ppxscal/embedding_network huggingface dataset:
Ge integration on Si via rare earth oxide buffers: From MBE to CVD (Invited Paper)
Authors: T. Schroeder, A. Giussani, H. -J. Muessig, G. Weidner, I. Costina, Ch. Wenger, M. Lukosius, P. Storck, P. Zaumseil
Venue: Microelectronic Engineering (2009)

Single crystalline rare earth oxide heterostructures are flexible buffer systems to achieve the monolithic integration of Ge thin film structures on Si. The development of engineered oxide systems suitable for mass-production compatible CVD processes is hereby of special importance. In this paper, the interaction of Ge with PrO"2(111)/Si(111) heterostructures is studied in detail to achieve this goal. MBE based in situ growth studies unveil the chemical reduction of the PrO"2 buffer during the initial Ge deposition, the occurrence of a Volmer Weber growth mode of Ge on the resulting Pr"2O"3 heterostructure and the final formation of single crystalline, atomically smooth and c(2x8) reconstructed Ge(111) film structures. Comparative CVD Ge heteroepitaxy studies on MBE grown PrO"2(111)/Si(111) and Pr"2O"3(111)/Si(111) buffer systems indicate that the highly reactive lattice oxygen of PrO"2 plays an active role to avoid during initial exposure to the reducing ambient of the GeH"4 precursor chemistry the decomposition of the oxide buffer system.
Enhanced bisecting k-means clustering using intermediate cooperation
Authors: R. Kashef, M. S. Kamel
Venue: Pattern Recognition (2009)

Bisecting k-means (BKM) is very attractive in many applications as document-retrieval/indexing and gene expression analysis problems. However, in some scenarios when a fraction of the dataset is left behind with no other way to re-cluster it again at each level of the binary tree, a ''refinement'' is needed to re-cluster the resulting solutions. Current approaches to refine the clustering solutions produced by the BKM employ end-result enhancement using k-means (KM) clustering. In this hybrid model, KM waits for the former BKM to finish its clustering and then it takes the final set of centroids as initial seeds for a better refinement. In this paper, a cooperative bisecting k-means (CBKM) clustering algorithm is presented. The CBKM concurrently combines the results of the BKM and KM at each level of the binary hierarchical tree using cooperative and merging matrices. Undertaken experimental results show that the CBKM achieves better clustering quality than that of KM, BKM, and single linkage (SL) algorithms with comparable time performance over a number of artificial, text documents, and gene expression datasets.
A New Efficient Algorithm for Computing the Longest Common Subsequence
Authors: Costas S. Iliopoulos, M. Sohel Rahman
Venue: Theory of Computing Systems (2009)

The Longest Common Subsequence (LCS) problem is a classic and well-studied problem in computer science. The LCS problem is a common task in DNA sequence analysis with many applications to genetics and molecular biology. In this paper, we present a new and efficient algorithm for solving the LCS problem for two strings. Our algorithm runs in O(&#x211b;log&#x2009;log&#x2009;n+n) time, where &#x211b; is the total number of ordered pairs of positions at which the two strings match.
The LOM application profile for agricultural learning resources of the CGIAR
Authors: Thomas Zschocke, Jan Beniest, Courtney Paisley, Jehad Najjar, Erik Duval
Venue: International Journal of Metadata, Semantics and Ontologies (2009)

The international agricultural research centres of the CGIAR have established a repository for agricultural learning resources in collaboration with the ARIADNE Foundation. To make it easier to find these resources, an application profile, CG LOM Core, was developed on the basis of the IEEE Learning Object Metadata (LOM) standard. It defines the collection of metadata elements and value spaces drawn from other namespaces, adapted to the requirements of the CGIAR in describing and sharing their learning resources with an international audience. It maintains increased semantic interoperability within the CGIAR community and preserves compatibility with other repositories outside of the CGIAR.
Optimisation of cam-follower motion using B-splines
Authors: N. Sateesh, C. S. P. Rao, T. A. Janardhan Reddy
Venue: International Journal of Computer Integrated Manufacturing (2008)

