software frameworks that is flexible and extensible enough to abstract the different hardware types and functionality that different PCs may have. The requirements of the software platform, architectural issues addressed, rationale behind the decisions made, and frameworks design implemented are discussed.
Data Mining Approach for Analyzing Call Center Performance
Venue: arXiv cs.AI 2004
Year: 2004

The aim of our research was to apply well-known data mining techniques (such as linear neural networks, multi-layered perceptrons, probabilistic neural networks, classification and regression trees, support vector machines and finally a hybrid decision tree neural network approach) to the problem of predicting the quality of service in call centers; based on the performance data actually collected in a call center of a large insurance company. Our aim was two-fold. First, to compare the performance of models built using the above-mentioned techniques and, second, to analyze the characteristics of the input sensitivity in order to better understand the relationship between the perform-ance evaluation process and the actual performance and in this way help improve the performance of call centers. In this paper we summarize our findings.
Hybrid Fuzzy-Linear Programming Approach for Multi Criteria Decision Making Problems
Venue: arXiv cs.AI 2004
Year: 2004

The purpose of this paper is to point to the usefulness of applying a linear mathematical formulation of fuzzy multiple criteria objective decision methods in organising business activities. In this respect fuzzy parameters of linear programming are modelled by preference-based membership functions. This paper begins with an introduction and some related research followed by some fundamentals of fuzzy set theory and technical concepts of fuzzy multiple objective decision models. Further a real case study of a manufacturing plant and the implementation of the proposed technique is presented. Empirical results clearly show the superiority of the fuzzy technique in optimising individual objective functions when compared to non-fuzzy approach. Furthermore, for the problem considered, the optimal solution helps to infer that by incorporating fuzziness in a linear programming model either in constraints, or both in objective functions and constraints, provides a similar (or even better) level of satisfaction for obtained results compared to non-fuzzy linear programming.
Computing Multi-Homogeneous Bezout Numbers is Hard
Venue: arXiv cs.CC 2004
Year: 2004

The multi-homogeneous Bezout number is a bound for the number of solutions of a system of multi-homogeneous polynomial equations, in a suitable product of projective spaces. Given an arbitrary, not necessarily multi-homogeneous system, one can ask for the optimal multi-homogenization that would minimize the Bezout number. In this paper, it is proved that the problem of computing, or even estimating the optimal multi-homogeneous Bezout number is actually NP-hard. In terms of approximation theory for combinatorial optimization, the problem of computing the best multi-homogeneous structure does not belong to APX, unless P = NP. Moreover, polynomial time algorithms for estimating the minimal multi-homogeneous Bezout number up to a fixed factor cannot exist even in a randomized setting, unless BPP contains NP.
Encryption Schemes using Finite Frames and Hadamard Arrays
Venue: arXiv cs.CR 2004
Year: 2004

We propose a cipher similar to the One Time Pad and McEliece cipher based on a subband coding scheme. The encoding process is an approximation to the One Time Pad encryption scheme. We present results of numerical experiments which suggest that a brute force attack to the proposed scheme does not result in all possible plaintexts, as the One Time Pad does, but still the brute force attack does not compromise the system. However, we demonstrate that the cipher is vulnerable to a chosen-plaintext attack.
Analysis of Hybrid Soft and Hard Computing Techniques for Forex Monitoring Systems
Venue: arXiv cs.AI 2004
Year: 2004

In a universe with a single currency, there would be no foreign exchange market, no foreign exchange rates, and no foreign exchange. Over the past twenty-five years, the way the market has performed those tasks has changed enormously. The need for intelligent monitoring systems has become a necessity to keep track of the complex forex market. The vast currency market is a foreign concept to the average individual. However, once it is broken down into simple terms, the average individual can begin to understand the foreign exchange market and use it as a financial instrument for future investing. In this paper, we attempt to compare the performance of hybrid soft computing and hard computing techniques to predict the average monthly forex rates one month ahead. The soft computing models considered are a neural network trained by the scaled conjugate gradient algorithm and a neuro-fuzzy model implementing a Takagi-Sugeno fuzzy inference system. We also considered Multivariate Adaptive Regression Splines (MARS), Classification and Regression Trees (CART) and a hybrid CART-MARS technique. We considered the exchange rates of Australian dollar with respect to US dollar, Singapore dollar, New Zealand dollar, Japanese yen and United Kingdom pounds. The models were trained using 70% of the data and remaining was used for testing and validation purposes. It is observed that the proposed hybrid models could predict the forex rates more accurately than all the techniques when applied individually. Empirical results also reveal that the hybrid hard computing approach also improved some of our previous work using a neuro-fuzzy approach.
Adaptation of Mamdani Fuzzy Inference System Using Neuro - Genetic Approach for Tactical Air Combat Decision Support System
Venue: arXiv cs.AI 2004
Year: 2004

