ppxscal/embedding_network huggingface dataset:
Anomaly-free Prediction of Gene Ontology Annotations Using Bayesian Networks
Authors: Marco Tagliasacchi, Marco Masseroli
Venue: Proceedings of the 2009 Ninth IEEE International Conference on Bioinformatics and Bioengineering (2009)

Gene and protein structural and functional annotations expressed through controlled terminologies and ontologies are paramount especially for the aim of inferring new biomedical knowledge through computational analyses. However, the available annotations are incomplete, in particular for recently studied genomes, and only a few of them are highly reliable human curated information. To support and speed up the time-consuming curation process, prioritized lists of computationally predicted annotations are hence extremely useful. In this paper we leverage a previous work on the automatic prediction of Gene Ontology annotations based on the singular value decomposition (SVD) of the gene-to-term annotation matrix, and we propose a novel post-processing method that uses a Bayesian network to eliminate predictions of anomalous annotations. In fact, we observed that the predicted annotation profiles might suggest that a gene shall be annotated to a term, but not to one of its ancestors, thus violating the constraint imposed by the Gene Ontology. To this end, the proposed algorithm processes the annotation profiles predicted by a SVD based method, and produces a ranked list of computationally discovered candidate annotations which is consistent with the Gene Ontology.
Approaching to Application of Business Process Re-engineering and Information Strategy and Technology
Authors: Chen Xin
Venue: Proceedings of the 2009 IITA International Conference on Control, Automation and Systems Engineering (case 2009) (2009)

As we enter into the digital age, information technology is playing a principal role in bringing process improvement to the forefront of business management consciousness. In the last decade, re-engineering efforts have produced a wide range of results. Many organizations in the West have undertaken business process reengineering initiatives with the aim of improving organizational performance. These initiatives inevitably involve redesign and alterations to the existing information systems that support the business processes. Many business process improvement efforts emphasize better integration, yet process integration can mean many things The recent emergence of the application service provision (ASP) business model has promised firms remote-access to industry robust business processes.
Fast planning in domains with derived predicates: an approach based on rule-action graphs and local search
Authors: Alfonso Gerevini, Alessandro Saetti, Ivan Serina, Paolo Toninelli
Venue: Proceedings of the 20th national conference on Artificial intelligence - Volume 3 (2005)

The ability to express "derived predicates" in the formalization of a planning domain is both practically and theoretically important. In this paper, we propose an approach to planning with derived predicates where the search space consists of "Rule-Action Graphs", particular graphs of actions and rules representing derived predicates. We present some techniques for representing rules and reasoning with them, which are integrated into a method for planning through local search and rule-action graphs. We also propose some new heuristics for guiding the search, and some experimental results illustrating the performance of our approach. Our proposed techniques are implemented in a planner that took part in the fourth International Planning Competition showing good performance in many benchmark problems.
Energy Harvesting in Substations for Powering Autonomous Sensors
Authors: M. Zhu, M. D. Judd, P. J. Moore
Venue: Proceedings of the 2009 Third International Conference on Sensor Technologies and Applications (2009)

The benefits of enhanced condition monitoring in the asset management of the electricity transmission infrastructure are increasingly being exploited by the grid operators. Adding more sensors helps to track the plant health more accurately. However, the installation or operating costs of any additional sensors could outweigh the benefits they bring due to the requirement for new cabling or battery maintenance. Energy harvesting devices are therefore being proposed to power a new generation of wireless sensors. The harvesting devices could enable the sensors to be maintenance free over their lifetime and substantially reduce the cost of installing and operating a condition monitoring system.
An Efficient Algorithm for Overlapping Community Detection in Complex Networks
Authors: Duanbing Chen, Yan Fu, Mingsheng Shang
Venue: Proceedings of the 2009 WRI Global Congress on Intelligent Systems - Volume 01 (2009)

Community structure is an important property of the complex networks. How to detect the communities is significant to understand the network structure and analyze the network properties. Many algorithms, such as K-L and GN, have been proposed to detect the community structure in complex networks. However, the communities detected by these algorithms are always not overlapping. According to daily experience, a node in the network may belong to several communities and a community should have many nodes and connections. Based on these principals and existing researches, an efficient algorithm for overlapping community detection in complex networks is proposed in this paper. The key strategy of the algorithm is to mine a node with the closest relations with the community and assign it to the community. Some real-world networks are used to test the performance of the algorithm. Experimental results demonstrate that the algorithm proposed is rather efficient to detect the overlapping community in complex networks.
Traffic Accident Macro Forecast Based on ARIMAX Model
Authors: Chunyan Li, Jun Chen
Venue: Proceedings of the 2009 International Conference on Measuring Technology and Mechatronics Automation - Volume 03 (2009)

