ppxscal/embedding_network huggingface dataset:
An expert diagnosis system for classification of human parasite eggs based on multi-class SVM
Authors: Derya Avci, Asaf Varol
Venue: Expert Systems with Applications: An International Journal (2009)

In this paper, it is proposed a new methodology based on invariant moments and multi-class support vector machine (MCSVM) for classification of human parasite eggs in microscopic images. The MCSVM is one of the most used classifiers but it has not used for classification of human parasite eggs to date. This method composes four stages. These are pre-processing stage, feature extraction stage, classification stage, and testing stage. In pre-processing stage, the digital image processing methods, which are noise reduction, contrast enhancement, thresholding, and morphological and logical processes. In feature extraction stage, the invariant moments of pre-processed parasite images are calculated. Finally, in classification stage, the multi-class support vector machine (MCSVM) classifier is used for classification of features extracted feature extraction stage. We used MATLAB software for estimating the success classification rate of proposed approach in this study. For this aim, proposed approach was tested by using test data. At end of test, 97.70% overall success rates were obtained.
An HMM approach to genome-wide identification of differential histone modification sites from ChIP-seq data
Authors: Han Xu, Chia-Lin Wei, Feng Lin, Wing-Kin Sung
Venue: Bioinformatics (2008)

Motivation: Epigenetic modifications are one of the critical factors to regulate gene expression and genome function. Among different epigenetic modifications, the differential histone modification sites (DHMSs) are of great interest to study the dynamic nature of epigenetic and gene expression regulations among various cell types, stages or environmental responses. To capture the histone modifications at whole genome scale, ChIP-seq technology is becoming a robust and comprehensive approach. Thus the DHMSs are potentially identifiable by comparing two ChIP-seq libraries. However, little has been addressed on this issue in literature. Results: Aiming at identifying DHMSs, we propose an approach called ChIPDiff for the genome-wide comparison of histone modification sites identified by ChIP-seq. Based on the observations of ChIP fragment counts, the proposed approach employs a hidden Markov model (HMM) to infer the states of histone modification changes at each genomic location. We evaluated the performance of ChIPDiff by comparing the H3K27me3 modification sites between mouse embryonic stem cell (ESC) and neural progenitor cell (NPC). We demonstrated that the H3K27me3 DHMSs identified by our approach are of high sensitivity, specificity and technical reproducibility. ChIPDiff was further applied to uncover the differential H3K4me3 and H3K36me3 sites between different cell states. Interesting biological discoveries were achieved from such comparison in our study. Availability: http://cmb.gis.a-star.edu.sg/ChIPSeq/tools.htm Contact:asflin@ntu.edu.sg; sungk@gis.a-star.edu.sg Supplementary information:Supplementary methods and data are available at Bioinformatics online.
The case for active block layer extensions
Authors: Jorge Guerra, Luis Useche, Medha Bhadkamkar, Ricardo Koller, Raju Rangaswami
Venue: ACM SIGOPS Operating Systems Review (2008)

Self-managing storage systems have recently received attention from the research community due to their promised ability of continuously adapting to best reflect high-level system goal specifications. However, this eventuality is currently being met by both conceptual and practical challenges that threaten to slow down the pace of innovation. We argue that two fundamental directions will help evolve the state of self-managing storage systems: (i) a standardized development environment for self-management extensions that also addresses ease of deployment, and (ii) a theoretical framework for reasoning about behavioral properties of individual and collective self-management extensions. We propose Active Block Layer Extensions (ABLE), an operating system infrastructure that aids the development and manages the deployed instances of self-management extensions within the storage stack. ABLE develops a theory behind block layer extensions that helps address key questions about overall storage stack behavior, data consistency, and reliability. We exemplify specific storage self-management solutions that can be built as stackable extensions using ABLE. Our initial experience with ABLE and few block layer extensions that we have been building, leads to believe that the ABLE infrastructure can substantially simplify the development and deployment of robust, self-managing, storage systems.
A random walk method for alleviating the sparsity problem in collaborative filtering
Authors: Hilmi Yildirim, Mukkai S. Krishnamoorthy
Venue: Proceedings of the 2008 ACM conference on Recommender systems (2008)

