ppxscal/embedding_network huggingface dataset:
Incremental learning in fuzzy pattern matching
Authors: Moamar Sayed Mouchaweh, Arnaud Devillez, Gerard Villermain Lecolier, Patrice Billaudel
Venue: Fuzzy Sets and Systems (2002)

We use learning methods to build classifiers in using a set of training samples. A classifier is capable to assign a new sample into one of the different learnt classes. In a non-stationary work environment, a classifier must be retrained every time a new sample is classified, to obtain new knowledge from it. This is an impractical solution since it requires the storage of all available samples and a considerable computation time. The development of a classifier that is capable to acquire new knowledge from each new classified sample while preserving the current one is known as incremental learning. Our team of research "Diagnosis of Industrial Processes" works on diagnosis in using fuzzy classification methods for data coming from industrial and medical sectors. We use the Fuzzy Pattern Matching (FPM) as a method of classification and the transformation probability-possibility of Dubois and Prade to construct densities of possibilities. These densities are used to assign each new sample to its suitable class. When FPM works in non-stationary environment, it must update its possibility densities after the classification of each new sample. The goal is to adapt the classifier to the possible changes in the work environment. When the number of samples increases, the update time also increases. Furthermore the memory size required increases to store all the samples. In the literature, there is not any published paper that integrates the incremental learning in FPM. Thus, in this paper, we propose a method to integrate it. Then we show that the update time and the memory size are constant and independent from the number of samples. Finally we illustrate the advantages of this method in using different examples.
A Marketing-Decision-Support Model for Evaluating and Selecting Concepts for New Products
Authors: Nikhil Jain, Anand Paul, Dennis Gensch
Venue: Interfaces (2001)

For a major manufacturer of heating and cooling systems for large buildings, under increasing pressure to produce new product components, I developed a marketing-decision-support model of its process for selecting and developing new products that was comprehensive, objective, and dynamic. This approach is particularly suited for firms that feel the timing (introduction date) of new products significantly affects their sales potential. The firm has relied on this model and its expansions for over 25 years. Marketing-decision-support systems generally utilize a technical structure for dealing with a complex real-world problem. The technical structure is generally provided by a skilled modeler, the reality by experienced line managers dealing with the problem area. This interaction is a critical element in determining the success of real-world marketing-decision-support projects. The modeler must make sure the line managers feel intellectual ownership of the support system.
A classification of BL-algebras
Authors: Michael C. Laskowski, Yvonne V. Shashoua
Venue: Fuzzy Sets and Systems (2002)

We give an algebraic classification of BL-chains, which generalizes to a classification of BL-algebras. Using this, we classify the finite and the finitely universal BL-chains. From these results we strengthen Hájek's Completeness Theorem for BL-logic and give a new proof of the decidability of the set of BL-tautologies.
Preventing plagiarism in computer literacy courses
Authors: Paul D. Wiedemeier
Venue: Journal of Computing Sciences in Colleges (2002)

When students enrolled in a computer literacy course are required to submit assignment for grades, plagiarism may occur. This unethical student behavior requires instructors to address the plagiarism that occurs in their classes. Unfortunately, each incident of plagiarism requires time on the part of the instructor: beyond their regular academic duties. This paper presents a method that truly prevents plagiarism in computer literacy courses, describes an experiment conducted during the Fall Semester 2001, and reviews the results of the experiment.
Creating successful calculus writing assignments
Authors: Kris H. Green
Venue: PRIMUS: problems, resources, and issues in mathematics undergraduate studies (2002)

I discuss three different writing assignments that I have used in my calculus courses. These assignments are introduced with a discussion of purpose and audience. Defining these qualities of an assignment will ensure that writing assignments are more successful. The assignments discussed and explored here represent three different purposes: personal, informational, and a blend of the two. The audiences for these assignments are diverse and force the students to incorporate particular modes of writing that demonstrate much of their thinking. Assessment of student learning as a result of these assignments is discussed. A fourth writing assignment is developed from a basic idea in order to illustrate the use of purpose and audience to create meaningful assignments.
Patterning of W/WNx/poly-Si gate electrode using Cl2/O2 plasmas
Authors: Hyoun-Woo Kim, Byong-Sun Ju, Chang-Jin Kang, Joo-Tae Moon
Venue: Microelectronic Engineering (2003)

The metal gate electrode with a tungsten (W)/tungsten nitride (WNx)/poly-Si structure has been successfully patterned by Cl2/O2 plasmas in a helicon etcher. The patterned metal gate electrode showed an almost vertical profile and no pitting of the gate oxide. The etch selectivity of W over polysilicon (poly-Si) increased with increasing source power, decreasing bias power, and increasing O2/(Cl2 + O2) gas flow ratio. We reveal that W etch rate enhances with increasing temperature.
On Machine Learning Methods for Chinese Document Categorization
Authors: Ji He, Ah-Hwee Tan, Chew-Lim Tan
Venue: Applied Intelligence (2003)

