ppxscal/embedding_network huggingface dataset:
Bayesian model-based approaches with mcmc computation to some bioinformatics problems
Authors: Kyounghwa Bae
Venue:  (2005)

Bioinformatics applications can address the transfer of information at several stages of the central dogma of molecular biology, including transcription and translation. This dissertation focuses on using Bayesian models to interpret biological data in bioinformatics, using Markov chain Monte Carlo (MCMC) for the inference method. First, we use our approach to interpret data at the transcription level. We propose a two-level hierarchical Bayesian model for variable selection on cDNA Microarray data. cDNA Microarray quantifies mRNA levels of a gene simultaneously so has thousands of genes in one sample. By observing the expression patterns of genes under various treatment conditions, important clues about gene function can be obtained. We consider a multivariate Bayesian regression model and assign priors that favor sparseness in terms of number of variables (genes) used. We introduce the use of different priors to promote different degrees of sparseness using a unified two-level hierarchical Bayesian model. Second, we apply our method to a problem related to the translation level. We develop hidden Markov models to model linker/non-linker sequence regions in a protein sequence. We use a linker index to exploit differences in amino acid composition between regions from sequence information alone. A goal of protein structure prediction is to take an amino acid sequence (represented as a sequence of letters) and predict its tertiary structure. The identification of linker regions in a protein sequence is valuable in predicting the three-dimensional structure. Because of the complexities of both models encountered in practice, we employ the Markov chain Monte Carlo method (MCMC), particularly Gibbs sampling (Gelfand and Smith, 1990) for the inference of the parameter estimation.
On the random 2-stage minimum spanning tree
Authors: Abraham D. Flaxman, Alan Frieze, Michael Krivelevich
Venue: Random Structures Algorithms (2006)

It is known [A. M. Frieze, Discrete Appl Math 10 (1985), 47&ndash;56] that if the edge costs of the complete graph Kn are independent random variables, uniformly distributed between 0 and 1, then the expected cost of the minimum spanning tree is asymptotically equal to $\zeta(3)=\sum_{i=1}^{\infty}i^{-3}$. Here we consider the following stochastic two-stage version of this optimization problem. There are two sets of edge costs cM: E &rarr; &Ropf; and cT: E &rarr; &Ropf;, called Monday's prices and Tuesday's prices, respectively. For each edge e, both costs cM(e) and cT(e) are independent random variables, uniformly distributed in [0, 1]. The Monday costs are revealed first. The algorithm has to decide on Monday for each edge e whether to buy it at Monday's price cM(e), or to wait until its Tuesday price cT(e) appears. The set of edges XM bought on Monday is then completed by the set of edges XT bought on Tuesday to form a spanning tree. If both Monday's and Tuesday's prices were revealed simultaneously, then the optimal solution would have expected cost &zeta;(3)&#x002F;2 + o(1). We show that, in the case of two-stage optimization, the expected value of the optimal cost exceeds &zeta;(3)&#x002F;2 by an absolute constant ε > 0. We also consider a threshold heuristic, where the algorithm buys on Monday only edges of cost less than &alpha; and completes them on Tuesday in an optimal way, and show that the optimal choice for &alpha; is &alpha; = 1&#x002F;n with the expected cost &zeta;(3) - 1&#x002F;2 + o(1). The threshold heuristic is shown to be sub-optimal. Finally we discuss the directed version of the problem, where the task is to construct a spanning out-arborescence rooted at a fixed vertex r, and show, somewhat surprisingly, that in this case a simple variant of the threshold heuristic gives the asymptotically optimal value 1 - 1&#x002F;e + o(1). &copy; 2005 Wiley Periodicals, Inc. Random Struct. Alg., 2006
The class imbalance problem in learning classifier systems: a preliminary study
Authors: Albert Orriols, Ester Bernadó-Mansilla
Venue: Proceedings of the 2005 workshops on Genetic and evolutionary computation (2005)

