ppxscal/embedding_network huggingface dataset:
University students' problem posing abilities and attitudes towards mathematics
Authors: Todd A. Grundmeier
Venue: PRIMUS: problems, resources, and issues in mathematics undergraduate studies (2002)

This study explored the problem posing abilities and attitudes towards mathematics of students in a university pre-calculus class and a university mathematical proof class. A measure of attitude towards mathematics and corresponding two sample t-test revealed a significant (p = .001) difference in the attitude levels of students in the two classes. A measure of problem posing ability explored students problem posing abilities in both numeric and non- numeric contexts. Two sample t-tests showed no significant difference in the problem posing ability (numeric or non-numeric) of students in the two classes. A matched pairs t-test showed a significant difference in numeric posing versus non-numeric posing ability in both classes. Lastly there was no correlation between students attitudes towards mathematics and problem posing abilities.
The behavior of malleable metals in tumbling mills, using coarse lead shots
Authors: M. Noaparast, A. R. Laplante
Venue: Iranian Journal of Science and Technology (2001)

The behaviour of coarse pure lead particles in different dry laboratory tumbling mills was investigated. It was modelled with first-order transfer rates to represent the various mass transfers observed, namely flattening, folding, agglomeration, breakage and smearing unto the mill shell and grinding media.This paper presents the models used and the experimental program of the grinding of lead shots, both spherical and flattened, with the Bond rod and ball mills. All five mechanisms were observed, particularly breakage and smearing in the rod mill, and folding and flattening in the ball mill. Agglomeration was only observed in the ball mill, during an intermediate phase of grinding. Particulate breakage generally required an induction time, which is believed to be associated with the formation and propagation of cracks at the edge of flakes. The different phases of each test were fitted into various models. The model which yielded the best fit generally corresponded with the dominant transfer mechanism observed. The reliability of parametric estimation generally became worse as the number of the model parameters increased.
The inference problem: a survey
Authors: Csilla Farkas, Sushil Jajodia
Venue: ACM SIGKDD Explorations Newsletter (2002)

Access control models protect sensitive data from unauthorized disclosure via direct accesses, however, they fail to prevent indirect accesses. Indirect data disclosure via inference channels occurs when sensitive information can be inferred from non-sensitive data and metadata. Inference channels are often low-bandwidth and complex; nevertheless, detection and removal of inference channels is necessary to guarantee data security. This paper presents a survey of the current and emerging research in data inference control and emphasizes the importance of targeting this so often overlooked problem during database security design.
Inventory Policies for Systems with Stochastic and Deterministic Demand
Authors: Matthew J. Sobel, Rachel Q. Zhang
Venue: Operations Research (2001)

We consider a periodic review inventory system with demand arriving simultaneously from a deterministic source and a random source. The deterministic demand has to be satisfied immediately and the stochastic demand can be backordered. Assuming that the stochastic demand is never backlogged if there is stock in the system, we prove that a modified ( s, S) policy is optimal under general conditions if there is a setup cost. If there is a smoothing cost instead of the setup cost, we observe that the problem corresponds to a standard model with one source of demand.
Semantic refinement and error correction in large terminological knowledge bases
Authors: James Geller, Huanying Gu, Yehoshua Perl, Michael Halper
Venue: Data Knowledge Engineering (2003)

Capturing the semantics of concepts in a terminology has been an important problem in AI. A two-level approach has been proposed where concepts are classified into high-level semantic types, with these types constituting a portion of the concepts' semantics. We present an algorithmic methodology for refining such two-level terminologic networks. A new network is produced consisting of "pure" semantic types and intersection types. Concepts are uniquely re-assigned to these new types. Overall, these types form a better conceptual abstraction, with each exhibiting uniform semantics. Using them, it becomes easier to detect classification errors. The methodology is applied to the UMLS.
Optimizing Expert Systems: Heuristics for Efficiently Generating Low-Cost Information Acquisition Strategies
Authors: Michael V. Mannino, Vijay S. Mookerjee
Venue: INFORMS Journal on Computing (1999)

We study the sequential information acquisition problem for rule-based expert systems as follows: find the information acquisition strategy that minimizes the expected cost to operate the system while maintaining the same output decisions. This problem arises for rule-based expert systems when the cost or time to collect inputs is significant and the inputs are not known until the system operates. We develop several "optimistic" heuristics to generate information acquisition strategies and study their properties. The heuristics provide choices concerning precision (i.e., how optimistic) versus computational effort. The heuristics are embedded into an informed search algorithm (based on AO*) that produces an optimal strategy and a greedy search algorithm. The search strategies are designed for situations in which rules can overlap and the cost of collecting an input may depend on the set of inputs previously collected. We study the properties of these approaches and simulate their performance on a variety of synthetic expert systems. Our results indicate that the heuristics are very precise, leading to near optimal results for greedy search and moderate search effort for optimal search.
Approximate protein folding in the HP side chain model on extended cubic lattices
Authors: Volker Heun
Venue: Discrete Applied Mathematics (2003)