Normally a decision support system is build to solve problem where multi-criteria decisions are involved. The knowledge base is the vital part of the decision support containing the information or data that is used in decision-making process. This is the field where engineers and scientists have applied several intelligent techniques and heuristics to obtain optimal decisions from imprecise information. In this paper, we present a hybrid neuro-genetic learning approach for the adaptation a Mamdani fuzzy inference system for the Tactical Air Combat Decision Support System (TACDSS). Some simulation results demonstrating the difference of the learning techniques and are also provided.
Security-Performance Tradeoffs of Inheritance based Key Predistribution for Wireless Sensor Networks
Venue: arXiv cs.NI 2004
Year: 2004

Key predistribution is a well-known technique for ensuring secure communication via encryption among sensors deployed in an ad-hoc manner to form a sensor network. In this paper, we propose a novel 2-Phase technique for key predistribution based on a combination of inherited and random key assignments from the given key pool to individual sensor nodes. We also develop an analytical framework for measuring security-performance tradeoffs of different key distribution schemes by providing metrics for measuring sensornet connectivity and resiliency to enemy attacks. In particular, we show analytically that the 2-Phase scheme provides better average connectivity and superior $q$-composite connectivity than the random scheme. We then prove that the invulnerability of a communication link under arbitrary number of node captures by an adversary is higher under the 2-Phase scheme. The probability of a communicating node pair having an exclusive key also scales better with network size under the 2-Phase scheme. We also show analytically that the vulnerability of an arbitrary communication link in the sensornet to single node capture is lower under 2-Phase assuming both network-wide as well as localized capture. Simulation results also show that the number of exclusive keys shared between any two nodes is higher while the number of $q$-composite links compromised when a given number of nodes are captured by the enemy is smaller under the 2-Phase scheme as compared to the random one.
Prediction with Expert Advice by Following the Perturbed Leader for General Weights
Venue: arXiv cs.LG 2004
Year: 2004

When applying aggregating strategies to Prediction with Expert Advice, the learning rate must be adaptively tuned. The natural choice of sqrt(complexity/current loss) renders the analysis of Weighted Majority derivatives quite complicated. In particular, for arbitrary weights there have been no results proven so far. The analysis of the alternative "Follow the Perturbed Leader" (FPL) algorithm from Kalai (2003} (based on Hannan's algorithm) is easier. We derive loss bounds for adaptive learning rate and both finite expert classes with uniform weights and countable expert classes with arbitrary weights. For the former setup, our loss bounds match the best known results so far, while for the latter our results are (to our knowledge) new.
Traffic Accident Analysis Using Decision Trees and Neural Networks
Venue: arXiv cs.AI 2004
Year: 2004

The costs of fatalities and injuries due to traffic accident have a great impact on society. This paper presents our research to model the severity of injury resulting from traffic accidents using artificial neural networks and decision trees. We have applied them to an actual data set obtained from the National Automotive Sampling System (NASS) General Estimates System (GES). Experiment results reveal that in all the cases the decision tree outperforms the neural network. Our research analysis also shows that the three most important factors in fatal injury are: driver's seat belt usage, light condition of the roadway, and driver's alcohol usage.
Mathematical and programming toolkit of the computer aided design of the axonometric piping diagrams
Venue: arXiv cs.CE 2004
Year: 2004

The problem of the automation of the designing of the axonometric piping diagrams include, as the minimum, manipulations with the flat schemas of three-dimensional wireframe objects (with dimension of 2,5). The specialized model, methodical and mathematical approaches are required because of large bulk of calculuss. Coordinate systems, data types, common principles of realization of operation with data and composition of the basic operations are described which are realised in the complex CAD system of the reconstruction of the plants TechnoCAD GlassX.
Neighborhood-Based Topology Recognition in Sensor Networks
Venue: arXiv cs.DS 2004
Year: 2004

We consider a crucial aspect of self-organization of a sensor network consisting of a large set of simple sensor nodes with no location hardware and only very limited communication range. After having been distributed randomly in a given two-dimensional region, the nodes are required to develop a sense for the environment, based on a limited amount of local communication. We describe algorithmic approaches for determining the structure of boundary nodes of the region, and the topology of the region. We also develop methods for determining the outside boundary, the distance to the closest boundary for each point, the Voronoi diagram of the different boundaries, and the geometric thickness of the network. Our methods rely on a number of natural assumptions that are present in densely distributed sets of nodes, and make use of a combination of stochastics, topology, and geometry. Evaluation requires only a limited number of simple local computations.
Efficiency Enhancement of Probabilistic Model Building Genetic Algorithms
Venue: arXiv cs.NE 2004
Year: 2004

