ppxscal/embedding_network huggingface dataset:
A case for bufferless routing in on-chip networks
Authors: Thomas Moscibroda, Onur Mutlu
Venue: ACM SIGARCH Computer Architecture News (2009)

Buffers in on-chip networks consume significant energy, occupy chip area, and increase design complexity. In this paper, we make a case for a new approach to designing on-chip interconnection networks that eliminates the need for buffers for routing or flow control. We describe new algorithms for routing without using buffers in router input/output ports. We analyze the advantages and disadvantages of bufferless routing and discuss how router latency can be reduced by taking advantage of the fact that input/output buffers do not exist. Our evaluations show that routing without buffers significantly reduces the energy consumption of the on-chip cache/processor-to-cache network, while providing similar performance to that of existing buffered routing algorithms at low network utilization (i.e., on most real applications). We conclude that bufferless routing can be an attractive and energy-efficient design option for on-chip cache/processor-to-cache networks where network utilization is low.
Transforming Programs into Recursive Functions
Authors: Magnus O. Myreen, Michael J. C. Gordon
Venue: Electronic Notes in Theoretical Computer Science (ENTCS) (2009)

This paper presents a new proof-assistant based approach to program verification: programs are translated, via fully-automatic deduction, into tail-recursive function defined in the logic of a theorem prover. This approach improves on well-established methods based on Hoare logic and verification condition generation (VCG) by removing the need to annotate programs with assertions, making the proof natural to the theorem prover and being easier to implement than a trusted VCG. Our tool has been implemented in the HOL4 theorem prover.
Grocery shopping recommendations based on basket-sensitive random walk
Authors: Ming Li, Benjamin M. Dias, Ian Jarman, Wael El-Deredy, Paulo J.G. Lisboa
Venue: Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining (2009)

We describe a recommender system in the domain of grocery shopping. While recommender systems have been widely studied, this is mostly in relation to leisure products (e.g. movies, books and music) with non-repeated purchases. In grocery shopping, however, consumers will make multiple purchases of the same or very similar products more frequently than buying entirely new items. The proposed recommendation scheme offers several advantages in addressing the grocery shopping problem, namely: 1) a product similarity measure that suits a domain where no rating information is available; 2) a basket sensitive random walk model to approximate product similarities by exploiting incomplete neighborhood information; 3) online adaptation of the recommendation based on the current basket and 4) a new performance measure focusing on products that customers have not purchased before or purchase infrequently. Empirical results benchmarking on three real-world data sets demonstrate a performance improvement of the proposed method over other existing collaborative filtering models.
Privacy preservation of aggregates in hidden databases: why and how?
Authors: Arjun Dasgupta, Nan Zhang, Gautam Das, Surajit Chaudhuri
Venue: Proceedings of the 35th SIGMOD international conference on Management of data (2009)

Many websites provide form-like interfaces which allow users to execute search queries on the underlying hidden databases. In this paper, we explain the importance of protecting sensitive aggregate information of hidden databases from being disclosed through individual tuples returned by the search queries. This stands in contrast to the traditional privacy problem where individual tuples must be protected while ensuring access to aggregating information. We propose techniques to thwart bots from sampling the hidden database to infer aggregate information. We present theoretical analysis and extensive experiments to illustrate the effectiveness of our approach.
Computing all skyline probabilities for uncertain data
Authors: Mikhail J. Atallah, Yinian Qi
Venue: Proceedings of the twenty-eighth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems (2009)

Skyline computation is widely used in multi-criteria decision making. As research in uncertain databases draws increasing attention, skyline queries with uncertain data have also been studied, e.g. probabilistic skylines. The previous work requires "thresholding" for its efficiency -- the efficiency relies on the assumption that points with skyline probabilities below a certain threshold can be ignored. But there are situations where "thresholding" is not desirable -- low probability events cannot be ignored when their consequences are significant. In such cases it is necessary to compute skyline probabilities of all data items. We provide the first algorithm for this problem whose worst-case time complexity is sub-quadratic. The techniques we use are interesting in their own right, as they rely on a space partitioning technique combined with using the existing dominance counting algorithm. The effectiveness of our algorithm is experimentally verified.
A domain decomposition strategy for alignment of multiple biological sequences on multiprocessor platforms
Authors: Fahad Saeed, Ashfaq Khokhar
Venue: Journal of Parallel and Distributed Computing (2009)

