ppxscal/embedding_network huggingface dataset:
Provision of External Data for DSS, BI, and DW by Syndicate Data Suppliers
Authors: Mattias Strand, Sven A. Carlsson
Venue: Proceeding of the 2008 conference on Collaborative Decision Making: Perspectives and Challenges (2008)

In order to improve business performance and competitiveness it is important for firms to use data from their external environment. More and more attention is directed towards data originating external to the organization, i.e., external data. A firm can either collect this data or cooperate with an external data provider. We address the latter case and focus syndicate data suppliers (SDSs). They are the most common sources when incorporating external data into business intelligence, DSS, and DW solutions. SDSs are specialized in collecting, compiling, refining, and selling data. We provide a detailed description regarding the business idea of syndicate data suppliers and how they conduct their business, as well as a description of the industry of syndicate data suppliers. As such, the paper increases the understanding for external data incorporation and the possibility for firms to cooperate with syndicate data suppliers.
On fast exploration in 2D and 3D terrains with multiple robots
Authors: Rahul Sawhney, K. Madhava Krishna, Kannan Srinathan
Venue: Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 1 (2009)

We present a fast multi-robotic exploration methodology for 2D and 3D terrains. An asynchronous exploration strategy is introduced which shows significant improvements over the existing synchronous ones. A per-time visibility metric is being utilized by the algorithm. The metric allots the same weight for points for next view whose visibility over time ratios are equal. The outcome of this is that while the number of points visited to explore a terrain is nearly the same as other popular metrics found in literature, the time length of the paths are smaller in this case resulting in reduced time exploration. The results have been verified through extensive simulations in 2D and 3D. In 2D multiple robots explore unknown terrains that are office like, cluttered, corridor like and various combinations of these. In 3D we consider the case of multiple UAVs exploring a terrain represented as height fields. We introduce a way for calculating expected visibilities and a way of incorporating explored features in the per-time metric. The maximum height of the UAV at each location is governed by the so called exposure surface, beneath which the UAVs are constrained to fly. We also show performance gain of the present metric over others in experiments on a Pioneer 3DX robot.
Toward Formal Models of the Theoretical Framework of Fundamental Economics
Authors: Yingxu Wang
Venue: Fundamenta Informaticae (2009)

Many fundamental theories and doctrines of micro- and macro-economics are not formally studied in economics. This paper presents a rigorous treatment and explanation of a set of fundamental empirical theories of economics. It is recognized that the adaptive equilibrium of market systems is rooted in the negative feedbackmechanisms of demands and supplies. A mathematical model of economic equilibrium developed in this paper provides a formal proof of Adam Smith's hypothesis of the 'invisible hand'. An economic equilibrium theorem is derived to deal with more complicated multivariable equilibrium problems that could not be handled in conventional economic theories. Then, a set of mathematical models is developed for dynamic cost analyses and the estimation of economical outcomes of engineering projects.
Approximately fair and secure protocols for multiple interdependent issues negotiation
Authors: Katsuhide Fujita, Takayuki Ito, Mark Klein
Venue: Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 2 (2009)

Multi-issue negotiation has been studied widely. Our work focuses on the important special case of negotiation with multiple interdependent issues, in which agent utility functions are nonlinear. In this paper, we propose a Distributed Mediator Protocol (DMP) for securely finding Pareto optimal agreements. We also propose a measure for selecting final agreements from the set of Pareto-optimal contracts, based on "approximated fairness" and the "rate of Nash bargaining solution". We demonstrate that the DMP finds the Nash bargaining solution better than previous work in this area.
Computer aided solution of the invariance equation for two-variable Gini means
Authors: Szabolcs Baják, Zsolt Páles
Venue: Computers Mathematics with Applications (2009)

Our aim is to solve the so-called invariance equation in the class of two-variable Gini means {G"p","q:p,q@?R}, i.e., to find necessary and sufficient conditions on the 6 parameters a,b,c,d,p,q such that the identity G"p","q(G"a","b(x,y),G"c","d(x,y))=G"p","q(x,y)(x,y@?R"+) be valid. We recall that, for p
Application of multivariate geostatistics in delineating management zones within a gravelly vineyard using geo-electrical sensors
Authors: F. Morari, A. Castrignanò, C. Pagliarin
Venue: Computers and Electronics in Agriculture (2009)

