ppxscal/embedding_network huggingface dataset:
MTCrossBit: A Dynamic Binary Translation System Using Multithreaded Optimization Framework
Authors: Xiaolong Li, Deen Zheng, Ruhui Ma, Alei Liang, Haibing Guan
Venue: Proceedings of the 9th International Conference on Algorithms and Architectures for Parallel Processing (2009)

Conventional optimization algorithms which are widely used in static compiler--including peephole, instruction selection, Graph coloring register allocation, and so on--cannot be effectively implemented in DBT (Dynamic Binary Translation) system since they bring too much overhead in run time.MTCrossBit is an experimental-multithreaded DBT optimization framework which utilizes an extra thread for building hot traces to test whether we can eliminate the overhead extremely caused by the algorithm itself. To make a better performance, a new threads' communication mechanism that we call ASLC is presented.According to the test results of SPECInt2000, we achieved some success using concurrent architecture as mentioned previously. In this paper, we illustrated that multithreaded dynamic optimization framework is an effective way to speed up DBT systems with a quantitative example.
A Novel Audio Watermarking Algorithm for Copyright Protection Based on DCT Domain
Authors: Yang Yan, Huang Rong, Xu Mintao
Venue: Proceedings of the 2009 Second International Symposium on Electronic Commerce and Security - Volume 01 (2009)

Audio digital watermarking technology is the new means of audio reproduction, which can pre-implant the special data as a watermark to the audio signal which pass the information on behalf of the owner of identity and prove the user's legitimacy. The novel technology of embedding image data into the audio signal and additive audio watermarking algorithm based on DCT domain is proposed. AC DCT coefficients play different influence in robust and inaudibility. First, we decompose the audio into no overlapping blocks (eight data per block). Then every block performs the DCT operation: watermark is embedded by modulating AC DCT coefficient. Every block is embedded one bit message. Experimental results demonstrate that the watermark is inaudible and this algorithm is robust to common operations of digital audio signal processing, such as low-pass filtering, smoothing, adding noise and so on. The extracted watermark image quality is showed by considering normalize correlation (NC) value with a suitable scaling parameter for embedding.
Chinese Blog Clustering by Hidden Sentiment Factors
Authors: Shi Feng, Daling Wang, Ge Yu, Chao Yang, Nan Yang
Venue: Proceedings of the 5th International Conference on Advanced Data Mining and Applications (2009)

In the Web age, blogs have become the major platform for people to express their opinions and sentiments. The traditional blog clustering methods usually group blogs by keywords, stories or timelines, which do not consider opinions and emotions expressed in the articles. In this paper, a novel method based on Probabilistic Latent Semantic Analysis (PLSA) is presented to model the hidden emotion factors and an emotion-oriented clustering approach is proposed according to the sentiment similarities between Chinese blogs. Extensive experiments were conducted on real world blog datasets with different topics and the results show that our approach can cluster Chinese blogs into sentiment coherent groups to allow for better organization and easy navigation.
NQAR: Network Quality Aware Routing in Wireless Sensor Networks
Authors: Jaewon Choi, Baek-Young Choi, Sejun Song, Kwang-Hui Lee
Venue: Proceedings of the 4th International Conference on Wireless Algorithms, Systems, and Applications (2009)

We propose a network quality aware routing (NQAR) mechanism to provide an enabling method of the delay-sensitive data delivery over error-prone wireless sensor networks. Unlike the existing routing methods that select routes with the shortest arrival latency or the minimum hop count, the proposed scheme adaptively selects the route based on the network qualities including link errors and collisions with minimum additional complexity. It is designed to avoid the paths with potential noise and collision that may cause many non-deterministic backoffs and retransmissions. We propose a generic framework to select a minimum cost route that takes the packet loss rate and collision history into account. NQAR uses a data centric approach to estimate a single-hop delay based on processing time, propagation delay, packet loss rate, number of backoffs, and the retransmission timeout between two neighboring nodes. This enables a source node to choose the shortest expected end-to-end delay path to send a delay-sensitive data. The experiment results show that NQAR reduces the end-to-end transfer delay up to approximately 50% in comparison with the latency-based directed diffusion and the hop count-based directed diffusion under the error-prone network environments. Moreover, NQAR performs better than other routing methods in terms of jitter, reachability, and network lifetime.
Multiple blocking sets in finite projective spaces and improvements to the Griesmer bound for linear codes
Authors: Simeon Ball, Szabolcs L. Fancsali
Venue: Designs, Codes and Cryptography (2009)