Multiple Sequences Alignment (MSA) of biological sequences is a fundamental problem in computational biology due to its critical significance in wide ranging applications including haplotype reconstruction, sequence homology, phylogenetic analysis, and prediction of evolutionary origins. The MSA problem is considered NP-hard and known heuristics for the problem do not scale well with increasing numbers of sequences. On the other hand, with the advent of a new breed of fast sequencing techniques it is now possible to generate thousands of sequences very quickly. For rapid sequence analysis, it is therefore desirable to develop fast MSA algorithms that scale well with an increase in the dataset size. In this paper, we present a novel domain decomposition based technique to solve the MSA problem on multiprocessing platforms. The domain decomposition based technique, in addition to yielding better quality, gives enormous advantages in terms of execution time and memory requirements. The proposed strategy allows one to decrease the time complexity of any known heuristic of O(N)^x complexity by a factor of O(1/p)^x, where N is the number of sequences, x depends on the underlying heuristic approach, and p is the number of processing nodes. In particular, we propose a highly scalable algorithm, Sample-Align-D, for aligning biological sequences using Muscle system as the underlying heuristic. The proposed algorithm has been implemented on a cluster of workstations using the MPI library. Experimental results for different problem sizes are analyzed in terms of quality of alignment, execution time and speed-up.
Minimum Distance between Pattern Transformation Manifolds: Algorithm and Applications
Authors: Effrosyni Kokiopoulou, Pascal Frossard
Venue: IEEE Transactions on Pattern Analysis and Machine Intelligence (2009)

Transformation invariance is an important property in pattern recognition, where different observations of the same object typically receive the same label. This paper focuses on a transformation-invariant distance measure that represents the minimum distance between the transformation manifolds spanned by patterns of interest. Since these manifolds are typically nonlinear, the computation of the manifold distance (MD) becomes a nonconvex optimization problem. We propose representing a pattern of interest as a linear combination of a few geometric functions extracted from a structured and redundant basis. Transforming the pattern results in the transformation of its constituent parts. We show that, when the transformation is restricted to a synthesis of translations, rotations, and isotropic scalings, such a pattern representation results in a closed-form expression of the manifold equation with respect to the transformation parameters. The MD computation can then be formulated as a minimization problem whose objective function is expressed as the difference of convex functions (DC). This interesting property permits optimally solving the optimization problem with DC programming solvers that are globally convergent. We present experimental evidence which shows that our method is able to find the globally optimal solution, outperforming existing methods that yield suboptimal solutions.
Adaptive multi-robot coordination based on resource spending velocity
Authors: Dan Erusalimchik, Gal A. Kaminka, Shai Shlomai, Dov Miron, Sarit Kraus
Venue: Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 2 (2009)

Multi-robot systems researchers have been investigating coordination methods for improving spatial coordination in teams [2]. Such methods attempt to resolve spatial conflicts between team-members, e.g., by dynamic setting of right-of-way priorities [3], or territorial separation [1]. It is accepted that no one method is always best [2], and that all methods reach a point where adding robots to the group (i.e., increasing the density of the robots in space) reduces overall productivity [1].
Recommendation system using location-based ontology on wireless internet: An example of collective intelligence by using 'mashup' applications
Authors: YoungHoon Yu, JiHyeok Kim, Kwangcheol Shin, Geun Sik Jo
Venue: Expert Systems with Applications: An International Journal (2009)

Location-Based Service (LBS) is considered as a key component of upcoming ubiquitous environments. A recommendation system based on LBS is expected to be an important service in ubiquitous environments, and most hardware technologies such as location estimation of a user by using Global Positioning System (GPS), as well as hi-speed internet access through cell phones, are currently supported. However, in terms of software, most services are driven and supported by a LBS service provider only. Consequently, lack of participation of users may occur in mobile environments. In this study, we suggest a LBS knowledge base inference platform with ontology which considers the current location and available time of users. Our knowledge base supports user participation as collective intelligence. We mashed up Open Application Programming Interface (OpenAPI) for scalable implementation of the system. Through experiments, we show that a user can build up his/her knowledge base, and by using this information, the system recommends to other users appropriate information that matches the user's condition and profile through inference.
The parity problem of polymatroids without double circuits
Authors: M&#x00e1;rton Makai, J&#x00e1;cint Szab&#x00f3;
Venue: Combinatorica (2008)

According to the present state of the theory of the matroid parity problem, the existence of a good characterization to the size of a maximum matching depends on the behavior of certain substructures, called double circuits. In this paper we prove that if a polymatroid has no double circuits then a partition type min-max formula characterizes the size of a maximum matching. Applications to parity constrained orientations and to a rigidity problem are given.
Optimization for signal setting problems using non-smooth techniques
Authors: Suh-Wen Chiou
Venue: Information Sciences: an International Journal (2009)

