ppxscal/embedding_network huggingface dataset:
Complex Systems, Artificial Intelligence and Theoretical Psychology
Authors: Richard Loosemore
Venue: Proceeding of the 2007 conference on Advances in Artificial General Intelligence: Concepts, Architectures and Algorithms: Proceedings of the AGI Workshop 2006 (2007)

The main finding of complex systems research is that there can be a disconnect between the local behavior of the interacting elements of a complex system and regularities that are observed in the global behavior of that system, making it virtually impossible to derive the global behavior from the local rules. It is arguable that intelligent systems must involve some amount of complexity, and so the global behavior of AI systems would therefore not be expected to have an analytic relation to their constituent mechanisms. This has serious implications for the methodology of AI. This paper suggests that AI researchers move toward a more empirical research paradigm, referred to as “theoretical psychology,” in which systematic experimentation is used to discover how the putative local mechanisms of intelligence relate to their global performance. There are reasons to expect that this new approach may allow AI to escape from a trap that has dogged it for much of its history: on the few previous occasions that something similar has been tried, the results were both impressive and quick to arrive.
What's on the grapevine?
Authors: Albert Angel, Nick Koudas, Nikos Sarkas, Divesh Srivastava
Venue: Proceedings of the 35th SIGMOD international conference on Management of data (2009)

User generated content and social media (in the form of blogs, wikis, online video, microblogs, etc) are proliferating online. Grapevine conducts large scale data analysis on the social media collective, distilling and extracting information in real time. It aims to track entities and stories of interest in millions of blog posts, thousands of tweets, news items, etc., daily. Grapevine facilitates the interactive exploration of content, allowing users to discover interesting or surprising stories, optionally narrowed down on a specific demographic of interest (e.g. "What are Torontonians talking about on blogs?", "What are popular stories across news sources in Canada?", "What are financiers in Texas blogging about today?"). Stories of interest can be explored in a variety of ways, such as modifying their scope, obtaining related content (blog posts, news, etc), and examining their temporal evolution.
Investigating the Reuse of Course Generation Knowledge
Authors: Carsten Ullrich, Qinghua Chen, Sushing Chen, Liping Shen, Ruimin Shen
Venue: Proceeding of the 2007 conference on Supporting Learning Flow through Integrative Technologies (2007)

Course generation knowledge, i.e., how to assemble a sequence of learning objects which is adapted to a learner's goals, competencies and preferences, is hard to assess and expensive to formalize, at least if it is based on pedagogical principles. On the other hand, once a course generator has been developed, it allows generating personalized courses for individual users at a relatively low cost. Therefore, course generation lends itself of being available as a (Web) service such that other systems can access its functionality without having to implement the knowledge themselves. In this paper we investigate whether this reuse of course generation knowledge works in practice. We took a course generator that was developed in the European project LeActiveMath and made it available for use in a Chinese distant university. In the paper, we describe how we represent the generic course generation knowledge and the difficulties we faced and the results we achieved when we applied the course generator in the Chinese setting. We also report on using course generation in a bioinformatic workflow environment.
Evolutionary hypernetwork classifiers for protein-proteininteraction sentence filtering
Authors: Jakramate Bootkrajang, Sun Kim, Byoung-Tak Zhang
Venue: Proceedings of the 11th Annual conference on Genetic and evolutionary computation (2009)

Protein-Protein Interaction (PPI) extraction, among ongoing biomedical text mining challenges, is becoming a topic in focus because of its crucial role in providing a starting point to understand biological processes. Machine learning (ML) techniques have been applied to extract the PPI information from biomedical literature. Although they have provided reasonable performance so far, more features are required for real use. In particular, many ML-approaches lack human understandability for learned models. Here, we propose a novel method for classifying PPI sentences. Our approach utilizes the modified hypernetwork model, a hypergraph with weighted hyperedges that are calibrated via an evolutionary learning method. The evolutionary hypernetwork memorizes fragments of training patterns while self-adjusting its own structure for detecting PPI sentences. For experiments, we show that our approach provides competitive performance compared to other ML methods. Apart from its superior classification performance, the evolving hypernetwork model comes with a highly interpretable structure. We show how significant PPI patterns can be naturally extracted from the learned model. We also analyze the discovered patterns.
Autonomic business service management
Authors: Donald F. Ferguson
Venue: Proceedings of the 6th international conference on Autonomic computing (2009)