One of the most important open problems in computational biology is the prediction of the conformation of a protein based on its amino acid sequence. In this paper, we design approximation algorithms for protein structure prediction in the so-called HP side chain model. The major drawback of the standard HP side chain model is the bipartiteness of the cubic lattice. To eliminate this drawback, we introduce the extended cubic lattice that extends the cubic lattice by diagonals in the plane. For this lattice, we present two linear algorithms with approximation ratios of 59/70 and 37/42, respectively. The second algorithm is designed for a 'natural' subclass of proteins, which covers more than 99.5% of all sequenced proteins. This is the first time that a protein structure prediction algorithm is designed for a 'natural' subclass of all combinatorial possible sequences.
From protocol stack to protocol heap: role-based architecture
Authors: Robert Braden, Ted Faber, Mark Handley
Venue: ACM SIGCOMM Computer Communication Review (2003)

Questioning whether layering is still an adequate foundation for networking architectures, this paper investigates non-layered approaches to the design and implementation of network protocols. The goals are greater flexibility and control with fewer feature interaction problems. The paper further proposes a specific non-layered paradigm called role-based architecture.
Object oriented programming for structural mechanics: a review
Authors: R. I. Mackie
Venue: Civil and structural engineering computing: 2001 (2001)

Object-oriented programming has become the main paradigm in general computing, and has started to make significant inroads into scientific computing. This paper reviews the progress made within the field of finite element analysis for structural engineering. The need for a new approach to finite element programming is established, namely the increasing complexity of software. Then the development of object-oriented methods to finite element programming is reviewed, and the progress made in handling the areas of complexity is considered. The main contribution of object-oriented methods to finite element analysis is the application of software engineering advances to finite element programming.
Self-organised evolutionary neural networks: algorithms and applications
Authors: S. D. Likothanassis, E. F. Georgopoulos
Venue: Highly parallel computaions: algorithms and applications (2001)

Evolving artificial neural networks (ANN) is a new method that, except for the training, was applied to the structure optimization problem. Several methods have been reported in recent years. Most of these methods are either very complicated or are applied under certain restrictions imposed by the designer. In this work, three new classes of evolutionary algorithms, for self-organized neural networks' training, will be presented. First, a modified genetic algorithm (MGA) is used to both evolve and train a population of multi-layered perceptrons (MLP) neural networks and to find a (near) optimum network architecture. This method is a generalisation of an existing one and is used for the first time for biosignal prediction. A different approach that combines ideas from both the evolution and the adaptive signal processing, considers the neural unit as a non-linear system, with p inputs and one output. Then the localized extended Kalman filter (LEKF) can be used as the training algorithm of such a neuron. First, we create a population of such systems with a random number of inputs. Then we apply the genetic operators to evolve the system's structure, using as a fitness function the inverse of the mean square error (MSE) function. After a small number of iterations the algorithm converges to the near optimum network, by means of the MSE minimization. A generalisation of this method, where the evolution is performed in the hidden region, is presented. Each of the proposed classes of algorithms was tested using artificial as well as real world data.
Making use of scenarios: a field study of conceptual design
Authors: Morten Hertzum
Venue: International Journal of Human-Computer Studies (2003)

Scenarios have gained acceptance in both research and practice as a way of grounding software-engineering projects in the users' work. However, the research on scenario-based design (SBD) includes very few studies of how scenarios are actually used by practising software engineers in real-world projects. Such studies are needed to evaluate current SBD approaches and advance our general understanding of what scenarios contribute to design. This longitudinal field study analyses the use of scenarios during the conceptual design of a large information system. The role of the scenarios is compared and contrasted with that of three other design artefacts: the requirements specification, the business model, and the user interface prototype. The distinguishing features of the scenarios were that they were task based and descriptive. By being task based the scenarios strung individual events and activities together m purposeful sequences and, thereby, provided an intermediate level of description that was both an instantiation of overall work objectives and a fairly persistent context for the gradual elaboration of subtasks. By being descriptive the scenarios preserved a real-world feel of the contents, flow, and dynamics of the users' work. The scenarios made the users' work recognizable to the software engineers as a complex but organized human activity. This way the scenarios attained a unifying role as mediator among both the design artefacts and the software engineers, whilst they were not used for communication with users. The scenarios were, however, discontinued before the completion of the conceptual design because their creation and management was dependent on a few software engineers who were also the driving forces of several other project activities. Finally, the software engineers valued the concreteness and coherence of the scenarios although that entailed a risk of missing some effective reconceptions of the users' work.
Convexity of the extreme zeros of Gegenbauer and Laguerre polynomials
Authors: Dimitar K. Dimitrov
Venue: Journal of Computational and Applied Mathematics (2003)