The class imbalance problem has been said recently to hinder the performance of learning systems. In fact, many of them are designed with the assumption of well-balance datasets. However, it is very common to find higher presence of one of the classes in real classification problems. The aim of this paper is to make a preliminary analysis on the effect of the class imbalance problem in learning classifier systems. Particularly we focus our study on UCS, a supervised version of XCS classifier system. We analyze UCS's behavior on unbalanced datasets and find that UCS is sensitive to high levels of class imbalance. We study strategies for dealing with class imbalances, acting either at the sampling level or at the classifier system's level.
Distributed virtual computers (DVC): simplifying the development of high performance Grid applications
Authors: N. Taesombut, A. A. Chien
Venue: Proceedings of the 2004 IEEE International Symposium on Cluster Computing and the Grid (2004)

The distributed virtual computer (DVC) is a computing environment, which simplifies the development and execution of distributed applications on computational Grids. DVC provides a simple set of abstractions to simplify application management of naming, security, communication, and resource, easing use of highly dynamic and heterogeneous resource environments. These abstractions enable complex collections of Grid resources to be used in a fashion similar to private user or workgroup resources. The DVC model is attractive for lambda-Grids with circuit-switched optical networks, providing a structure for exploiting unique communication and security properties. Examples of DVC include virtual clusters and virtual heterogeneous resource collections. We introduce the concept of a DVC, its system structure and mechanisms. We discuss the potential benefits of DVC for application programmers.
Markovian Modeling and Analysis of Internet Worm Propagation
Authors: Hiroyuki Okamura, Hisashi Kobayashi, Tadashi Dohi
Venue: Proceedings of the 16th IEEE International Symposium on Software Reliability Engineering (2005)

Propagation of Internet worms is a serious problem in our highly information oriented society. In this paper, we propose a stochastic model for Internet worm propagation to evaluate its dependability measures quantitatively. More precisely, the deterministic kill-signal model is reformulated based on a continuous-time Markov chain. We define some dependability measures and derive the recursive computation algorithms to assess them. In numerical experiments, we investigate the behavior of actual Internet worms with real infection data and characterize their propagation.
Multi-Thread Based Synchronization of Locomotion Control in Snake Robots
Authors: Laxmisha Rai, Soon Ju Kang
Venue: Proceedings of the 11th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications (2005)

In this paper, we present an approach to control the locomotion of snake robot with concurrent programming model constructed using threads and semaphores. The multi-thread based concurrent programming model adds the flexibility to design and synchronize the movement of snake robots as compared with microcontroller and mechanical based approaches. We have designed a physical snake robot using LEGO sensors and actuator blocks and the wave motion of the snake robot is generated by multi-thread based concurrent programming under RT-Linux. The different robot movements in a desired direction along with different types of snake movements are achieved using angle sensors.
Educational Video Understanding: Mapping Handwritten Text to Textbook Chapters
Authors: Lijun Tang, John R. Kender
Venue: Proceedings of the Eighth International Conference on Document Analysis and Recognition (2005)

Handwritten text frames appear frequently in educational videos and can be used as an important cue for semantic analysis of educational videos. We detect text frames using a motion pattern analyzing algorithm. Then we extract binary handwritten word images from the text frames in various visual formats: handwritten slides, electronic slides, handwriting on chalkboard, etc. We propose a handwritten word recognition method, using combined dynamic programming stroke-based character segmentation with optimal statistical handwritten character recognition. In parallel, we construct a small vocabulary from topic words taken from table-of-contents of course materials such as the course textbook. We use the handwritten word recognition results to query this table-of-contents structure, implemented as latent semantic analysis matrix operations. We are able to spot the most likely discussed chapters and topic words for each frame. We evaluate the overall approach on 12 videos of two courses, and the results are encouraging.
Power-aware bandwidth and stereo-image scalable audio decoding
Authors: Wendong Huang, Ye Wang, Samarjit Chakraborty
Venue: Proceedings of the 13th annual ACM international conference on Multimedia (2005)