This paper reports our comparative evaluation of three machine learning methods, namely k Nearest Neighbor (kNN), Support Vector Machines (SVM), and Adaptive Resonance Associative Map (ARAM) for Chinese document categorization. Based on two Chinese corpora, a series of controlled experiments evaluated their learning capabilities and efficiency in mining text classification knowledge. Benchmark experiments showed that their predictive performance were roughly comparable, especially on clean and well organized data sets. While kNN and ARAM yield better performances than SVM on small and clean data sets, SVM and ARAM significantly outperformed kNN on noisy data. Comparing efficiency, kNN was notably more costly in terms of time and memory than the other two methods. SVM is highly efficient in learning from well organized samples of moderate size, although on relatively large and noisy data the efficiency of SVM and ARAM are comparable.
Semidefinite programming for discrete optimization and matrix completion problems
Authors: Henry Wolkowicz, Miguel F. Anjos
Venue: Discrete Applied Mathematics (2002)

Semidefinite programming (SDP) is currently one of the most active areas of research in optimization. SDP has attracted researchers from a wide variety of areas because of its theoretical and numerical elegance as well as its wide applicability. In this paper we present a survey of two major areas of application for SDP, namely discrete optimization and matrix completion problems.In the first part of this paper we present a recipe for finding SDP relaxations based on adding redundant constraints and using Lagrangian relaxation. We illustrate this with several examples. We first show that many relaxations for the max-cut problem (MC) are equivalent to both the Lagrangian and the well-known SDP relaxation. We then apply the recipe to obtain new strengthened SDP relaxations for MC as well as known SDP relaxations for several other hard discrete optimization problems.In the second part of this paper we discuss two completion problems, the positive semidefinite matrix completion problem and the Euclidean distance matrix completion problem. We present some theoretical results on the existence of such completions and then proceed to the application of SDP to find approximate completions. We conclude this paper with a new application of SDP to find approximate matrix completions for large and sparse instances of Euclidean distance matrices.
Query processing techniques for arrays
Authors: Arunprasad P. Marathe, Kenneth Salem
Venue: The VLDB Journal &mdash; The International Journal on Very Large Data Bases (2002)

Arrays are a common and important class of data. At present, database systems do not provide adequate array support: arrays can neither be easily defined nor conveniently manipulated. Further, array manipulations are not optimized. This paper describes a language called the Array Manipulation Language (AML), for expressing array manipulations, and a collection of optimization techniques for AML expressions.In the AML framework for array manipulation, arbitrary externally-defined functions can be applied to arrays in a structured manner. AML can be adapted to different application domains by choosing appropriate external function definitions. This paper concentrates on arrays occurring in databases of digital images such as satellite or medical images.AML queries can be treated declaratively and subjected to rewrite optimizations. Rewriting minimizes the number of applications of potentially costly external functions required to compute a query result. AML queries can also be optimized for space. Query results are generated a piece at a time by pipelined execution plans, and the amount of memory required by a plan depends on the order in which pieces are generated. An optimizer can consider generating the pieces of the query result in a variety of orders, and can efficiently choose orders that require less space. An AML-based prototype array database system called ArrayDB has been built, and it is used to show the effectiveness of these optimization techniques.
Model-integrated system development: models, architecture, and process
Authors: Gabor Karsai, Amit Misra, Janos Sztipanovits, Akos Ledeczi, Michael Moore
Venue: Proceedings of the 21st International Computer Software and Applications Conference (1997)

Many large software systems are tightly integrated with their physical environments and must be adapted when their environment changes. Typically, software development methodologies do not place a great emphasis on modeling the system's environment, and hence environmental changes may lead to significant and complicated changes in the software. We argue that (1) the modeling of the environment should be an integral part of the process, and (2) to support software evolution, wherever possible, the software should be automatically generated. We present a model-integrated development approach that is capable of supporting cost effective system evolution in accordance with changes in the system's environment. The approach is supported by a "meta-architecture" that provides a framework for building model-based systems. This framework has been successfully used in various projects. One of these projects, a site-production flow visualization system for a large manufacturing operation, is analyzed in detail.
Experimental Economics and Supply-Chain Management
Authors: Rachel Croson, Karen Donohue
Venue: Interfaces (2002)

