ppxscal/embedding_network huggingface dataset:
Metabolic network properties help assign weights to elementary modes to understand physiological flux distributions
Authors: Qingzhao Wang, Yudi Yang, Hongwu Ma, Xueming Zhao
Venue: Bioinformatics (2007)

Motivation: Elementary modes (EMs) analysis has been well established. The existing methodologies for assigning weights to EMs cannot be directly applied for large-scale metabolic networks, since the tremendous number of modes would make the computation a time-consuming or even an impossible mission. Therefore, developing more efficient methods to deal with large set of EMs is urgent. Result: We develop a method to evaluate the performance of employing a subset of the elementary modes to reconstruct a real flux distribution by using the relative error between the real flux vector and the reconstructed one as an indicator. We have found a power function relationship between the decrease of relative error and the increase of the number of the selecting EMs, and a logarithmic relationship between the increases of the number of non-zero weighted EMs and that of the number of the selecting EMs. Our discoveries show that it is possible to reconstruct a given flux distribution by a selected subset of EMs from a large metabolic network and furthermore, they help us identify the ‘governing modes’ to represent the cellular metabolism for such a condition. Contact:diana_kingson@yahoo.com.cn(or) Wangqingzhao@eyou.com Supplementary information: Supplementary data are available at Bioinformatics online.
An Improved Test Case Generation Method of Pair-Wise Testing
Authors: Qian Feng-an, Jiang Jian-hui
Venue: Proceedings of the 16th Asian Test Symposium (2007)

Pair-wise testing is a testing criterion based on specification, which requires that for each pair of parameters, every combination of their valid value should be covered by at least one test case in the test set. This paper presents an improved method based on AETG. Experimental results show that the size of test set produced by our method is relatively small. In addition, the method can be easily implemented.
Web resources for language modeling in conversational speech recognition
Authors: Ivan Bulyko, Mari Ostendorf, Manhung Siu, Tim Ng, Andreas Stolcke, Özgür Çetin
Venue: ACM Transactions on Speech and Language Processing (TSLP) (2007)

This article describes a methodology for collecting text from the Web to match a target sublanguage both in style (register) and topic. Unlike other work that estimates n-gram statistics from page counts, the approach here is to select and filter documents, which provides more control over the type of material contributing to the n-gram counts. The data can be used in a variety of ways; here, the different sources are combined in two types of mixture models. Focusing on conversational speech where data collection can be quite costly, experiments demonstrate the positive impact of Web collections on several tasks with varying amounts of data, including Mandarin and English telephone conversations and English meetings and lectures.
An Immune Fault Detection System with Automatic Detector Generation by Genetic Algorithms
Authors: Jorge L. M. Amaral, Jose F. M. Amaral, Daneil Morin, Ricardo Tanscheit
Venue: Proceedings of the Seventh International Conference on Intelligent Systems Design and Applications (2007)

This work deals with fault detection of electronic analog circuits. A fault detection system for analog circuits based on cross-correlation and artificial immune systems is proposed. It is capable of detecting faulty components in analog circuits by analyzing its impulse response. The use of cross-correlation for preprocessing the impulse response drastically reduces the size of the detector used by the Real- valued Negative Selection Algorithm (RNSA). The proposed method makes use of genetic algorithms to automatically generate a small number of very efficient detectors. Results have demonstrated that the proposed system is able to detect faults in a Sallen-Key bandpass filter and in a universal filter.
Voltage Sags Detection and Identification Based on Phase-Shift and RBF Neural Network
Authors: Ganyun Lv, Xiaodong Wang
Venue: Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 01 (2007)

Voltage sags are probably one of the most important power quality problems because of its impact on malfunctioning electrical equipment in industrial and commercial installations and high frequency. This fact highlights the need for an effective technique of detection, evaluation and classification of the sags problems. This paper proposed a voltage sags detection and identification method based phase-shift and RBF neural network. The voltage sag magnitude, duration and shape were extract out with the proposed phase-shift method, according to instantaneous virtual peak value. The proposed technique has good performance of real-time. Through a data dealing process of detecting outputs by the phase-shift method, a set of features is extracted for identification of voltage sags. Finally, a RBF network was developed for voltage sags classification according to the Cause. The proposed method is simple and reach 92% identification correct ratio even under noise. The results are useful for the diagnosis of the sags cause.
Optimization of the Trade-Off by Artificially Re-sampling for Ensemble Learning
Authors: Xiaofei Zhu, Jianmin Zhong, Lixia Zhuo
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 05 (2007)

