ppxscal/embedding_network huggingface dataset:
Architectural exploration of heterogeneous multiprocessor systems for JPEG
Authors: Seng Lin Shee, Andrea Erdos, Sri Parameswaran
Venue: International Journal of Parallel Programming (2008)

Multicore processors have been utilized in embedded systems and general computing applications for some time. However, these multicore chips execute multiple applications concurrently, with each core carrying out a particular task in the system. Such systems can be found in gaming, automotive real-time systems and video / image encoding devices. These system are commonly deployed to overcome deadline misses, which are primarily due to overloading of a single multitasking core. In this paper, we explore the use of multiple cores for a single application, as opposed to multiple applications executing in a parallel fashion. A single application is parallelized using two different methods: one, a master-slave model; and two, a sequential pipeline model. The systems were implemented using Tensilica's Xtensa LX processors with queues as the means of communications between two cores. In a master-slave model, we utilized a course grained approach whereby a main core distributes the workload to the remaining cores and reads the processed data before writing the results back to file. In the pipeline model, a lower granularity is used. The application is partitioned into multiple sequential blocks; each block representing a stage in a sequential pipeline. For both models we applied a number of differing configurations ranging from a single core to a nine-core system. We found that without any optimization for the seven core system, the sequential pipeline approach has a more efficient area usage, with an area increase to speedup ratio of 1.83 compared to the master-slave approach of 4.34. With selective optimization in the pipeline approach, we obtained speed ups of up to 4.6× while with an area increase of only 3.1× (area increase to speedup ratio of just 0.68).
Fine Granularity Access Rights for Information Flow Control in Object Oriented Systems
Authors: Allaoua Maamir, Abdelaziz Fellah, Lina A. Salem
Venue: Proceedings of the 2008 International Conference on Information Security and Assurance (isa 2008) (2008)

One of the main features of information flow control is to ensure the enforcement of privacy and regulated accessibility. However, most information flow control models that have been proposed do not provide substantial assurance to enforce end-to-end confidentiality policies or they are too restrictive, overprotected, and inflexible. We present a model for discretionary access controls that is in harmony with the object oriented paradigm. The model uses access rights applied to object attributes and methods, thus allowing considerable flexibility without compromising system security by leaking sensitive information. Models based on message filtering intercept every message exchanged among objects to control the flow of information. We present an algorithm which enforces message filtering based on the defined access rights.
Assessing the Applicability of Use Case Maps for Business Process and Workflow Description
Authors: Gunter Mussbacher, Daniel Amyot
Venue: Proceedings of the 2008 International MCETECH Conference on e-Technologies (2008)

Use Case Maps (UCMs) have already been used to describe business processes and workflows at a high level of abstraction. The semantics of UCMs, however, require further clarification and enhancement. An initial assessment based on 27 workflow and communication patterns (a) highlighted some of the semantic variation points of UCMs, (b) introduced small extensions to the UCM language in order to more precisely define scenarios, high-level business processes, and workflows, and (c) compared UCMs with other business process and workflow languages. This short paper summarizes the continuation of the assessment with a larger set of workflow patterns recently made available. The assessment concludes that the UCM notation including the proposed extensions is a competitive language to describe high-level business processes and workflows, while providing additional benefits over the other languages.
Convergence of an implicit, constraint preserving finite element discretization of p-harmonic heat flow into spheres
Authors: S&#x00f6;ren Bartels, Andreas Prohl
Venue: Numerische Mathematik (2008)

We propose an implicit discretization of the p-harmonic map heat flow into the sphere S 2 that enjoys a discrete energy inequality and converges under only a mild mesh constraint to a weak solution. A fully practical iterative scheme that approximates the solution of the nonlinear system of equations in each time step is proposed and analyzed. Computational studies to motivate possible finite-time blow-up behavior of solutions for p&#x00a0;&#x2260; 2 are included.
Combinational pricing method for active and reactive power in power system
Authors: J. Aghaei, A. Kazemi, H. A. Shayanfar, M. Yari
Venue: Proceedings of the 9th International Conference on Circuits (2005)

