ppxscal/embedding_network huggingface dataset:
Input Variable Selection: Mutual Information and Linear Mixing Measures
Authors: Thomas Trappenberg Jie Ouyang Andrew Back
Venue: IEEE Transactions on Knowledge and Data Engineering (2006)

Determining the most appropriate inputs to a model has a significant impact on the performance of the model and associated algorithms for classification, prediction, and data analysis. Previously, we proposed an algorithm ICAIVS which utilizes independent component analysis (ICA) as a preprocessing stage to overcome issues of dependencies between inputs, before the data being passed through to an inout variable selection (IVS) stage. While we demonstrated previously with artificial data that ICA can prevent an overestimation of necessary input variables, we show here that mixing between input variables is common in real-world data sets so that ICA preprocessing is useful in practice. This experimental test is based on new measures introduced in this paper. Furthermore, we extend the implementation of our variable selection scheme to a statistical dependency test based on mutual information and test several algorithms on Gaussian and sub-Gaussian signals. Specifically, we propose a novel method of quantifying linear dependencies using ICA estimates of mixing matrices with a new Linear Mixing Measure (LMM).
Personalization of Web browsing: adaptations to meet the needs of older adults
Authors: L. Hanson, Susan Crayne
Venue: Universal Access in the Information Society (2005)

Despite difficulties in using the Web, older adults are motivated to use it. This paper reports on work underway to ease Web access for this population. Although Web accessibility standards provide specifications that Web content providers must incorporate if their pages are to be accessible, these standards do not guarantee a good experience for all Web users. This paper will discuss user controls that make a number of dynamic adaptations to page presentation and input that can greatly increase the usability of Web pages for older users. The paper will discuss the authors&#x2019; original work on the topic, lessons learned, and usage patterns. Current extensions to that work are also discussed.
Context enabled Multi-CBR based Recommendation Engine for E-commerce
Authors: F'rashant Kumar, Srividya Gopalan, V Sridhar
Venue: Proceedings of the IEEE International Conference on e-Business Engineering (2005)

Electronic commerce is steadily becoming more important in changing the way people buyhell products and services. Case-Based Reasoning (CBR) has been used in various E-Commerce applications for product recommendations. The appropriateness of the use of CBR in E-commerce applications is enhanced by introducing context-sensitive information related to E-commerce as cases in CBR. Usage of context leads to providing the right level of information to users in assisting them to take right decisions quickly. In this paper, we have proposed a Context enabled Multi- CBR approach comprising of two CBRs (User context CBR and Product context CBR) to aid the Recommendation engine (RE) in retrieving appropriate information for E-commerce applications. The RE further derives personalized negotiation and presentation strategies based on contextual information and ontology.
The Effect of the Specification Model on the Complexity of Adding Masking Fault Tolerance
Authors: Sandeep S. Kulkarni, Ali Ebnenasir
Venue: IEEE Transactions on Dependable and Secure Computing (2005)

In this paper, we investigate the effect of the representation of safety specification on the complexity of adding masking fault tolerance to programs¿where, in the presence of faults, the program 1) recovers to states from where it satisfies its (safety and liveness) specification and 2) preserves its safety specification during recovery. Specifically, we concentrate on two approaches for modeling the safety specifications: 1) the bad transition (BT) model, where safety is modeled as a set of bad transitions that should not be executed by the program, and 2) the bad pair (BP) model, where safety is modeled as a set of finite sequences consisting of at most two successive transitions. If the safety specification is specified in the BT model, then it is known that the complexity of automatic addition of masking fault tolerance to high atomicity programs¿where processes can read/write all program variables in an atomic step¿ is polynomial in the state space of the program. However, for the case where one uses the BP model to specify safety specification, we show that the problem of adding masking fault tolerance to high atomicity programs is NP-complete. Therefore, we argue that automated synthesis of fault-tolerant programs is likely to be more successful if one focuses on problems where safety can be represented in the BT model.
Extended Analysis with Reduced Pessimism for Systems with Limited Parallelism
Authors: K. Bletsas, N. C. Audsley
Venue: Proceedings of the 11th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications (2005)

Under limited parallelism, processes competing for a single processor may issue at any time operations on remote co-processors, during which the processor is not idled but granted to other ready processes instead. We reduce the pessimism in existing Worst-case Response Time (WCRT) analysis for such systems by examining temporal patterns of local/remote execution. We extend to multi-CPU variants of the model and offer a WCRT-based feasibility test for Symmetric Multiprocessor (SMP) systems.
Data Driven Image Models through Continuous Joint Alignment
Authors: Erik G. Learned-Miller
Venue: IEEE Transactions on Pattern Analysis and Machine Intelligence (2006)

