ppxscal/embedding_network huggingface dataset:
Combining segmental semi-Markov models with neural networks for protein secondary structure prediction
Authors: Niranjan P. Bidargaddi, Madhu Chetty, Joarder Kamruzzaman
Venue: Neurocomputing (2009)

Motivation: Predicting the secondary structure of proteins from a primary sequence alone has been variously approached from either a classification or a generative model perspective. The most prominent classification methods have used neural networks, which involves mappings from a local window of residues in the sequence to the structural state of the central residue in the window, thus capturing the local interactions effectively. However, they fail to capture distant interactions among residues. The generative models based on Bayesian segmentation capture sequence structure relationships using generalized hidden Markov models with explicit state duration. They capture non-local interactions through a joint sequence-structure probability distribution based on structural segments. In this paper, we investigate a combined architecture of Bayesian segmentation at the first stage and neural network at the second stage which captures both local and non-local correlation, to increase the single sequence prediction accuracy. The combined architecture is further enhanced by using neural network optimization and ensemble techniques. Results: The proposed architecture has been built and tested on two widely studied databases comprising 480 and 608 protein sequences, respectively. It achieved accuracies of above 71%, which is comparable to the highest accuracies reported so far for single sequence methods, without using the evolutionary information provided by multiple sequence alignments. The required data sets and program codes are available at http://www.gippsland.monash.edu.au/research/publish/neurocomputing.zip.
Optimal Trajectory Generation for Walking Up and Down a Staircase with a Biped Robot Using Genetic Algorithm (GA)
Authors: Eunsu Kim, Manseok Kim, Jong-Wook Kim
Venue: Proceedings of the FIRA RoboWorld Congress 2009 on Advances in Robotics (2009)

In this paper, a humanoid is simulated and implemented to walk up and down a staircase using the blending polynomial and genetic algorithm (GA). Both ascending and descending a staircase are scheduled by four steps. Each step mimics natural gait of human being and is easy to analyze and implement. Optimal trajectories of ten motors in a lower extremity of a humanoid are rigorously computed to simultaneously satisfy stability condition, walking constraints, and energy efficiency requirements. As an optimization method, GA is applied to search optimal trajectory parameters in blending polynomials. The feasibility of this approach will be validated by simulation with a small humanoid robot.
Mental states as multi-context systems
Authors: Aldo Franco Dragoni
Venue: Annals of Mathematics and Artificial Intelligence (2008)

Although Belief-Desire-Intention (BDI) agents have been deeply investigated from both a theoretical and a pragmatic perspective, less attention has been paid to the inherent recursive structure of mental states, which plays an essential role when modelling high level interaction between intelligent agents. This paper tries to capture this property by introducing a multi-context approach to the representation of mental states. A semantics for multi-context formalisms is provided based on the definition of "mental structure", which is a hierarchical lattice of triangular modules <x,B,D>, where the component x represents the agent x's mental state as a whole, while B and D represent specifically x's beliefs and x's desires. If other mental attitudes, as intention and commitment, are to be considers as primitives, then they can be embodied in the basic module, otherwise they can be represented in terms of beliefs and desires. The old notion of clause is rediscovered in order to facilitate the heavy automated theorem-proving necessary to exploit the potentiality of the formalism for the intelligent interaction with the external environment. The main advantages of this approach are the support for "unconsciousness" and the fact that inferences themselves can be modelled as mental attitudes. Some advanced dynamics of mental states, as the abductive revision of mental states after the reception of a communication, will easily be applied over this formalism.
Semantics of a runtime adaptable transaction manager
Authors: Florian Irmert, Frank Lauterwald, Christoph P. Neumann, Michael Daum, Richard Lenz, Klaus Meyer-Wegener
Venue: Proceedings of the 2009 International Database Engineering & Applications Symposium (2009)