This paper proposes a price mechanism with one price assigned for each level of bundled real and reactive power. The better allocation under this pricing method raises system efficiency via better allocation of the reactive power reserves, neglected in the traditional pricing approach. Pricing reactive power separately is not very practical since its cost is highly dependent on real power output. Equilibrium allocation of the bundled pricing is simulated on the simple 3-bus system power auction and compared with free reactive power optimal power flow solution. The efficiency of this approach is shown in the general case, and tested on the 30-bus IEEE network with piecewise linear cost functions of the generators.
Detection of interesting rules using visualization of differences between rules' syntactic and semantic similarities using multidimensional scaling
Authors: Shusaku Tsumoto, Shoji Hirano
Venue: International Journal of Knowledge-based and Intelligent Engineering Systems (2007)

One of the most important problems with rule induction methods is that it is very difficult for domain experts to check millions of rules generated from large datasets, although the discovery from these rules requires deep interpretation from domain knowledge. Although several solutions have been proposed in the studies on data mining and knowledge discovery, these studies are not focused on similarities between rules obtained. When one rule r_1 has reasonable features and the other rule r_2 with high similarity to r_1 includes unexpected factors, the relations between these rules will become a trigger to the discovery of knowledge. In this paper, we propose a visualization approach to show the similarity relations between rules based on multidimensional scaling, which assign a two-dimensional cartesian coordinate to each data point from the information about similarities between this data and others data. We evaluated this method on two medical data sets, whose experimental results show that knowledge useful for domain experts can be found.
A Novel Method for Extraction of Spleen by Using Thin-plate Splines (TPS) Deformation and Edge Detection from Abdominal CT Images
Authors: Xuejun Zhang, Hiroshi Fujita, Tuanfa Qin, Jinchuang Zhao, Yurong Qin, Chao Gao, Liling Long, Zuojun Zhang
Venue: Proceedings of the 2008 International Conference on BioMedical Engineering and Informatics - Volume 01 (2008)

The spleen is always hypertrophied in the patient with cirrhotic liver, which is regarded as one of complementary features for analysis of cirrhosis. Furthermore, segmentation of an abnormal spleen region based on CT or MR images is a crucial step in surgical planning. However, precisely carrying out this step remains a challenge due to either connectivities of the spleen to other organs or the shape, internal texture, and homogeneity of spleen that maybe extensively affected in case of liver diseases. In this paper, we propose a non-density based method for extracting the abnormal spleen region by edge detection processing. The accuracy of segmentation of spleen in 20 cases is the coincidence ratio 0.96 with the average error rate of 4.3%, and the result showed that our fully automatic method for the segmentation is effective and robust despite the presence of abnormal tissues within the spleen.
Local asymptotic identifiability of the periodic linear systems
Authors: N. A. Bodunov
Venue: Automation and Remote Control (2008)

For the linear periodic systems of differential equations depending on a vector parameter, the notion of local asymptotic identifiability was introduced. Conditions for which local parametric identifiability at a singlefold observation of the system state vector follows from local asymptotic identifiability were obtained. A class of systems for which these conditions are satisfied was specified.
Combining metaheuristics and constraint programming to solve a scheduling problem
Authors: Nuno Gomes, Zita Vale, Carlos Ramos
Venue: Proceedings of the 4th WSEAS International Conference on Applied Mathematics and Computer Science (2005)

In this paper we present a hybrid method, named Quasi Local Search, which combines Simulated Annealing augmented with a type of Tabu List to guide the search globally with Constraint Programming to search locally the optimal solution. The method can also be seen as an integration framework, once the Local Search module is independent of the Constraint Programming one and either can be worked independently. The method is used to solve a Generator Maintenance Scheduling Problem with promising results. We also present a study about the se-lection of certain parameters and neighbourhood structure. The result allows us to conclude about their influence on the method's performance.
Fuzzy adaptive networks in credit rating and loan approval
Authors: Kuental Chen, E. Stanley Lee
Venue: Proceedings of the 10th WSEAS International Conference on APPLIED MATHEMATICS (2006)