This paper proposes design of cam-follower velocity curve by using B-spline polynomials. B-spline polynomials are smooth curves defined by control points. Curve shape can be modified by changing the control points. The traditional design method for improving the motion characteristics of the follower is to find an optimum displacement curve for which follower velocity, acceleration curves to be continuous and their peak values as small as possible (i.e. minimum jerk). B-spline polynomials of degree three and six control points are used in design of follower velocity curve. The B-spline curve is used to approximate the various basic curves which have better motion characteristics. A computer-aided design and computer-aided manufacturing (CAD/CAM) system is developed which generates follower motion curves, i.e. displacement, velocity, acceleration, jerk and cam profiles. An analysis is carried out on B-splines with basic curves for maximum accelerations to select the best cam follower motion. It also provides cam profile coordinates to manufacture a cam on computer numerical control (CNC) machines.
On the consistency of a Fuzzy C-Means algorithm for multisets
Authors: Vicenç Torra, Sadaaki Miyamoto
Venue: Proceeding of the 2005 conference on Artificial Intelligence Research and Development (2005)

The use of fuzzy multisets or fuzzy bags in AI applications is increasing. They are used as a tool for modeling data. In unsupervised learning, clustering methods have been succesful for a long time. In this paper we study fuzzy c-means and we compare their application to fuzzy sets and fuzzy multisets.
A Gateway to Modern Geometry: The Poincare Half-Plane, 2nd edition
Authors: Saul Stahl
Venue:  (2007)

Stahl's Second Edition continues to provide students with the elementary and constructive development of modern geometry that brings them closer to current geometric research. At the same time, repeated use is made of high school geometry, algebra, trigonometry, and calculus, thus reinforcing the students' understanding of these disciplines as well as enhancing their perception of mathematics as a unified endeavor. This distinct approach makes these advanced geometry principles accessible to undergraduates and graduates alike. 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
Microfluidic device for continuous magnetophoretic separation of white blood cells
Authors: Ciprian Iliescu, Guolin Xu, Elena Barbarini, Marioara Avram, Andrei Avram
Venue: Microsystem Technologies (2009)

This paper presents a microfluidic device for magnetophoretic separation of red blood cells from blood under continuous flow. The separation method consists of continuous flow of a blood sample (diluted in PBS) through a microfluidic channel which presents on the bottom &#x201c;dots&#x201d; of ferromagnetic layer. By applying a magnetic field perpendicular on the flowing direction, the ferromagnetic &#x201c;dots&#x201d; generate a gradient of magnetic field which amplifies the magnetic force. As a result, the red blood cells are captured on the bottom of the microfluidic channel while the rest of the blood is collected at the outlet. Experimental results show that an average of 95% of red blood cells is trapped in the device.
Reverse data exchange: coping with nulls
Authors: Ronald Fagin, Phokion G. Kolaitis, Lucian Popa, Wang-Chiew Tan
Venue: Proceedings of the twenty-eighth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems (2009)

An inverse of a schema mapping M is intended to "undo" what M does, thus providing a way to perform "reverse" data exchange. In recent years, three different formalizations of this concept have been introduced and studied, namely, the notions of an inverse of a schema mapping, a quasi-inverse of a schema mapping, and a maximum recovery of a schema mapping. The study of these notions has been carried out in the context in which source instances are restricted to consist entirely of constants, while target instances may contain both constants and labeled nulls. This restriction on source instances is crucial for obtaining some of the main technical results about these three notions, but, at the same time, limits their usefulness, since reverse data exchange naturally leads to source instances that may contain both constants and labeled nulls. We develop a new framework for reverse data exchange that supports source instances that may contain nulls, thus overcoming the semantic mismatch between source and target instances of the previous formalizations. The development of this new framework requires a careful reformulation of all the important notions, including the notions of the identity schema mapping, inverse, and maximum recovery. To this effect, we introduce the notions of extended identity schema mapping, extended inverse, and maximum extended recovery, by making systematic use of the homomorphism relation on instances. We give results concerning the existence of extended inverses and of maximum extended recoveries, and results concerning their applications to reverse data exchange and query answering. Moreover, we show that maximum extended recoveries can be used to capture in a quantitative way the amount of information loss embodied in a schema mapping specified by source-to-target tuple-generating dependencies.
Extricating the Web of Learning: The Case for Learning Communities
Authors: Elaine Khoo
Venue: Proceeding of the 2005 conference on Towards Sustainable and Scalable Educational Innovations Informed by the Learning Sciences: Sharing Good Practices of Research, Experimentation and Innovation (2005)

