ppxscal/embedding_network huggingface dataset:
Replicated declustering of spatial data
Authors: Hakan Ferhatosmanoǧlu, Ali Şaman Tosun, Aravind Ramachandran
Venue: Proceedings of the twenty-third ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems (2004)

The problem of disk declustering is to distribute data among multiple disks to reduce query response times through parallel I/O. A strictly optimal declustering technique is one that achieves optimal parallel I/O for all possible queries. In this paper, we focus on techniques that are optimized for spatial range queries. Current declustering techniques, which have single copies of the data, have been shown to be suboptimal for range queries. The lower bound on extra disk accesses is proved to be &Omega;(log N) for N disks even in the restricted case of an N-by-N grid, and all current approaches have been trying to achieve this bound. Replication is a well-known and effective solution for several problems in databases, especially for availability and load balancing. In this paper, we explore the idea of replication in the context of declustering and propose a framework where strictly optimal parallel I/O is achievable using a small amount of replication. We provide some theoretical foundations for replicated declustering, e.g., a bound for number of copies for strict optimality on any number of disks, and propose a class of replicated declustering schemes, periodic allocations, which are shown to be strictly optimal. The results for optimal disk allocation are extended for larger number of disks by increasing replication. Our techniques and results are valid for any arbitrary a-by-b grids, and any declustering scheme can be further improved using our replication framework. Using the framework, we perform experiments to identify a strictly optimal disk access schedule for any given arbitrary range query. In addition to the theoretical bounds, we compare the proposed replication based scheme to other existing techniques by performing experiments on real datasets.
An Iterative Global Optimization Algorithm for Potential Energy Minimization
Authors: N. P. Moloi, M. M. Ali
Venue: Computational Optimization and Applications (2005)

In this paper we propose an algorithm for the minimization of potential energy functions. The new algorithm is based on the differential evolution algorithm of Storn and Price (Journal of Global Optimization, vol. 11, pp. 341--359, 1997). The algorithm is tested on two different potential energy functions. The first function is the Lennard Jones energy function and the second function is the many-body potential energy function of Tersoff (Physics Review B, vol. 37, pp. 6991--7000, 1988; vol. 38, pp. 9902--9905, 1988). The first problem is a pair potential and the second problem is a semi-empirical many-body potential energy function considered for silicon-silicon atomic interactions. The minimum binding energies of up to 30 atoms are reported.
Language model adaptation with additional text generated by machine translation
Authors: Hideharu Nakajima, Hirofumi Yamamoto, Taro Watanabe
Venue: Proceedings of the 19th international conference on Computational linguistics - Volume 1 (2002)

Statistical language modeling requires a large corpus for the application domain. When a large corpus is not available, the language model adaptation technique has often been used in the speech recognition research domain. This adaptation needs only a small corpus of the application domain (the "target corpus") and the corpus should be written in the language of the model. However, it is sometimes difficult to collect even a small corpus, especially of spoken language, due to its high cost. To address this problem, this paper proposes a novel scheme that generates a small target corpus in the language of the model by machine translation of the target corpus in another language. As information about adjacent words, which is necessary for a statistical language model, is stored in the translation knowledge, it can be extracted by machine translation and used for adaptation. Experiments showed that the language model improvement was about half of that which was obtained with a human collected corpus, and this provided some initial proof of the concept experiments.
From the Newsstand
Authors: Alison Skratt
Venue: IEEE Internet Computing (2005)

Review of Internet-related stories in IEEE, Computer Society, and trade press.
Spectral Segmentation with Multiscale Graph Decomposition
Authors: Timothee Cour, Florence Benezit, Jianbo Shi
Venue: Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02 (2005)

We present a multiscale spectral image segmentation algorithm. In contrast to most multiscale image processing, this algorithm works on multiple scales of the image in parallel, without iteration, to capture both coarse and fine level details. The algorithm is computationally efficient, allowing to segment large images. We use the Normalized Cut graph partitioning framework of image segmentation. We construct a graph encoding pairwise pixel affinity, and partition the graph for image segmentation.We demonstrate that large image graphs can be compressed into multiple scales capturing image structure at increasingly large neighborhood. We show that the decomposition of the image segmentation graph into different scales can be determined by ecological statistics on the image grouping cues. Our segmentation algorithm works simultaneously across the graph scales, with an inter-scale constraint to ensure communication and consistency between the segmentations at each scale. As the results show, we incorporate long-range connections with linear-time complexity, providing high-quality segmentations efficiently. Images that previously could not be processed because of their size have been accurately segmented thanks to this method.
Innate and Acquired Immunity in Real Time Systems
Authors: Dan W. Taylor, David W. Corne
Venue: Proceedings of the Fourth International Conference on Hybrid Intelligent Systems (2004)