Ensemble learning methods like Bagging and Boosting that train a diversity of classifiers by manipulating the training set given to a base learning algorithm and then combine their predictions in classification. And the trade- off between accuracy and diversity of component classifiers is the crucial factor in determining its generalization error. Both Bagging and Boosting approach the trade-off by bootstrap sampling or re- weighting the existing training set. Some improved methods such as Decorate does this by adding artificial training instances into the existing training set. Although they achieve a suitable trade-off to some extent, they have not focused directly on the goal of find the best trade-off between accuracy and diversity of component classifiers. This paper studies empirically the influence of the trade- off, and an artificially re-sampling method is given by cross-grouping the training set to provide the best trade- off, which felicitously groups the original training set into a number of crossed derived training sets, and a base learning algorithm will be trained on them. The experiments show that the performance of this method is better than that of Boosting and Bagging.
Segmentation and Recognition of Marrow Cells Image Based on Wavelet and Genetic Cluster
Authors: Hou Zhenjie, Ma Shuoshi, Pei Xichun, Zhang Wei
Venue: Proceedings of the Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing - Volume 01 (2007)

Due to the variety and the complexity of marrow cells image, better results may be achieved by adopting multi-threshold for the image segmentation. However, with regard to no significant peak and valley values in the histogram, it is too difficult to determine thresholds. Therefore, a new method of combining the spatial scales filter and the wavelet transform analysis is adopted to find suitable thresholds and the obtained edge is optimized by the active contour model. Proposed a new genetic clustering algorithm based on entropy to classify the marrow cells. Through the experiences, better result can be attained.
Securing Virtual Private Networks with SIM Authentication
Authors: Torstein Bjornstad, Ivar Jorstad, Do Van Thanh
Venue: Proceedings of the Third IEEE International Conference on Wireless and Mobile Computing, Networking and Communications (2007)

With the ever increasing amount of systems requiring user authentication, users are experiencing a substantial inconvenience. A huge amount of passwords needs to be remembered, which in many cases decrease system security, as users choose to write them down or use the same password for several systems. The number of username/password pairs has simply become unmanageable. Other, stronger authentication mechanisms are added to some systems, which increase administration costs for the enterprises/service providers. There is an immediate need for a stronger, yet at the same time simpler and cost-efficient authentication mechanism which can be reused across many different types of services. This paper proposes a novel VPN solution which employs the GSM SIM authentication mechanism for authenticating users towards VPN networks and for setting up the encrypted tunnel between the VPN client and server. The solution ensures strong security, is user-friendly and cost-efficient.
Window Detection in Facades
Authors: Haider Ali, Christin Seifert, Nitin Jindal, Lucas Paletta, Gerhard Paar
Venue: Proceedings of the 14th International Conference on Image Analysis and Processing (2007)

This work is about a novel methodology for window detection in urban environments and its multiple use in vision system applications. The presented method for window detection includes appropriate early image processing, provides a multi-scale Haar wavelet representation for the determination of image tiles which is then fed into a cascaded classifier for the task of window detection. The classifier is learned from a Gentle Adaboost driven cascaded decision tree [1] on masked information from training imagery and is tested towards window based ground truth information which is - together with the original building image databases - publicly available [10, 11, 13]. The experimental results demonstrate that single window detection is to a sufficient degree successful, e.g., for the purpose of building recognition, and, furthermore, that the classifier is in general capable to provide a region of interest operator for the interpretation of urban environments. The extraction of this categorical information is beneficial to index into search spaces for urban object recognition as well as aiming towards providing a semantic focus for accurate post-processing in 3D information processing systems. Targeted applications are (i) mobile services on uncalibrated imagery, e.g. , for tourist guidance, (ii) sparse 3D city modeling, and (iii) deformation analysis from high resolution imagery.
Designing for new photographic experiences: how the lomographic practice informed context photography
Authors: Sara Ljungblad
Venue: Proceedings of the 2007 conference on Designing pleasurable products and interfaces (2007)

This paper reports on how we learned from an alternative practice in order to design engaging interactive technology intended for a more general user group. When investigating new types of digital photography we designed context photography, where real-time context data visually affects digital pictures as they are taken. To understand how to design for a meaningful photographic experience, we took inspiration from an amateur practice involving a particular type of analogue camera --- Lomography. This paper shows how such alternative or marginal practices can help to ground design of interactive technology in existing human interests, while at the same time leading to a novel design outcome.
The family of biarcs that matches planar, two-point G1 Hermite data
Authors: D. S. Meek, D. J. Walton
Venue: Journal of Computational and Applied Mathematics (2008)