Let Cnλ(x), n=0, 1,....,λ -½, be the ultraspherical (Gegenbauer) polynomials, orthogonal in (-1, 1) with respect to the weight function (1 - x2)λ-1/2. Denote by xnk(λ), k = 1,.... ,n, the zeros of Cnλ(x) enumerated in decreasing order. In this short note, we prove that, for any n ∈ N, the product (λ + 1)3/2xn1(λ) is a convex function of λ if λ ≥ 0. The result is applied to obtain some inequalities for the largest zeros of Cnλ(x). If xnk(α), k = 1,..... n, are the zeros of Laguerre polynomial Lnα(x), also enumerated in decreasing order, we prove that xn1(λ)/(α + 1) is a convex function of α for α - 1.
Solving Semi-Markov Decision Problems Using Average Reward Reinforcement Learning
Authors: Tapas K. Das, Abhijit Gosavi, Sridhar Mahadevan, Nicholas Marchalleck
Venue: Management Science (1999)

A large class of problems of sequential decision making under uncertainty, of which the underlying probability structure is a Markov process, can be modeled as stochastic dynamic programs (referred to, in general, as Markov decision problems or MDPs). However, the computational complexity of the classical MDP algorithms, such as value iteration and policy iteration, is prohibitive and can grow intractably with the size of the problem and its related data. Furthermore, these techniques require for each action the one step transition probability and reward matrices, and obtaining these is often unrealistic for large and complex systems. Recently, there has been much interest in a simulation-based stochastic approximation framework called reinforcement learning (RL), for computing near optimal policies for MDPs. RL has been successfully applied to very large problems, such as elevator scheduling, and dynamic channel allocation of cellular telephone systems. In this paper, we extend RL to a more general class of decision tasks that are referred to as semi-Markov decision problems (SMDPs). In particular, we focus on SMDPs under the average-reward criterion. We present a new model-free RL algorithm called SMART (Semi-Markov Average Reward Technique). We present a detailed study of this algorithm on a combinatorially large problem of determining the optimal preventive maintenance schedule of a production inventory system. Numerical results from both the theoretical model and the RL algorithm are presented and compared.
Dissecting Cyclops: a detailed analysis of a multithreaded architecture
Authors: George Almási, Cǎlin Caşcaval, José G. Castaños, Monty Denneau, Derek Lieber, José E. Moreira, Henry S. Warren,  Jr.
Venue: ACM SIGARCH Computer Architecture News (2003)

Multiprocessor systems-on-a-chip offer a structured approach to managing complexity in chip design. Cyclops is a new family of multithreaded architectures which integrates processing logic, main memory and communications hardware on a single chip. Its simple, hierarchical design allows the hardware architect to manage a large number of components to meet the design constraints in terms of performance, power or application domain.This paper evaluates several alternative Cyclops designs with different relative costs and trade-offs. We compare the performance of several scientific kernels running on different configurations of this architecture. We show that by increasing the number of threads sharing a floating point unit we can hide fairly high cache and memory latencies. We prove that we can reach the theoretical peak performance of the chip and we identify the optimal balance of components for each application. We demonstrate that the design is well adapted to solve problems that are difficult to optimize. For example, we show that sparse matrix vector multiplication obtains 16 GFlops out of 32 GFlops of peak performance.
Motion segmentation and pose recognition with motion history gradients
Authors: Gary R. Bradski, James W. Davis
Venue: Machine Vision and Applications (2002)

This paper presents a fast and simple method using a timed motion history image (tMHI) for representing motion from the gradients in successively layered silhouettes. This representation can be used to (a) determine the current pose of the object and (b) segment and measure the motions induced by the object in a video scene. These segmented regions are not "motion blobs", but instead are motion regions that are naturally connected to parts of the moving object. This method may be used as a very general gesture recognition "toolbox". We demonstrate the approach with recognition of waving and overhead clapping motions to control a music synthesis program.
Ranking and Selection for Steady-State Simulation: Procedures and Perspectives
Authors: David Goldsman, Seong-Hee Kim, William S. Marshall, Barry L. Nelson
Venue: INFORMS Journal on Computing (2002)

