ppxscal/embedding_network huggingface dataset:
Maximal pattern complexity of higher dimensional words
Authors: Yan-hui Qu, Hui Rao, Zhi-ying Wen, Yu-mei Xue
Venue: Journal of Combinatorial Theory Series A (2010)

This paper studies the pattern complexity of n-dimensional words. We show that an n-recurrent but not n-periodic word has pattern complexity at least 2k, which generalizes the result of [T. Kamae, H. Rao, Y.-M. Xue, Maximal pattern complexity of two dimension words, Theoret. Comput. Sci. 359 (1-3) (2006) 15-27] on two-dimensional words. Analytic directions of a word are defined and its topological properties play a crucial role in the proof. Accordingly n-dimensional pattern Sturmian words are defined. Irrational rotation words are proved to be pattern Sturmian. A new class of higher dimensional words, the simple Toeplitz words, are introduced. We show that they are also pattern Sturmian words.
Brief paper: Stability analysis of planar systems with nilpotent (non-zero) linear part
Authors: Laura Menini, Antonio Tornambè
Venue: Automatica (Journal of IFAC) (2010)

A simple necessary and sufficient condition for asymptotic stability of the origin is derived for a large class of planar nonlinear systems that cannot be studied by means of their linearization, which is nilpotent and not zero. The condition is based on the use of Darboux polynomials, to derive a Lyapunov function for the first approximation of the system with respect to a vector function representing a dilation. Results by Andreev (1958), on the qualitative behaviour of equilibrium points, and the Belitskii normal form are used in the proofs. The proposed condition is applied to the asymptotic stabilization of the origin, for a class of planar systems whose linearization cannot be stabilized.
Energy-efficient fault-tolerance schemes for multi-core hard real-time systems
Authors: Piyush Mishra
Venue:  (2009)

As technology advances towards the deep submicron devices, all digital systems are expected to be remarkably vulnerable to single event upset (SEU)-induced transient faults with the continuous shrinking of the feature size and reducing of the threshold voltage. However, for the current rate of transient fault arrival, fault occurrences are expected to remain infrequent in the foreseeable future and fault-free operation will continue to dominate, which necessitates designing hard real-time embedded systems assuming no fault occurrences while maintaining the schedule timeliness when faults occur in burst. This dissertation explores the joint optimization of fault-tolerance and energy in addition to timeliness for fixed-priority-based hard real-time embedded systems. For uniprocessor systems, two low-cost offline scheduling schemes with varying granularity of dynamic voltage scaling (DVS) policies are designed that enable the dynamic extensions of the offline schedules to adapt to the runtime behavior of fault occurrences. The optimality, complexity, fault-tolerance, and energy consumption of the proposed schemes are investigated and compared with those of the state-of-art optimal schemes. Two dynamic scheduling schemes that re-evaluate DVS policies at runtime to achieve energy savings are also devised. Energy-efficient task allocation and scheduling schemes with deterministic fault-tolerance capabilities for symmetric multiprocessor or multi-core hard real-time systems aim at achieving optimum energy savings in the absence of faults and meeting application timing requirements in the worst case faults at the cost of energy inefficiency. A novel task allocation scheme with proven optimal load-balancing property is designed for optimum energy savings, and an optimistic fault-tolerance task allocation and scheduling scheme is proposed to achieve optimum energy savings in reliable hard real-time multiprocessor systems. Finally, a real-life test bed comprising Intel Core Duo T2500 processor with DVS capability and running Linux Fedora 8-based hard real-time scheduling has been developed, and the proposed energy-efficient fault-tolerance task allocation and scheduling schemes are implemented and validated on the test bed. The experimental results on the test bed are reported and the discrepancies between the experimental results and simulation results are investigated. As a whole, this dissertation investigates and justifies the designing of energy-efficient fault-tolerance hard real-time systems for the best case of fault occurrences without compromising the schedule timeliness. The research results show that this design strategy is particularly promising for emerging applications where timeliness, fault-tolerance, and energy dimensions need to be simultaneously addressed. 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
A scatter search algorithm for solving vehicle routing problem with loading cost
Authors: Jiafu Tang, Jun Zhang, Zhendong Pan
Venue: Expert Systems with Applications: An International Journal (2010)