Database Management Systems (DBMSs) that can be tailored to specific requirements offer the potential to improve reliability and maintainability and simultaneously the ability to reduce the footprint of the code base. If the requirements of an application change during runtime the DBMS should be adapted without a shutdown. Runtime-adaptation is a new and promising research direction to dynamically change the behavior of a DBMS. Especially the adaptation of the Transaction Manager (TM) states a challenge. In this paper, we present the session semantics of a runtime-adaptable TM. We define preliminaries and assumptions to activate the TM during sessions from a conceptual point of view. The advantages and disadvanteges of different approaches are discussed, especially regarding the occurence of ANSI SQL phenomena. From a technical point of view, we define requirements for the architecture of the TM and the DBMS that arose in our prototype.
Letter-to-sound conversion for Urdu text-to-speech system
Authors: Sarmad Hussain
Venue: Proceedings of the Workshop on Computational Approaches to Arabic Script-based Languages (2004)

Urdu is spoken by more than 100 million people across a score countries and is the national language of Pakistan (http://www.ethnologue.com). There is a great need for developing a text-to-speech system for Urdu because this population has low literacy rate and therefore speech interface would greatly assist in providing them access to information. One of the significant parts of a text-to-speech system is a natural language processor which takes textual input and converts it into an annotated phonetic string. To enable this, it is necessary to develop models which map textual input onto phonetic content. These models may be very complex for various languages having unpredictable behaviour (e.g. English), but Urdu shows a relatively regular behaviour and thus Urdu pronunciation may be modelled from Urdu text by defining fairly regular rules. These rules have been identified and explained in this paper.
Augmented Cognition as Rehabilitation: Facilitating Neuroplasticity?
Authors: Michael Feuerstein, Gina Luff, Mark Peugeot, Miki Moskowitz, Briana Todd
Venue: Proceedings of the 5th International Conference on Foundations of Augmented Cognition. Neuroergonomics and Operational Neuroscience: Held as Part of HCI International 2009 (2009)

Different types of brain injury are associated with deficits in working memory, executive functioning, and information processing speed, which can impact performance at work. Augmented Cognition (AugCog), a technology developed to improve human performance in complex tasks, may have potential for optimizing cognitive functioning in the context of work for those with mild to moderate cognitive deficits. AugCog is a way to accommodate or augment function thus improving the performance of the operator. This approach may facilitate neuroplasticity that can occur following injury to the brain. The authors will provide the rationale, operational structure, and potential application to occupational rehabilitation.
An ontology-based view on prepositional senses
Authors: Tine Lassen
Venue: Proceedings of the Third ACL-SIGSEM Workshop on Prepositions (2006)

This paper describes ongoing work, aimed at producing a lexicon of prepositions, i.e. relations denoted by prepositions, to be used for information retrieval purposes. The work is ontology based, which for this project means that the ontological types of the arguments of the preposition are considered, rather than the word forms. Thus, sense distinctions are made based on ontological constraints on the arguments.
Optimal Layer-Based Unequal Error Protection for Robust JPEG 2000 Images and Video Transmission over Wireless Channels
Authors: Max Agueh, Henoc Soude
Venue: Proceedings of the 2009 First International Conference on Advances in Multimedia (2009)

In this paper we propose an optimal layer-oriented Unequal Error Protection Forward Error Correction rate allocation scheme for efficient transmission of JPEG 2000 codestreams over wireless channels. The main advantages of the proposed scheme are its optimality, its compliance to Wireless JPEG 2000 (the 11th part of JPEG 2000 standard) and its low time consumption. We demonstrate that our proposed scheme outperforms the layer oriented FEC scheme proposed by Z. Guo et al and other existing layer based FEC schemes. We also show that, due to its low run time, our layer based scheme is a good candidate for highly time constrained motion JPEG 2000 video streaming applications, thus, in this sense, its overcomes the limitation of optimal packet oriented FEC rate allocation scheme. We then validate the effectiveness of our proposed layer oriented scheme with a Wireless Motion JPEG 2000 client/server application.
Image Retrieval Algorithm Based on Texture and Color Features
Authors: Yu Cai-xiang, Qiu Shu-bo
Venue: Proceedings of the 2009 WASE International Conference on Information Engineering - Volume 01 (2009)