Collaborative Filtering is one of the most widely used approaches in recommendation systems which predicts user preferences by learning past user-item relationships. In recent years, item-oriented collaborative filtering methods came into prominence as they are more scalable compared to user-oriented methods. Item-oriented methods discover item-item relationships from the training data and use these relations to compute predictions. In this paper, we propose a novel item-oriented algorithm, Random Walk Recommender, that first infers transition probabilities between items based on their similarities and models finite length random walks on the item space to compute predictions. This method is especially useful when training data is less than plentiful, namely when typical similarity measures fail to capture actual relationships between items. Aside from the proposed prediction algorithm, the final transition probability matrix computed in one of the intermediate steps can be used as an item similarity matrix in typical item-oriented approaches. Thus, this paper suggests a method to enhance similarity matrices under sparse data as well. Experiments on MovieLens data show that Random Walk Recommender algorithm outperforms two other item-oriented methods in different sparsity levels while having the best performance difference in sparse datasets.
Implementation of warm-start strategies in interior-point methods for linear programming in fixed dimension
Authors: Elizabeth John, E. Alper Yıldırım
Venue: Computational Optimization and Applications (2008)

We implement several warm-start strategies in interior-point methods for linear programming (LP). We study the situation in which both the original LP instance and the perturbed one have exactly the same dimensions. We consider different types of perturbations of data components of the original instance and different sizes of each type of perturbation. We modify the state-of-the-art interior-point solver PCx in our implementation. We evaluate the effectiveness of each warm-start strategy based on the number of iterations and the computation time in comparison with "cold start" on the NETLIB test suite. Our experiments reveal that each of the warm-start strategies leads to a reduction in the number of interior-point iterations especially for smaller perturbations and for perturbations of fewer data components in comparison with cold start. On the other hand, only one of the warm-start strategies exhibits better performance than cold start in terms of computation time. Based on the insight gained from the computational results, we discuss several potential improvements to enhance the performances of such warm-start strategies.
Robust gesture processing for multimodal interaction
Authors: Srinivas Bangalore, Michael Johnston
Venue: Proceedings of the 10th international conference on Multimodal interfaces (2008)

With the explosive growth in mobile computing and communication over the past few years, it is possible to access almost any information from virtually anywhere. However, the efficiency and effectiveness of this interaction is severely limited by the inherent characteristics of mobile devices, including small screen size and the lack of a viable keyboard or mouse. This paper concerns the use of multimodal language processing techniques to enable interfaces combining speech and gesture input that overcome these limitations. Specifically we focus on robust processing of pen gesture inputs in a local search application and demonstrate that edit-based techniques that have proven effective in spoken language processing can also be used to overcome unexpected or errorful gesture input. We also examine the use of a bottom-up gesture aggregation technique to improve the coverage of multimodal understanding.
PicShark: mitigating metadata scarcity through large-scale P2P collaboration
Authors: Philippe Cudré-Mauroux, Adriana Budura, Manfred Hauswirth, Karl Aberer
Venue: The VLDB Journal &mdash; The International Journal on Very Large Data Bases (2008)

With the commoditization of digital devices, personal information and media sharing is becoming a key application on the pervasive Web. In such a context, data annotation rather than data production is the main bottleneck. Metadata scarcity represents a major obstacle preventing efficient information processing in large and heterogeneous communities. However, social communities also open the door to new possibilities for addressing local metadata scarcity by taking advantage of global collections of resources. We propose to tackle the lack of metadata in large-scale distributed systems through a collaborative process leveraging on both content and metadata. We develop a community-based and self-organizing system called PicShark in which information entropy--in terms of missing metadata--is gradually alleviated through decentralized instance and schema matching. Our approach focuses on semi-structured metadata and confines computationally expensive operations to the edge of the network, while keeping distributed operations as simple as possible to ensure scalability. PicShark builds on structured Peer-to-Peer networks for distributed look-up operations, but extends the application of self-organization principles to the propagation of metadata and the creation of schema mappings. We demonstrate the practical applicability of our method in an image sharing scenario and provide experimental evidences illustrating the validity of our approach.
Vehicle Multi-sensor Information Optimization Based on Federal Fusion Valuation
Authors: Hong Zhu, Minhua Wu, Guixia Guan, Yong Guan, Weizhen Sun
Venue: Proceedings of the 2008 Fourth International Conference on Natural Computation - Volume 06 (2008)

Dead Reckoning system (DR) and Global Positioning System (GPS), which consist of integrated navigation system, are two important positioning methods in the intelligent vehicle navigation. The information from the different sensors of vehicle GPS and DR integrated navigation system needs to be fused in order to implement the optimal evaluation of global states, because of the different measurements and their noise characteristics. The federal Kalman filter is designed to fuse GPS and DR information. Two local filters process GPS and DR data respectively, and the main filter is responsible for data fusion and reset to the local filters. The information fusion based on federal filter solves some key problems such as system unavailability, big accumulative errors with GPS or DR alone, and it makes the system's global evaluation optimal. The simulation results show that the positioning accuracy and the credibility of the vehicle integrated navigation are much higher than that when GPS or DR is used alone.
Computational parametric Willmore flow
Authors: Gerhard Dziuk
Venue: Numerische Mathematik (2008)