The vehicle routing problem (VRP) is an important scientific problem addressed in distribution management. In classical VRP and its variants, the vehicle load is often regarded as a constant during transportation; therefore the loading cost associated with the amount of the load on the vehicle, are neglected in the objective function when optimizing a vehicle routine. However, in real-world, the vehicle load varies from one customer to another in a vehicle route. Thus, the vehicle route without considering the effect of loading cost may lead to sub-optimal routes. In this paper, we investigate VRP with loading cost (VRPLC), which considers the costs associated with the amount of the load on the vehicle when determining the vehicle routes. Considering the features of the VRPLC, a scatter search (SS) is proposed. By introducing customer-oriented three-dimensional encoding method, sweep algorithm and optimal splitting procedure are combined to obtain better trial solutions. The arc combination and improved nearest neighbor heuristic are adopted as a solution combination method and an improvement method to generate and improve new solutions, respectively. Computational experiments were carried out on benchmark problems of capacitated VRP with seven categories of distribution scenarios. The computational results show that the SS is competitive and superior to other algorithms on most instances, and that the VRPLC can more reasonably and exactly formulate the vehicle routing problem with more cost savings than general VRP models.
A novel design of self-routing strictly nonblocking switching networks
Authors: E. Lu, M. Yang, B. Yang, X. Feng, S. Q. Zheng
Venue: International Journal of Computers and Applications (2008)

Optical communications with photonic switching are promising to provide high bandwidth and low error bit. Self-routing strictly nonblocking networks are always favoured to be used as switching networks due to their simple routing mechanisms and nonblocking properties. However, crosstalk problems in photonic switching add a new dimension of nonblocking constraints on optical switching networks. The classical self-routing strictly nonblocking N x N crossbar network has N2 switching elements (SEs) and 2N -- 1 connection diameter, and needs N wavelengths for nonblocking switching. In this paper, we propose a new class of self-routing strictly nonblocking networks by studying the connection capacity of self-routing blocking Banyan-type networks. The new proposed N x N networks have no more than N2 -- N SEs and (log N) connection diameter. Furthermore, they need no more than two wavelengths for nonblocking switching. Compared with existing strictly nonblocking self-routing networks, the presented new networks have lower hardware cost, shorter connection diameter, and much smaller number of required wavelengths. Consequently, they are more feasible for implementation with reduced optical signal attenuation and crosstalk.
Schubmehl-Prein essay competition: "What are the Potential Social and Ethical Implications of the $100 Laptop?"
Authors: Kevin W. Bowyer
Venue: ACM SIGCAS Computers and Society (2010)

The 2009 competition was the fifth year of the Schubmehl-Prein contest for the Best Essay on Social Impact of Computing. The competition is open to high school juniors each year, with a submission deadline at the end of May. The essay topic varies each year, with the 2009 topic being, "What are the potential social and ethical implications of the $100 laptop?" The 2009 competition attracted a number of essays that strongly engaged with the topic. The 2009 First Place winner is Katherine Heit (Saint Thomas Aquinas High School, Kansas), the Second Place winner is Danielle Harris (Mayfield Senior School, California), and the Third Place winner is David Purington (Damien High School, California). In addition, this year, for the first time, two Honorable Mention winners were also selected: Bryan Dongre (Brookfield Central High School, Wisconsin) and Erica Smith (St. Agnes Academy, Texas). Revised versions of the First, Second and Third Place essays appear in this issue of Computers and Society. Congratulations to all of this year's winners. Thanks to all of the students who prepared and submitted an entry to the competition. And thanks as well to all of the teachers and school counselors who worked with all of the students.
Poincaré inequalities with the Radon measure for differential forms
Authors: Yuming Xing, Shusen Ding
Venue: Computers Mathematics with Applications (2010)

We establish the local and global Poincare inequalities with the Radon measure for the solutions to the nonlinear elliptic partial differential equation for differential forms.
A one-step 7-stage Hermite-Birkhoff-Taylor ODE solver of order 11
Authors: Truong Nguyen-Ba, Vladan Bozic, Emmanuel Kengne, Rémi Vaillancourt
Venue: Journal of Computational and Applied Mathematics (2010)

A one-step 7-stage Hermite-Birkhoff-Taylor method of order 11, denoted by HBT(11)7, is constructed for solving nonstiff first-order initial value problems y^'=f(t,y), y(t"0)=y"0. The method adds the derivatives y^' to y^(^6^), used in Taylor methods, to a 7-stage Runge-Kutta method of order 6. Forcing an expansion of the numerical solution to agree with a Taylor expansion of the true solution to order 11 leads to Taylor- and Runge-Kutta-type order conditions. These conditions are reorganized into Vandermonde-type linear systems whose solutions are the coefficients of the method. The new method has a larger scaled interval of absolute stability than the Dormand-Prince DP87 and a larger unscaled interval of absolute stability than the Taylor method, T11, of order 11. HBT(11)7 is superior to DP87 and T11 in solving several problems often used to test higher-order ODE solvers on the basis of the number of steps, CPU time, and maximum global error. Numerical results show the benefit of adding high-order derivatives to Runge-Kutta methods.
GO-Bayes
Authors: Song Zhang, Jing Cao, Y. Megan Kong, Richard H. Scheuermann
Venue: Bioinformatics (2010)