Belov, Logachev and Sandimirov construct linear codes of minimum distance d for roughly 1/q k/2 of the values of d < q k-1. In this article we shall prove that, for q = p prime and roughly $${\frac{3}{8}}$$ -th's of the values of d < q k-1, there is no linear code meeting the Griesmer bound. This result uses Blokhuis' theorem on the size of a t-fold blocking set in PG(2, p), p prime, which we generalise to higher dimensions. We also give more general lower bounds on the size of a t-fold blocking set in PG(¿, q), for arbitrary q and ¿ ¿ 3. It is known that from a linear code of dimension k with minimum distance d < q k-1 that meets the Griesmer bound one can construct a t-fold blocking set of PG(k¿1, q). Here, we calculate explicit formulas relating t and d. Finally we show, using the generalised version of Blokhuis' theorem, that nearly all linear codes over $${{\mathbb F}_p}$$ of dimension k with minimum distance d < q k-1, which meet the Griesmer bound, have codewords of weight at least d + p in subcodes, which contain codewords satisfying certain hypotheses on their supports.
Data Matching for Physical Integration of Biochemical Pathway Databases
Authors: Jyh-Jong Tsay, Bo-Liang Wu, Chien-Wen Chen
Venue: Proceedings of the 2009 Ninth IEEE International Conference on Bioinformatics and Bioengineering (2009)

As databases can overlap each other, data matching that aims to identify data records or elements describing the same object is one of the fundamental problems in physical integration of databases. Matching results can be applied to induce more accurate and complete object descriptions, remove data redundancy, check data consistency and generate cross-links. In this paper, we present a multilevel approach to match data between pathway databases that consist of 3 levels of information, compounds, reactions and pathways. Compounds comprise reactions, and reactions comprise pathways. Our main idea is to use relationships discovered in lower levels to infer relationships in upper levels, and use relationships in upper levels to enhance relationships in lower levels. In particular, we first use attributes of compounds to identify compound matching, i.e. to map compounds in one database to those in another database. Compound matching is then used to induce reaction matching. Reaction matching is used to induce pathway matching as well as to enhance compound matching. We experiment our approach for integration of two well known pathway databases KEGG and MetaCyc. The experiment shows that our approach identifies 1025 matchings in compound level, 968 matchings in reaction level, and 387 relations in pathway level. According to matching result, we assign EC number to 84 reactions in MetaCyc that do not have EC number, and discover some duplicate errors in both databases. Furthermore, our approach identifies 532 of the 544 unification links provided by MetaCyc. The recall rate is 0.977.
Sequential labeling with latent variables: an exact inference algorithm and its efficient approximation
Authors: Xu Sun, Jun'ichi Tsujii
Venue: Proceedings of the 12th Conference of the European Chapter of the Association for Computational Linguistics (2009)

Latent conditional models have become popular recently in both natural language processing and vision processing communities. However, establishing an effective and efficient inference method on latent conditional models remains a question. In this paper, we describe the latent-dynamic inference (LDI), which is able to produce the optimal label sequence on latent conditional models by using efficient search strategy and dynamic programming. Furthermore, we describe a straightforward solution on approximating the LDI, and show that the approximated LDI performs as well as the exact LDI, while the speed is much faster. Our experiments demonstrate that the proposed inference algorithm outperforms existing inference methods on a variety of natural language processing tasks.
Partially-Commutative Context-Free Processes
Authors: Wojciech Czerwiński, Sibylle Fröschle, Sławomir Lasota
Venue: Proceedings of the 20th International Conference on Concurrency Theory (2009)