We propose a new algorithm for the computation of Willmore flow. This is the L 2-gradient flow for the Willmore functional, which is the classical bending energy of a surface. Willmore flow is described by a highly nonlinear system of PDEs of fourth order for the parametrization of the surface. The spatially discrete numerical scheme is stable and consistent. The discretization relies on an adequate calculation of the first variation of the Willmore functional together with a derivation of the second variation of the area functional which is well adapted to discretization techniques with finite elements. The algorithm uses finite elements on surfaces. We give numerical examples and tests for piecewise linear finite elements. A convergence proof for the full algorithm remains an open question.
What's wrong with high-dimensional similarity search?
Authors: Stephen Blott, Roger Weber
Venue: Proceedings of the VLDB Endowment (2008)

Similarity search in high-dimensional vector spaces has been the subject of substantial research, motivated in part by the need to provide query support for images and other complex data types. The paper VLDB 1998 paper "Quantitative Analysis and Performance Study for Similarity-Search Methods in High-Dimensional Spaces" analyses why this search problem can be so tricky, and shows with intuitive yet formal proofs that nearest-neighbour search is fundamentally linear beyond a certain dimensionality. Consequently, the paper proposes a new, linear search structure (the VA-File) which focuses on accelerating the indispensable sequential scan with approximations and computational schemes to reduce both CPU and IO efforts. Experiments with both synthetic and image data showed -- surprisingly, at the time -- that such schemes outperform hierarchical methods in all cases where the dimensionality is greater than five. In this paper, we review that work and identify both what we got right in the paper and its impact, and also (with the benefit of hindsight) those elements of the work for which we were off the mark. The lessons learned are relevant not just to the narrow area of similarity search, but also more broadly across the fields of databases and computing.
On the Complexity of Succinct Zero-Sum Games
Authors: Lance Fortnow, Russell Impagliazzo, Valentine Kabanets, Christopher Umans
Venue: Computational Complexity (2008)

We study the complexity of solving succinct zero-sum games, i.e., the games whose payoff matrix M is given implicitly by a Boolean circuit C such that M(i,j) = C(i,j). We complement the known EXP-hardness of computing the exact value of a succinct zero-sum game by several results on approximating the value. (1) We prove that approximating the value of a succinct zero-sum game to within an additive error is complete for the class promise- $$S^{p}_{2}$$ , the "promise" version of $$S^{p}_{2}$$ . To the best of our knowledge, it is the first natural problem shown complete for this class. (2) We describe a ZPP NP algorithm for constructing approximately optimal strategies, and hence for approximating the value, of a given succinct zero-sum game. As a corollary, we obtain, in a uniform fashion, several complexity-theoretic results, e.g., a ZPP NP algorithm for learning circuits for SAT (Bshouty et al., JCSS, 1996) and a recent result by Cai (JCSS, 2007) that $$S^{p}_{2} \subseteq$$ ZPP NP . (3) We observe that approximating the value of a succinct zero-sum game to within a multiplicative factor is in PSPACE, and that it cannot be in promise- $$S^{p}_{2}$$ unless the polynomial-time hierarchy collapses. Thus, under a reasonable complexity-theoretic assumption, multiplicative-factor approximation of succinct zero-sum games is strictly harder than additive-error approximation.
Investigating a physically-based signal power model for robust low power wireless link simulation
Authors: Tal Rusak, Philip A. Levis
Venue: Proceedings of the 11th international symposium on Modeling, analysis and simulation of wireless and mobile systems (2008)

We propose deriving wireless simulation models from experimental traces of radio signal strength. Because experimental traces have holes due to packet losses, we explore two algorithms for filling the gaps in lossy experimental traces. Using completed traces, we apply the closest-fit pattern matching (CPM) algorithm, originally designed for modeling external interference, to model signal strength. We compare the observed link behavior using our models with that of the experimental packet trace. Our approach results in more accurate packet reception ratios than current simulation methods, reducing the absolute error in PRR by up to about 30%. We also find that using CPM for signal strength improves simulation of packet burstiness, reducing the Kantorovich-Wasserstein (KW) distance of conditional packet delivery functions (CPDFs) by a factor of about 3 for intermediate links. These improvements give TOSSIM, a standard sensor network simulator, a better capability to capture real-world dynamics and edge conditions that protocol designers typically must wait until deployment to detect.
Multi-layer Bayesian Network for Variable-Bound Inference
Authors: Shizhuo Zhu, Po-Chun Chen, John Yen
Venue: Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 02 (2008)