In most potential industrial applications of artificial immune systems for early fault detection, some form of simple fault detection system already exists. We propose that this existing layer of simple, generally rule-based fault detection is analogous to innate immunity in the natural immune system. We argue that the artificial acquired immune system should focus on the detection of fault conditions not already covered by the innate immune system, most importantly on the very early symptoms of faults which, we believe, are often very similar to self. This has implications for detector generation algorithms. We test two novel detector generation algorithms that address this issue, using temperature data from refrigerated cabinets in UK supermarkets. Results show that location of detectors in problem space is important and that detector sets concentrated close to self in problem space are better at detecting early stages of fault.
Teaching concepts of virtual memory with the Moses2 microcomputer operating system environment simulator
Authors: Robert E. England
Venue: Journal of Computing Sciences in Colleges (2005)

A clear understanding of the concepts of virtual memory is important to any student of computer science or professional computer scientist, especially those who work in system administration or program at the systems level. Virtual memory is now the standard paradigm for solving the classic trade-off between expensive but fast main memory and the cheaper yet much slower hard disk drive space.This paper discusses the design and implementation of the virtual memory simulation facility of Moses2, a virtual computing environment for use in undergraduate operating systems courses. Moses2 is an original software system produced and refined by the author over fourteen years in conjunction with teaching senior level operating systems courses. In the Moses2 environment, students run and test original kernel emulator programs as they develop these programs incrementally over a semester. Presented here is how the Moses2 system teaches fundamental concepts of a paged segmentation virtual memory manager.
Branch elimination by condition merging
Authors: William C. Kreahling, David Whalley, Mark W. Bailey, Xin Yuan, Gang-Ryung Uh, Robert van Engelen
Venue: Software&mdash;Practice Experience (2005)

Conditional branches are expensive. Branches require a significant percentage of execution cycles since they occur frequently and cause pipeline flushes when mispredicted. In addition, branches result in forks in the control flow, which can prevent other code-improving transformations from being applied. In this paper we describe profile-based techniques for replacing the execution of a set of two or more branches with a single branch on a conventional scalar processor. These sets of branches can include tests of multiple variables. For instance, the test if (p1 ! = 0 && p2 ! = 0), which is testing for NULL pointers, can be replaced with if (p1 & p2 ! = 0). Program profiling is performed to target condition merging along frequently executed paths. The results show that eliminating branches by merging conditions can significantly reduce the number of conditional branches executed in non-numerical applications.
Review of "Techniques for 21st Century Fiction by A. S. Glassner", A. K. Peters, Ltd., Natick, MA 511 pages. ISBN 1-56881-221-3. $35.00.
Authors: Edgar A. Maldonado, Joseph A. Zupko
Venue: Computers in Entertainment (CIE) (2005)

For centuries, people have enjoyed both stories and games. As a result, a form of entertainment that combines storytelling with game-playing seems a great idea. It has the potential to be a lot of fun. Unfortunately, the road to this entertainment form is long and complicated and many difficulties must be overcome. Andrew Glassner, in his new book Interactive Storytelling: Techniques for 21st Century Fiction, does an excellent job identifying these difficulties. He analyzes games and storytelling, and describes the principal problems that developers face in merging these two activities into an interactive form of entertainment.
On Recent Advances in Time/Utility Function Real-Time Scheduling and Resource Management
Authors: Binoy Ravindran, E. Douglas Jensen, Peng Li
Venue: Proceedings of the Eighth IEEE International Symposium on Object-Oriented Real-Time Distributed Computing (2005)

We argue that the key underpinning of the current state-of-the real-time practice - the priority artifact - and that of the current state-of-the real-time art - deadline-based timelinessoptimality - are entirely inadequate for specifying timeliness objectives, for reasoning about timeliness behavior, and for performing resource management that can dependably satisfy timeliness objectives in many dynamic real-time systems. We argue that time/utility functions and the utility accrual scheduling paradigm provide a more generalized, adaptive, and flexible approach. Recent research in the utility accrual paradigm have significantly advanced the state-of-the-art of that paradigm. We survey these advances.
The molecule role ontology: an ontology for annotation of signal transduction pathway molecules in the scientific literature: Conference Papers
Authors: Satoko Yamamoto, Takao Asanuma, Toshihisa Takagi, Ken Ichiro Fukuda
Venue: Comparative and Functional Genomics (2004)