Bisimulation equivalence is decidable in polynomial time for both sequential and commutative normed context-free processes, known as BPA and BPP, respectively. Despite apparent similarity between the two classes, different techniques were used in each case. We provide one polynomial-time algorithm that works in a superclass of both normed BPA and BPP. It is derived in the setting of partially-commutative context-free processes, a new process class introduced in the paper. It subsumes both BPA and BPP and seems to be of independent interest.
Online Prediction of Ovarian Cancer
Authors: Fedor Zhdanov, Vladimir Vovk, Brian Burford, Dmitry Devetyarov, Ilia Nouretdinov, Alex Gammerman
Venue: Proceedings of the 12th Conference on Artificial Intelligence in Medicine: Artificial Intelligence in Medicine (2009)

In this paper we apply computer learning methods to the diagnosis of ovarian cancer using the level of the standard biomarker CA125 in conjunction with information provided by mass spectrometry. Our algorithm gives probability predictions for the disease. To check the power of our algorithm we use it to test the hypothesis that CA125 and the peaks do not contain useful information for the prediction of the disease at a particular time before the diagnosis. It produces p-values that are less than those produced by an algorithm that has been previously applied to this data set. Our conclusion is that the proposed algorithm is especially reliable for prediction the ovarian cancer on some stages.
Fuzzy Smoothed Composition of Local Mapping Transformations for Non-rigid Image Registration
Authors: Edoardo Ardizzone, Roberto Gallea, Orazio Gambino, Roberto Pirrone
Venue: Proceedings of the 15th International Conference on Image Analysis and Processing (2009)

This paper presents a novel method for medical image registration. The global transformation is obtained by composing affine transformations, which are recovered locally from given landmarks.Transformations of adjacent regions are smoothed to avoid blocking artifacts, so that a unique continuous and differentiable global function is obtained. Such composition is operated using a technique derived from fuzzy C-means clustering. The method was successfully tested on several datasets; results, both qualitative and quantitative, are shown. Comparisons with other methods are reported. Final considerations on the efficiency of the technique are explained.
Measuring Mobile Emotions: Measuring the Impossible?
Authors: Arjan Geven, Manfred Tscheligi, Lucas Noldus
Venue: Proceedings of the 11th International Conference on Human-Computer Interaction with Mobile Devices and Services (2009)

Emotions as such is a research topic with a lot of coverage in various domains (neuroscience, psychology, medicine, criminology and more recently in user experience research). This workshop addresses multidisciplinary approaches, discussing ways of implementing mobile research about emotions. Particularly, this workshop aims to improve the assessment of emotions in the mobile context of field research. The workshop addresses particularly the state-of-the-art in emotion measurement and investigates the possibilities to apply and adopt these methods in the field of mobile HCI.
Ensuring security in depth based on heterogeneous network security technologies
Authors: Meharouech Sourour, Bouhoula Adel, Abbes Tarek
Venue: International Journal of Information Security (2009)

With the explosive growth of Internet connectivity that includes not only end-hosts but also pervasive devices, security becomes a requirement for enterprises. Although a significant effort has been made by the research community to develop defense techniques against security attacks, less focus has been given to manage security configuration efficiently. Network security devices, such as firewalls, intrusion detection and prevention systems, honeypot as well as vulnerability scanner, operate as a stand-alone system for solving a particular security problem. Yet these devices are not necessarily independent. The focus of this work is encompassing a security infrastructure where multiple security devices form a global security layer. Each component is defined with respect to the others and interacts dynamically and automatically with the different security devices in order to choose the best solution to be launched to prevent the final malicious objective. Our solution aims at solving, at the same time, the need for active defence, speed, reliability, accuracy and usability of the network.
Points on Computable Curves of Computable Lengths
Authors: Robert Rettinger, Xizhong Zheng
Venue: Proceedings of the 34th International Symposium on Mathematical Foundations of Computer Science 2009 (2009)