We propose a new workload-scalable audio decoding scheme that would enable users to control the tradeoff between playback quality and power consumption in battery-powered portable audio players. Our objective is to give users a control at the decoder side, similar to the Long Play (LP) recording mode at the encoder side in many media recording devices. The main contribution of this paper is a proposal for a Bandwidth and Stereo-image Scalable (BSS) decoding scheme for single-layer audio formats such as MP3. The proposed scheme is based on an analysis of the perceptual relevance of different audio components in the compressed bitstream. The bandwidth and stereo-image scalability directly translates into scalability in terms of the computational workload generated by the decoder. This can be exploited by a voltage/frequency scalable processor to save energy and prolong the battery life.
Tangible weather channel
Authors: Yu-Cheng Hsu
Venue: Proceedings of the 13th annual ACM international conference on Multimedia (2005)

Tangible Weather Channel is an interactive sculptural apparatus that enables the participant to type in the remote location of a loved one and interprets its real-time weather information as a way of creating an emotional connection. Rather than employing traditional graphical representation, Tangible Weather Channel renders weather information into a multi-sensory experience by using natural elements such as water, air and sound. By materializing weather dynamics on intimate sites to mediate what occurs in another place, Tangible Weather Channel encourages the participant to establish links with his or her experiential memories of a specific place and to create a sense of closeness to a loved one via touch and contemplation. It investigates the experiential and performative aspects of information representation, and interrelationship among material, meaning, memory and perception. The system can be built upon to make more elaborate installations and this is the first iteration of a work which can be greatly expanded.
Searching Optimal Resequencing and Feature Assignment on an Automated Assembly Line
Authors: Andrew Lim, Zhou Xu
Venue: Proceedings of the 17th IEEE International Conference on Tools with Artificial Intelligence (2005)

The resequencing and feature assignment problem (RFAP) is to schedule a set of jobs on a moving assembly line so that the total changeover cost is minimized. Each job in the assembly line must be assigned a feature from its feasible feature set. However, a changeover cost is incurred between two consecutive jobs with different features. To minimize the total changeover cost, the job sequence needs to be rearranged, but the rearrangement is restricted to the number of off-line buffers where a job removed from the line can be temporarily stored before it is reinserted.
Evaluating Teachers' Attitudes toward the Use of Wireless-Mobile Technologies in Supporting Learning: An Instrument Development Study
Authors: Christina C. Chao
Venue: Proceedings of the IEEE International Workshop on Wireless and Mobile Technologies in Education (2005)

What are teachers' attitudes toward the use of mobile technologies in the classroom? A positive attitude toward innovation is crucial and indicative of a state of readiness to sustain or use that innovation. This paper describes an instrument developed to measure teachers' attitudes toward the use of wirelessmobile technologies in the classroom. A factorial analysis revealed an estimated alpha internal consistency score of .85 for a heterogeneous group of school teachers. Collecting reliable data from teachers, with regard to their attitude toward the use of mobile technologies in the classroom, can provide valuable insights into assessing readiness to integrate mobile technologies into the classroom and interventions designed to help teachers enhance their teaching.
Shader Performance Analysis on a Modern GPU Architecture
Authors: Victor Moya, Carlos Gonzalez, Jordi Roca, Agustin Fernandez, Roger Espasa
Venue: Proceedings of the 38th annual IEEE/ACM International Symposium on Microarchitecture (2005)

This paper presents an analysis of the performance of the shader processing units in a modern Graphics Processor Unit (GPU) architecture using real graphic applications. The architecture of a modern GPU is described and a simulator and associated framework used to evaluate the architecture is introduced. The paper analyses the effects in performance of different configurations of the shader processing units and compares a classic GPU with a unified shader GPU. The evaluated unified shader architecture proves to be 15% to 30% more efficient, in terms of area, with a 2% to 7% improvement in performance when compared with a similar non-unified architecture.
DiffServ Aware Link Adaptation for CDMA Radio Systems
Authors: Lin Wang, Vasilis Friderikos, Mikio Iwamura, Nima Nafisi, A. Hamid Aghvami, Misha Dohler
Venue: Proceedings of the Second International Conference on Quality of Service in Heterogeneous Wired/Wireless Networks (2005)