Agent decision-making is an information-intensive activity. Its performance is affected by the availability of relevant information. Bayesian networks have provided a probabilistic estimate for uncertain information. However, for those decision problems where information is represented in predicates, Bayesian inferences are required to process the variable-bound relations across predicates. Multi-Layer Bayesian Network (MLBN) is an extension of the classical model of Bayesian networks with multiple layers of conditional probability tables, each corresponding to one specific variable binding. The MLBN has been implemented based on an agent architecture. Experiments have shown its capability of improving performance in an experience-based decision-making framework.
DrugViz
Authors: Bing Xiong, Ke Liu, Jie Wu, David L. Burk, Hualiang Jiang, Jingkang Shen
Venue: Bioinformatics (2008)

Summary: DrugViz is a Cytoscape plugin that is designed to visualize and analyze small molecules within the framework of the interactome. DrugViz can import drug–target network information in an extended SIF file format to Cytoscape and display the two-dimensional (2D) structures of small molecule nodes in a unified visualization environment. It also can identify small molecule nodes by means of three different 2D structure searching methods, namely isomorphism, substructure and fingerprint-based similarity searches. After selections, users can furthermore conduct a two-side clustering analysis on drugs and targets, which allows for a detailed analysis of the active compounds in the network, and elucidate relationships between these drugs and targets. DrugViz represents a new tool for the analysis of data from chemogenomics, metabolomics and systems biology. Availability: DrugViz and data set used in Application are freely available for download at http://202.127.30.184:8080/software.html Contact: jkshen@mail.shcnc.ac.cn
Detection and localization of 3d audio-visual objects using unsupervised clustering
Authors: Vasil Khalidov, Florence Forbes, Miles Hansard, Elise Arnaud, Radu Horaud
Venue: Proceedings of the 10th international conference on Multimodal interfaces (2008)

This paper addresses the issues of detecting and localizing objects in a scene that are both seen and heard. We explain the benefits of a human-like configuration of sensors (binaural and binocular) for gathering auditory and visual observations. It is shown that the detection and localization problem can be recast as the task of clustering the audio-visual observations into coherent groups. We propose a probabilistic generative model that captures the relations between audio and visual observations. This model maps the data into a common audio-visual 3D representation via a pair of mixture models. Inference is performed by a version of the expectation-maximization algorithm, which is formally derived, and which provides cooperative estimates of both the auditory activity and the 3D position of each object. We describe several experiments with single- and multiple-speaker detection and localization, in the presence of other audio sources.
Behavior Specification of Product Lines via Feature Models and UML Statecharts with Variabilities
Authors: Ariel Gonzalez, Carlos Luna
Venue: Proceedings of the 2008 International Conference of the Chilean Computer Science Society (2008)

The study of variability in software development has become increasingly important in recent years. The research areas in which this is involved range from software specialization to product lines. A common mechanism to represent the variability in a product line is by means of feature models. However, the relationship between these models and UML design models is not straightforward. The contribution of this work is the proposal of an extension of UML statecharts, which consists of introducing variability in their main components, so that the behavior of product lines can be specified. This is accomplished via the use of feature models, in order to describe the common and variant components, in such a way that, starting from different feature configurations, concrete state machines corresponding to different products of a line can be obtained.
Remotely controlled intelligent vehicle to handle public places security
Authors: Abdel Latif Abu Dalhoum, Mohammed Al-Rawi, Ahmed Al-Sharieh, Ayman M. Najjar, Maen M. Najjar, S. Shayreh
Venue: WSEAS TRANSACTIONS on SYSTEMS (2008)

In this paper we propose a simple design and implementation of an intelligent robot that can be used to handle security breaches. Applications may include counter terrorism, handling pollution crises, monitoring for security purpose, etc. Ultrasound sensors, temperature sensors, GPS devices, and wireless cameras are mounted on the robot in order to give 360 degrees stereo vision and other environmental sensing. JPEG2000 image compression is used to enable efficient video streaming for views scanned by the cameras to the server that manages the Robot. The Robot is designed to work as a server based, and many authorized security personals can connect to the Robot in order to monitor public places such as malls, parking, etc.
Joint uplink and downlink admission control to both streaming and elastic flows in CDMA/HSDPA systems
Authors: T. Chahed, E. Altman, S. E. Elayoubi
Venue: Performance Evaluation (2008)

TCP-based data flows generate packets and ACKs in two directions, be it in the wireline or wireless networks. In the latter case, packets are typically found in the downlink whereas ACKs are in the uplink. These two links are asymmetric in the case of CDMA-based High Data Rate (HDR) and High-Speed Downlink Packet Access (HSDPA) systems, the uplink being much slower than the downlink and thus, in some cases, restrictive in terms of the achievable throughput of the TCP flow. The aim of this work is to evaluate the performance of such a setting, in the presence of both streaming and elastic traffic, under a dynamic scenario where users arrive at the system and leave it after completion of their service. We specifically quantify the impact of the uplink on the overall performance of TCP and study the model variations as functions of several parameters such as load, file size and radio conditions.