In general, it is not easy to specify a single sequence identity for each molecule name that appears in a pathway in the scientific literature. A molecule name may stand for concepts of various granularities, from concrete objects such as H-Ras and ERK1 to abstract concepts or categories such as Ras and MAPK. Typically, the relations among molecule names derive a hierarchical structure; without a proper way to handle this knowledge, it becomes ever more difficult to develop a reliable pathway database. This paper describes an ontology that is designed to annotate molecules in the scientific literature on signal transduction pathways. Copyright &copy; 2004 John Wiley & Sons, Ltd.
Exploiting Query Repetition and Regularity in an Adaptive Community-Based Web Search Engine
Authors: Barry Smyth, Evelyn Balfe, Jill Freyne, Peter Briggs, Maurice Coyle, Oisin Boydell
Venue: User Modeling and User-Adapted Interaction (2005)

Search engines continue to struggle with the challenges presented by Web search: vague queries, impatient users and an enormous and rapidly expanding collection of unmoderated, heterogeneous documents all make for an extremely hostile search environment. In this paper we argue that conventional approaches to Web search -- those that adopt a traditional, document-centric, information retrieval perspective -- are limited by their refusal to consider the past search behaviour of users during future search sessions. In particular, we argue that in many circumstances the search behaviour of users is repetitive and regular; the same sort of queries tend to recur and the same type of results are often selected. We describe how this observation can lead to a novel approach to a more adaptive form of search, one that leverages past search behaviours as a means to re-rank future search results in a way that recognises the implicit preferences of communities of searchers. We describe and evaluate the I-SPY search engine, which implements this approach to collaborative, community-based search. We show that it offers potential improvements in search performance, especially in certain situations where communities of searchers share similar information needs and use similar queries to express these needs. We also show that I-SPY benefits from important advantages when it comes to user privacy. In short, we argue that I-SPY strikes a useful balance between search personalization and user privacy, by offering a unique form of anonymous personalization, and in doing so may very well provide privacy-conscious Web users with an acceptable approach to personalized search.
MITRE: description of the Alembic system used for MUC-6
Authors: John Aberdeen, John Burger, David Day, Lynette Hirschman, Patricia Robinson, Marc Vilain
Venue: Proceedings of the 6th conference on Message understanding (1995)

As with several other veteran MUC participants, MITRE's Alembic system has undergone a major transformation in the past two years. The genesis of this transformation occurred during a dinner conversation at the last MUC conference, MUC-5. At that time, several of us reluctantly admitted that our major impediment towards improved performance was reliance on then-standard linguistic models of syntax. We knew we would need an alternative to traditional linguistic grammars, even to the somewhat non-traditional categorial pseudo-parser we had in place at the time. The problem was, which alternative?
A theory of epineuronal memory
Authors: Roman Borisyuk, Frank Hoppensteadt
Venue: Neural Networks (2004)

How can a brain maintain stable memories and behaviors when its underlying electrical and chemical structures are constantly changing? We investigate this stability problem thinking that the state variables (e.g. voltages, ionic currents, etc.) are governed by a complex system that itself is closely regulated. Regulation of the network is through its operating environment, which is described by parameters. We study a standard neural network model, but one whose parameters are governed by a mnemonic landscape function. Parameter configurations are attracted to local maxima of this landscape, which represent memorized parameter configurations. The operating environment changes slowly (relative to the state variables) guided by the mnemonic landscape function, and this provides a quasi-static operating environment for the network. We describe shaping the mnemonic landscape, how it acts as a probability density function to guide slow parameter dynamics, and how the parameters shape the network output. Simulations of memory registration, activity patterns, and sequential recall are described.
Location and pose estimation for active vision using panoramic edge histograms
Authors: Caihua Wang, Hideki Tanahashi, Yutaka Satoh, Hidekazu Hirayu, Yoshinori Niwa, Kazuhiko Yamamoto
Venue: Systems and Computers in Japan (2004)

In this paper, the authors propose a new technique for robust location and pose estimation for an active vision sensor using images obtained by a camera system (omnidirectional sensor) that can acquire panoramic information of the environment. The proposed technique first calculates a panoramic edge histogram in advance from images obtained by the omnidirectional sensor at several reference points in the environment. To estimate the sensor location and pose, dynamic programming (DP) is extended to two-pass DP, and the current location is matched with the panoramic edge histogram at the reference points to obtain the edge shift magnitude at each direction angle. These shift magnitudes have the same periodicity as a sine curve, the sensor rotation corresponds to the offset of the sine curve, and its movement direction corresponds to the 0-phase of the sine curve. In the current research, the sensor's movement direction and rotation angle are efficiently estimated by independently fitting the offset and the 0-phase of its period from these edge shift magnitudes. Finally, the exact location is calculated from the movement directions for the two closest reference points. The effectiveness of the proposed technique is shown by experiments in an actual environment. &copy; 2004 Wiley Periodicals, Inc. Syst Comp Jpn, 35(14): 32&ndash;43, 2004; Published online in Wiley InterScience (). DOI 10.1002&sol;scj.10699
A Dynamic Hybrid Scheduling Algorithm with Clients' Departure for Impatient Clients in Heterogeneous Environments
Authors: Navrati Saxena, Kalyan Basu, Sajal K. Das, Christina M. Pinotti
Venue: Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium (IPDPS'05) - Workshop 12 - Volume 13 (2005)