A computable plane curve is defined as the image of a computable real function from a closed interval to the real plane. As it is showed by Ko [7] that the length of a computable curve is not necessarily computable, even if the length is finite. Therefore, the set of the computable curves of computable lengths is different from the set of the computable curves of finite lengths. In this paper we show further that the points covered by these two sets of curves are different as well. More precisely, we construct a computable curve K of a finite length and a point z on the curve K such that the point z does not belong to any computable curve of computable length. This gives also a positive answer to an open question of Gu, Lutz and Mayordomo in [4].
Analysis of the Relation between Highway Horizontal Curve and Traffic Safety
Authors: Yingxue Zhang
Venue: Proceedings of the 2009 International Conference on Measuring Technology and Mechatronics Automation - Volume 03 (2009)

Road traffic safety is a complex problem which involves many factors as human, vehicle, road and environment and so on. For the road factor, the horizontal alignment can not be ignored, especially the horizontal curve. Although the accident rate happened on curve is higher than the straight line, it is inevitable to design horizontal curve. As the traffic accident becomes serious gradually, the paper analyzes the relation between road horizontal alignment and traffic safety based on investigation, in the horizontal alignment design, the curve radius, super-elevation, widen, transition curve and sight distance have the important effect for traffic accidents, summarizes the importance of the geometric design elements which improves safety and the consistency of each element. At last the paper puts forward some advice for highway horizontal curve design.
Using 3D Head and Respirator Shapes to Analyze Respirator Fit
Authors: Kathryn M. Butler
Venue: Proceedings of the 2nd International Conference on Digital Human Modeling: Held as Part of HCI International 2009 (2009)

A computational approach to analyzing respirator fit is demonstrated using geometries generated by laser scanning, mechanical drawings, and CAD files. Three fit-related problems that can be solved using computational tools are demonstrated: 1) The study of an outward leak of breathing gases into a near-flammable environment. 2) The study of a flow field inside a half-facepiece respirator. 3) The characterization of the relationship of respirator design and head shape to fit and comfort.
Reviews
Venue: IEEE Annals of the History of Computing (2009)

Two books are reviewed in this issue: Calculating a Natural World: Scientisits, Engineers, and Computers During the Rise of U.S. Cold War Research by Atushi Akera, and Memorable Ideas of a Computer School: The Life and Work of Antonin Svoboda, edited by George J. Klir.
Implementation Specific Verification of Divide and Square Root Instructions
Authors: Elena Guralnik, Ariel J. Birnbaum, Anatoly Koyfman, Avi Kaplan
Venue: Proceedings of the 2009 19th IEEE Symposium on Computer Arithmetic (2009)

Floating point operations such as divide and square root are typically implemented in microcode rather than dedicated logic. Bugs in these operations missed by generic black-box verification tools, were analyzed. This led to the conclusion that the corner cases, in addition to being implementation dependent, could not be characterized in terms of special input or output values in a straightforward manner.However, many of those cases can be easily generalized for many known implementations. The typical implementation uses a known iterative approximation algorithm, such as the Newton-Raphson method, to calculate the desired result; thus, it is sufficient to produce the corner cases associated with the specific algorithm.We investigated the following problem: given an iterative algorithm to compute a binary floating point operation, the iteration number, and an interval, find random inputs for the operation that, after the requested iteration, yield a relative error within the specified interval. This paper describes a method to solve this problem. This method was implemented in a floating-point test generator and is currently being used to verify the floating-point units of several processors.
Transmit Power Control in Wireless Mesh Networks Considered Harmful
Authors: Sebastian Max, Tinghuai Wang
Venue: Proceedings of the 2009 Second International Conference on Advances in Mesh Networks (2009)