A link adaptation schemes is proposed to improve the efficiency to support DiffServ traffic over CDMA air interface. To differentiate the resource allocation between DiffServ PHBs and between the in/out profile packets within each AF class, two-level differentiation is done in the proposed scheme: inter-class differentiation and intra-class differentiation. Through this interaction between the two levels, a better QoS balance between classes is achieved and therefore a higher capacity is gained as shown by our numerical evaluation.
Towards a debugging system for sensor networks
Authors: Nithya Ramanathan, Eddie Kohler, Deborah Estrin
Venue: International Journal of Network Management (2005)

Due to their resource constraints and tight physical coupling, sensor networks afford limited visibility into an application's behavior. As a result it is often difficult to debug issues that arise during development and deployment. Existing techniques for fault management focus on fault tolerance or detection; before we can detect anomalous behavior in sensor networks, we need first to identify what simple metrics can be used to infer system health and correct behavior. We propose metrics and events that enable system health inferences, and present a preliminary design of Sympathy, a debugging tool for pre-and post-deployment sensor networks. Sympathy will contain mechanisms for collecting system performance metrics with minimal memory overhead; mechanisms for recognizing application-defined events based on these metrics; and a system for collecting events in their spatiotemporal context. The Sympathy system will help programmers draw correlations between seemingly unrelated, distributed events, and produce graphs that highlight those correlations. As an example, we describe how we used a preliminary version of Sympathy to help debug a complex application, Tiny Diffusion.
High Performance Dense Ring Generators
Authors: Grzegorz Mrugalski Nilanjan Mukherjee, Janusz Rajski, Jerzy Tyszer
Venue: IEEE Transactions on Computers (2006)

This paper presents an enhanced architecture of on-chip pseudorandom test pattern generators, test data decompressors, and test response compactors based on ring generators. The new structure is aimed at improving layout and routing properties while, at the same time, reducing propagation delays introduced by associated phase shifters.
Zone Identification in the Printed Gujarati Text
Authors: Jignesh Dholakia, Atul Negi, S. Rama Mohan
Venue: Proceedings of the Eighth International Conference on Document Analysis and Recognition (2005)

Gujarati, is a language from the Indo-Aryan family of languages, used by 50 million people in the western part of India. Gujarati - script used to write the Gujarati language, is a multilevel script, written in three zones: base character zone, upper modifier zone and lower modifier zone. Several characters are discriminated by the specific modifiers, which exist in the upper and lower zones. Hence, detecting the zone boundaries is an important task in the Gujarati OCR. Although the Gujarati script is in some respects related to the Devanagari script, there are certain peculiar differences, which prevent the use of already known techniques for zone boundary detection for scripts such as Bengali, Assamese and Devanagari where mature OCR systems already do exist. There is only one previous documented effort for Gujarati OCR, in which an approach to recognize a small subset of Gujarati alphabet was discussed. The present paper proposes a sophisticated method for accurate zone detection in images of printed Gujarati. It is expected that this approach shall make the way smoother for the design and development of Gujarati OCR systems for complete character sets.
A soft computing framework for software effort estimation
Authors: Xishi Huang, Danny Ho, Jing Ren, F. Capretz
Venue: Soft Computing - A Fusion of Foundations, Methodologies and Applications (2006)

Accurate software estimation such as cost estimation, quality estimation and risk analysis is a major issue in software project management. In this paper, we present a soft computing framework to tackle this challenging problem. We first use a preprocessing neuro-fuzzy inference system to handle the dependencies among contributing factors and decouple the effects of the contributing factors into individuals. Then we use a neuro-fuzzy bank to calibrate the parameters of contributing factors. In order to extend our framework into fields that lack of an appropriate algorithmic model of their own, we propose a default algorithmic model that can be replaced when a better model is available. One feature of this framework is that the architecture is inherently independent of the choice of algorithmic models or the nature of the estimation problems. By integrating neural networks, fuzzy logic and algorithmic models into one scheme, this framework has learning ability, integration capability of both expert knowledge and project data, good interpretability, and robustness to imprecise and uncertain inputs. Validation using industry project data shows that the framework produces good results when used to predict software cost.
Basis Pursuit Based Algorithm for Intra-Voxel Recovering Information in DW-MRI.
Authors: Alonso Ramirez-Manzanares, Mariano Rivera
Venue: Proceedings of the Sixth Mexican International Conference on Computer Science (2005)