Medium and large enterprises think of information technology implementing business services. Examples include online banking or Web commerce. Most systems and application management technology manage individual hardware and software systems. A business service is inherently a composite comprised from multiple HW, SW and logical entities. For example, a Web commerce system may have a Web server, Web application server, database server and messaging system to connect to mainframe inventory management. Each of the systems has various installed software. Businesses want to automate management of the business service, not the individual instances. IT management systems must manage the service, "unwind" the high level policies and operations, and apply them to individual HW and SW elements. SOA makes managing composites more difficult due to dynamic binding and request routing. This presentation describes the design and implementation of a business service management system. The core elements include: A Unified Service Model A real-time management database that extends the concept of a Configuration Management Database (CMDB) [http://en.wikipedia.org/wiki/CMDB], and integrates external management and monitoring systems. Rule based event correlation and rule based discovery of the structure of a business service. Algorithmic analysis of the composite service to automatically detect and repair availability and end-to-end performance problems. The presentation suggests topics for additional research.
Reliable algorithm for slab region localization using robust features
Authors: JongHyun Choi, Jong Pil Yun, SungHoo Choi, KeunHwi Koo, Yong Ju Jeon, Sang Woo Kim
Venue: Proceedings of the 8th WSEAS international conference on Signal processing, robotics and automation (2009)

In steel making production line, steel slabs are marked with slab management number (SMN). Identification of SMN has been done by workers, but this is expensive and not accurate. Consequently, to improve efficiency, automatic recognition system is desirable. In order to expect a high recognition rate, text localization is a prerequisite. However, because of many text-like patterns in a complex background and high fuzziness between the slab and background, directly extracting text region is difficult to process. This paper describes about the slab region localization using SIFT features in the image. First, SIFT algorithm is applied the captured background and slab image, then features of two images are matched by using geometric locations of the feature points. Finally, search rectangle method is performed, and then the top boundary and side boundaries of the slab region are determined. Thus, we can reduce search region for extraction of SMN from the slab image. Experimental results show that the proposed algorithm has a good performance.
Reconstructing generalized logical networks of transcriptional regulation in mouse brain from temporal gene expression data
Authors: Mingzhou Song, Chris K. Lewis, Eric R. Lance, Elissa J. Chesler, Roumyana Kirova Yordanova, Michael A. Langston, Kerrie H. Lodowski, Susan E. Bergeson
Venue: EURASIP Journal on Bioinformatics and Systems Biology (2009)

Gene expression time course data can be used not only to detect differentially expressed genes but also to find temporal associations among genes. The problem of reconstructing generalized logical networks to account for temporal dependencies among genes and environmental stimuli from transcriptomic data is addressed. A network reconstruction algorithm was developed that uses statistical significance as a criterion for network selection to avoid false-positive interactions arising from pure chance. The multinomial hypothesis testing-based network reconstruction allows for explicit specification of the false-positive rate, unique from all extant network inference algorithms. The method is superior to dynamic Bayesian network modeling in a simulation study. Temporal gene expression data from the brains of alcohol-treated mice in an analysis of the molecular response to alcohol are used for modeling. Genes from major neuronal pathways are identified as putative components of the alcohol response mechanism. Nine of these genes have associations with alcohol reported in literature. Several other potentially relevant genes, compatible with independent results from literature mining, may play a role in the response to alcohol. Additional, previously unknown gene interactions were discovered that, subject to biological verification, may offer new clues in the search for the elusive molecular mechanisms of alcoholism.
Resource discovery and request-redirection for dynamic load sharing in multi-provider peering content delivery networks
Authors: Mukaddim Pathan, Rajkumar Buyya
Venue: Journal of Network and Computer Applications (2009)

A constellation of Content Delivery Networks (CDNs), termed as peering CDNs, endeavors to guarantee adequate delivery performance when the incoming request load is overwhelming for a single provider alone. Each user is served by an optimal Web server in terms of network cost, even under heavy load conditions. Before it could be comprehended, appropriate resource discovery and request-redirection mechanisms, coupled with an optimal server selection strategy, should be in place to perform the distribution of highly skewed loads. In this paper, we devise an effective load distribution strategy by adopting distributed resource discovery and dynamic request-redirection mechanisms, taking traffic load and network proximity into account. The load distribution strategy reacts to overload conditions, at a time instance, in any primary CDN server(s) and instantly distributes loads to the target servers, minimizing network cost and observing practical constraints. In this context, we exercise an asynchronous resource discovery protocol, reminiscent of the public/subscribe notion, and formulate the resulting redirection scheme. Extensive simulation analyses demonstrate the novelty of our approach. In particular, we show that our approach is effective to handle high load skews by preserving locality, and thus achieve service ''responsiveness''. We also perform a sensitivity analysis to reveal that our redirection scheme outperforms other alternatives to handle peak loads.
Using context and behavioral patterns for intelligent traffic management
Authors: Derek Fagan, René Meier
Venue: Proceedings of the 1st International Workshop on Context-Aware Middleware and Services: affiliated with the 4th International Conference on Communication System Software and Middleware (COMSWARE 2009) (2009)