Fuzzy adaptive network (FAN) is proposed to help decision makers in credit scores and to assign the amount of loan. By combining with neural networks to incorporate the learning ability, FAN provides an alternative approach for the imprecision and fuzziness of the credit rating system. A loan approval example is given and the performance of FAN is compared with the regression algorithm. The results show that FAN is favored than regression in this financial application.
A fast haplotype inference method for large population genotype data
Authors: Ji-Hong Zhang, Ling-Yun Wu, Jian Chen, Xiang-Sun Zhang
Venue: Computational Statistics Data Analysis (2008)

With the rapid progress of genotyping techniques, many large-scale, genome-wide disease studies are now under way. One of the challenges of large disease-association studies is developing a fast and accurate computing method for haplotype inference from genotype data. In this paper, a new computing method for population-based haplotype inference problem is proposed. The designed method does not assume haplotype blocks in the population and allows each individual haplotype to have its own structure, and thus is able to accommodate recombination and obtain higher adaptivity to the genotype data, specifically in the case of long marker maps. This method develops a dynamic programming algorithm, which is theoretically guaranteed to find exact maximum likelihood solutions of the variable order Markov chain model for haplotype inference problem within linear running time. Hence, it is fast and, as a result, practicable for large genotype datasets. Through extensive computational experiments on large-scale real genotype data, the proposed method is shown to be fast and efficient.
Fuzzy Q-Learning with the modified fuzzy ART neural network
Authors: Hiroaki Ueda, Takeshi Naraki, Naoki Hanada, Hideaki Kimoto, Kenichi Takahashi, Tetsuhiro Miyahara
Venue: Web Intelligence and Agent Systems (2007)

We present a method to acquire rules for agent behavior, where continuous numeric percepts are classified into categories by fuzzy ART and fuzzy Q-learning is employed to acquire rules. To make fuzzy ART be fit for fuzzy Q-learning, we modify fuzzy ART such that it selects multiple categories for a percept vector and calculate their fitness values. For efficient learning, we also implement category integration that integrates two categories into one in order to reduce the number of categories. Moreover, we modify the choice function to be fit for our modified fuzzy ART and also modify the timing of category integration for efficient learning. Experimental results show that our method acquires good rules for agent behavior more efficiently than Q-learning with fuzzy ART.
Graph transduction via alternating minimization
Authors: Jun Wang, Tony Jebara, Shih-Fu Chang
Venue: Proceedings of the 25th international conference on Machine learning (2008)

Graph transduction methods label input data by learning a classification function that is regularized to exhibit smoothness along a graph over labeled and unlabeled samples. In practice, these algorithms are sensitive to the initial set of labels provided by the user. For instance, classification accuracy drops if the training set contains weak labels, if imbalances exist across label classes or if the labeled portion of the data is not chosen at random. This paper introduces a propagation algorithm that more reliably minimizes a cost function over both a function on the graph and a binary label matrix. The cost function generalizes prior work in graph transduction and also introduces node normalization terms for resilience to label imbalances. We demonstrate that global minimization of the function is intractable but instead provide an alternating minimization scheme that incrementally adjusts the function and the labels towards a reliable local minimum. Unlike prior methods, the resulting propagation of labels does not prematurely commit to an erroneous labeling and obtains more consistent labels. Experiments are shown for synthetic and real classification tasks including digit and text recognition. A substantial improvement in accuracy compared to state of the art semi-supervised methods is achieved. The advantage are even more dramatic when labeled instances are limited.
Compiler error messages: what can help novices?
Authors: Marie-Hélène Nienaltowski, Michela Pedroni, Bertrand Meyer
Venue: Proceedings of the 39th SIGCSE technical symposium on Computer science education (2008)