This paper presents two different efficiency-enhancement techniques for probabilistic model building genetic algorithms. The first technique proposes the use of a mutation operator which performs local search in the sub-solution neighborhood identified through the probabilistic model. The second technique proposes building and using an internal probabilistic model of the fitness along with the probabilistic model of variable interactions. The fitness values of some offspring are estimated using the probabilistic model, thereby avoiding computationally expensive function evaluations. The scalability of the aforementioned techniques are analyzed using facetwise models for convergence time and population sizing. The speed-up obtained by each of the methods is predicted and verified with empirical results. The results show that for additively separable problems the competent mutation operator requires O(k 0.5 logm)--where k is the building-block size, and m is the number of building blocks--less function evaluations than its selectorecombinative counterpart. The results also show that the use of an internal probabilistic fitness model reduces the required number of function evaluations to as low as 1-10% and yields a speed-up of 2--50.
Designing Competent Mutation Operators via Probabilistic Model Building of Neighborhoods
Venue: arXiv cs.NE 2004
Year: 2004

This paper presents a competent selectomutative genetic algorithm (GA), that adapts linkage and solves hard problems quickly, reliably, and accurately. A probabilistic model building process is used to automatically identify key building blocks (BBs) of the search problem. The mutation operator uses the probabilistic model of linkage groups to find the best among competing building blocks. The competent selectomutative GA successfully solves additively separable problems of bounded difficulty, requiring only subquadratic number of function evaluations. The results show that for additively separable problems the probabilistic model building BB-wise mutation scales as O(2^km^{1.5}), and requires O(k^{0.5}logm) less function evaluations than its selectorecombinative counterpart, confirming theoretical results reported elsewhere (Sastry & Goldberg, 2004).
Note on Counting Eulerian Circuits
Venue: arXiv cs.CC 2004
Year: 2004

We show that the problem of counting the number of Eulerian circuits in an undirected graph is complete for the class #P.
Aspects de la Programmation d'Applications Win32 avec un Langage Fonctionnel
Venue: arXiv cs.PL 2004
Year: 2004

A useful programming language needs to support writing programs that take advantage of services and communication mechanisms supplied by the operating system. We examine the problem of programming native Win32 applications under Windows with Standard ML. We introduce an framework based on the IDL interface language et a minimal foreign-functions interface to explore the Win32 API et COM in the context of Standard ML.
The Design of a COM-Oriented Module System
Venue: arXiv cs.PL 2004
Year: 2004

We present in this paper the preliminary design of a module system based on a notion of components such as they are found in COM. This module system is inspired from that of Standard ML, and features first-class instances of components, first-class interfaces, and interface-polymorphic functions, as well as allowing components to be both imported from the environment and exported to the environment using simple mechanisms. The module system automates the memory management of interfaces and hides the IUnknown interface and QueryInterface mechanisms from the programmer, favoring instead a higher-level approach to handling interfaces.
Learning Hybrid Algorithms for Vehicle Routing Problems
Venue: arXiv cs.PL 2004
Year: 2004

This paper presents a generic technique for improving hybrid algorithms through the discovery of and tuning of meta-heuristics. The idea is to represent a family of push/pull heuristics that are based upon inserting and removing tasks in a current solution, with an algebra. We then let a learning algorithm search for the best possible algebraic term, which represents a hybrid algorithm for a given set of problems and an optimization criterion. In a previous paper, we described this algebra in detail and provided a set of preliminary results demonstrating the utility of this approach, using vehicle routing with time windows (VRPTW) as a domain example. In this paper we expand upon our results providing a more robust experimental framework and learning algorithms, and report on some new results using the standard Solomon benchmarks. In particular, we show that our learning algorithm is able to achieve results similar to the best-published algorithms using only a fraction of the CPU time. We also show that the automatic tuning of the best hybrid combination of such techniques yields a better solution than hand tuning, with considerably less effort.
Web search engine based on DNS
Venue: arXiv cs.NI 2004
Year: 2004

Now no web search engine can cover more than 60 percent of all the pages on Internet. The update interval of most pages database is almost one month. This condition hasn't changed for many years. Converge and recency problems have become the bottleneck problem of current web search engine. To solve these problems, a new system, search engine based on DNS is proposed in this paper. This system adopts the hierarchical distributed architecture like DNS, which is different from any current commercial search engine. In theory, this system can cover all the web pages on Internet. Its update interval could even be one day. The original idea, detailed content and implementation of this system all are introduced in this paper.
An analysis of a bounded resource search puzzle
Venue: arXiv cs.DS 2004
Year: 2004