A novel image retrieval algorithm based on texture and color feathers was proposed. Firstly, the image was divided into non-overlapped blocks with equal size, and every pixel was given a new value (0 or 1) according to different color, then do the second division to the whole image and coding new blocks, counting the probability of every code and primary color. Finally, texture and color feathers method was applied in image retrieval. Experimental results show that the proposed algorithm has reasonable and robust performance and is more effective.
Improving User Control with Minimum Involvement in User-Guided Segmentation by Image Foresting Transform
Authors: T. V. Spina, Javier A. Montoya-Zegarra, P. A. Miranda, A. X. Falcão
Venue: Proceedings of the 13th International Conference on Computer Analysis of Images and Patterns (2009)

The image foresting transform (IFT) can divide an image into object and background, each represented by one optimum-path forest rooted at internal and external markers selected by the user. We have considerably reduced the number of markers (user involvement) by separating object enhancement from its extraction. However, the user had no guidance about effective marker location during extraction, losing segmentation control. Now, we pre-segment the image automatically into a few regions. The regions inside the object are selected and merged from internal markers. Regions with object and background pixels are further divided by IFT. This provides more user control with minimum involvement, as validated on two public datasets. 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
Chinese Automatic Text Summarization Based on Keyword Extraction
Authors: Xiao-yu Jiang
Venue: Proceedings of the 2009 First International Workshop on Database Technology and Applications (2009)

In order to over the shortcoming of the incomprehensive of summarization, a new lexical-chain-based keywords extraction and automatic summarization algorithm from Chinese texts based on the unknown word recognition using co-occurrence of neighbor words is proposed in this paper, and an algorithm for constructing lexical chains based on Hownet knowledge database is given in the method, lexical chains are firstly constructing by calculating the semantic similarity between terms, then keywords are extracted and the importance of each sentence is calculated according to the lexical chain's intensity, the terms' entropy and position. The experimental results show that the summarization generated by the improved algorithm gets better performance than other methods both in recall and precision.
On reachability, relevance, and resolution in the planning as satisfiability approach
Authors: Ronen I. Brafman
Venue: Journal of Artificial Intelligence Research (2001)

In recent years, there is a growing awareness of the importance of reachability and relevance-based pruning techniques for planning, but little work specifically targets these techniques. In this paper, we compare the ability of two classes of algorithms to propagate and discover reachability and relevance constraints in classical planning problems. The first class of algorithms operates on SAT encoded planning problems obtained using the linear and GRAPHPLAN encoding schemes. It applies unit-propagation and more general resolution steps (involving larger clauses) to these plan encodings. The second class operates at the plan level and contains two families of pruning algorithms: Reachable-k and Relevant-k . Reachable-k provides a coherent description of a number of existing forward pruning techniques used in numerous algorithms, while Relevant-k captures different grades of backward pruning. Our results shed light on the ability of different plan-encoding schemes to propagate information forward and backward and on the relative merit of plan-level and SAT-level pruning methods.
Managing Diversity on an AIS That Solves 3-Colouring Problems
Authors: María-Cristina Riff, Elizabeth Montero
Venue: Proceedings of the 8th International Conference on Artificial Immune Systems (2009)

Constraint Directed Network Artificial Immune System is an artificial immune algorithm, recently proposed, to solve constraint satisfaction problems. The algorithm has shown to be able to solve hard instances. However, some problems are still unsolved using this approach. In this paper, we propose a method to improve the search done by the algorithm. Our method can be included in other immune algorithms which manage constraints. The tests are carried out to solve very hard instances randomly generated of 3-colouring problems. The results show that using our method, the algorithm is able to solve more problems in less execution time.
Delay-Dependent Output Feedback Passive Control for Time-Delayed System
Authors: Gui-Fang Li, Sheng-guo Huang
Venue: Proceedings of the 2009 International Conference on Measuring Technology and Mechatronics Automation - Volume 01 (2009)