This paper presents a family of techniques that we call congealing for modeling image classes from data. The idea is to start with a set of images and make them appear as similar as possible by removing variability along the known axes of variation. This technique can be used to eliminate "nuisance” variables such as affine deformations from handwritten digits or unwanted bias fields from magnetic resonance images. In addition to separating and modeling the latent images—i.e., the images without the nuisance variables—we can model the nuisance variables themselves, leading to factorized generative image models. When nuisance variable distributions are shared between classes, one can share the knowledge learned in one task with another task, leading to efficient learning. We demonstrate this process by building a handwritten digit classifier from just a single example of each class. In addition to applications in handwritten character recognition, we describe in detail the application of bias removal from magnetic resonance images. Unlike previous methods, we use a separate, nonparametric model for the intensity values at each pixel. This allows us to leverage the data from the MR images of different patients to remove bias from each other. Only very weak assumptions are made about the distributions of intensity values in the images. In addition to the digit and MR applications, we discuss a number of other uses of congealing and describe experiments about the robustness and consistency of the method.
New centralized automatic vehicle location communications software system under GIS environment: Research Articles
Authors: Omar Al-Bayari, Balqies Sadoun
Venue: International Journal of Communication Systems (2005)

Recent advances in wireless communications and networks have integrated relatively new technologies such as Global Positioning System (GPS), to the popular Global System for Mobile Communication (GSM), second generation cellular systems and the Geographic Information Systems (GIS) technologies. Automatic Vehicle Location (AVL) is based on a combination of GPS, GIS and telecommunication technologies. Automatic Vehicle Tracking systems are more and more used for different purposes, especially those related to tracking one vehicle or a fleet of vehicles.In this work, we introduce a new AVL system, which is based and developed under GIS software environment. The centralized software at the control station offers a new technology of transferring the intelligence of tracking system from the car unit, into the control office PC software. Centralized software will reduce the programming efforts in the car unit and will offer better fleet management. Moreover, the core of our system is based on the objects or the controllers of the GIS software, which reduces dramatically the overall system cost. Our system provides an easy access to change the functions of the system, with great possibility to satisfy the local needs. The design of our software will be presented with an explanation of the new supporting technologies that were to create the system. Finally, our software system has been validated using data from local road networks. Copyright &copy; 2005 John Wiley & Sons, Ltd.
QoS-aware dynamic service composition in ambient intelligence environments
Authors: Sonia Ben Mokhtar, Jinshan Liu, Nikolaos Georgantas, Valérie Issarny
Venue: Proceedings of the 20th IEEE/ACM international Conference on Automated software engineering (2005)

Due to the large success of wireless networks and handheld devices, the ambient intelligence (AmI) paradigm is becoming a reality. One of the most challenging objectives to achieve in AmI environments is to enable a user to perform a task by composing on the fly networked services available at a specific time and place. Towards this goal, we propose a solution based on semantic Web services, and we show how service capabilities described as conversations can be integrated to perform a user task that is also described as a conversation, further meeting the QoS requirements of the user task. Experimental results show that the runtime overhead of our algorithm is reasonable, and further, that QoS-awareness improves its performance.
A hierarchical model of data locality
Authors: Chengliang Zhang, Chen Ding, Mitsunori Ogihara, Yutao Zhong, Youfeng Wu
Venue: Conference record of the 33rd ACM SIGPLAN-SIGACT symposium on Principles of programming languages (2006)

In POPL 2002, Petrank and Rawitz showed a universal result---finding optimal data placement is not only NP-hard but also impossible to approximate within a constant factor if P ≠ NP. Here we study a recently published concept called reference affinity, which characterizes a group of data that are always accessed together in computation. On the theoretical side, we give the complexity for finding reference affinity in program traces, using a novel reduction that converts the notion of distance into satisfiability. We also prove that reference affinity automatically captures the hierarchical locality in divide-and-conquer computations including matrix solvers and N-body simulation. The proof establishes formal links between computation patterns in time and locality relations in space.On the practical side, we show that efficient heuristics exist. In particular, we present a sampling method and show that it is more effective than the previously published technique, especially for data that are often but not always accessed together. We show the effect on generated and real traces. These theoretical and empirical results demonstrate that effective data placement is still attainable in general-purpose programs because common (albeit not all) locality patterns can be precisely modeled and efficiently analyzed.
Segmenting documents by stylistic character
Authors: Neil Graham, Graeme Hirst, Bhaskara Marthi
Venue: Natural Language Engineering (2005)