To overcome the deficiency of traditional traffic accident estimation models, this paper introduced a new way. It gave two categories on traffic accident affected factors and selected the main ones, using stepwise regression model. ARIMAX model, a dynamic regression one, was used to forecast traffic accident volumes. The former job ensures the precision of estimation, while the latter one owns both regression and ETS models’ merits. The example of traffic accident data from 1983 to 2005 in China was taken to validate the feasibility of the model. It established the relationship between dead people due to traffic accident and total population, mileage of road rank, the number of passenger transport, the population of drivers, the average GDP and automobile numbers, and gave an estimation adopting ARIMAX model. The result shows that the error is small and it has a much better foreground on traffic accident macro forecast.
Manufacturing Finance with SAP ERP Financials
Authors: Subbu Ramakrishnan
Venue:  (2009)

This book provides Manufacturing Finance Managers, finance team members, implementation project managers, and consultants with a comprehensive, practical guide to the Finance functionality available for the manufacturing environment and the configuration and integration processes necessary for optimizing SAP ERP Financials for manufacturing. Focusing primarily on the core functions of the Financial Accounting and Controlling components, the book provides readers with a holistic look at the business drivers, KPIs, configuration schemes, and technical issues relevant to the manufacturing finance function. For Finance users, the book covers the standard business drivers and KPIs as they apply to the major manufacturing models, and lends guidance for configuring Financial Accounting and Controlling to maximize functionality for manufacturing finance. Implementation managers and consultants will benefit from the coverage of integrating SAP ERP Financials with other SAP applications such as PP and MM, as well as the configuration sections for Master Data, Cost Object Controlling, and the Information System, among others. Highlights: Master Data Requirements Make-to-Stock Manufacturing Cost Object Controlling Material Ledger Business Transactions Annual Costing Information System 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
Large-scale parallel breadth-first search
Authors: Richard E. Korf, Peter Schultze
Venue: Proceedings of the 20th national conference on Artificial intelligence - Volume 3 (2005)

Recently, best-first search algorithms have been introduced that store their nodes on disk, to avoid their inherent memory limitation. We introduce several improvements to the best of these, including parallel processing, to reduce their storage and time requirements. We also present a linear-time algorithm for bijectively mapping permutations to integers in lexicographic order. We use breadth-first searches of sliding-tile puzzles as testbeds. On the 3×5 Fourteen Puzzle, we reduce both the storage and time needed by a factor of 3.5 on two processors. We also performed the first complete breadth-first search of the 4×4 Fifteen Puzzle, with over 1013 states.
Control of Personal Tempo to Support Individual Action and Cognition
Authors: Naoya Nobutani, Yoshio Nakatani
Venue: Proceedings of the Symposium on Human Interface 2009 on ConferenceUniversal Access in Human-Computer Interaction. Part I: Held as Part of HCI International 2009 (2009)

We live in our own rhythms in daily lives. Human life is closely related to rhythm as the words "talk rhythm," "getting into the rhythm" and the "Biorhythm" show. The rhythm is important for us to live in order and cheerfully. Each person has his/her own action rhythm called the "Personal Tempo." It is the basic rhythm observed in person's voluntary actions, such as tapping on a table. Psychology has been studying this phenomenon for long years. By measuring the personal tempo, person's psychological condition can be inferred in all situations because personal tempo changes within a certain width according to person's psychological condition, while it basically shows homeostasis. Most studies have focused on relation between personal tempo and physiological measures, such as cardiac rate, but not on control of cognitions and actions by controlling personal tempo. In this paper, a control method of individual action by controlling the personal tempo is proposed. Drum beat pattern is used to control the personal tempo. We show the effectiveness of this method by applying this to cooking, especially chopping by a knife.
An Immune Inspired Algorithm for Solving Dynamic Vehicle Dispatching Problem in a Port Container Terminal
Authors: N. M. Lee, H. Y. Lau, A. W. Ko
Venue: Proceedings of the 8th International Conference on Artificial Immune Systems (2009)

A typical Vehicle Dispatching Problem (VDP) for a port container terminal often involves offline resource allocation and is often successfully solved by heuristics algorithms. In this research, an autonomous and decentralized vehicle dispatching algorithm is proposed in which the algorithm is inspired by the human immune system. Specifically, the proposed algorithm is inspired by the cell-mediate immune response of T-cells that possess the capability of exploring the environment and providing an adaptive and specific immune response to the invading antigens. We conduct extensive simulation studies to study the performance of the algorithm in solving a typical vehicle dispatch problem derived from realistic terminal configurations and operational constraints. The results show good vehicle utilization and low computational cost when comparing with a GA-based algorithm.
Space Target Recognition Based on Biomimetic Pattern Recognition
Authors: Wenming Cao, Hao Feng, Lili Hu, Tiancheng He
Venue: Proceedings of the 2009 First International Workshop on Database Technology and Applications (2009)

