ppxscal/embedding_network huggingface dataset:
Automatically identifying learners' problem solving strategies in-process solving algorithmic problems
Authors: Ulrich Kiesmueller, Torsten Brinda
Venue: Proceedings of the 14th annual ACM SIGCSE conference on Innovation and technology in computer science education (2009)

Learners often use learning and programming environments to practice basics of programming and solving algorithmic problems. To adapt the software feedback to each learner's problem solving process, the learning environment will be enhanced with a tool to identify the individual problem solving strategy in-process automatically. Former attribution of problem solving strategies to patterns in recorded learner-system interactions by human researchers should be validated with the help of questionnaires based on the Theory of Reasoned Action. To identify the patterns automatically, speech recognition methods can be used. In this research project each single problem solving strategy is modelled by a hidden markov model.
TS-fuzzy system-based support vector regression
Authors: Chia-Feng Juang, Cheng-Da Hsieh
Venue: Fuzzy Sets and Systems (2009)

This paper proposes a new regression model, the Takagi-Sugeno Fuzzy System-based Support Vector Regression (TSFS-SVR). The TSFS-SVR is motivated by TS-type fuzzy rules and its parameters are learned by a combination of fuzzy clustering and linear SVR. In contrast to a kernel-based SVR, the TSFS-SVR has a smaller number of parameters while retaining the SVR's good generalization ability. In TSFS-SVR, a one-pass clustering algorithm clusters the input training data. A new TS-kernel, which corresponds to a TS-type fuzzy rule, is then constructed by the product of a cluster output and a linear combination of input variables. The TSFS-SVR output is a linear weighted sum of the TS-kernels. To achieve high generalization ability, TSFS-SVR weights are learned through linear SVR. This paper demonstrates the capabilities of TSFS-SVR by conducting simulations in clean and noisy function approximations and signal prediction. This paper also compares simulation results from the TSFS-SVR with Gaussian kernel-based SVR and other learning models.
“Be bold and take a challenge”: Could motivational strategies improve help-seeking?
Authors: Genaro Rebolledo Mendez, Benedict du Boulay, Rosemary Luckin
Venue: Proceeding of the 2005 conference on Artificial Intelligence in Education: Supporting Learning through Intelligent and Socially Informed Technology (2005)

We are exploring whether the use of facilities aimed at improving the learner's motivation has an effect on learning food-chains and food-webs, but also on help-seeking behaviour. The M-Ecolab is a Vygotskyan intelligent learning environment that incorporates both cognitive and affective feedback by combining a cognitive model capable of providing written feedback at the cognitive and meta-cognitive level and a model-driven, considerate more-able partner who gives spoken, affective feedback. A preliminary study of the effects of the M-Ecolab in learning was carried out in a real-class situation. The results showed that learners in the M-Ecolab had significantly greater learning in their post-test scores than students in the control condition in which affective feedback was not available. Moreover, in the M-Ecolab, engaged students (those having an above-average use of the motivating facilities) tended to look more effectively both for quality and quantity of help resulting in more fruitful interactions.
New statistical models of cutting tool wear and cutting speed in turning 20MoCr130 stainless steel
Authors: Mihaiela Iliescu, Aurelian Vlase
Venue: Proceedings of the 10th WSEAS international conference on Mathematical and computational methods in science and engineering (2008)

Special materials, with very good mechanical characteristics and special look, are represented by the stainless steels. Parts made of these materials are used in special and various industrial fields but, most of the times need machining. Because of the fact that turning is a very important machining procedure and that, special conditions are needed for obtaining optimum machined surface characteristics, this paper deals with aspects involved by the way statistical models of cutting tool wear and cutting speed in turning 20MoCr130 stainless steel were obtained.. Further application of the obtained models are also, mentioned.
A new CMOS current-mode classifier circuit for statistics applications
Authors: Cosmin Popa
Venue: Proceedings of the 10th WSEAS international conference on Neural networks (2009)