In gravelly soils, surveys are generally time-consuming, labour-intensive and costly. This limits the possibility of adopting an appropriate sampling to determine within-field spatial variability. The potential use of electro-magnetic induction scans (EMI) to measure apparent electrical conductivity (EC) and improve the estimate accuracy of sparsely sampled primary variables was assessed in a 5-ha gravelly soil vineyard in Valpolicella, north-eastern Italy. EC was measured using a Geonics EM38DD operating in both horizontal and vertical mode. Geo-electrical investigations were also done in 18 positions with the electrical resistivity tomography (ERT) method to obtain high-resolution images of the soil profile. The spatial variability of soil properties and their relationships with EC in horizontal and vertical mode was estimated using multivariate geostatistical techniques. Spatial dependence between EC and physical soil properties (particle-size distribution) was explored with factorial kriging analysis (FKA) that could isolate and display sources of variation acting at different spatial scales, expressed as regionalised factors, which was followed by fuzzy c-means classification for zoning the vineyard. There was a generally close relationship between EC and the measured physical properties: EC was negatively correlated with the coarser texture components (gravel and sand) and positively with the finer ones (clay and silt). EC measurements were also consistent with ERT profiles, evidencing the presence of gravelly parent material, with low electrical conductivity, variably distributed in the 3 dimensions and affecting vine rooting depth. FKA isolated two significant regionalised factors which, with an acceptable loss of information, give a concise description of the soil physical variability at the different selected spatial scales. These factors, used in fuzzy c-means classification, allowed the delineation of zones to be managed separately. The results prove that EM38DD could be advantageously used to map soil spatial variability in gravelly soils, even if ground-truth soil samples are obligatory to understand and interpret the EC measurements.
Small Semi-Weakly Universal Turing Machines
Authors: Damien Woods, Turlough Neary
Venue: Fundamenta Informaticae (2009)

We present three small universal Turing machines that have 3 states and 7 symbols, 4 states and 5 symbols, and 2 states and 13 symbols, respectively. These machines are semi-weakly universal which means that on one side of the input they have an infinitely repeated word, and on the other side there is the usual infinitely repeated blank symbol. This work can be regarded as a continuation of early work by Watanabe on semi-weak machines. One of our machines has only 17 transition rules, making it the smallest known semi-weakly universal Turing machine. Interestingly, two of our machines are symmetric with Watanabe's 7-state and 3-symbol, and 5-state and 4-symbol machines, even though we use a different simulation technique.
Solving Sparse Linear Systems on NVIDIA Tesla GPUs
Authors: Mingliang Wang, Hector Klie, Manish Parashar, Hari Sudan
Venue: Proceedings of the 9th International Conference on Computational Science: Part I (2009)

Current many-core GPUs have enormous processing power, and unlocking this power for general-purpose computing is very attractive due to their low cost and efficient power utilization. However, the fine-grained parallelism and the stream-programming model supported by these GPUs require a paradigm shift, especially for algorithm designers. In this paper we present the design of a GPU-based sparse linear solver using the Generalized Minimum RESidual (GMRES) algorithm in the CUDA programming environment. Our implementation achieved a speedup of over 20x on the Tesla T10P based GTX280 GPU card for benchmarks with from a few thousands to a few millions unknowns. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
Divergent evolution of a Rossmann fold and identification of its oldest surviving ancestor
Authors: William L. Duax, Robert Huether, Vladimir Pletnev, Timothy C. Umland, Charles M. Weeks
Venue: International Journal of Bioinformatics Research and Applications (2009)

&beta;-ketoacyl (acyl carrier protein) reductase (&beta;-k-ACPR) enzymes are essential to fatty acid synthesis in bacteria. The analyses revealed the most primitive member of the &beta;-k-ACPRs family was a NADP reductase where NADP was recognised by a Thr residue in the &beta;2&alpha;3 turn. Aromatic residue stacking at the dimer interface and a previously undetected conserved sequence at the C-terminus, stabilise the oligomeric assembly of these proteins. Our analysis indicates that the primordial members of the &beta;-k-ACPR family probably arose in the &alpha;-proteobacteria and are characterised by the presence of multiple open reading frames and an extreme codon and amino acid bias.
Partial order embedding with multiple kernels
Authors: Brian McFee, Gert Lanckriet
Venue: Proceedings of the 26th Annual International Conference on Machine Learning (2009)

We consider the problem of embedding arbitrary objects (e.g., images, audio, documents) into Euclidean space subject to a partial order over pair-wise distances. Partial order constraints arise naturally when modeling human perception of similarity. Our partial order framework enables the use of graph-theoretic tools to more efficiently produce the embedding, and exploit global structure within the constraint set. We present an embedding algorithm based on semidefinite programming, which can be parameterized by multiple kernels to yield a unified space from heterogeneous features.
Learning Agents and Enhanced Presence for Generation of Services on the Grid
Authors: Clement Jonquet, Marc Eisenstadt, Stefano A. Cerri
Venue: Proceeding of the 2005 conference on Towards the Learning Grid: Advances in Human Learning Services (2005)