Consider a road network with severe traffic congestion. A set of efficient strategies can be addressed to simultaneously minimize road users' travel times and maximize possible increase in travel demands. Due to the non-differentiability of the perturbed solutions in equilibrium constraints, non-smooth optimization models for delay-minimizing and capacity-maximizing signal setting problems are established. In this paper, we propose a new bundle subgradient projection approach to solve the signal setting problems with global convergence. Various control policies are numerically tested one against another. Numerical results disclose that the proposed approach has successfully solved the delay-minimizing and capacity maximizing signal setting problems and achieved significant performance in cost reduction when compared to other alternatives.
Partially Observable Markov Decision Process Approximations for Adaptive Sensing
Authors: Edwin K. Chong, Christopher M. Kreucher, Alfred O. Hero,  Iii
Venue: Discrete Event Dynamic Systems (2009)

Adaptive sensing involves actively managing sensor resources to achieve a sensing task, such as object detection, classification, and tracking, and represents a promising direction for new applications of discrete event system methods. We describe an approach to adaptive sensing based on approximately solving a partially observable Markov decision process (POMDP) formulation of the problem. Such approximations are necessary because of the very large state space involved in practical adaptive sensing problems, precluding exact computation of optimal solutions. We review the theory of POMDPs and show how the theory applies to adaptive sensing problems. We then describe a variety of approximation methods, with examples to illustrate their application in adaptive sensing. The examples also demonstrate the gains that are possible from nonmyopic methods relative to myopic methods, and highlight some insights into the dependence of such gains on the sensing resources and environment.
What's in a rectangle? An issue for AIED in the design of semiotic learning tools
Authors: Erica de Vries
Venue: Proceeding of the 2005 conference on Artificial Intelligence in Education: Supporting Learning through Intelligent and Socially Informed Technology (2005)

This poster presents a tentative analysis of the conventions for a rectangle as a widespread graphical element in computer-based learning tools.
Continuous and impulsive harvesting strategies in a stage-structured predator-prey model with time delay
Authors: Pei Yongzhen, Li Changguo, Chen Lansun
Venue: Mathematics and Computers in Simulation (2009)

In this paper, the continuous and impulsive harvesting policies are considered in a predator-prey system with stage-structure. In the case in which a continuous harvesting is used, it is shown that the mature predator becomes extinct under appropriate conditions. In the case in which an impulsive harvesting is used, using the discrete dynamical system determined by the stroboscopic map, we obtain the mature predator-eradication periodic solution of the system which is globally attractive. The conditions of permanence are established by the method of comparison involving multiple Liapunov functions and auxiliary function. These results indicate that: a short period of pulse harvest is a sufficient condition for the eradication of the population; the impulsive harvest policy is more effective than the continuous one from eradicating predator point of view. Our results offer a more economical and safe strategy in controlling pest in contrast with biological control and chemical control. Furthermore, we give a summary of the dynamic behavior when the impulsive period takes values in different intervals. Finally, numerical results show that the impulsive system we considered has more complex dynamics including quasi-periodic oscillation and chaos.
The Artilect War: Cosmists vs. Terrans. A Bitter Controversy Concerning Whether Humanity Should Build Godlike Massively Intelligent Machines
Authors: Hugo de Garis
Venue: Proceeding of the 2008 conference on Artificial General Intelligence 2008: Proceedings of the First AGI Conference (2008)

This paper claims that the “species dominance” issue will dominate our global politics later this century. Humanity will be bitterly divided over the question whether to build godlike, massively intelligent machines, called “artilects” (artificial intellects) which with 21st century technologies will have mental capacities trillions of trillions of times above the human level. Humanity will split into 3 major camps, the “Cosmists” (in favor of building artilects), the “Terrans” (opposed to building artilects), and the “Cyborgs” (who want to become artilects themselves by adding components to their own human brains). A major “artilect war” between the Cosmists and the Terrans, late in the 21st century will kill not millions but billions of people.
Understanding and improving flow in digital photo ecosystems
Authors: Carman Neustaedter, Elena Fedorovskaya
Venue: Proceedings of Graphics Interface 2009 (2009)

Families use a range of devices and locations to capture, manage, and share digital photos as part of their digital photo ecosystem. The act of moving media between devices and locations is not always simple though and can easily become time consuming. We conducted interviews and design sessions in order to better understand the movement of media in digital photo ecosystems and investigate ways to improve it. Our results show that users must manage multiple entry points into their ecosystem, avoid segmentation in their collections, and explicitly select and move photos between desired devices and locations. Through design sessions, we present and evaluate design ideas to overcome these challenges that utilize multipurpose devices, always-accessible photo collections, and sharing from any device. These show how automation can be combined with recommendation and user interaction to improve flow within digital photo ecosystems.
High-scalability parallelization of a molecular modeling application: performance and productivity comparison between OpenMP and MPI implementations
Authors: Russell Brown, Ilya Sharapov
Venue: International Journal of Parallel Programming (2007)