This paper considers the problem of output feedback passive control for delayed systems with time-varying delay. We develop a dynamic output feedback controller design method and propose such controllers that guarantee the closed-loop system be strongly stable with strictly passive. Sufficient conditions for the solvability of the problem are derived in terms of linear matrix inequalities (LMIs). The sufficient conditions are delay dependent. Also, a procedure of constructing such controllers from the solutions of LMIs is given.
Segmentation of Touching Cell Nuclei Using a Two-Stage Graph Cut Model
Authors: Ondřej Daněk, Pavel Matula, Carlos Ortiz-De-Solórzano, Arrate Muñoz-Barrutia, Martin Maška, Michal Kozubek
Venue: Proceedings of the 16th Scandinavian Conference on Image Analysis (2009)

Methods based on combinatorial graph cut algorithms received a lot of attention in the recent years for their robustness as well as reasonable computational demands. These methods are built upon an underlying Maximum a Posteriori estimation of Markov Random Fields and are suitable to solve accurately many different problems in image analysis, including image segmentation. In this paper we present a two-stage graph cut based model for segmentation of touching cell nuclei in fluorescence microscopy images. In the first stage voxels with very high probability of being foreground or background are found and separated by a boundary with a minimal geodesic length. In the second stage the obtained clusters are split into isolated cells by combining image gradient information and incorporated a priori knowledge about the shape of the nuclei. Moreover, these two qualities can be easily balanced using a single user parameter. Preliminary tests on real data show promising results of the method.
A Study on Computing Resource Partition for Increasing Efficiency of Grid System
Authors: Changsun Lim, Seongjin Ahn, Jinwook Chung
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)

This study deals with resolving the indefinite wait forced on normal resource reservations caused by the presence of priorities between normal resource reservations and advanced resource reservations. The algorithm we propose modifies the algorithm of the PLUS system that uses the GT4 toolkit and suggests improving flexibility by partitioning the normal reservation sector from the advanced reservation sector. With this partition, we are able to offer a more guaranteed use of normal resources. After we have discovered the specifications regarding the ratio of normal jobs to advanced reservations and guaranteeing advanced reservations, further studies will need to find ways to promote the efficiency of resource use.
Without a 'doubt'?: unsupervised discovery of downward-entailing operators
Authors: Cristian Danescu-Niculescu-Mizil, Lillian Lee, Richard Ducott
Venue: Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics (2009)

An important part of textual inference is making deductions involving monotonicity, that is, determining whether a given assertion entails restrictions or relaxations of that assertion. For instance, the statement 'We <u>know</u> the epidemic spread quickly' does not entail 'We know the epidemic spread quickly via fleas', but 'We <u>doubt</u> the epidemic spread quickly' entails 'We doubt the epidemic spread quickly via fleas'. Here, we present the first algorithm for the challenging lexical-semantics problem of learning linguistic constructions that, like 'doubt', are downward entailing (DE). Our algorithm is unsupervised, resource-lean, and effective, accurately recovering many DE operators that are missing from the hand-constructed lists that textual-inference systems currently use.
Dynamic Supplying Desired Web Service for E-Business
Authors: Xuejuan Huang, Xinmeng Chen, Jiazhen Xu, Jie Yang
Venue: Proceedings of the 2009 Second International Symposium on Electronic Commerce and Security - Volume 01 (2009)