A Wireless Mesh Network (WMN) serves to extend the coverage of Access Points (APs) by means of Relay Nodes (RNs) that forward data between Mobile Nodes (MNs) and an AP. This concept reduces deployment costs by exchanging the wires between APs by a wireless backbone. Unfortunately, this also reduces capacity, owing to multiple transmissions of the same data packet on its multi-hop route.Hence, different mechanisms to increase the capacity of WMNs are investigated, one of them being transmit power control. By limiting the transmission power, interference on other links is reduced. As a consequence, it should be possible for them to use more susceptible and thus higher rate Modulation- and Coding Schemes (MCSs), which improves the system capacity.Unfortunately, the reduction of the transmission power has also the effect that the received signal power is reduced, which then requires more robust (lower-rate)MCSs, reducing capacity.In this paper, we use an analytical framework to compute the upper capacity bound of Wireless Mesh Networks(WMNs) with and without transmit power control. The comparison shows that the negative influence of the power control dominates the positive.
Compromising anonymous communication systems using blind source separation
Authors: Ye Zhu, Riccardo Bettati
Venue: ACM Transactions on Information and System Security (TISSEC) (2009)

We propose a class of anonymity attacks to both wired and wireless anonymity networks. These attacks are based on the blind source separation algorithms widely used to recover individual signals from mixtures of signals in statistical signal processing. Since the philosophy behind the design of current anonymity networks is to mix traffic or to hide in crowds, the proposed anonymity attacks are very effective. The flow separation attack proposed for wired anonymity networks can separate the traffic in a mix network. Our experiments show that this attack is effective and scalable. By combining the flow separation method with frequency spectrum matching, a passive attacker can derive the traffic map of the mix network. We use a nontrivial network to show that the combined attack works. The proposed anonymity attacks for wireless networks can identify nodes in fully anonymized wireless networks using collections of very simple sensors. Based on a time series of counts of anonymous packets provided by the sensors, we estimate the number of nodes with the use of principal component analysis. We then proceed to separate the collected packet data into traffic flows that, with help of the spatial diversity in the available sensors, can be used to estimate the location of the wireless nodes. Our simulation experiments indicate that the estimators show high accuracy and high confidence for anonymized TCP traffic. Additional experiments indicate that the estimators perform very well in anonymous wireless networks that use traffic padding.
CSL Model Checking of Biochemical Networks with Interval Decision Diagrams
Authors: Martin Schwarick, Monika Heiner
Venue: Proceedings of the 7th International Conference on Computational Methods in Systems Biology (2009)

This paper presents an Interval Decision Diagram based approach to symbolic CSL model checking of Continuous Time Markov Chains which are derived from stochastic Petri nets. Matrix-vector and vector-matrix multiplication are the major tasks of exact analysis. We introduce a simple, but powerful algorithm which uses explicitly the Petri net structure and allows for parallelisation. We present results demonstrating the efficiency of our first prototype implementation when applied to biochemical network models, specifically with increasing token numbers. Our tool currently supports CSL model checking of time-bounded operators and the Next operator for ordinary stochastic Petri nets.
Local Feature Selection in Text Clustering
Authors: Marcelo N. Ribeiro, Manoel J. Neto, Ricardo B. Prudêncio
Venue: Advances in Neuro-Information Processing: 15th International Conference, ICONIP 2008, Auckland, New Zealand, November 25-28, 2008, Revised Selected Papers, Part II (2009)

Feature selection has improved the performance of text clustering. Global feature selection tries to identify a single subset of features which are relevant to all clusters. However, the clustering process might be improved by considering different subsets of features for locally describing each cluster. In this work, we introduce the method ZOOM-IN to perform local feature selection for partitional hierarchical clustering of text collections. The proposed method explores the diversity of clusters generated by the hierarchical algorithm, selecting a variable number of features according to the size of the clusters. Experiments were conducted on Reuters collection, by evaluating the bisecting K-means algorithm with both global and local approaches to feature selection. The results of the experiments showed an improvement in clustering performance with the use of the proposed local method.