Human learning on the Grid will be based on the synergies between advanced artificial and human agents. These synergies will be possible to the extent that conversational protocols among agents, human and/or artificial ones, can be adapted to the ambitious goal of dynamically generating services for human learning. In the paper we highlight how conversations may procure learning both in human and in artificial agents. The STROBE model for communicating agents and its current evolutions shows how an artificial agent may “learn” dynamically (at run time) at the Data, Control and Interpreter level, in particular exemplifying the “learning by being told” modality. The enhanced presence research, exemplified by Buddyspace, in parallel, puts human agents in a rich communicative context where learning effects may occur also as a “serendipitous” side effect of communication.
The color cut quantization algorithm
Authors: Rance D. Necaise, Richard H. Prosl
Venue: Proceedings of the 47th Annual Southeast Regional Conference (2009)

Color quantization is the process of reducing the number of colors used in an image while maintaining the appearance of the original as much as possible. We introduce a new adaptive heuristic color quantization algorithm that can be used in solving this problem. The color cut algorithm iteratively sub divides the RGB color space into clusters containing an equal number of unique image colors from which a representative set is selected for recoloring the image. The new color cut algorithm produces better analytical and visual results compared to some of the more popular heuristic algorithms.
The Influence of Learner Characteristics on Task-Oriented Tutorial Dialogue
Authors: Kristy Elizabeth Boyer, Mladen A. Vouk, James C. Lester
Venue: Proceeding of the 2007 conference on Artificial Intelligence in Education: Building Technology Rich Learning Contexts That Work (2007)

Tutorial dialogue has been the subject of increasing attention in recent years, and it has become evident that empirical studies of human-human tutorial dialogue can contribute important insights to the design of computational models of dialogue. Students with particular characteristics may have specific dialogue profiles, and knowledge of such profiles could inform the design of tutorial dialogue systems whose strategies leverage the characteristics of the target population and address the communicative needs of those students. This paper reports on a study that was conducted to investigate the influence of learner characteristics (performance levels, self-efficacy, and gender) on the structure of task-oriented tutorial dialogue. A tutorial dialogue corpus was gathered from interactions transpiring in the course of problem-solving in a learning environment for introductory computer science. Analyses of the annotated dialogues suggest that the dialogue structure of (1) low-performing students differs significantly from that of high-performing students, (2) students with low self-efficacy differs significantly from that of students with high self-efficacy, and (3) males differs significantly from that of females.
Tunable robust compensator design for an adaptive optics system
Authors: Reziwan Maimaiti, Noriaki Miura, Toshio Eisaka
Venue: Proceedings of the 7th WSEAS international conference on Computational intelligence, man-machine systems and cybernetics (2008)

Adaptive Optics is a developing technology, which is commonly used in ground-based astronomical telescopes. To achieve high-resolution imaging of targets in space, it is of key importance to reduce the effects of atmospheric turbulence by operating a deformable mirror. Various computer control approaches have been applied to overcome this problem. In this paper, we propose a simple and tunable robust controller design for an AO system. Simulation and experimental results are presented demonstrating the efficiency of the proposed design.
Enhance Neural Networks Training Using GA with Chaos Theory
Authors: K. Y. Leong, Augustina Sitiol, Kalaiarasi Sonai Anbananthen
Venue: Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part II (2009)

There are numerous algorithms available for training artificial neural networks. Besides classical algorithms for supervised learning such as backpropagation, associative memory and radial basis function, this training task can be employed by evolutionary computation since most of the gradient descent related algorithms can be view as an application of optimization theory and stochastic search. In this paper, the logistic model of population growth from ecology is integrated into initialization, selection and crossover operators of genetic algorithms for neural network training. These chaotic operators are very efficient in maintaining the population diversity during the evolution process of genetic algorithms. A comparison is done on the basis of a benchmark comprising several data classification problems for neural networks. Three variants of training --- Backpropagation (BP), Genetic Algorithms (GA) and Genetic Algorithms with Chaotic Operators (GACO) --- are described and compared. The experimental results confirm the dynamic mobility of chaotic algorithms in GACO network training, which can overcome saturation and improve the convergence rate.
Impact of multiple channels and radios on the performance of a TDMA based wireless mesh network
Authors: A. Antony Franklin, Vibhav Bukkapatanam, C. Siva Ram Murthy
Venue: Computer Networks: The International Journal of Computer and Telecommunications Networking (2009)