Biomimetic Pattern Recognition is a new model of Pattern Recognition based on “matter cognition” instead of “matter classification”. This new model is much closer to the function of human being, than traditional statistical Pattern Recognition using “optimal separating” as its main principle.But it has been investigated in 2D sample space, In this paper, we extend to space target Image sample space by Clifford Algebra, and study its property. The experiment result proves the efficiency of our theory.
Improving unsupervised dependency parsing with richer contexts and smoothing
Authors: William P. Headden,  III, Mark Johnson, David McClosky
Venue: Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics (2009)

Unsupervised grammar induction models tend to employ relatively simple models of syntax when compared to their supervised counterparts. Traditionally, the unsupervised models have been kept simple due to tractability and data sparsity concerns. In this paper, we introduce basic valence frames and lexical information into an unsupervised dependency grammar inducer and show how this additional information can be leveraged via smoothing. Our model produces state-of-the-art results on the task of unsupervised grammar induction, improving over the best previous work by almost 10 percentage points.
A Flexible Business Process Customization Framework for SaaS
Authors: Yuliang Shi, Shuai Luan, Qingzhong Li, Haiyang Wang
Venue: Proceedings of the 2009 WASE International Conference on Information Engineering - Volume 02 (2009)

With the rapid development of Internet and the gradual maturity of SOA, SaaS has become a popular software service mode. This paper proposes a flexible business process customization framework to solve problems caused byorchestrating SaaS business process through BPEL specifications. The framework is fully independent of BPEL engine and web services, which can realize a series of functions as following: enabling the tenant to customize service and process during defining process, verifying and checking the correctness of process logic while deploying process, modifying dynamically, substituting services andhandling abnormal situations according to the rules provided by tenants or the framework automatically at the runtime of process.
Towards Faceted Search for Named Entity Queries
Authors: Sofia Stamou, Lefteris Kozanidis
Venue: Advances in Web and Network Technologies, and Information Management: APWeb/WAIM 2009 International Workshops: WCMT 2009, RTBI 2009, DBIR-ENQOIR 2009, PAIS 2009, Suzhou, China, April 2-4, 2009, Revised Selected Papers (2009)

A considerable fraction of the web queries contain named entities. This, coupled with the fact that a proper name might refer to multiple entities, imposes the ever-increasing need that search engines handle efficiently named entity queries. In this paper, we present a technique that automatically identifies the distinct subject classes to which a named entity query might refer and selects a set of appropriate facets for denoting the query properties within every class. We also suggest a method that examines the distribution of the identified query facets within the contents of the query matching pages and groups search results according to their entity denotation types. Our preliminary study shows that our technique identifies useful facets for representing the named entity query properties in each of their referenced subject classes.
Application for Matter-Element Model in Eco-environment Impact Assessment of Tourism Highway
Authors: Zhan Ting, Wang Xuancang
Venue: Proceedings of the 2009 International Conference on Environmental Science and Information Application Technology - Volume 02 (2009)

According to characteristics of tourism highway and research results of eco-environmental evaluation at home and abroad, an index system about eco-environmental impact of tourism highway has been constructed. On the basis of the index system, a matter-element evaluation model for eco-environmental impact was constructed with the support of matter-element model and extension theory. By the application of one project case and the comparison with evaluation model of fuzzy mathematics, the model proved to be effective and feasible. The results show the model can eliminate impact of man-made in the process of evaluation and improve the accuracy of evaluation.
Design validation of multithreaded architectures using concurrent threads evolution
Authors: D. Ravotto, E. Sanchez, M. Sonza Reorda, G. Squillero
Venue: Proceedings of the 22nd Annual Symposium on Integrated Circuits and System Design: Chip on the Dunes (2009)

Within the design arena of modern devices based on cutting-edge processor cores, the availability of effective verification, validation and test methodologies able to work on high-level descriptions of processor cores represents an interesting advantage, since it can dramatically reduce the overall time for design and manufacturing, while improving yield and quality. In this paper we propose a semi-automatic test program generation technique able to target modules in modern computer architectures that implement the multithreading paradigm. The methodology starts from high level descriptions of processor cores and using an incremental multi-run approach produces, with very limited manual intervention, a test set able to maximize verification metrics. Experimental results gathered on a real complex design, the OpenSPARC&trade; T2 core, show the effectiveness of the proposed methodology.
Research on Control Algorithm for DYC and Integrated Control with 4WS
Authors: Zhu Tianjun, Zong Changfu
Venue: Proceedings of the 2009 International Conference on Computational Intelligence and Natural Computing - Volume 02 (2009)