Consider the commonly known puzzle, given $k$ glass balls, find an optimal algorithm to determine the lowest floor of a building of $n$ floors from which a thrown glass ball will break. This puzzle was originally posed in its original form in \cite{focs1980}and was later cited in the book \cite{algthc}. There are several internet sites that presents this puzzle and its solution to the special case of $k=2$ balls. This is the first such analysis of the puzzle in its general form. Several variations of this puzzle have been studied with applications in Network Loading \cite{cgstctl} which analyzes a case similar to a scenario where an adversary is changing the lowest floor with time. Although the algorithm specified in \cite{algthc} solves the problem, it is not an efficient algorithm. In this paper another algorithm for the same problem is analyzed. It is shown that if $m$ is the minimum number of attempts required then for $k \geq m$ we have $m = \log (n+1)$ and for $k < m$ we have, $1 + \sum_{i=1}^{k}{{m-1}\choose{i}} < n \leq \sum_{i=1}^{k}{{m}\choose{i}}$
Algorithms for weighted multi-tape automata
Venue: arXiv cs.CL 2004
Year: 2004

This report defines various operations for weighted multi-tape automata (WMTAs) and describes algorithms that have been implemented for those operations in the WFSC toolkit. Some algorithms are new, others are known or similar to known algorithms. The latter will be recalled to make this report more complete and self-standing. We present a new approach to multi-tape intersection, meaning the intersection of a number of tapes of one WMTA with the same number of tapes of another WMTA. In our approach, multi-tape intersection is not considered as an atomic operation but rather as a sequence of more elementary ones, which facilitates its implementation. We show an example of multi-tape intersection, actually transducer intersection, that can be compiled with our approach but not with several other methods that we analysed. To show the practical relavance of our work, we include an example of application: the preservation of intermediate results in transduction cascades.
Dichotomy Theorems for Alternation-Bounded Quantified Boolean Formulas
Venue: arXiv cs.CC 2004
Year: 2004

In 1978, Schaefer proved his famous dichotomy theorem for generalized satisfiability problems. He defined an infinite number of propositional satisfiability problems, showed that all these problems are either in P or NP-complete, and gave a simple criterion to determine which of the two cases holds. This result is surprising in light of Ladner's theorem, which implies that there are an infinite number of complexity classes between P and NP-complete (under the assumption that P is not equal to NP). Schaefer also stated a dichotomy theorem for quantified generalized Boolean formulas, but this theorem was only recently proven by Creignou, Khanna, and Sudan, and independently by Dalmau: Determining truth of quantified Boolean formulas is either PSPACE-complete or in P. This paper looks at alternation-bounded quantified generalized Boolean formulas. In their unrestricted forms, these problems are the canonical problems complete for the levels of the polynomial hierarchy. In this paper, we prove dichotomy theorems for alternation-bounded quantified generalized Boolean formulas, by showing that these problems are either $Σ_i^p$-complete or in P, and we give a simple criterion to determine which of the two cases holds. This is the first result that obtains dichotomy for an infinite number of classes at once.
O(1) Reversible Tree Navigation Without Cycles
Venue: arXiv cs.PL 2004
Year: 2004

Imperative programmers often use cyclically linked trees in order to achieve O(1) navigation time to neighbours. Some logic programmers believe that cyclic terms are necessary to achieve the same in logic-based languages. An old but little-known technique provides O(1) time and space navigation without cyclic links, in the form of reversible predicates. A small modification provides O(1) amortised time and space editing.
Uncovering the epistemological and ontological assumptions of software designers
Venue: arXiv cs.SE 2004
Year: 2004

The ontological and epistemological positions adopted by information systems design methods are incommensur-able when pushed to their extremes. Information systems research has therefore tended to focus on the similarities between different positions, usually in search of a single, unifying position. However, by focusing on the similari-ties, the clarity of argument provided by any one philoso-phical position is necessarily diminished. Consequently, researchers often treat the philosophical foundations of design methods as being of only minor importance. In this paper, we have deliberately chosen to focus on the differences between various philosophical positions. From this focus, we believe we can offer a clearer under-standing of the empirical behaviour of software as viewed from particular philosophical positions. Since the em-pirical evidence does not favour any single position, we conclude by arguing for the validity of ad hoc approaches to software design which we believe provides a stronger and more theoretically grounded approach to software design.