This paper presents the findings of a study to explore the nature of web-based learning (WBL) from students' views in a university in New Zealand. The study is part of a bigger project conducted to understand the pedagogical, design, and implementation issues of WBL that promote successful and high quality teaching-learning. 37 students attending online classes of 10 lecturers at the School of Education in the university responded to a survey and interview as part of a review of existing WBL teaching-learning practices. Findings highlight the idea of building a learning community as key to facilitating learning online. This has implications for the future design and implementation of web-based courses in the context studied.
Real: a reflective agent learning environment
Authors: John B. Black
Venue:  (2008)

A cognitive framework called REflective Agent Learning environment (REAL) is developed in this study. REAL provides an interactive learning environment that allows students to construct their imaginary world (Black, 1992), reflect upon the quality of their understanding, and test it out in the simulation games. The reflective agent in REAL is an autonomous character that can decide how to behave on its own in a simulation game, based upon an explicit representation of some knowledge about its world taught by students. It is a cognitive tool for engaging students in learning by teaching. It also provides a way to use computer programs to understand and simulate human mental activities. In the study, the evaluation of the REAL system design and development is our main focus. The external evaluation of specific implementations serves as the guidance for the future design of the REAL applications. The REAL cognitive framework stresses reflection as part of the thinking process. The use of the term &ldquo;reflective&rdquo; gives the agent two layers of meaning: it reflects the users' domain knowledge back to them (similar to looking into a glass box and seeing their own reasoning); the users reflect on that knowledge (similar to looking at a mirror, criticizing their own thinking processes). One of the major components in cognitive architecture is knowledge representation, which provides a formalization of declarative knowledge, procedural skills, and mental images (Black, 1992). These representations correspond to percepts, memories, goals, and beliefs, etc, over which cognitive processes operate. A reflective agent helps students externalize their internal knowledge representation in the symbolic level, and more importantly, it allows them to construct explanation explicitly about phenomena based on these representations. REAL is implemented in the domains of ecology and probability. It is an attempt to build a simulation-based learning environment that is otherwise unobtainable in classrooms. This research emphasizes the design of the platform and the testing of its usability. We hope, by grounding itself in the needs of local practice, the REAL applications can give us opportunities to understand how theoretical claims about teaching and learning can be effectively transformed into meaningful learning.
Theoretical and algorithmic developments in markov chain monte carlo
Authors: L. Mark Berliner
Venue:  (2008)