The integration of information and communications technologies across existing transportation infrastructure, systems and vehicles is fundamental to reducing traffic congestion, to improving driver safety, and to improving traveler experiences. Central to such intelligent traffic management are techniques and algorithms that are capable of analyzing the wealth of available contextual sensor data in "real time". Initial existing approaches tend to apply probability models and inference techniques to optimize traffic flow but fail to take into account certain aspects of human behavior that can affect the flow of traffic, such as patterns in human travel behavior. In this paper we explore how vehicle context information can be combined with the behavioral patterns of travelers to facilitate and improve intelligent traffic management. We present services for deriving reports on vehicle journeys that assist in the analysis of route performance, for enabling passengers to have remote access to real-time route performance information, and for the observation, learning, and utilization of human travel behavior patterns. These services provide essential traffic analysis information that is ultimately expected to lead to further improvements in intelligent traffic management, which aims at easing the flow of traffic in urban and suburban environments.
Low complexity real-time video transcoders for mobile video applications
Authors: Kazunori Ozawa, Hironori Ito, Kazuteru Watanabe, Ryota Takeshima, Kazuhiro Koyama
Venue: Proceedings of the 2008 International Symposium on a World of Wireless, Mobile and Multimedia Networks (2008)

This paper proposes low complexity real-time video transcoders based on both H.264 (AVC) and MPEG-4 which are suitable for mobile video applications. The transcoders proposed are PT (Picture Type Transcoder) and ST (Syntax Transcoder) and are used for video upload, delivery and video conference applications. In PT, relationship among PSNR, QP values and code length is obtained for H.264 baseline profile (BP) by simulation experiment to determine suitable QP values. Further, video mixing function for displaying multiple pictures at the same time in video conference application in which the proposed PT can be applied is described. The proposed PT and ST are implemented on a high-performance DSP, and complexity of PT and ST is compared with that of CPDT (Cascaded Pixel Domain Transcoder) for both H.264 BP and MPEG-4 simple profile (SP) cases. The complexity of the proposed PT and ST is very low. The complexity of PT is less than 1/3 of CPDT at both 64 kbps (QCIF) and 384 kbps (CIF) in H.264 BP.
The Use of Context-Aware Policies and Ontologies to Facilitate Business-Aware Network Management
Authors: John Strassner, Sven Meer, Declan O'Sullivan, Simon Dobson
Venue: Journal of Network and Systems Management (2009)

The purpose of autonomic networking is to manage the business and technical complexity of networked components and systems. However, existing network management data has no link to business concepts. This makes it very difficult to ensure that services offered by the network are meeting business objectives. This paper describes a novel context-aware policy model that uses a combination of modeled and ontological data to determine the current context, which policies are applicable to that context, and what services and resources should be offered to which users and applications.
Verifying realizability and reachability in recursive interaction protocol specifications
Authors: Hywel Dunn-Davies, Jim Cunningham
Venue: Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 2 (2009)

The Propositional Statechart language described in [4] makes it possible to provide unambiguous joint diagrammatic specifications of complex recursive interaction protocols such as the multilateral voting protocol. Recursive protocols described using Propositional Statecharts are not necessarily finite state, meaning that verification of properties of these protocols cannot be achieved solely by means of finite state model checking. In this paper we discuss the verification of realizability, and reachability analysis, in recursive joint protocol specifications expressed using joint Propositional Statecharts.
An Hybrid Soft Computing Approach for Automated Computer Design
Authors: Alessandro G. Di Nuovo, Maurizio Palesi, Davide Patti
Venue: Proceeding of the 2006 conference on STAIRS 2006: Proceedings of the Third Starting AI Researchers' Symposium (2006)

In this paper we present an intelligent approach for Computer Aided Design, that is capable to learn from its experience in order to speedup the design process. The proposed approach integrates two well known soft-computing techniques, Multi-Objective Genetic Algorithms (MOGAs) and Fuzzy Systems (FSs): MOGA smartly explores the design space, in the meanwhile the FS learn from the experience accumulated during the MOGA evolution, storing knowledge in fuzzy rules. The joined rules build the Knowledge Base through which the integrated system quickly predict the results of complex simulations thus avoiding their long execution times. The methodology is applied to a real case study and evaluated in terms of both efficiency and accuracy, demonstrating the superiority of the intelligent approach against brute force random search.
Requirements and Algorithms for Cooperation of Heterogeneous Radio Access Networks
Authors: Albena Mihovska, Elias Tragos, Emilio Mino, Jijun Luo, Christian Mensing, Roberta Fracchia, Sana Horrich, Lin Hui, Annika Klockar, Sofoklis Kyriazakos
Venue: Wireless Personal Communications: An International Journal (2009)