In this paper, we theoretically analyze the performance in terms of end-to-end call acceptance in Multi-Channel Multi-Radio (MC-MR) Wireless Mesh Networks (WMNs) using queueing theory techniques. We study the impact of the routing protocol and the channel assignment algorithm on the end-to-end call acceptance and address the issue of providing deterministic QoS guarantees to a designated set of nodes. The significance of our work lies in providing an insight into the bounds of the probability of call acceptance under a given set of parameters for a WMN and provide a framework for comparison of existing routing protocols and channel assignment algorithms. This can be used for network dimensioning and comparative study of different protocols. We have adopted a TDMA-based WMN as our base framework. We consider the case of differentiated class of users and derive upper P"A"c"c^M^a^x and lower P"A"c"c^M^i^n bounds for the probability of call acceptance (P"A"c"c) and theoretically estimate the probability of system saturation (P"S"a"t) (which is the probability that no more new calls can be accepted in the network). Through simulations, we study the dependence of the (P"A"c"c) on the number of radios in each node (K), the number of channels available in the network (C), the network load (@r), the routing protocol used, and the channel assignment algorithm. We also study the effect of Weighted Cumulative Expected Transmission Time (WCETT) routing metric and compare its performance with the Shortest Path (SP) routing protocol. The increase in P"A"c"c with the WCETT metric emphasizes the need to consider better routing metrics in an MC-MR network.
Multimodal student interaction online: An ecological perspective
Authors: Therese Örnberg Berglund
Venue: ReCALL (2009)

This article describes the influence of tool and task design on student interaction in language learning at a distance. Interaction in a multimodal desktop video conferencing environment, FlashMeeting, is analyzed from an ecological perspective with two main foci: participation rates and conversational feedback strategies. The quantitative analysis of participation rates shows that as far as verbal interaction is concerned, multimodality did not have an equalizing effect in this context, contradicting previous research on multimodal student interaction. Additionally, the qualitative analysis of conversational feedback strategies shows that whereas some multimodal strategies were employed, the students did not manage to fully act upon the communicative affordances of the tool, as the feedback ratio during and after the often long broadcasts was relatively low. These findings are related to task and tool design and the article discusses how design improvements in these areas might result in a more constructive language learning ecology.
An empirical investigation of perceived violence in communication in six different university settings in Romania
Authors: Victoria Burtea, Livia Sangeorzan, Liliana Rogozea, Corneliu Mosoiu, Anisor Nedelcu, Mihaela Popescu
Venue: Proceedings of the 10th WSEAS international conference on Mathematical and computational methods in science and engineering (2008)

This paper is the result of a research that examined, analyzed and interpreted the differences in the perceptions of violence in communication in six different university settings in Romania, by investigating the relative and the combined influence of the place and frequency of violence with relevance to the response. The study utilized a new analytic framework for understanding the personalized perception of violence through a self-administered questionnaires divided into five sections, investigating the socio-demographic data, the presence of violence as a problem of the main issue, the places, the frequencies, the perception of different forms of verbal and non-verbal violence in communication and their induced response. The data were analyzed by using statistical elements. The findings have suggested that communication is far from being a neutral way even in the same country and everyday life perceptions of violence can induce a specific response.
Cascading Trilinear Tensors for Face Authentication
Authors: Gregory M. Wagner, Eric D. Sinzinger
Venue: Proceedings of the 2008 IEEE Workshop on Applications of Computer Vision (2008)

This paper presents a method to improve the accuracy rates of face authentication between images with different poses. Trilinear tensors are used to adjust the pose of the training and testing images. All the images are transformed by a pose adjustment algorithm so novel images are generated that have the same pose. These novel images are then used to train and test support vector machine (SVM) face authentication functions to verify the identity of the people in the images. The overall results show that the accuracy improves when the poses of the images are adjusted.
Benefits of inserting support devices in electronic learning environments
Authors: Geraldine Clarebout, Jan Elen
Venue: Computers in Human Behavior (2009)

Research on support device-usage reveals that support devices are seldom used, and if used often in an inadequate way such that it is no longer a learning opportunity [Aleven, V., Stahl, E., Schworm, S., Fischer, F., & Wallace, R. (2003). Help seeking and help design in interactive learning environments. Review of Educational Research,73, 277-320; Clarebout, G., & Elen, J. (2006). Tool use in computer-based learning environments: Towards a research framework. Computers in Human Behavior,22, 389-411.]. In view of establishing a solid research agenda on the optimization of the use of instructional interventions and support devices, this article discusses three experimental studies, each dealing with different aspects of support device use. In a first study, the impact on support device use of different types and numbers of adjunct aids was investigated. In a second study, the influence of advice on support device use in an open learning environment is studied, while also considering various learner related variables. A third study addresses the use of support devices in a text-based environment. The results of the three studies reveal that the amount of support device usage is limited and that even advice on the use of the support device cannot always enhance this use. Studies 1 and 2 revealed that the type of support devices influenced the amount of usage. With respect to learner characteristics, studies 2 and 3 revealed no significant effect of self regulation. Students' mastery orientation on the other hand did influence the support device usage. Reasons for the low usage of support devices are addressed in the discussion.