We present and evaluate three ranking-and-selection procedures for use in steady-state simulation experiments when the goal is to find which among a finite number of alternative systems has the largest or smallest long-run average performance. All three procedures extend existing methods for independent and identically normally distributed observations to general stationary output processes, and all procedures are sequential. We also provide our thoughts about the evaluation of simulation design and analysis procedures, and illustrate these concepts in our evaluation of the new procedures.
A study of CodePack: optimizing embedded code space
Authors: Avishay Orpaz, Shlomo Weiss
Venue: Proceedings of the tenth international symposium on Hardware/software codesign (2002)

CodePack is a code compression system used by IBM in its PowerPC family of embedded processors. CodePack combines high compression capability along with fast and simple decoding hardware. IBM did not release much information about the design of the system and the influence of various design parameters on its performance. In our work we will present the system and its design parameters and investigate how each affects its performance on the compression rate and decoder complexity. We also present a novel efficient algorithm to optimize the class structure of the system.
Determining optimum disassembly sequences in electronic equipment
Authors: Alfred J. D. Lambert
Venue: Computers and Industrial Engineering (2002)

This paper presents a study on disassembly sequence generation for electronic equipment. This is particularly useful because adequate end-of-life disassembly becomes crucial as take-back obligations are imposed for environmental reasons. Besides this, the hierarchical structure, typical to electronic products, makes product remanufacturing to an important topic. Methods from disassembly of mechanical assemblies are successfully adapted to these specific challenges.First, a modeling method for assemblies is described, which is aimed at automatically determining the optimum disassembly sequence. It is argued that the information, which is condensed in the connection diagram and the set of precedence relations, is sufficient for the automatic generation of such a sequence. Appropriate use of the precedence relations reduces the size of the model, that can be represented as an AND/OR graph with a restricted number of subassemblies and actions. With disassembly costs and revenues included, the optimum disassembly sequence can be found with standard linear programming software, thus without the need of visiting the complete search space. As a matter of fact, the size of the problem is strongly reduced, as it increases only linear with the number of parts in the assembly. It has been demonstrated that the model nearly instantaneously generates the optimum disassembly sequence. Besides this, the model can generate near optimum sequences as well, which is beneficial if multiple criteria are considered.
Transformation-Based Diagnosis of Student Programs for Programming Tutoring Systems
Authors: Songwen Xu, Yam San Chee
Venue: IEEE Transactions on Software Engineering (2003)

A robust technology that automates the diagnosis of students' programs is essential for programming tutoring systems. Such technology should be able to determine whether programs coded by a student are correct. If a student's program is incorrect, the system should be able to pinpoint errors in the program as well as explain and correct the errors. Due to the difficulty of this problem, no existing system performs this task entirely satisfactorily, and this problem still hampers the development of programming tutoring systems. This paper describes a transformation-based approach to automate the diagnosis of students' programs for programming tutoring systems. Improved control-flow analysis and data-flow analysis are used in program analysis. Automatic diagnosis of student programs is achieved by comparing the student program with a specimen program at the semantic level after both are standardized. The approach was implemented and tested on 525 real student programs for nine different programming tasks. Test results show that the method satisfies the requirements stated above. Compared to other existing approaches to automatic diagnosis of student programs, the approach developed here is more rigorous and safer in identifying student programming errors. It is also simpler to make use of in practice. Only specimen programs are needed for the diagnosis of student programs. The techniques of program standardization and program comparison developed here may also be useful for research in the fields of program understanding and software maintenance.
Comparing a brain-inspired robot action selection mechanism with winner-takes-all
Authors: Benoît Girard, Vincent Cuzin, Agnés Guillot, Kevin N. Gurney, Tony J. Prescott
Venue: Proceedings of the seventh international conference on simulation of adaptive behavior on From animals to animats (2002)

We present a new robotic implementation of a brain-inspired model of action selection described by Gurney et al. (Gurney et al., 2001a, Gurney et al., 2001b) based on neural circuits located in the basal ganglia and thalamus of the vertebrate brain. Compared on an earlier robot implementation (Montes-Gonzalez et al., 2000), the new model demonstrates the capacity of the selection system to produce efficient 'energy' consumption/conversion in a 'feeding/resting' task whilst maintaining essential state variables within a 'zone of viability'. Generating appropriate action selection in this new setting entailed using biologically plausible Sigma-Pi units that can exploit correlated and anti-correlated dependencies between input signals when computing the 'salience' (urgency) of competing actions. A comparison between this brain-inspired selection mechanism and classical 'winner-takes-all' showed that the former can provide better behavioral persistence leading to more efficient energy intake.