Very useful in many fields of applied electronics, the classifier find a lot of immediate applications in pattern recognition, artificial intelligence and statistics domains. A new current-mode CMOS classifier based on an Euclidean distance circuit will be further presented. The system is designed for a low-power low-voltage operation that could be achieved by avoiding to use any cascode stage. As a result of the current-mode functioning, the dynamic range of the proposed circuit could be strongly increased, while the operation in saturation region of all the MOS transistors allows obtaining a very good signal-to-noise ratio. In order to simplify the increasing of the number of input vectors, the circuit is characterized by a high modularity. All the resistors will be replaced by active MOS transistors for reducing the circuit area consumption. The Euclidean distance circuit error will be strongly reduced by designing the circuit in such a way that the output current to be independent on technological parameters. The SPICE simulations confirm the theoretical estimated results, showing a very good accuracy of the proposed circuit.
Identifying Inter-Domain Similarities through Content-Based Analysis of Hierarchical Web-Directories
Authors: Shlomo Berkovsky, Dan Goldwasser, Tsvi Kuflik, Francesco Ricci
Venue: Proceeding of the 2006 conference on ECAI 2006: 17th European Conference on Artificial Intelligence August 29 -- September 1, 2006, Riva del Garda, Italy (2006)

Providing accurate personalized information services to the users requires knowing their interests and needs, as defined by their User Models (UMs). Since the quality of the personalization depends on the richness of the UMs, services would benefit from enriching their UMs through importing and aggregating partial UMs built by other services from relatively similar domains. The obvious question is how to determine the similarity of domains? This paper proposes to compute inter-domain similarities by exploiting well-known Information Retrieval techniques for comparing textual contents of the Web-sites, classified under the domain nodes in Web-directories. Initial experiments validate feasibility of the proposed approach and raise open research questions.
Combination of Bayesian Network and Overlay Model in User Modeling
Authors: Loc Nguyen, Phung Do
Venue: Proceedings of the 9th International Conference on Computational Science (2009)

The core of adaptive system is user model containing personal information such as knowledge, learning styles, goals which is requisite for learning personalized process. There are many modeling approaches, for example: stereotype, overlay, plan recognition... but they do not bring out the solid method for reasoning from user model. This paper introduces the statistical method that combines Bayesian network and overlay modeling so that it is able to infer user's knowledge from evidence collected during user's learning process.
A Planning Graph Heuristic for Forward-Chaining Adversarial Planning
Authors: Pascal Bercher, Robert Mattmüller
Venue: Proceeding of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence (2008)

In contrast to classical planning, in adversarial planning, the planning agent has to face an adversary trying to prevent him from reaching his goals. In this paper, we investigate a forwardchaining approach to adversarial planning based on the AO* algorithm. The exploration of the underlying AND/OR graph is guided by a heuristic evaluation function, inspired by the relaxed planning graph heuristic used in the FF planner. Unlike FF, our heuristic uses an adversarial planning graph with distinct proposition and action layers for the protagonist and antagonist. First results suggest that in certain planning domains, our approach yields results competitive with the state of the art.
Plenary lecture 4: multi-criterion decision making by artificial intelligence techniques
Authors: Jerzy Balicki
Venue: Proceedings of the 8th WSEAS international conference on Artificial intelligence, knowledge engineering and data bases (2009)