Novices find it difficult to understand and use compiler error messages. It is useful to refine this observation and study the effect of different message styles on how well and quickly students identify errors in programs. For example, does an increased level of detail simplify the understanding of errors and their correction? We analyzed messages produced by a number of compilers for five programming languages, and grouped them into three style categories from their level of detail and presentation format, and correlated the level of experience and error type with performance and speed of response. The study involved two groups of students taking an introductory programming course at two different institutions; they used messages in these three styles to debug erroneous code. The results indicate that more detailed messages do not necessarily simplify the understanding of errors but that it matters more where information is placed and how it is structured.
A note on two source location problems
Authors: Guy Kortsarz, Zeev Nutov
Venue: Journal of Discrete Algorithms (2008)

We consider Source Location (SL) problems: given a capacitated network G=(V,E), cost c(v) and a demand d(v) for every v@?V, choose a min-cost S@?V so that @l(v,S)>=d(v) holds for every v@?V, where @l(v,S) is the maximum flow value from v to S. In the directed variant, we have demands d^i^n(v) and d^o^u^t(v) and we require @l(S,v)>=d^i^n(v) and @l(v,S)>=d^o^u^t(v). Undirected SL is (weakly) NP-hard on stars with r(v)=0 for all v except the center. But, it is known to be polynomially solvable for uniform costs and uniform demands. For general instances, both directed an undirected SL admit a (lnD+1)-approximation algorithms, where D is the sum of the demands; up to constant this is tight, unless P=NP. We give a pseudopolynomial algorithm for undirected SL on trees with running time O(|V|@D^3), where @D=max"v"@?"Vd(v). This algorithm is used to derive a linear time algorithm for undirected SL with @D=
A new adaptive fuzzy controller with saturation employing influential rule search scheme (IRSS)
Authors: A. Chatterjee, M. Maitra, A. Rakshit, P. Siarry
Venue: International Journal of Knowledge-based and Intelligent Engineering Systems (2007)

The present paper describes the development of a new adaptive fuzzy logic controller (AFLC), which can directly employ an adaptive fuzzy/neuro/neuro-fuzzy function approximator to develop a desired controller, based on an ideal controller input-output data set. The system also proposes the development of the AFLC based on a new adaptive fuzzy system, called influential rule search scheme (IRSS), as a pure function approximation tool. The proposed AFLC employs two additional sub-modules: i) a new static fuzzy resetting action controller (FRAC), which fuzzily changes the resetting action of the controller at each sampling instant, to enhance system performance, and ii) a new fuzzy inverse process estimator, based on IRSS as a function approximator itself. Simulation studies are shown to demonstrate the effectiveness of the proposed controller scheme over conventional PID controllers and other existing fuzzy and neural network based controllers.
Blood Electrolyte Homeostasis of Rat after High-intensive Swimming Training
Authors: Seol-Hee Jeon, Mun-Young Lee, Shang-Jin Kim, Md. Mizanur Rahmana, Gi-Beum Kim, Jin-Shang Kim, Hyung-Sub Kang
Venue: Proceedings of the 2008 International Conference on BioMedical Engineering and Informatics - Volume 01 (2008)

In sports medicine, very little attention has been given to magnesium compared with potassium and calcium. Magnesium ions (Mg2+) play a central role of neuronal activity, cardiac excitability, neuromuscular transmission, muscular contraction, vasomotor tone, and blood pressure significantly related to physical performance. Exercise is a potent stressor that appears to lead to magnesium depletion through alterations on blood magnesium levels as well as increased sweat and urine excretion. After exhausted swimming (3-4 hrs) in rats, the iCa2+/iMg2+ were significantly decreased. The Na+, iCa2+, iMg2+, and anion gap were significantly increased. These data suggest that exercise could alter blood iMg2+, iCa2+ and the ratio of iCa2+/iMg2+ and point to important uses for iMg2+ and the ratio of iCa2+/iMg2+ during the training and examination of athletic performance in sports medicine.
Concurrent topology and routing optimization in automotive network integration
Authors: Martin Lukasiewycz, Michael Glaß, Christian Haubelt, Jürgen Teich, Richard Regler, Bardo Lang
Venue: Proceedings of the 45th annual Design Automation Conference (2008)

