ppxscal/embedding_network huggingface dataset:
Sensitivity of drainage to rainfall, vegetation and soil characteristics
Authors: Abdul R. Bah, Olena Kravchuk, Gunnar Kirchhof
Venue: Computers and Electronics in Agriculture (2009)

Rainfall, vegetation characteristics and soil hydraulic properties influence deep drainage patterns in agricultural landscapes, but more information is required on the variability of their interactions with site conditions. Therefore, the objective of the study was to investigate the impact of the interactions of soil permeability, vegetation rooting depth and growth duration on drainage in 3 sites in northern New South Wales, Australia. Local sensitivity analysis was used on drainage estimated by two biophysical models-WaterMod 3, with a crop growth module, and HYDRUS-1D without a crop growth module. The effect of saturated hydraulic conductivity (K"s), growth duration (GD), rooting depth (RD), annual rainfall, and their interactions on deep drainage was evaluated at 3 sites. Simulations were conducted using 30 years of randomly selected climate data from 115 years historical data. Rainfall variability was similar in all 3 sites, so annual rainfall was the dominant factor dictating drainage in all 30 rainfall-years whereas GD was more important than RD after accounting for rainfall and drainage was least sensitive to K"s. The minor impact of RD was ascribed to the soil water content being at the lower extraction limit of crops due to potential evaporation being greater than rainfall in almost all months of the rainfall-year. The importance of GD varied between rainfall-years and sites, and was generally higher at high annual rainfall. We conclude that the level of precision at which model inputs are defined would vary with annual rainfall level. Therefore, GD could be defined on a rough scale in low rainfall zones, whereas more precise definitions are necessary at high rainfall. This would depend on classification of rainfall zones based on reliable rainfall data.
Flexfields for Oracle E-Business Suite
Authors: Roel A. Hogendoorn
Venue:  (2007)

This book explains in the purpose and concepts of Flexfields in the Oracle e-Business Suite. It is explained via step-by-step examples, with lots of screenshots. Most parts of Flexfields are not difficult, as long as you have good examples. And this book is packed with clear examples that you can easily copy for your purpose. The content is valid both for Oracle eBS R11i and R12.
Ura: a universal data replication architecture
Authors: Mike Dahlin
Venue:  (2008)

Data replication is a key building block for large-scale distributed systems to improve availability, performance, and scalability. Because there is a fundamental trade-off between performance and consistency as well as between availability and consistency, systems must make trade-offs among these factors based on the demands and technologies of their target environments and workloads. Unfortunately, existing replication protocols and mechanisms are intrinsically entangled with specific policy assumptions. Therefore, to accommodate new trade-offs for new policy requirements, developers have to either build a new replication system from scratch or modify existing mechanisms. This dissertation presents a universal data replication architecture (URA) that cleanly separates mechanism and policy and supports Partial Replication (PR), Any Consistency (AC), and Topology Independence (TI) simultaneously. Our architecture yields two significant advantages. First, by providing a single set of mechanisms that capture the common underlying abstractions for data replication, URA can serve as a common substrate for building and deploying new replication systems. It therefore can significantly reduce the effort required to construct or modify a replication system. Second, by providing a set of general and flexible mechanisms independent of any specific policy, URA enables better trade-offs than any current system can provide. In particular, URA can simultaneously provide the three PRACTI properties while any existing system can provide at most two of them. Our experimental results and case-study systems confirm that universal data replication architecture is a way to build better replication systems and a better way to build replication systems.
Noise-induced sampling of alternative Hamiltonian paths in quantum adiabatic search
Authors: Frank Gaitan
Venue: Complexity (2009)

We numerically simulate the effects of noise-induced sampling of alternative Hamiltonian paths on the ability of quantum adiabatic search (QuAdS) to solve randomly generated instances of the NP-complete problem N-bit Exact Cover 3. The noise-averaged median runtime is determined as the noise-power and number of bits N are varied, and power-law and exponential fits are made to the data. Noise is seen to slowdown QuAdS, though a downward shift in the scaling exponent is found for N > 12 over a range of noise-power values. We discuss whether this shift might be connected to arguments in the literature that suggest that altering the Hamiltonian path might benefit QuAdS performance. &copy; 2008 Wiley Periodicals, Inc. Complexity, 2009 This article was submitted as an invited paper to the &ldquo;Understanding Complex Systems&rdquo; conference held at the University of Illinois at Urbana-Champaign,May 2007
Practical modeling technique for large-scale 3D building models from ground images
Authors: Kyung Ho Jang, Soon Ki Jung
Venue: Pattern Recognition Letters (2009)