Decision making for complex systems are based on multi-criterion-optimisation. For instance, a task assignment in a distributed computer system may reduce both the total cost of a program run and a workload of the bottleneck computer. Moreover, it can decrease the cost of computers if a selection of the computer sort is carried out. A total amount of the system performance is another measure that can be minimized by task distribution. The probability that all computers remain fault-free during the execution of the modules assigned to computers is the first criterion of evaluation task assignments. Above benchmark problem can be formulated as a multiobjective combinatorial optimisation question, which is solved by an approach based on artificial intelligence. It is applied for finding the subset of Pareto-optimal solutions. Genetic algorithms, evolutionary algorithms, evolution strategies and genetic programming are the alternative evolutionary approaches to the modern metaheuristic multicriteria optimisation methods such as simulated annealing, tabu search or Hopfield models of neural networks. Especially, genetic programming paradigm is implemented as a genetic algorithm written in the Matlab language. Chromosomes are generated as the Matlab functions and then genetic operators are applied for finding Pareto-suboptimal task assignment. Results are compared with outcomes obtained by an adaptive evolutionary algorithm.
Monte Carlo methods in fuzzy queuing theory
Authors: Areeg Abdalla, James J. Buckley
Venue: Soft Computing - A Fusion of Foundations, Methodologies and Applications (2009)

In this paper, we consider an optimization problem in fuzzy queuing theory that was first used in web planning. This fuzzy optimization problem has no solution algorithm and approximate solutions were first produced by computing the fuzzy value of the objective function for only sixteen values of the fuzzy variables. We introduce our fuzzy Monte Carlo method, using a quasi-random number generator, to produce 100,000 random sequences of fuzzy vectors for the fuzzy variables, which will present a much better approximate solution.
The Nikon D80 Dbook: Your Interactive Guide to DSLR Photography
Authors: Rainer Dorau, Rudolf Krahm, Helmut Kraus
Venue:  (2007)

Rocky Nook Dbooks are the ideal companion for anyone who wants to get the most from their Nikon D80. With more than 580 digital pages in Acrobat format, you will discover the fundamentals on all aspects of the digital image creation process: digital photography basics, taking pictures, image optimization, lenses, accessories, and much more. Rocky Nook Dbooks go well beyond the Nikon camera manuals and are well-organized, beautifully illustrated introductions to digital photography with the Nikon system. The Dbooks offer clickable examples and digital images that explain before-and-after situations and clearly illustrate the individual stages of the processes involved. Navigation is easy with the built-in hyperlinks or the detailed index and Acrobat search functions. Rocky Nook Dbooks make reading just as exciting and interactive as digital photography itself. High-resolution RGB images help to illustrate subtle differences and effects which would hardly be visible on a printed book page. Rocky Nook Dbooks also include a handy booklet for use on the road, which is filled with practical overviews of your camera and menu options. The Rocky Nook Dbook series is a must for all serious amateur, semi-professional, or professional photographers who want to get the most out of their Nikon equipment, and who strive to produce impressive, polished, digital images.
ScalaTrace: Scalable compression and replay of communication traces for high-performance computing
Authors: Michael Noeth, Prasun Ratn, Frank Mueller, Martin Schulz, Bronis R. de Supinski
Venue: Journal of Parallel and Distributed Computing (2009)

Characterizing the communication behavior of large-scale applications is a difficult and costly task due to code/system complexity and long execution times. While many tools to study this behavior have been developed, these approaches either aggregate information in a lossy way through high-level statistics or produce huge trace files that are hard to handle. We contribute an approach that provides orders of magnitude smaller, if not near-constant size, communication traces regardless of the number of nodes while preserving structural information. We introduce intra- and inter-node compression techniques of MPI events that are capable of extracting an application's communication structure. We further present a replay mechanism for the traces generated by our approach and discuss results of our implementation for BlueGene/L. Given this novel capability, we discuss its impact on communication tuning and beyond. To the best of our knowledge, such a concise representation of MPI traces in a scalable manner combined with deterministic MPI call replay is without any precedent.
Showing the non-existence of solutions in systems of linear Diophantine equations
Authors: Antonio Hernando, Luis de Ledesma, Luis M. Laita
Venue: Mathematics and Computers in Simulation (2009)