The biarc is a curve made by joining two circular arcs in a G^1 fashion. There is a one-parameter family of biarcs that can match given planar, two-point G^1 Hermite data. This note considers the range of G^1 Hermite data that can be matched, identifies the region in which the members of the family of biarcs lie, and shows that there is exactly one member biarc passing through each point in that region.
Faster Calculation of Superquadric Shapes
Authors: Wm. R. Franklin
Venue: IEEE Computer Graphics and Applications (1981)

Nonparametric methods of calculating points on the curve produce the recently introduced superquadric objects at great savings in time.
Some Effects of Advances in Memory System Technology on Computer Organization
Authors: D. C. Gunderson
Venue: Computer (1970)

Technological improvements in memory systems in the '70s are expected to have a significant impact on computer organization. The expected advances will result in associative memories at reasonable cost, small-capacity random-access memories at low cost, and mass memories with greatly reduced access time. Possible implications or effects of each of these advances on the organization or design of future computer systems are identified. 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
Battle Damage Assessment based on Bayesian Network
Authors: Ma Zhi-jun, Shi Quan, Li Bin
Venue: Proceedings of the Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing - Volume 02 (2007)

With increasing tempo of war and complication of battle field, battle damage assessment (BDA) has become more critical to the decision of commander. In the Persian Gulf War, the BDA system of U.S. army couldn't meet the needs of commanders in both accuracy and speed, and badly blocked operations, one of its main reasons was lack of scientific and reasonable assessment model for BDA. According to the fact of BDA and the characters of Bayesian network, paper studies the theory of BDA based on Bayesian network, expatiates upon the modeling of Bayesian decision model for BDA, and puts forward a way to update the model, to enhance the accuracy of assessment.
On-the-Fly Data Flow Analysis Based on Verification Technology
Authors: María del Mar Gallardo, Christophe Joubert, Pedro Merino
Venue: Electronic Notes in Theoretical Computer Science (ENTCS) (2007)

The combination of static and dynamic software analysis, such as data flow analysis (Dfa) and model checking, provides benefits for both disciplines. On the one hand, the information extracted by Dfas about program data may be utilized by model checkers to optimize the state space representation. On the other hand, the expressiveness of logic formulas allows us to consider model checkers as generic data flow analyzers. Following this second approach, we propose in this paper an algorithm to calculate Dfas using on-the-fly resolution of boolean equation systems (Bess). The overall framework includes the abstraction of the input program into an implicit labeled transition system (Lts), independent of the program specification language. Moreover, using Bess as an intermediate representation allowed us to reformulate classical Dfas encountered in the literature, which were previously encoded in terms of @m-calculus formulas with forward and backward modalities. Our work was implemented and integrated into the widespread verification platform Cadp, and experimented on real examples.
An experimental study of random knapsack problems
Authors: Rene Beier, Berthold V&#x00f6;cking
Venue: Algorithmica (2006)

The size of the Pareto curve for the bicriteria version of the knapsack problem is polynomial on average. This has been shown for various random input distributions. We experimentally investigate the number of Pareto points for knapsack instances overn elements whose profits and weights are chosen at random according to various classes of input distributions. The numbers observed in our experiments are significantly smaller than the known upper bounds. For example, the upper bound for so-called uniform instances isO(n 3). Based on our experiments, we conjecture that the number of Pareto points for these instances is only &#x0398;(n 2). We also study other structural properties for random knapsack instances that have been used in theoretical studies to bound the average-case complexity of the knapsack problem. Furthermore, we study advanced algorithmic techniques for the knapsack problem. In particular, we review several ideas that originate from theory as well as from practice. Most of the concepts that we use are simple and have been known for at least 20 years, but apparently have not been used in this combination. Surprisingly, the result of our study is a very competitive code that outperforms the best previous implementationCombo by orders of magnitude for various classes of random instances, including harder random knapsack instances in which profits and weights are chosen in a correlated fashion.
Context-aware wrapping: synchronized data extraction
Authors: Shui-Lung Chuang, Kevin Chen-Chuan Chang, ChengXiang Zhai
Venue: Proceedings of the 33rd international conference on Very large data bases (2007)

The deep Web presents a pressing need for integrating large numbers of dynamically evolving data sources. To be more automatic yet accurate in building an integration system, we observe two problems: First, across sequential tasks in integration, how can a wrapper (as an extraction task) consider the peer sources to facilitate the subsequent matching task? Second, across parallel sources, how can a wrapper leverage the peer wrappers or domain rules to enhance extraction accuracy? These issues, while seemingly unrelated, both boil down to the lack of "context awareness": Current automatic wrapper induction approaches generate a wrapper for one source at a time, in isolation, and thus inherently lack the awareness of the peer sources or domain knowledge in the context of integration. We propose the concept of context-aware wrappers that are amenable to matching and that can leverage peer wrappers or prior domain knowledge. Such context awareness inspires a synchronization framework to construct wrappers consistently and collaboratively across their mutual context. We draw the insight from turbo codes and develop the turbo syncer to interconnect extraction with matching, which together achieve context awareness in wrapping. Our experiments show that the turbo syncer can, on the one hand, enhance extraction consistency and thus increase matching accuracy (from 17--83% to 78--94% in F-measure) and, on the other hand, incorporate peer wrappers and domain knowledge seamlessly to reduce extraction errors (from 09--60% to 01--11%).
Production scheduling and rescheduling with genetic algorithms
Authors: Christian Bierwirth, Dirk C. Mattfeld
Venue: Evolutionary Computation (1999)