Motivation: A typical approach for the interpretation of high-throughput experiments, such as gene expression microarrays, is to produce groups of genes based on certain criteria (e.g. genes that are differentially expressed). To gain more mechanistic insights into the underlying biology, overrepresentation analysis (ORA) is often conducted to investigate whether gene sets associated with particular biological functions, for example, as represented by Gene Ontology (GO) annotations, are statistically overrepresented in the identified gene groups. However, the standard ORA, which is based on the hypergeometric test, analyzes each GO term in isolation and does not take into account the dependence structure of the GO-term hierarchy. Results: We have developed a Bayesian approach (GO-Bayes) to measure overrepresentation of GO terms that incorporates the GO dependence structure by taking into account evidence not only from individual GO terms, but also from their related terms (i.e. parents, children, siblings, etc.). The Bayesian framework borrows information across related GO terms to strengthen the detection of overrepresentation signals. As a result, this method tends to identify sets of closely related GO terms rather than individual isolated GO terms. The advantage of the GO-Bayes approach is demonstrated with a simulation study and an application example. Contact:song.zhang@utsouthwestern.edu; richard.scheuermann@utsouthwestern.edu Supplementary information: Supplementary data are available at Bioinformatics online. 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
Medical decision support systems based on machine learning methods
Authors: W. Nick Street
Venue:  (2009)

This dissertation discusses three problems from different areas of medical research and their machine learning solutions. Each solution is a distinct type of decision support system. They show three common properties: personalized health care decision support, reduction of the use of medical resources, and improvement of outcomes. The first decision support system assists individual hospital selection. This system can help a user make the best decision in terms of the combination of mortality, complication, and travel distance. Both machine learning and optimization techniques are utilized in this type of decision support system. Machine learning methods, such as Support Vector Machines, learn a decision function. Next, the function is transformed into an objective function and then optimization methods are used to find the values of decision variables to reach the desired outcome with the most confidence. The second decision support system assists diagnostic decisions in a sequential decision-making setting by finding the most promising tests and suggesting a diagnosis. The system can speed up the diagnostic process, reduce overuse of medical tests, save costs, and improve the accuracy of diagnosis. In this study, the system finds the test most likely to confirm a diagnosis based on the pre-test probability computed from the patient's information including symptoms and the results of previous tests. If the patient's disease post-test probability is higher than the treatment threshold, a diagnostic decision will be made, and vice versa. Otherwise, the patient needs more tests to help make a decision. The system will then recommend the next optimal test and repeat the same process. The third decision support system recommends the best lifestyle changes for an individual to lower the risk of cardiovascular disease (CVD). As in the hospital recommendation system, machine learning and optimization are combined to capture the relationship between lifestyle and CVD, and then generate recommendations based on individual factors including preference and physical condition. The results demonstrate several recommendation strategies: a whole plan of lifestyle changes, a package of n lifestyle changes, and the compensatory plan (the plan that compensates for unwanted lifestyle changes or real-world limitations). 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
SoDA2
Authors: Supriya Munshaw, Thomas B. Kepler
Venue: Bioinformatics (2010)

Motivation: The inference of pre-mutation immunoglobulin (Ig) rearrangements is essential in the study of the antibody repertoires produced in response to infection, in B-cell neoplasms and in autoimmune disease. Often, there are several rearrangements that are nearly equivalent as candidates for a given Ig gene, but have different consequences in an analysis. Our aim in this article is to develop a probabilistic model of the rearrangement process and a Bayesian method for estimating posterior probabilities for the comparison of multiple plausible rearrangements. Results: We have developed SoDA2, which is based on a Hidden Markov Model and used to compute the posterior probabilities of candidate rearrangements and to find those with the highest values among them. We validated the software on a set of simulated data, a set of clonally related sequences, and a group of randomly selected Ig heavy chains from Genbank. In most tests, SoDA2 performed better than other available software for the task. Furthermore, the output format has been redesigned, in part, to facilitate comparison of multiple solutions. Availability: SoDA2 is available online at https://hippocrates.duhs.duke.edu/soda. Simulated sequences are available upon request. Contact: kepler@duke.edu 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
Processing online analytics with classification and association rule mining
Authors: Amy H. L. Lim, Chien-Sing Lee
Venue: Knowledge-Based Systems (2010)