The present paper is concerned with expounding an altogether new method specifically designed to provide a straightforward proof that there is no possible solution for some family of systems of Diophantine linear equations which share the same dependent terms while differing in its independent terms. On the basis of this novel approach, a definition of testers is given and consequently used to shape this particular method, as illustrated with some suitable examples.
On a criterion of stability for a mechanical system with clearances
Authors: Nicolae-Doru Stanescu
Venue: Proceedings of the 10th WSEAS international conference on Mathematical and computational methods in science and engineering (2008)

In this paper we consider a mechanical system consisting of an axle and two journals with clearances. The clearances are modelled each of them by an even number of identical springs. For this system we make a cinematic study, we describe the forces which appear due to the model of the clearances, we determine the equations of motion and we present the linear approximation. Based on the linear approximation we give a practical criterion for the stability of the motion. Finally, an example is completely solved.
Electronic properties of defects in polycrystalline dielectric materials
Authors: K. P. McKenna, A. L. Shluger
Venue: Microelectronic Engineering (2009)

Grain boundaries have been implicated in current leakage and dielectric breakdown of CMOS devices. We calculate the electronic properties of oxygen vacancy defects near grain boundaries in the dielectric insulators MgO and HfO"2 using first principles methods. In both materials we find that oxygen vacancies favourably segregate to grain boundaries, in various charge states. Their electronic properties are different from their counterparts in the bulk. At increased concentrations, such defects at grain boundaries may play a key role in processes such as electron tunneling, charge trapping and dielectric breakdown in electronic devices.
Robust feature extraction via information theoretic learning
Authors: Xiao-Tong Yuan, Bao-Gang Hu
Venue: Proceedings of the 26th Annual International Conference on Machine Learning (2009)

In this paper, we present a robust feature extraction framework based on information-theoretic learning. Its formulated objective aims at simultaneously maximizing the Renyi's quadratic information potential of features and the Renyi's cross information potential between features and class labels. This objective function reaps the advantages in robustness from both redescending M-estimator and manifold regularization, and can be efficiently optimized via half-quadratic optimization in an iterative manner. In addition, the popular algorithms LPP, SRDA and LapRLS for feature extraction are all justified to be the special cases within this framework. Extensive comparison experiments on several real-world data sets, with contaminated features or labels, well validate the encouraging gain in algorithmic robustness from this proposed framework.
Reference-driven performance anomaly identification
Authors: Kai Shen, Christopher Stewart, Chuanpeng Li, Xin Li
Venue: Proceedings of the eleventh international joint conference on Measurement and modeling of computer systems (2009)

Complex system software allows a variety of execution conditions on system configurations and workload properties. This paper explores a principled use of reference executions--those of similar execution conditions from the target--to help identify the symptoms and causes of performance anomalies. First, to identify anomaly symptoms, we construct change profiles that probabilistically characterize expected performance deviations between target and reference executions. By synthesizing several single-parameter change profiles, we can scalably identify anomalous reference-to-target changes in a complex system with multiple execution parameters. Second, to narrow the scope of anomaly root cause analysis, we filter anomaly-related low-level system metrics as those that manifest very differently between target and reference executions. Our anomaly identification approach requires little expert knowledge or detailed models on system internals and consequently it can be easily deployed. Using empirical case studies on the Linux I/O subsystem and a J2EE-based distributed online service, we demonstrate our approach's effectiveness in identifying performance anomalies over a wide range of execution conditions as well as multiple system software versions. In particular, we discovered five previously unknown performance anomaly causes in the Linux 2.6.23 kernel. Additionally, our preliminary results suggest that online anomaly detection and system reconfiguration may help evade performance anomalies in complex online systems.
Numerical modelling of temperature variations in a Chinese solar greenhouse
Authors: G. Tong, D. M. Christopher, B. Li
Venue: Computers and Electronics in Agriculture (2009)