This PhD thesis is concerned with three problems: (1) &ldquo;Bayesian Change Point Analysis for Mechanistic Modeling,&rdquo; (3) &ldquo;Assessing Convergence and Mixing of Markov Chain Monte Carlo via Stratification,&rdquo; and (2) &ldquo;Bayesian Analysis via Diffusion Monte Carlo.&rdquo;In Bayesian parametric change point modeling, the primary challenges are detection of the number and locations of change points and obtaining the posterior distribution of other unknown parameters involved in the model. Chapter 2 suggests approaches for dealing with the computational burden arising in change point models that involving mechanistic reasoning as well as random explanatory variables. We present an example involving flow velocities of ice sheets in the Lambert Glacial Basin of east Antarctica. We pay special attention to the development of reasonable priors that can reflect a variety of prior information.In Chapter 3 we apply the notion of post-stratification to develop assessment tools for MCMC analysis. These tools are based on comparison of variances of two natural estimators. Based on the estimates of these variances we propose a test statistic which helps in checking convergence and mixing of MCMC. Our method is illustrated using a Bayesian change-point model for ice flow velocity in East Antarctica, a logistic regression model, a latent variable model for Arsenic concentration in public water systems in Arizona, and a regime-switching model for Pacific sea surface temperatures.Markov chain algorithms using langevin-type diffusion sometimes offer potentially useful methods in cases for which other MCMC methods are challenging. The key idea is to develop a stochastic process whose stationary distribution is the target posterior using diffusions represented as solutions to stochastic differential equations (SDE). The main challenge is to solve the required SDE&rsquo;s. Naive discretizations like the Euler method can lead to lack of ergodicity. Hence, more sophisticated discretizations or Metropolis-Hastings correction steps are prescribed. Chapter 4 of my dissertation research deals with development of diffusion based algorithms for posterior distributions arising from non-conjugate Gaussian models with non-linear mean and variance functions.
Position and force augmentation in a telepresence system and their effects on perceived realism
Authors: Carolina Weber, Verena Nitsch, Ulrich Unterhinninghofen, Berthold Farber, Martin Buss
Venue: Proceedings of the World Haptics 2009 - Third Joint EuroHaptics conference and Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems (2009)

Haptic assistance functions for a telepresence system are presented and assessed. These assistance functions are based on the augmentation of exchanged position and force data, and they are intended to increase the transparency of the telepresence system while maintaining stability. We present the concept and implementation of different assistance functions. Furthermore, we show the setup and results of a psychophysical experiment, which was designed to evaluate the effects of the assistance functions on perceived realism. As a result, the position assistance can increase stability and safety without negatively affecting transparency, and the force assistance can even increase the feeling of presence under certain conditions.
Exploring optimised route selection strategy in tree- and mesh-based multicast routing in MANETs
Authors: E. Baburaj, V. Vasudevan
Venue: International Journal of Computer Applications in Technology (2009)

Mobile ad hoc networks are collections of mobile nodes with dynamism forming a momentary network, with no pre-existing network infrastructure or centralised administration. Disaster relief, education and armed forces are widespread situations where mobile nodes need to communicate in areas without any pre-existing infrastructure. Multicast routing protocols outperform the basic broadcast routing by giving out the resources along general links while sending information to a set of multiple destinations. As the network topology is dynamic, optimised routing protocols are needed for communication proficiency. This paper explores the intelligent Genetic Algorithm (GA)-based on-demand multicast routing protocol and GA-based multicast ad hoc on-demand distance vector protocol which improve the control overheads and packet delivery ratio in the routing messages.
Plenary lecture 3: an information flow based model of representation for developing informatics as an academic discipline
Authors: Ioan-Gheorghe Ratiu
Venue: Proceedings of the 8th Wseas international conference on Telecommunications and informatics (2009)

We present a new approach for solving the optimal power flow problem. In this approach we propose to use fuzzy logic techniques to dynamically control parameter settings of genetic algorithms (GA's). This framework allows one to qualitatively express GA control strategies based on experience or intuition. To make Dynamic Parametric GA's accessible to everybody; we have also presented an automatic fuzzy design technique, which is based on GA's. This technique was in turn used to design an optimal fuzzy system for GA control. The result was a Dynamic Parametric GA controlled by a fuzzy system that exhibited better performance than a simple static GA. This Dynamic Parametric GA was then evaluated on different cases for the economic dispatch and without additional optimization it out-performed a simple static GA. This indicates that the rules found by the automatic design technique may be universally applicable to control GA's in other optimization tasks. In addition, because the representation of control knowledge is based on a fuzzy rule base, knowledge about GA control can be easily extracted after optimization. We would also like to point out that using the meta-level GA to find the optimized fuzzy system for the dynamic parameterized GA did consume many hours of computation time. However, because the performance of the final system transferred to another task or system without additional tuning may suggest that if good knowledge-base were found, then optimizing the fuzzy knowledge-based system for the dynamic parameterized GA need not be performed very often. The performance of our method demonstrated through its evaluation on the number - bus power system. The test results have shown the proposed genetic algorithm can provide better solutions than the simple static genetic algorithm.
(L, M)-fuzzy matroids
Authors: Fu-Gui Shi
Venue: Fuzzy Sets and Systems (2009)