The best advantage of the DYC is it can greatly improve vehicle handling and stability. It is proposed integrated control of four wheel steering systems (4WS) and direct yaw moment control. A desirable vehicle model is established with the best performance of side slip angle and yaw rate. The strategy of both the forward controller and feedback controller of tracking the desirable model is adopted and an optimal controller is designed. By the simulation, it is compared to only DYC and integrated control of 4WS and DYC. The simulation results indicated that integrated control could effectively control side slip angle and yaw rate tracking the desirable value.
Hypernetwork Model to Represent Similarity Details Applied to Musical Instrument Performance
Authors: Tetsuya Maeshiro, Midori Maeshiro, Katsunori Shimohara, Shin-Ichi Nakayama
Venue: Proceedings of the 13th International Conference on Human-Computer Interaction. Part I: New Trends (2009)

This paper treats the quantification and description of similarities among entities being represented as a network. The proposed representation model, hypernetwork model, allows more specific description of relationships among represented entities than conventional knowledge representation models. Musical instruments performance is represented with hypernetwork model. Detailed description of similarity relationships provided by the hypernetwork model enables the discrimination of various types and degrees of similarity. A method to compare similar relationships is also discussed, which leads to the analogical reasoning, associative search and retrieval.
Direct maximization of average precision by hill-climbing, with a comparison to a maximum entropy approach
Authors: William Morgan, Warren Greiff, John Henderson
Venue: Proceedings of HLT-NAACL 2004: Short Papers on XX (2004)

We describe an algorithm for choosing term weights to maximize average precision. The algorithm performs successive exhaustive searches through single directions in weight space. It makes use of a novel technique for considering all possible values of average precision that arise in searching for a maximum in a given direction. We apply the algorithm and compare this algorithm to a maximum entropy approach.
Causal Probabilistic Modelling for Two-View Mammographic Analysis
Authors: Marina Velikova, Maurice Samulski, Peter J. Lucas, Nico Karssemeijer
Venue: Proceedings of the 12th Conference on Artificial Intelligence in Medicine: Artificial Intelligence in Medicine (2009)

Mammographic analysis is a difficult task due to the complexity of image interpretation. This results in diagnostic uncertainty, thus provoking the need for assistance by computer decision-making tools. Probabilistic modelling based on Bayesian networks is among the suitable tools, as it allows for the formalization of the uncertainty about parameters, models, and predictions in a statistical manner, yet such that available background knowledge about characteristics of the domain can be taken into account. In this paper, we investigate a specific class of Bayesian networks--causal independence models--for exploring the dependencies between two breast image views. The proposed method is based on a multi-stage scheme incorporating domain knowledge and information obtained from two computer-aided detection systems. The experiments with actual mammographic data demonstrate the potential of the proposed two-view probabilistic system for supporting radiologists in detecting breast cancer, both at a location and a patient level.
Jointmotion estimation and layer segmentation in transparent image sequenc: application to noise reduction in X-ray image sequences
Authors: Vincent Auvray, Patrick Bouthemy, Jean Liénard
Venue: EURASIP Journal on Advances in Signal Processing (2009)

This paper is concerned with the estimation of the motions and the segmentation of the spatial supports of the different layers involved in transparent X-ray image sequences. Classical motion estimation methods fail on sequences involving transparent effects since they do not explicitly model this phenomenon. We propose a method that comprises three main steps: initial block-matching for two-layer transparent motion estimation, motion clustering with 3D Hough transform, and joint transparent layer segmentation and parametric motion estimation. It is validated on synthetic and real clinical X-ray image sequences. Secondly, we derive an original transparent motion compensation method compatible with any spatiotemporal filtering technique. A direct transparentmotion compensation method is proposed. To overcome its limitations, a novel hybrid filter is introduced which locally selects which type of motion compensation is to be carried out for optimal denoising. Convincing experiments on synthetic and real clinical images are also reported.
A task-based comparison of information extraction pattern models
Authors: Mark A. Greenwood, Mark Stevenson
Venue: Proceedings of the Workshop on Deep Linguistic Processing (2007)

Several recent approaches to Information Extraction (IE) have used dependency trees as the basis for an extraction pattern representation. These approaches have used a variety of pattern models (schemes which define the parts of the dependency tree which can be used to form extraction patterns). Previous comparisons of these pattern models are limited by the fact that they have used indirect tasks to evaluate each model. This limitation is addressed here in an experiment which compares four pattern models using an unsupervised learning algorithm and a standard IE scenario. It is found that there is a wide variation between the models' performance and suggests that one model is the most useful for IE.