The essence of efficient scheduling and data transmission techniques lies in providing the web-applications with advanced data processing capabilities. In this paper we have efficiently combined the push and the pull scheduling to develop a new, practical, dynamic, hybrid scheduling strategy for heterogenous, asymmetric environments. The proposed algorithm dynamically computes the probabilities and the optimal cutoff-point to separate the push and the pull data sets. The data items are also assumed to be of variable lengths. While the push strategy uses the flat, roundrobin scheduling, the pull items are determined by stretch-optimal (max-request min-service time) scheduling policy. In order to make the scheduling more practical, we have considered the impact of the impatience of the clients waiting to get the service of a particular data item. The effects of this impatience can lead to departure of specific client(s) from the system. Our proposed hybrid scheduling strategy takes care of these effects to capture a real portrayal of the system dynamics. These scenarios are modelled by suitable birth and death process to analyze the overall expected delay of the system. Subsequently, simulation results corroborate the average system performance and points out significant improvement over existing hybrid systems in terms of average waiting time spent by a client.
Modeling Anatomical-Based Humans
Authors: N. Magnenat-Thalmann, L. Yahia-Cherif, H. Seo
Venue: Proceedings of the Third International Conference on Image and Graphics (2004)

We present two complementary methodologies to automatically generate 3D surfaces of human bodies including internal bones. The first methodology is a data-driven approach and uses a database of human bodies in conjunction with a learning model synthesizer to create 3D surfaces subject to desired shape and size. In the second methodology, we use medical scanning devices to capture the internal anatomy of the individual and reconstruct 3D surfaces of bones. The final result is an animatable human body including skin external surface as well as the internal skeleton.
Characterization of logic circuit techniques and optimization for high-leakage CMOS technologies
Authors: Phillip Chin, Charles A. Zukowski, George D. Gristede, Stephen V. Kosonocky
Venue: Integration, the VLSI Journal (2005)

Channel subthreshold and gate leakage currents are predicted by many to become much more significant in advanced CMOS technologies and are expected to have a substantial impact on logic circuit design strategies. To reduce static power, techniques such as the use of monotonic logic and management of various evaluation and idle modes within logic stages may become important options in circuit optimization. In this paper, we present a general, multilevel model for logic blocks consisting of logic gates that include a wide range of options for static power reduction, in both the domains of topology and timing. Existing circuit techniques are classified within this framework and experiments are presented showing how aspects of performance might vary across this range in a hypothetical technology. The framework also allows exploration of optimal mixing of techniques.
Destructive Transaction: Human-Oriented Cluster System Management Mechanism
Authors: Taoying Liu, Zhiwei Xu, Ninghui Sun, Dan Meng
Venue: Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium (IPDPS'05) - Workshop 18 - Volume 19 (2005)

Traditional cluster system management tools seldom consider the relevance betweenmanaged objects. Such relevance is the reason of related fault and may also lead to human operation errors. Because of this defect, traditional tools do not have the capability of handling of consistency, atomicity and recovery. This article proposes a transaction-based facility, destructive transaction, to solve the problems at some degree. Destructive transaction is a construct to wire down management rules stored in a system administrator's mind. It provides a method to describe managed objects relationships, atomicity facility and recovery for failed operation. And it significantly reduces human caused error possibility.
A Divide-and-Conquer Learning Approach to Radial Basis Function Networks
Authors: Yiu-Ming Cheung, Rong-Bo Huang
Venue: Neural Processing Letters (2005)

This paper presents a new divide-and-conquer based learning approach to radial basis function (RBF) networks, in which a conventional RBF network is divided into several RBF sub-networks. Each of them individually takes an input sub-space as its input. The original network's output then becomes a linear combination of the sub-networks' outputs with the coefficients adaptively learned together with the system parameters of each sub-network. Since this approach reduces the structural complexity of a RBF network by describing a high-dimensional modelling problem via several low-dimensional ones, the network's learning speed is considerably improved as a whole with the comparable generalization capability. The empirical studies have shown its outstanding performance on forecasting two real time series as well as synthetic data. Besides, we have found that the performance of this approach generally varies with the different decompositions of the network's input and the hidden layer. We therefore further explore the decomposition rule with the results verified by the experiments.