In this paper, an extension of matroids is introduced in lattice-valued fuzzy set theory. Such a generalized matroid is a pair made of a finite set and a fuzzy subfamily of its lattice-valued fuzzy subsets satisfying three axioms. It uses two lattices: one for membership grades of elements to fuzzy sets, and another for membership degrees of fuzzy sets in a fuzzy family of fuzzy sets. It is a logical generalization of the notions of matroids and fuzzifying matroids. In our definition of generalized fuzzy matroids, each L-fuzzy subset can be regarded to be independent of other ones to some degree. The relevance of generalized fuzzy matroids is shown in the setting of fuzzy vector spaces and fuzzy graphs.
Information Modelling for Preference Analysis of Musical Instrument Sounds
Authors: Yukari Shirota
Venue: Proceeding of the 2009 conference on Information Modelling and Knowledge Bases XX (2009)

In the paper, I propose a new information modeling for preference analysis of musical instrument sounds. I think that the Gunji's classification method is suitable as the base of the model. Concerning the preference analysis, I am planning to use the conjoint analysis methods and I discuss the problems to overcome while conducting the conjoint analysis on the model.
Resilient workload manager: taming bursty workload of scaling internet applications
Authors: Hui Zhang, Guofei Jiang, Kenji Yoshihira, Haifeng Chen, Akhilesh Saxena
Venue: Proceedings of the 6th international conference industry session on Autonomic computing and communications industry session (2009)

In data centers hosting scaling Internet applications, operators face the tradeoff dilemma between resource efficiency and Quality of Service (QoS), and the root cause lies in workload dynamics. In this paper, we address the problem with the design of Resilient Workload Manager (ROM). ROM explicitly segregates base workload and trespassing workload, the two naturally different components in application workload, and manages them separately in two resource zones with specialized optimization techniques. As a comprehensive workload management framework, ROM covers workload, data, resource, and Quality of Service of the target applications. It features a fast workload factoring algorithm for distributing incoming application requests, not only on volume but also on content, between the two resource zones; integrated two-dimensional workload shaping, resource planning, and request dispatching schemes for efficient utilization of base workload zone resource; and a simple and high-performance system architecture for dynamic provisioning in trespassing workload zone. Through extensive evaluation, we showed ROM can achieve resource efficiency (e.g., 54.9% server saving) guarantee QoS (based on client-side perceived service quality), reduce data access overhead in the trespassing workload zone during peak load (up to two orders of magnitude), and be adaptive at processing speed (running faster at peak load periods than at regular periods).
Structural reliability improvement using non-linear and adaptive multi-model techniques
Authors: Vassilios C. Moussas
Venue: Proceedings of the 10th WSEAS international conference on Mathematical methods, computational techniques and intelligent systems (2008)

Structural reliability of a complex structure is related to the residual lifetime of its components. Structural components often contain flaws that propagate due to fatigue and when the crack size becomes critical they eventually fail. In this paper, a number of nonlinear and adaptive identification algorithms are applied to the problem of Fatigue Crack Growth (FCG) monitoring and identification, in order to improve the prediction of the residual time to failure. Several algorithms ranging from simple Non-Linear Least Squares (NLLS) to Extended Kalman Filter (EKF) and adaptive Multi-Model Partitioning algorithms (MMPA) are tested in order to compare their efficiency. As it is shown, using real experimental data, the more advanced identification algorithms have superior performance in estimating future crack size and predicting the residual lifetime of a component.