In this paper, we propose a practical modeling method for large-scale building modeling with multiple image sequences. First, a scene is acquired via a pose camera, which annotates each image with navigation information using GPS and a digital compass. An adjacency graph was built to determine the approximate spatial adjacency given roughly known poses of each image sequences, to organize the nodes into a set of sequences and to access the nodes. The camera positions are obtained by using a standard Structure from Motion algorithm. After the pose estimation, the user-assistant modeling approach is used based on a half-edge data structure. For accuracy and validity in the approach, some experimental results are shown.
Flexibility in modeling languages and tools: a call to arms
Authors: Eric Van Wyk, Mats Per Erik Heimdahl
Venue: International Journal on Software Tools for Technology Transfer (STTT) (2009)

In model-based development, the software development effort is centered around a formal description of the proposed software system; a description that can be subjected to various types of analysis and code generation. Based on years of experience with model-based development and formal modeling we believe that the following conjectures describe fundamental obstacles to wide adoption of formal modeling and the potential for automation that comes with it; (1) no single modeling notation will suit all, or even most, modeling needs, (2) no analysis tool will fit all, or even most, analysis tasks, and (3) flexible and stable tools must be made available for realistic evaluations and technology transfer. These conjectures form the basis for the call to arms outlined in this report. To make automated software engineering techniques more useful for more types of developers and allow us to move forward as a community it is crucial that we develop the foundation for building extensible and flexible modeling language processing tools. New common- infrastructure-based approaches are needed as traditional approaches based on file-based processing of intermediate language representations are not adequate. In this report we outline and illustrate the problem and discuss a possible solution. To initiate the discussions in the community, we hypothesize that languages and tools built using higher-order attribute grammars with forwarding can serve as a basis for such flexible language processing tools; tools that will allow us to unify our efforts and help bring our collective work to a broader audience.
Statistical models for text query-based image retrieval
Authors: R. Manmatha
Venue:  (2008)

Image indexing and retrieval has been an active research area for more than one decade. Although many accomplishments have been made in this domain, it is still a challenging problem and far from being solved. Traditional content-based approaches make use of queries based on image examples or image attributes like color and texture, and images are retrieved according to the similarity of each target image with the query image. However, image query based retrieval systems do not really capture the semantics or meanings of images well. Furthermore, image queries are difficult and inconvenient to form for most users. To capture the semantics of images, libraries and other organizations have manually annotated each image with keywords and captions, and then search on those annotations using text retrieval engines. The disadvantage of this approach is the huge cost of annotating large number of images and the inconsistency of annotations by different people. In this work, we focus on general image and historical handwritten document retrieval based on textual queries. We explore statistical model based techniques that allow us to retrieve general images and historical handwritten document images with text queries. These techniques are (i) image retrieval based on automatic annotation, (ii) direct retrieval based on computing the posterior of an image given a text query, and (iii) handwritten document image recognition. We compare the performance of these approaches on several general image and historical handwritten document collections. The main contributions of this work include (i) two probabilistic generative models for annotation-based retrieval, (ii) a direct retrieval model for general images, and (iii) a thorough investigation of machine learning models for handwritten document recognition. Our experimental results and retrieval systems show that our proposed approaches may be applied to practical textual query based retrieval systems on large image data sets.
Effects of Interface Interactions on Mechanical Properties in RDX-Based PBXs HTPB-DOA: Molecular Dynamics Simulations
Authors: Mounir Jaidann, Louis-Simon Lussier, Amal Bouamoul, Hakima Abou-Rachid, Josée Brisson
Venue: Proceedings of the 9th International Conference on Computational Science (2009)

Atomistic molecular dynamics simulation was carried out to study interface interactions between a crystal structure and a plastic bonded explosive (PBX) system. In this work, the polymer is hydroxyl-terminated polybutadiene (HTPB), the plasticizer is dioctyl adipate (DOA) and the crystal phase is hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX). Experimental RDX crystallo-graphic data show that (020), (200) and (210) crystal faces usually dominate, and these were therefore only these were studied. Interface models were built and interfacial bonding energies calculated to investigate HTPB/RDX adhesion properties in the (DOA+HTPB)/RDX system. Mechanical properties such as Poisson's ratio, Young, bulk and shear moduli were also predicted. The most favourable interactions occur between HTPB-DOA and the RDX (020) crystal face: obtaining crystals with prominent (020) faces may provide a more flexible mixture, with a lower Young's modulus and an increased ductility.
An evolutionary model of multi-agent learning with a varying exploration rate
Authors: M. Kaisers, K. Tuyls, S. Parsons, F. Thuijsman
Venue: Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 2 (2009)