The time-dependent temperature distributions inside a Chinese solar greenhouse are numerically predicted from external climatic conditions using a computational fluid dynamics (CFD) analysis. The boundary conditions are based on hourly measured data for the solar insolation and the sky, soil (1m below the soil surface) and outside air temperatures, plus other parameters describing the external convection and radiation. The numerical model takes into account all of the heat transfer mechanisms including the variable solar insolation, the air infiltration, the heat capacities of the thick walls and the ground and the natural convection inside the greenhouse. The temperatures were measured experimentally in an enclosed solar greenhouse with a 12m span and 5.5m ridge height during the winter in northern China with the south roof covered with a thin plastic film during the daytime and with a thermal blanket added at night to reduce heat losses. The large temperature variations in the greenhouse were measured and predicted for the climatic conditions in northern China during three clear days followed by a cloudy day during the winter. The simulated air and soil temperatures have the same profile as the measured temperatures with the average temperature differences between the simulated and measured air temperatures during the nighttime less than 1.0^oC on the clear days and no more than 1.5^oC during the entire cloudy day.
A neuro-symbolic hybrid system methodology for quality inspection on artificial textures
Authors: Vianey G. Cruz Sánchez, Osslan O. Vergara Villegas, Gerardo Reyes Salgado, Humberto J. Ochoa Domínguez, José Ruiz Ascencio
Venue: Proceedings of the 2nd conference on European computing conference (2008)

The Neuro-Symbolic Hybrid Systems (NSHS) are used to solve problems where there exists a necessity of combining and integrating the artificial neural networks and the symbolic representations in only one system in order to obtain better results. We developed a NSHS Methodology to integrate the knowledge of a human expert and the numeric knowledge obtained from a computer vision process. We implement the methodology to solve a quality inspection problem in artificial textures. The construction of neurosymbolic integration strategies allows us defining an adequate type of neuro-symbolic system to obtain an increment of the efficiency of an inspection task, which is shown with the better results obtained compared with other approaches.
How to improve postgenomic knowledge discovery using imputation
Authors: Muhammad Shoaib B. Sehgal, Iqbal Gondal, Laurence S. Dooley, Ross Coppel
Venue: EURASIP Journal on Bioinformatics and Systems Biology (2009)

While microarrays make it feasible to rapidly investigate many complex biological problems, their multistep fabrication has the proclivity for error at every stage. The standard tactic has been to either ignore or regard erroneous gene readings as missing values, though this assumption can exert a major influence upon postgenomic knowledge discovery methods like gene selection and gene regulatory network (GRN) reconstruction. This has been the catalyst for a raft of new flexible imputation algorithms including local least square impute and the recent heuristic collateral missing value imputation, which exploit the biological transactional behaviour of functionally correlated genes to afford accurate missing value estimation. This paper examines the influence of missing value imputation techniques upon postgenomic knowledge inference methods with results for various algorithms consistently corroborating that instead of ignoring missing values, recycling microarray data by flexible and robust imputation can provide substantial performance benefits for subsequent downstream procedures
An efficient analytical model for QoS engineering in mobile cellular networks
Authors: Georges Nogueira, Bruno Baynat, Ahmed Ziram
Venue: Proceedings of the 2008 International Symposium on a World of Wireless, Mobile and Multimedia Networks (2008)

This paper presents a simple and accurate analytical model to dimension mobile cellular networks with QoS differentiation. QoS per applicative flow is commonly defined in GPRS/EDGE and 3G systems where streaming applications with real time properties and elastic data applications have to share radio resources. The need for accurate and fast-computing tools is of primary importance to tackle complex and exhaustive dimensioning issues. In this paper, we present a generic QoS modeling methodology developed in the context of EDGE networks but that can be adapted easily to a different technology. We develop a “conditional product-form” Markovian model that takes into account the QoS differentiation between real time and non-real time classes and gives closed form expressions for all the required performance parameters at a click speed. We compare our model with simulation and show its accuracy. The speed of our analytical tool allows tackling dimensioning issues that require several thousands of evaluations, which is not tractable with any simulation tool.