with the number of available web services growing large, supplying the appropriate services for E-business becomes crucial. Dynamic change of customer requirement and available service space challenges the service discovery and selection process. In this paper, we propose a web service dynamic supplying framework, called Web Service Community (WSC), to facilitate invocation of one single service or the composition of several services to complete various business tasks. The prominent features of web service description, discovery and selection in the circumstance of WSC are depicted based on the explanation of the structure of WSC. The desired web services are dynamically discovered and selected by carrying out an efficient service supplying mechanism aimed at maintenance of demand-supply balance on the condition that the utmost satisfaction of customers’ requirements is achieved. The invocation process of single service or composition of several services to support E-business is also presented in the paper.
Modeling and Simulation of 3-RRRT Parallel Manipulator Based on MALTAB with SimMechanics
Authors: Li Hanchen, Zhao Xinhua, Xun Haoliang
Venue: Proceedings of the 2009 International Forum on Information Technology and Applications - Volume 03 (2009)

Based on the SimMechanics Toolbox of MATLAB, this paper introduces a method of simulation in researching 3-RRRT parallel manipulator. Through deeply studying fuzzy control theory, for overcoming the shortcomings and inadequacies of the PID control algorithm, a fuzzy adaptive supervisory algorithm is presented in this paper. The paper discusses how to use it to optimize the conventional PID controller, and to achieve more excellent control results. Firstly, a 3-RRRT parallel manipulator model is established by the SimMechanics in Matlab. Secondly, the manipulator's fuzzy adaptive supervisory controller is built for the model. A simulation experiment is conducted to test the effect of the trajectory tracking through Matlab/SimMechanics. The simulation results demonstrate that the 3-RRRT parallel manipulator realizes the trajectory tracking with very good robustness to the parameter auto-adapted.
A note on variational Bayesian factor analysis
Authors: Jian-hua Zhao, Philip L. H. Yu
Venue: Neural Networks (2009)

Existing works on variational bayesian (VB) treatment for factor analysis (FA) model such as [Ghahramani, Z., & Beal, M. (2000). Variational inference for Bayesian mixture of factor analysers. In Advances in neural information proceeding systems. Cambridge, MA: MIT Press; Nielsen, F. B. (2004). Variational approach to factor analysis and related models. Master's thesis, The Institute of Informatics and Mathematical Modelling, Technical University of Denmark.] are found theoretically and empirically to suffer two problems: @? penalize the model more heavily than BIC and @? perform unsatisfactorily in low noise cases as redundant factors can not be effectively suppressed. A novel VB treatment is proposed in this paper to resolve the two problems and a simulation study is conducted to testify its improved performance over existing treatments.
Design and Realization of Traffic Scene Editor Based on XML Framework
Authors: Hui Zhang, Chaozhong Wu, Xianqiao Chen, Song Gao, Xinping Yan
Venue: Proceedings of the 2009 First International Workshop on Database Technology and Applications (2009)

Vehicle driving simulator has been popularly used for researching on traffic safety. Modeling the traffic scene is one of the key technologies. In this study, traffic scene editor is proposed to solve this problem by editing the parameter of each traffic element. The five important functions of it are also designed. By analyzing the advantage of XML structure; XML is suggest to storage the edit data, and the XML framework of editor was designed based on the traffic chrematistics. As an example, traffic flow was used to explain how the traffic scene editor works with XML. Then make a comparison of the XML data and non-XML data when rendering the virtual scene. The conclusion is that, the data storaged by XML framework can be rapidly loaded and has more actual rendering effect.
A Practical Edit-Distance Model for RNA Secondary-Structure Comparison
Authors: Chan-Shuo Wu, Guan-Shieng Huang
Venue: Proceedings of the 2009 Ninth IEEE International Conference on Bioinformatics and Bioengineering (2009)

We point out the importance to incorporate affinegappenalties in RNA secondary-structure comparison. Twonotions of affine-gap penalties, one for sequences and the otherfor structures, are developed. A model from Jiang et al. in [JComput Biol, 2002, 9, (2), pp. 371–388] is extended to allowthis facility, and a polynomial-time algorithm is provided inthis paper. Experimental results in this paper revealed that ournew model generates more accurate and biological meaningfulalignments than several existing algorithms.