Multi-agent learning is a challenging problem and has recently attracted increased attention by the research community [4, 5]. It promises control over complex multi-agent systems such that agents enact a global desired behavior while operating on local knowledge.
A cooperative and self-adaptive metaheuristic for the facility location problem
Authors: David Meignan, Jean-Charles Créput, Abderrafiaa Koukam
Venue: Proceedings of the 11th Annual conference on Genetic and evolutionary computation (2009)

This paper presents a coalition-based metaheuristic (CBM) to solve the uncapacitated facility location problem. CBM is a population-based metaheuristic where individuals encapsulate a single solution and are considered as agents. In comparison to classical evolutionary algorithms, these agents have additional capacities of decision, learning and cooperation. Our approach is also a case study to present how concepts from multiagent systems' domain may contribute to the design of new metaheuristics. The tackled problem is a well-known combinatorial optimization problem, namely the uncapacitated facility location problem, that consists in determining the sites in which some facilities must be set up to satisfy the requirements of a client set at minimum cost. A computational experiment is conducted to test the performance of learning mechanisms and to compare our approach with several existing metaheuristics. The results showed that CBM is competitive with powerful heuristics approaches and presents several advantages in terms of flexibility and modularity.
Image processing for sediment classification
Authors: Cristian Molder, Florin Serban, Iulian C. Vizitiu, Mihai I. Stanciu
Venue: Proceedings of the 7th WSEAS international conference on Computational intelligence, man-machine systems and cybernetics (2008)

Sediment analysis using data obtained from a profiler helps geologists to interpret and classify different structural layer of the sea and ocean floor. Different sonar can be used (the monobeam, the multibeam, or the side-scan) and several sonar specific image profiles are recorder. The process of interpretation is made exclusively by a human expert analysis of a paper print or a display image, therefore leading to misinterpretations and a long time required to process a great amount of recorder data. There is a immediate need to create an automatic or semiautomatic system in order to speed up the interpretation process, allowing more time to data refinement that to brute interpretation. In this article we propose the use of two image processing techniques which characterize the recorder data using sediment layer contour extraction and inter-layer texture analysis. The results based on real data are compared with the ones obtained from a geologist and confirms the proposed approach.
Technologies within transnational social activist communities: an ethnographic study of the european social forum
Authors: Saqib Saeed, Markus Rohde, Volker Wulf
Venue: Proceedings of the fourth international conference on Communities and technologies (2009)

ICT support for transnational social movements and civil society organizations is an important field of research: not only due to the increased political importance of this sector in a globalizing world but also due to their organizational characteristics. Transnational social movement organizations are typically characterized by a lack of resources, an absence of formal hierarchical structures, and differences in languages and culture among the activists. In order to design appropriate technological support for social activists' communities, it is important to understand their work practices which widely differ from traditional business organizations. This paper investigates into the organizational practices of the European Social Forum, in particular its 2008 meeting in Malmo, Sweden. We describe organizational practices in preparing and conducting the event. Since the goal of our research is directed towards enhancing the capabilities of social movements by means of ICT, we focus particularly on the usage of ICT.
Novel modeling and optimization techniques for nano-scale vlsi designs
Authors: Yu Hen Hu
Venue:  (2008)

Today's integrated circuit design involves dealing with complex VLSI systems and increasingly large number of design constraints. Modern technology demands techniques for efficiently designing high-performance low-power integrated circuits, while requirements for shorter time-to-market restrict the design time. Hence, the design of circuits with millions of components relies on efficient design automation techniques and algorithms. This dissertation introduces several algorithms and modeling techniques for applying mathematical optimization to nano-scale VLSI designs. A novel design flow is proposed using a new mathematical model Numerically Convex Form, which advocates a fundamentally new paradigm for optimizing discrete data using geometric programming techniques. Convex fit, an algorithm for modeling discrete data in this form using the semidefinite programming framework is developed. Compared to the current closed-form modeling, significant reduction in modeling error is demonstrated using this new model. The dissertation proposes two smoothing algorithms; ConvexSmooth: a simultaneous convex fitting and smoothing algorithm and SmartSmooth: a linear time convexity preserving smoothing algorithm. The new model along with the smoothing algorithms are applied to the gate sizing optimization problem for combinational circuits. To demonstrate the applicability of numerically convex forms, a novel algorithm is developed for sizing synchronous sequential circuits, which form the core of modern IC designs. This algorithm combines gate sizing and clock skew optimization algorithm to add an additional degree of freedom to the optimization and can also handle feedback loops. Finally, a robust multi-corner gate sizing algorithm is proposed to concurrently account for the design constraints in multiple process corners and/or modes, while still achieving timing optimization in polynomial time for fast design-for-manufacturing closure.
The Effectiveness of Haptic Cues as an Assistive Technology for Human Memory
Authors: Stacey Kuznetsov, Anind K. Dey, Scott E. Hudson
Venue: Proceedings of the 7th International Conference on Pervasive Computing (2009)