This paper defines the requirements for cooperation of heterogeneous radio access networks (RANs) and proposes a novel radio resource management (RRM) framework for support of mobility and quality of service (QoS) in a heterogeneous communication environment comprising IMT-Advanced and legacy systems. The reference IMT-Advanced system is the one developed within the IST project WINNER (IST-2003-507581 Project Wireless Initiative New Radio, http://www.ist-winner.org ). The RRM mechanisms are evolved from traditional ones to comply with the requirements imposed by a simplified new (RAN) architecture as proposed for IMT-Advanced systems. The RRM mechanisms are evaluated for the scenario of intra-RAN and inter-RAN user mobility. The RRM framework incorporates as novelty improved triggering mechanisms, a network-controlled mobility management scheme with policy enforcement on different levels in the RAN architecture, and a distributed handover and admission control mechanism for fast decision polling at different levels of the RAN. The RRM framework is further enhanced with computational intelligence based on fuzzy logic algorithms to enhance the process of handover. The RRM framework has been evaluated in terms of reduced user blocking probabilities.
Embedding Metadata in Computer Graphics for Interaction- Existing techniques, introduction for the digital medium
Authors: Henry Sonnet
Venue:  (2007)

Digital images or 3D visualizations often need to be augmented with information that assists the viewer in understanding what is portrayed or that provides additional knowledge. The data representation of such descriptive metadata is a challenging task since digital media can be stored in various forms each of which provides, if at all, its own specific method for integrating its assigned metadata. The author analyzes existing techniques and introduces new approaches to store a digital medium, for example a digital image, and additional information associated with that medium, for example texts, other images, or auditory data. Illustration Watermarking as a subclass of information hiding emerged as an applicable technique in this regard. Besides the internal representation of descriptive metadata, its visual representation is another aspect addressed in this work. Taking into consideration that display space is limited, techniques for guiding the viewer to those regions associated with the metadata sought and techniques for presenting the metadata are introduced. Many interesting application scenarios illustrate what is envisioned by the author. 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
Modeling Problem Transformations based on Data Complexity
Authors: Ester Bernadó-Mansilla, Núria Macià-Antolínez
Venue: Proceeding of the 2007 conference on Artificial Intelligence Research and Development (2007)

This paper presents a methodology to transform a problem to make it suitable for classification methods, while reducing its complexity so that the classification models extracted are more accurate. The problem is represented by a dataset, where each instance consists of a variable number of descriptors and a class label. We study dataset transformations in order to describe each instance by a single descriptor with its corresponding features and a class label. To analyze the suitability of each transformation, we rely on measures that approximate the geometrical complexity of the dataset. We search for the best transformation minimizing the geometrical complexity. By using complexity measures, we are able to estimate the intrinsic complexity of the dataset without being tied to any particular classifier.
Synthetic Modeling and Policy Simulation of Regional Economic System: A Case Study
Authors: Zhi Yang, Wei Zeng, Hongtao Zhou, Lingru Cai, Guangyong Liu, Qi Fei
Venue: Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part III (2009)

System dynamics and econometrics are proposed for a quantitative analysis of regional economy combined with qualitative analysis. The system dynamic model captures causal relationships of regional economic system, while econometrics is used to estimate equation parameters of system dynamics model. A system dynamics model for the development of regional economy is built by combination of system dynamics and econometrics. Finally, a case study of Shenzhen city gives some policy suggestions according to policy simulation results.
Catalogue of Design Patterns
Authors: L'ubomír Majtás
Venue: Proceeding of the 2006 conference on Knowledge-Based Software Engineering: Proceedings of the Seventh Joint Conference on Knowledge-Based Software Engineering (2006)

The paper deals with development of new catalogue specialized on design patterns. It specifies its content as a summary of extensions to well-known GoF catalogue. In the next part it focuses on representation of collected knowledge. Finally author decided to use technologies provided by Semantic Web and specifies the structure of ontology representing the content of the catalogue.
Fuzzy compensation for nonlinear friction in a hard drive
Authors: Wilaiporn Ngernbaht, Kongpol Areerak, Sarawut Sujitjorn
Venue: Proceedings of the 10th WSEAS international conference on Fuzzy systems (2009)

This paper presents the fuzzy control approach to compensate for nonlinear friction in a hard-disk drive. The dynamic of the read/write head at low-frequency is significantly affected by the nonlinearity and friction caused by the nonlinear damping characteristic of the data flex and the pivot bearing of the voice-coilmotor. Nonlinear dynamic models of the head are given. Design of the fuzzy controller as well as simulation results are presented. The step response of the closed-loop fuzzy control exhibits no overshoot, and settles within 1.6 msec.