One area in which experimental economics methods have been used to study operations problems is supply-chain management. We survey results from a series of human experiments based on the popular beer distribution game and find cognitive limitations on the part of managers, in particular an underweighting of the supply line. We suggest mechanisms that may alleviate this bias, including sharing inventory and point-of-sale data, and reducing ordering and shipping delays. Our research provides managerial lessons and identifies supply-chain issues that need further experimental study.
Computing tall skinny solutions of AX - XB = C
Authors: Jan Brandts
Venue: Mathematics and Computers in Simulation (2003)

We will concentrate on the numerical computation of so-called tall and skinny solutions X of the Sylvester equations AX - XB = C. By this we mean that A is an n × n matrix with cheaply applicable action (A is for example sparse), and B a k × k matrix, with k ≤ n. This type of Sylvester equation plays an important role in the computation of invariant subspaces when block Rayleigh quotient or block Jacobi-Davidson methods are used.There exist essentially two types of subspace projection methods for such equations. One in which the tall skinny matrices are treated as rigid objects, and one in which they are treated as a basis of a subspace. In this paper we review the two different types, design new methods, and aim to identify which application should make use of which solution method.
On the complexity of computing and learning with multiplicative neural networks
Authors: Michael Schmitt
Venue: Neural Computation (2002)

In a great variety of neuron models, neural inputs are combined using the summing operation. We introduce the concept of multiplicative neural networks that contain units that multiply their inputs instead of summing them and thus allow inputs to interact nonlinearly. The class of multiplicative neural networks comprises such widely known and well-studied network types as higher-order networks and product unit networks.We investigate the complexity of computing and learning for multiplicative neural networks. In particular, we derive upper and lower bounds on the Vapnik-Chervonenkis (VC) dimension and the pseudodimension for various types of networks with multiplicative units. As the most general case, we consider feedforward networks consisting of product and sigmoidal units, showing that their pseudo-dimension is bounded from above by a polynomial with the same order of magnitude as the currently best-known bound for purely sigmoidal networks. Moreover, we show that this bound holds even when the unit type, product or sigmoidal, may be learned. Crucial for these results are calculations of solution set components bounds for new network classes. As to lower bounds, we construct product unit networks of fixed depth with superlinear VC dimension.For sigmoidal networks of higher order, we establish polynomial bounds that, in contrast to previous results, do not involve any restriction of the network order. We further consider various classes of higher-order units, also known as sigma-pi units, that are characterized by connectivity constraints. In terms of these, we derive some asymptotically tight bounds.Multiplication plays an important role in both neural modeling of biological behavior and computing and learning with artificial neural networks. We briefly survey research in biology and in applications where multiplication is considered an essential computational element. The results we present here provide new tools for assessing the impact of multiplication on the computational power and the learning capabilities of neural networks.
Combining trigram and automatic weight distribution in Chinese spelling error correction
Authors: Jianhua Li, Xiaolong Wang
Venue: Journal of Computer Science and Technology (2002)

The researches on spelling correction aimmg at detecting errors in texts tend context-sensitive spellng error correction, which is more difficult than traditional isloated-word error correction. A novel and efficient algorithm for the system of Chinese spelling error correction, CInsunSpell, is presented. In this system, the work of correction lncludes two parts: checking phase and correcting phase. At the first phase, a Trigram algorithm within one fixed-size window is designed to locate potenuat errors in local area. This second phase employs a new method ot automatically and dynamically distributing weights among the characters in the confusion set as well as in the Bayesian language model. The tactics used abov exhibits good performances.
A new blocking problem from Java-based schedulers
Authors: Peter G. Harrison, Catalina M. Lladó
Venue: Performance Evaluation (2003)

We consider a form of blocking, which is typical in client-server systems including those implemented under the Enterprise JavaBean (EJB) specification. The novel feature is that tasks must wait for one of a number of parallel queues to clear its outstanding work. Thus, blocking time is the minimum of sojourn times at the parallel queues. Under certain simplifying assumptions, we solve this model for the probability distribution of blocking time and obtain a simple formula for its mean value. We then use this result in an aggregate server model of a larger queueing network in which further non-standard techniques are included to represent this form of blocking. We compare our approximate results against simulation data, obtaining good agreement for both system throughput and queue length probability distributions at equilibrium.
A Tactical Decision Support System for Empty Railcar Management
Authors: Hanif D. Sherali, Arief B. Suharko
Venue: Transportation Science (1998)