Many people experience difficulty recalling and recognizing information during everyday tasks. Prior assistive technology has leveraged audio and video cues, but this approach is often disruptive and inappropriate in socially-sensitive situations. Our work explores vibro-tactile feedback as an alternative that unobtrusively aids human memory. We conducted several user studies comparing within-participant performance on memory tasks without haptic cues (control) and tasks augmented with tactile stimuli (intervention). Our studies employed a bracelet prototype that emits vibratory pulses, which are uniquely mapped to audio and visual information. Results show interaction between performance on control and intervention conditions. Poor performers on unaided tasks improve recognition by more than 20% (p<0.05) when haptic cues are employed. Thus, we suggest vibro-tactile feedback as an effective memory aid for users with impaired memory, and offer several design recommendations for integrating haptic cues into wearable devices.
A novel method for MicroRNA secondary structure prediction using a bottom-up algorithm
Authors: Dianwei Han, Guiliang Tang, Jun Zhang
Venue: Proceedings of the 47th Annual Southeast Regional Conference (2009)

MicroRNAs (miRNAs) are newly discovered endogenous small non-coding RNAs (21-25nt) that are thought to regulate expression of target genes by direct interaction with mRNAs. MicroRNAs have been identified through both experimental and computational methods, and microRNA secondary structure prediction is important and essential. Generally, there are two classes of methods to predict the secondary structure of RNAs. Thermodynamics-based methods have been the dominant strategy for single-stranded RNA secondary structure prediction for many years. Recently, probabilistic-based methods have emerged to replace the free energy minimization methods for modeling RNA structures. However, the accuracies of the currently best available probabilistic-based models have yet to match those of the best thermodynamics-based methods. So this situation motivates us to develop a new prediction algorithm which will focus on microRNA structure prediction with high accuracy. A new model, nucleotide cyclic motifs (NCM), was recently proposed by Major et al. to predict RNA secondary structure. We propose and implement a novel model based on a Modified NCM (MNCM) model with a physics-based scoring strategy to tackle the problem of microRNA folding. By making use of a global optimal algorithm based on the bottom-up local optimal solutions, we implement MicroRNAfold. Our experimental results show that MicroRNAfold outperforms the current leading prediction tools.
On Automatically Detecting Malicious Impostor Emails
Authors: Erhan J. Kartaltepe, Shouhuai Xu
Venue: Proceeding of the 2005 conference on Applied Public Key Infrastructure: 4th International Workshop: IWAP 2005 (2005)

In this paper we explore the problem we call “malicious impostor emails.” Compared with the fairly well-known abuses such as spam and email worms, malicious impostor emails could be much more catastrophic because their payloads may directly target at the victim users' cryptographic keys (via whatever means) and their content---except the malicious payload as an attachment---could look perfectly like a legitimate one. As a first step in dealing with malicious impostor emails, we present a partial solution that mitigates their damage without forcing the involvement of the users.
Efficient Euclidean projections in linear time
Authors: Jun Liu, Jieping Ye
Venue: Proceedings of the 26th Annual International Conference on Machine Learning (2009)

We consider the problem of computing the Euclidean projection of a vector of length n onto a closed convex set including the l1 ball and the specialized polyhedra employed in (Shalev-Shwartz & Singer, 2006). These problems have played building block roles in solving several l1-norm based sparse learning problems. Existing methods have a worst-case time complexity of O(n log n). In this paper, we propose to cast both Euclidean projections as root finding problems associated with specific auxiliary functions, which can be solved in linear time via bisection. We further make use of the special structure of the auxiliary functions, and propose an improved bisection algorithm. Empirical studies demonstrate that the proposed algorithms are much more efficient than the competing ones for computing the projections.
Improving Bound Propagation
Authors: Bozhena Bidyuk, Rina Dechter
Venue: Proceeding of the 2006 conference on ECAI 2006: 17th European Conference on Artificial Intelligence August 29 -- September 1, 2006, Riva del Garda, Italy (2006)

This paper extends previously proposed bound propagation algorithm [11] for computing lower and upper bounds on posterior marginals in Bayesian networks. We improve the bound propagation scheme by taking advantage of the directionality in Bayesian networks and applying the notion of relevant subnetwork. We also propose an approximation scheme for the linear optimization subproblems. We demonstrate empirically that while the resulting bounds loose some precision, we achieve 10-100 times speedup compared to original bound propagation using a simplex solver.