As part of a larger project to develop an aid for writers that would help to eliminate stylistic inconsistencies within a document, we experimented with neural networks to find the points in a text at which its stylistic character changes. Our best results, well above baseline, were achieved with time-delay networks that used features related to the author's syntactic preferences, whereas low-level and vocabulary-based features were not found to be useful. An alternative approach with character bigrams was not successful.
Power and code management in wireless networks
Authors: Ming T. Liu
Venue:  (2005)

Among different wireless technologies, wireless ad hoc networks and cellular networks account for a large part of wireless communications. In this work, we take an extensive study at the management of the two of very important resources in both wireless ad hoc networks and cellular networks: power and code (bandwidth). In the first part, we focus on the power management in IEEE 802.11 ad hoc networks. We first aim at the mismatch between the power management protocol and the ever-increasing transfer rate. We propose modifications on the power management operations of IEEE 802.11 which introduce very little overhead but bring a big boost on the performance in both power efficiency and data throughput by combining a scheduling algorithm with the power management. Then, we concentrate on the new challenges faced by the power and synchronization protocols when pushing the IEEE 802.11 ad hoc mode into the multi-hop environment. We study the relationship between clock synchronization and power management in Mobile Multi-hop Ad Hoc Network (MANET). After reaching the conclusion that clock synchronization is vital for not only efficient power management, but many other network operations as well, we present a protocol to generate a globally synchronous system from synchronized sub-networks. We discuss the correctness of the protocol, and show the power efficiency brought by such a synchronous system in simulations. Lastly, we present a framework, which takes advantage both of the two main approaches in energy conservation, i.e. power management and power control, to maximize power-saving. Because the goals that each scheme seeks contradict each other, we study the balance and the trade-off between them, and use them as the guideline on building our framework. In the second part of this work, we shift to the code (bandwidth) assignment for multimedia traffic in Code Division Multiple Access (CDMA) networks. We propose several algorithms to handle the jitters of compressed video transmissions, and try to get a better playback quality while reducing the effects which video traffic has on other users in the system. Our simulations show the improved performance from those algorithms, especially at heavy traffic scenarios.
Using fuzzy set theory and scale-free network properties to relate MEDLINE terms
Authors: Jonathan D. Wren
Venue: Soft Computing - A Fusion of Foundations, Methodologies and Applications (2006)

Automated construction and annotation of biological networks is becoming increasingly important in bioinformatics as the amount of biological data increases. At the center of this are metrics required for relating biological entities such as genes, diseases, signaling molecules and chemical compounds. Co-occurrence of terms within abstracts is widely used to establish tentative relationships because it is easy to use, implement, understand, and is reasonably accurate. However, it is also very imprecise &#x2013; the cutoffs for how many co-occurrences of terms are necessary to establish a relationship is arbitrary and the nature of the relationship is generic. Since the frequency of co-occurrence for terms usually follows a scale-free distribution, this property can be exploited to define degree of membership in fuzzy sets. Beginning with a set of co-occurrences for any biomedical term (or its synonyms), relations are defined by the overlap of sets, normalizing by the area under the curve that the two sets share. The ability of this method to rank the relative specificity of biological relationships is tested by comparing cumulative term co-occurrences within 7.5 million MEDLINE abstracts with focused summaries of gene function and disease association within LocusLink. On average, the fuzzy set ranking (FSR) was in the top 0.6% of all potential associations, showing a good correlation between domain overlap and the biological association between two terms.
The emotional hearing aid: an assistive tool for children with Asperger syndrome
Authors: R. el Kaliouby, P. Robinson
Venue: Universal Access in the Information Society (2005)

People diagnosed along the autistic spectrum often have difficulties interacting with others in natural social environments. The emotional hearing aid is a portable assistive computer-based technology designed to help children with Asperger syndrome read and respond to the facial expressions of people they interact with. The tool implements the two principal elements that constitute one&#x2019;s ability to empathize with others: the ability to identify a person&#x2019;s mental state, a process known as mind-reading or theory of mind, and the ability to react appropriately to it (known as sympathizing). An automated mind-reading system attributes a mental state to a person by observing the behaviour of that person in real-time. Then the reaction advisor suggests to the user of the emotional hearing an appropriate reaction to the recognized mental state. This paper describes progress in the development and validation of the emotional hearing aid on two fronts. First, the implementation of the reaction advisor is described, showing how it takes into account the persistence, intensity and degree of confidence of a mental state inference. Second, the paper presents an experimental evaluation of the automated mind-reading system on six classes of complex mental states. In light of this progress, the paper concludes with a discussion of the challenges that still need to be addressed in developing and validating the emotional hearing aid.
A Generalized Framework for Network Component Analysis
Authors: Riccardo Boscolo, Chiara Sabatti, James C. Liao, Vwani P. Roychowdhury
Venue: IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB) (2005)