In this paper, we present a tactical model to assist in the task faced by the railroad industry on a day-to-day basis of centrally managing the distribution and repositioning of empty railcars for shipping automobiles. The problem involves a group of eight principal automobile manufacturers (shippers) who have pooled their autorack resources (railcars for shipping automobiles) to improve utilization and reduce the number of empty miles logged. However, this consolidation gives rise to various equity and priority issues related to timeliness in service, particularly in the case of shortages. Accordingly, our model takes into account such practical issues, including uncertainties in transit times, priorities with respect to time and demand locations, multiple objectives related to minimizing different degrees of latenesses in delivery, and blocking considerations. We investigate the performance of two principal models that have been developed for this purpose. The first model, TDSS1 incorporates all the identified features of the problem except for blocking (a consolidation of shipments from any origin to only a limited number of destinations), and results in a network formulation of the problem. The second model, TDSS2 extends TDSS1 by further including blocking considerations, and results in a network flow problem with side constraints and discrete side variables. We then show how the resulting mixed-integer-programming formulation can be enhanced via some partial convex hull constructions. To accommodate the strict run-time limit requirements imposed in practice, 21 principal heuristics are developed and tested to solve this problem. By examining the performance of these procedures with respect to speed of operation and the quality of solutions produced on a test bed of real-world problem instances, we prescribe a solution strategy for implementation in making production runs.
Generating Experimental Data for Computational Testing with Machine Scheduling Applications
Authors: Nicholas G. H Hall, Marc E. Posner
Venue: Operations Research (2001)

The operations research literature provides little guidance about how data should be generated for the computational testing of algorithms or heuristic procedures. We discuss several widely used data generation schemes, and demonstrate that they may introduce biases into computational results. Moreover, such schemes are often not representative of the way data arises in practical situations. We address these deficiencies by describing several principles for data generation and several properties that are desirable in a generation scheme. This enables us to provide specific proposals for the generation of a variety of machine scheduling problems. We present a generation scheme for precedence constraints that achieves a target density which is uniform in the precedence constraint graph. We also present a generation scheme that explicitly considers the correlation of routings in a job shop. We identify several related issues that may influence the design of a data generation scheme. Finally, two case studies illustrate, for specific scheduling problems, how our proposals can be implemented to design a data generation scheme.
Productivity of Information Systems in the Healthcare Industry
Authors: Nirup M. Menon, Byungtae Lee, Leslie Eldenburg
Venue: Information Systems Research (2000)

This research paper analyzes the impact of information technology (IT)in a healthcare setting using a longitudinal sample of hospital data from 1976 to 1994. We classify production inputs into labor and capital categories. Capital is classified into three components--medical IT capital, medical capital, and IT capital--and labor is classified into two components, medical labor and IT labor. Results provide evidence that IT contributes positively to the production of services in the healthcare industry.
Finite-Size Facility Placement in the Presence of Barriers to Rectilinear Travel
Authors: Selçuk Savas, Rajan Batta, Rakesh Nagi
Venue: Operations Research (2002)

We consider the placement (location and orientation) of a single finite-size (finite-area, arbitrary shape) facility in the plane under the assumption that all travel occurs according to the rectilinear (or Manhattan) metric in the presence of impenetrable barriers to travel. Facility users are distributed over a finite set of demand points. The facility serves the users via a service point (server) located on the boundary of the facility. We consider aninteractive model in the sense that there is interaction between not only the facility and the users, but also among the users themselves. We identify the candidates for optimal placement(s) for a facility with a fixed orientation and then for a facility with a fixed server location. Finally, we present a heuristic for the solution of the general problem, when the location and orientation are both unknown.
Topological incompleteness and order incompleteness of the lambda calculus
Authors: Antonino Salibra
Venue: ACM Transactions on Computational Logic (TOCL) (2003)

A model of the untyped lambda calculus univocally induces a lambda theory (i.e., a congruence relation on &lambda;-terms closed under &alpha;- and &beta;-conversion) through the kernel congruence relation of the interpretation function. A semantics of lambda calculus is (equationally) incomplete if there exists a lambda theory that is not induced by any model in the semantics. In this article, we introduce a new technique to prove in a uniform way the incompleteness of all denotational semantics of lambda calculus that have been proposed so far, including the strongly stable one, whose incompleteness had been conjectured by Bastonero, Gouy and Berline. We apply this technique to prove the incompleteness of any semantics of lambda calculus given in terms of partially ordered models with a bottom element. This incompleteness removes the belief that partial orderings with a bottom element are intrinsic to models of the lambda calculus, and that the incompleteness of a semantics is only due to the richness of the structure of representable functions. Instead, the incompleteness is also due to the richness of the structure of lambda theories. Further results of the article are: (i) an incompleteness theorem for partially ordered models with finitely many connected components (= minimal upward and downward closed sets); (ii) an incompleteness theorem for topological models whose topology satisfies a suitable property of connectedness; (iii) a completeness theorem for topological models whose topology is non-trivial and metrizable.