A general model for job shop scheduling is described which applies to static, dynamic and non-deterministic production environments. Next, a Genetic Algorithm is presented which solves the job shop scheduling problem. This algorithm is tested in a dynamic environment under different workload situations. Thereby, a highly efficient decoding procedure is proposed which strongly improves the quality of schedules. Finally, this technique is tested for scheduling and rescheduling in a non-deterministic environment. It is shown by experiment that conventional methods of production control are clearly outperformed atreasonable runtime costs.
Experimental Prototyping in Smalltalk
Authors: J. Diederich
Venue: IEEE Software (1987)

Smalltalk promotes fearless programming. Users can signicantly alter an application even the system itself without fearing unrecoverable disasters.
Requirements and design spaces of mobile medical care
Authors: Prajakta Kulkarni, Yusuf Öztürk
Venue: ACM SIGMOBILE Mobile Computing and Communications Review (2007)

Pervasive care and chronic disease management to reduce institutionalization is a priority for most western countries. The realization of next generation ubiquitous and pervasive healthcare systems will be a challenging task, as these systems are likely to involve a complex structure. Such systems will consist of various devices, ranging from resource-constrained sensors and actuators to complex multimedia devices, supporting time critical applications. This is further compounded by cultural and socio-economical factors that must be addressed for next generation healthcare systems to be widely diffused and used. These factors have a direct impact on the system and security models and will require further understanding to encourage users to embrace and adopt the new technology. These models must capture not only the perceived value of the new technology and its ease of use, but most importantly the perceived risk of using this technology. This paper outlines the design space of pervasive health monitoring with body sensor networks and derives the requirements for connected pervasive medical care systems. Commercial and academic mobile medical sensor systems have been mapped to the requirements derived and a comparative analysis of state of the technology is given.
Virtual worlds: a political incubator
Authors: Doina Cajvaneanu
Venue: ACM SIGMIS Database (2007)

This article raises the question of political innovation that can potentially emerge within, and spread from, the virtual worlds. Locating the signs of political change in the surfacing of innovative political concepts, the article proposes the investigation of keywords in the codes and rules of the virtual communities, as well as the compilation of a glossary of such keywords, as a way to map and analyze the conceptual and political innovation of the latest political incubator.
Alternative B-Sequences
Authors: Lihua Duan, Jessica Chen
Venue: Proceedings of the Seventh International Conference on Quality Software (2007)

When an implementation under test (IUT) is state-based, and its expected abstract behavior is given in terms of a fi- nite state machine (FSM), a checking sequence generated from the specification FSM and applied on the IUT for test- ing can provide us with high-level confidence in the cor- rect functional behavior of our implementation. One of the issues here is to generate efficient checking sequences in terms of their lengths. In this paper, we discuss the possi- bility of reducing the lengths of checking sequences by mak- ing use of the invertible transitions in the specification FSM to increase the choice of -sequences to be included into a checking sequence. We present a sufficient condition for adopting alternative -sequences and illustrate a possible way of incorporating these alternative -sequences into ex- isting methods for checking sequence generation to further reduce their lengths. Keywords: conformance testing, finite state machine, checking sequence, distinguishing sequence.
Motivations for using the mobile phone for mass communications and entertainment
Authors: Ran Wei
Venue: Telematics and Informatics (2008)

This study draws on the uses and gratifications framework to examine expanded use of a hybrid medium-the mobile phone-for mass communications and entertainment. Results of a telephone survey of 208 users show different motivations predict diverse uses of the mobile phone. Instrumental use motives drive the use of the mobile phone for news-seeking and Web-surfing. Further, the motive of pass time is significantly linked to playing video games via the mobile phone. In addition, the high-tech mobile phone enabled users to be more active: the more intensively people use mobile phones for voice calls, the more likely they will be to use mobile data services. Thus, the hybrid mobile phone bridges interpersonal and mass communication. Finally, younger users are more likely to use mobile phones for getting news and entertainment. Implications for the industry and recommendations for future research are discussed.