Business performance measurements, decision support systems (DSS) and online analytical processing (OLAP) have a common goal i.e., to assist decision-makers during the decision-making process. Integrating DSS and OLAP into existing business performance measurements hopes to improve the accuracy of analysis and provide in-depth, multi-angle view of data. This paper describes a decision support system containing our methodology, Weighted and Layered workflow evaluation (WaLwFA), extended to incorporate business intelligence using C4.5 and association rule algorithms. C4.5 produces more comprehensible decision trees by showing only important attributes. Furthermore, C4.5 can be transformed into IF-THEN rules. However, association rules are preferred as data can be described in rules of multiple granularities. Sorting rules based on rules' complexities permits OLAP to navigate through layers of complexities to extract rules of relevant sizes and to view data from multidimensional perspectives in each layer. Experimental results on an airline domain are presented.
Evaluation of a selective distributed discovery strategy in a fully decentralized biologically inspired environment
Authors: Ognen Paunovski, George Eleftherakis, Konstantinos Dimopoulos, Tony Cowling
Venue: Information Sciences: an International Journal (2010)

The increased demand and complexity of services operating within open distributed environments has emphasized the need for systems that are adaptive, self-organizing and more robust. In order to address these issues some agent oriented approaches have adopted ideas from natural systems as possible solutions. The introduction of biological properties, especially birth and death of agents as expected events, generates an extremely dynamic environment where it is difficult to maintain the overall connectivity of the overlay network and facilitate efficient discovery processes. In this paper we evaluate the performance of a selective discovery mechanism in a distributed bio-inspired multi-agent community through a simulation study. The primary focus of the study is on the impacts which death and (sexual/asexual) reproduction events have on the effectiveness of the discovery process in different overlay networks.
Analysis of coordinated load sharing for large distributed systems
Authors: R. Benlamri, H. Barada, A. Al-Raqabani
Venue: International Journal of Computers and Applications (2008)

The performance of a distributed system (DS) is limited by how good the load sharing scheme used in the system is. This fact is especially true for a large-scale DS where the communication bandwidth between machines may be limited. Load sharing is the process of sharing computational resources by distributing the load of a distributed computing system among the various computers in the system. This paper proposes and analyzes new type of algorithms for sharing system loads based on a coordinated dynamic semi-centralized scheme. In this scheme, load state information at each node is centrally collected by a coordinator to optimize the transfer policy, a policy for transferring loads from one computer to another. This information is periodically broadcasted to nodes for decentralizing the decision making for best load allocation policy. The paper discusses the implementation of the scheme and the optimization of its parameters for small systems as well as for large DS where the system is partitioned into multiple partitions according to the available communication bandwidth. Simulations results have shown that this coordinated scheme outperforms widely-used probing-based schemes in most system loads.
Stability assessment of aspect-oriented software architectures: A quantitative study
Authors: Ambra Molesini, Alessandro Garcia, Christina von Flach Garcia Chavez, Thais Vasconcelos Batista
Venue: Journal of Systems and Software (2010)

Design of stable software architectures has increasingly been a deep challenge to software developers due to the high volatility of their concerns and respective design decisions. Architecture stability is the ability of the high-level design units to sustain their modularity properties and not succumb to modifications. Architectural aspects are new modularity units aimed at improving design stability through the modularization of otherwise crosscutting concerns. However, there is no empirical knowledge about the positive and negative influences of aspectual decompositions on architecture stability. This paper presents an exploratory analysis of the influence exerted by aspect-oriented composition mechanisms in the stability of architectural modules addressing typical crosscutting concerns, such as error handling and security. Our investigation encompassed a comparative analysis of aspectual and non-aspectual decompositions based on different architectural styles applied to an evolving multi-agent software architecture. In particular, we assessed various facets of components' and compositions' stability through such alternative designs of the same multi-agent system using conventional quantitative indicators. We have also investigated the key characteristics of aspectual decompositions that led to (in)stabilities being observed in the target architectural options. The evaluation focused upon a number of architecturally-relevant changes that are typically performed through real-life maintenance tasks.
A new perspective on fuzzy process capability indices: Robustness
Authors: İhsan Kaya, Cengiz Kahraman
Venue: Expert Systems with Applications: An International Journal (2010)

Process performance can be analyzed by using process capability indices (PCIs), which are summary statistics to depict the process' location and dispersion successfully. Many PCIs have been proposed in the literature. Although they are very usable statistics to summarize process' performance, they can give misleading results and can cause incorrect interpretation if the process parameters have a correlation. In this case, the new PCIs called robust PCIs (RPCIs) should be applied. In this paper RPCIs are obtained for a piston manufacturing company and the fuzzy set theory is incorporated to increase PCIs' flexibility and sensitivity by defining specification limits and standard deviation as fuzzy numbers. Then fuzzy RPCIs are obtained to express the process performance more realistic for the piston manufacturing stage.