Important components of molecular modeling applications are estimation and minimization of the internal energy of a molecule. For macromolecules such as proteins and amino acids, energy estimation is performed using empirical equations known as force fields. Over the past several decades, much effort has been directed towards improving the accuracy of these equations, and the resulting increased accuracy has come at the expense of greater computational complexity. For example, the interactions between a protein and surrounding water molecules have been modeled with improved accuracy using the generalized Born solvation model, which increases the computational complexity to O (n3). Fortunately, many force-field calculations are amenable to parallel execution. This paper describes the steps that were required to transform the Born calculation from a serial program into a parallel program suitable for parallel execution in both the OpenMP and MPI environments. Measurements of the parallel performance on a symmetric multiprocessor reveal that the Born calculation scales well for up to 144 processors. In some cases the OpenMP implementation scales better than the MPI implementation, but in other cases the MPI implementation scales better than the OpenMP implementation. However, in all cases the OpenMP implementation performs better than the MPI implementation, and requires less programming effort as well.
Hexahedral mesh development of free-formed geometry: The human femur exemplified
Authors: Alexandra Schonning, Binu Oommen, Irina Ionescu, Ted Conway
Venue: Computer-Aided Design (2009)

The objective of the present research is to develop a standard hexahedral Finite Element (FE) model of the human femur accounting for the material characteristics of cortical bone, cancellous bone and bone marrow. The anatomical data were acquired from the Visible Human Project. A detailed outline of the steps necessary in developing hexahedral FE meshes from computed tomography (CT) data is provided, along with a section on modelling strategies providing comprehensive suggestions on how to overcome meshing difficulties due to geometrical non-linearities. The stress and deformation results are discussed.
AOR-Simulation.org: cognitive agent simulation
Authors: Gerd Wagner, Mircea Diaconescu
Venue: Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 2 (2009)

In this paper, we describe an ontologically well-founded agent-based discrete event simulation framework with a high-level rule-based simulation language and an abstract simulator architecture and execution model, which allows both basic discrete event simulations without agents and complex agent-based simulations with (possibly distorted) perceptions and (possibly false) beliefs. The framework includes the simulation language AORSL, a Java simulator with a statistics and a 2D visualization tab, a player for the 3D rendering of simulation logs, and a Web simulation server. It is available on www.AOR-Simulation.org.
Online privacy and security of internet digital certificates: a study of the awareness, perceptions, and understanding of internet users
Authors: Rubye Braye
Venue:  (2008)

As electronic commerce develops, its success critically depends on providing security and privacy for its customers' personal data. Unlike Business to Consumer (B2C) commerce where the technological transactions are managed by the business, B2C e-commerce requires the consumers to engage the technologies. In doing so, the consumers face a variety of security risks. The prevailing solution is Public Key Infrastructure (PKI). When e-commerce PKI transactional processes fail, consumers are required to make decisions about digital certificate technologies, in the middle of their transactions. Consumers must often agree to trust digital certificates in order to complete an Internet purchase, when the majority of them do not know what a digital certificate is or who it represents. This study addressed consumers' familiarity with the Internet digital certificate authentication process. The research specifically addressed the following questions: Are consumers aware of the presence and purpose of Internet digital certificates in the online purchasing process? Does Internet experience impact consumers' privacy concerns about Web browser invalidated Internet digital certificates? The research was completed using a descriptive quantitative cross-sectional methodology, with an online survey instrument. The analyses were completed with Pearson's chi-square exact test and descriptive cross-tabulations. The analyses provided descriptive frequencies for the research variables&mdash;education, income, gender, age&mdash;and for each of the study&rsquo;s research constructs&mdash;Awareness, Understanding, Perception, Privacy Concern, and Internet experience. The findings suggested that Internet experience is significant in its relationship of awareness, understanding, and perception of the Internet digital certificate authentication process. This study contributes to the online consumer security behavior line of research introducing consumer behavior toward Internet digital certificate technology as an e-commerce security problem.
Analytical model-based technique for efficient evaluation of noise robustness considering parameter variations
Authors: Yehia Massoud, Sami Kirolos, Kartik Mohanram
Venue: Analog Integrated Circuits and Signal Processing (2009)

In this paper, we present an accurate method for analytical derivation of noise rejection curves (NRCs) and the associated noise susceptibility metric in the presence of variations in process and environmental parameters. The method involves modeling of the pull-up and pull-down resistances of combinational gates using approximated BSIM4 model-based device equations. Comparisons of the analytical model with circuit simulations show that the impact of parameter variations on the noise susceptibility is accurately captured by our model. The average (maximum) error associated with the noise susceptibility is found to be as low as 2.6% (6.7%). Our model can predict the noise susceptibility under parameter variations more than five orders of magnitude faster than circuit simulations, which makes it suitable for design optimization for noise robustness.