In this work we applied the Basis Pursuit (BP) methodology for recovering the intra-voxel information in Diffusion Weighted MR Images (DW-MRI). We compare the proposed BP approach with the Diffusion Basis Function Estimation (DBFE) algorithm. DBFE approach was previously applied to recover intra-voxel diffusion information in brain DW-MRI. The intra-voxel information is recovered at voxels that contain axon fiber crosses or bifurcations by means of a linear combination of a known diffusion functions. We state the DBFE solution in the signal decomposition context, i.e., the measured DW-MRI signal is decomposed as a linear combination of signals that belongs to a Base of Diffusion Functions (BDF). In such a BDF, each signal is a M-dimensional vector, where each component indicates the water diffusion coefficient in a known three-dimensional orientation. In this work, we analyze and compare the solution given by DBFE method with the BP methodology. The BP methodology is used in order to select the set of base signals (which are taken from a dictionary) that best explain a given arbitrary signal. Moreover, solution strategies used in the BP and DBFE algorithm are compared and discussed. Examples in synthetic and real images are shown in order to demonstrate the performance of the compared methods.
Two-Stage Reconfigurable Computing System Architecture
Authors: Yan-Xiang Deng, Chao-Jang Hwang, Der-Chyuan Lou
Venue: Proceedings of the 18th International Conference on Systems Engineering (2005)

There are many successful applications of reconfigurable computing architecture in the past decade. They can be implemented into reconfigurable computing system according to their function algorithms usually. But, due to the influence of Gordon Moore's Law on FPGA (field programmable gate arrays) structure, the gate array sizes have been expanded widely under the technology of ULSI (ultra large scale integration). So, Using FPGAs to implement the design of function level is waste of reconfigurable units. Therefore, how to build a powerful reconfigurable computing architecture is an important research topic. In this article, a new reconfigurable computing architecture named TSRCS (two-stage reconfigurable computing system) is proposed. The concept of TSRCS is to split the reconfiguration into two stages, one is SSR (system-stage reconfiguration) and another is FSR (function-stage reconfiguration). The SSR dynamically rebuilds routing networks that connect between RFBs (reconfigurable function blocks) but the FSR busily reconfigures RFBs following some computing algorithm that we want to do. The TSRCS can dynamic change not only the system architecture but also any function. The advantages of using TSRCS to implement a system are architecture flexible, function varied, system opening and performance changeable but the disadvantage is construction longer. In this paper, a new design method is proposed which can combine the forte of software and hardware to build a new system architecture and the research results have important contribution to computer science.
DiReC: distributing the render cache to PC-clusters for interactive environments
Authors: Nils Beck, André Hinkenjann
Venue: Proceedings of the ACM symposium on Virtual reality software and technology (2005)

The Render Cache [1,2] allows the interactive display of very large scenes, rendered with complex global illumination models, by decoupling camera movement from the costly scene sampling process. In this paper, the distributed execution of the individual components of the Render Cache on a PC cluster is shown to be a viable alternative to the shared memory implementation.As the processing power of an entire node can be dedicated to a single component, more advanced algorithms may be examined. Modular functional units also lead to increased flexibility, useful in research as well as industrial applications.We introduce a new strategy for view-driven scene sampling, as well as support for multiple camera viewpoints generated from the same cache. Stereo display and a CAVE multi-camera setup have been implemented.The use of the highly portable and inter-operable CORBA networking API simplifies the integration of most existing pixel-based renderers. So far, three renderers (C++ and Java) have been adapted to function within our framework.