The authors recently introduced a framework, named Network Component Analysis (NCA), for the reconstruction of the dynamics of transcriptional regulators' activities from gene expression assays. The original formulation had certain shortcomings that limited NCA's application to a wide class of network dynamics reconstruction problems, either because of limitations in the sample size or because of the stringent requirements imposed by the set of identifiability conditions. In addition, the performance characteristics of the method for various levels of data noise or in the presence of model inaccuracies were never investigated. In this article, the following aspects of NCA have been addressed, resulting in a set of extensions to the original framework: 1) The sufficient conditions on the a priori connectivity information (required for successful reconstructions via NCA) are made less stringent, allowing easier verification of whether a network topology is identifiable, as well as extending the class of identifiable systems. Such a result is accomplished by introducing a set of identifiability requirements that can be directly tested on the regulatory architecture, rather than on specific instances of the system matrix. 2) The two-stage least square iterative procedure used in NCA is proven to identify stationary points of the likelihood function, under Gaussian noise assumption, thus reinforcing the statistical foundations of the method. 3) A framework for the simultaneous reconstruction of multiple regulatory subnetworks is introduced, thus overcoming one of the critical limitations of the original formulation of the decomposition, for example, occurring for poorly sampled data (typical of microarray experiments). A set of monte carlo simulations we conducted with synthetic data suggests that the approach is indeed capable of accurately reconstructing regulatory signals when these are the input of large-scale networks that satisfy the suggested identifiability criteria, even under fairly noisy conditions. The sensitivity of the reconstructed signals to inaccuracies in the hypothesized network topology is also investigated. We demonstrate the feasibility of our approach for the simultaneous reconstruction of multiple regulatory subnetworks from the same data set with a successful application of the technique to gene expression measurements of the bacterium Escherichia coli.
Ambient functionnality: human interfaces for the digital life
Authors: Francis Jutand
Venue: Proceedings of the 2005 joint conference on Smart objects and ambient intelligence: innovative context-aware services: usages and technologies (2005)

How to use the power of digital technologies to create new contents, to better communicate, and to access and produce knowledges. First efforts have been done on ubiquity and language processing. Progresses in process on sensitive and perceptive interfaces open the way to a kind of a new information and communication exented human environment, that is going to be more and more entangled with the development of new abilities to exchange, cooperate, and learn. Beyond the revolution of internet, what are going to be the most important evolutions based on new ambient functionnalities, affordable, acceptable and disruptive for the future. Combining technical, usage and prospective points of views, the "target speak" is aiming at bringing some materials to open research tracks and experiments in that field. 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
Document Ranking by Layout Relevance
Authors: May Huang, Daniel DeMenthon, David Doermann, Lynn Golebiowski, Booz Allen Hamilton
Venue: Proceedings of the Eighth International Conference on Document Analysis and Recognition (2005)

This paper describes the development of a new document ranking system based on layout similarity. The user has a need represented by a set of "wanted" documents, and the system ranks documents in the collection according to this need. Rather than performing complete document analysis, the system extracts text lines, and models layouts as relationships between pairs of these lines. This paper explores three novel feature sets to support scoring in large document collections. First, pairs of lines are used to form quadrilaterals, which are represented by their turning functions. A non- Euclidean distance is used to measure similarity. Second, the quadrilaterals are represented by 5D Euclidean vectors, and third, each line is represented by a 5D Euclidean vector. We compare the classification performance and computation speed of these three feature sets using a large database of diverse documents including forms, academic papers and handwritten pages in English and Arabic. The approach using quadrilaterals and turning functions produces slightly better results, but the approach using vectors to represent text lines is much faster for large document databases.
Integrating Notion of Agency and Semantics in Information Retrieval: An intelligent multi-agent model
Authors: Tanveer J. Siddiqui, U. S. Tiwary
Venue: Proceedings of the 5th International Conference on Intelligent Systems Design and Applications (2005)

We present an intelligent information retrieval model based on multi-agent paradigm and conceptual graphs. The growing amount of on-line information and its dynamic nature forces us to reconsider existing passive approaches for information retrieval. Because of this ever-growing size of information sources the burden of retrieving information can not be simply left on users. We attempt to handle this problem through software agents. Our model makes use of a user modeling agent (UMA), a facilitator and integrator(FACINT) module and a number of retrieval agents. UMA is responsible for creating a user profile. Actual retrieval is done by retrieval agents. FACINT is responsible for controlling and coordinating activities of various agents. It also does final ranking of the documents based on conceptual graph (CG) representation of documents. The use of CG brings semantics in making relevance judgment resulting in improved ranking. The model proposed by us is simple, efficient, scalable and can work actively as well as passively.