In this paper, a novel automatic approach for the concurrent topology and routing optimization that achieves a high quality network layout is proposed. This optimization is based on a specialized binary Integer Linear Program (ILP) in combination with a Multi-Objective Evolutionary Algorithm (MOEA). The ILP is formulated such that each solution represents a topology and routing that fulfills all requirements and demands of the network. Thus, in an iterative process, this ILP is solved to obtain feasible networks whereas the MOEA is used for the optimization of multiple even non-linear objectives and ensures a fast convergence towards the optimal solutions. Additionally, a domain specific preprocessing algorithm for the ILP is presented that decreases the problem complexity and, thus, allows to optimize large and complex networks efficiently. The experimental results validate the performance of this methodology on two state-of-the-art prototype automotive networks.
Non-data-aided carrier-frequency offset estimation for pulse-shaping OFDM/OQAM systems
Authors: Tilde Fusco, Angelo Petrella, Mario Tanda
Venue: Signal Processing (2008)

In this paper we consider the problem of blind carrier-frequency offset (CFO) estimation for pulse-shaping orthogonal frequency-division multiplexing (OFDM) systems based on offset quadrature amplitude modulation (OQAM). In particular, under the assumption of low signal-to-noise ratio, three maximum-likelihood (ML) CFO estimators for non-dispersive channels are derived. Due to their significant computational complexity a more feasible closed-form CFO synchronization algorithm is considered. The performance of the derived blind estimators is assessed via computer simulations and compared with that of a blind CFO estimator previously proposed in the literature, exploiting the second-order cyclostationarity property of the OFDM/OQAM signal.
Query efficiency in probabilistic XML models
Authors: Benny Kimelfeld, Yuri Kosharovsky, Yehoshua Sagiv
Venue: Proceedings of the 2008 ACM SIGMOD international conference on Management of data (2008)

Various known models of probabilistic XML can be represented as instantiations of abstract p-documents. Such documents have, in addition to ordinary nodes, distributional nodes that specify the probabilistic process of generating a random document. Within this abstraction, families of pdocuments, which are natural extensions and combinations of previous models, are considered. The focus is on efficiency of applying twig queries (with projection) to p-documents. A closely related issue is the ability to (efficiently) translate a given document of one family into another family. Furthermore, both of these tasks have two variants that correspond to the value-based and object-based semantics. The translation relationships among different families of p-documents are studied. An efficient algorithm for evaluating twig queries over one specific family is given. This algorithm generalizes a known algorithm and significantly improves its running time, both analytically and experimentally. It is shown that this family is the maximal, among the ones considered, for which query evaluation is tractable. For the rest, efficient approximate algorithms for query evaluation are presented.
Pedestrian navigation systems: a showcase for deep personalization theory
Authors: Xiangkui Yao
Venue: Proceedings of the 9th international conference on Human computer interaction with mobile devices and services (2007)

There has been a rapid growth in navigation aids recently. However, no meaningful personalization exists in these devices. Theories and pilot studies show the importance of individual differences in designing pedestrian navigation assistants. I take a Requirements Engineering (RE) perspective to approach the personalization problem. Different from viewing users as a general consumer group, I propose a "deep personalization" method that pays attention to knowledge of an individual user's skills and limitations. In some cases, these skills and limitations might not be self- aware, i.e., a user cannot accurately self- reflect on his or her skills and weaknesses. In this paper, I will demonstrate the notion of deep personalization in the domain of personal navigation systems. I find this an interesting domain for several reasons: (1) There is a domain theory of navigation skills that draws from both Cartography and Psychology. (2) There are individual differences in navigation skills. (3) An individual user may not be self- aware of his or her skills. (4) If a system is delivered that does not match the skills of the user, it may be less than effective, and at worst, abandoned.