ppxscal/embedding_network huggingface dataset:
Delay and capacity trade-offs in mobile ad hoc networks: a global perspective
Authors: Gaurav Sharma, Ravi Mazumdar, Ness B. Shroff
Venue: IEEE/ACM Transactions on Networking (TON) (2007)

Since the original work of Grossglauser and Tse, which showed that mobility can increase the capacity of an ad hoc network, there has been a lot of interest in characterizing the delay-capacity relationship in ad hoc networks. Various mobility models have been studied in the literature, and the delay-capacity relationships under those models have been characterized. The results indicate that there are trade-offs between the delay and capacity, and that the nature of these trade-offs is strongly influenced by the choice of the mobility model. Some questions that arise are: (i) How representative are these mobility models studied in the literature? (ii) Can the delay-capacity relationship be significantly different under some other "reasonable" mobility model? (iii) What sort of delay-capacity trade-off are we likely to see in a real world scenario? In this paper, we take the first step toward answering some of these questions. In particular, we analyze, among others, the mobility models studied in recent related works, under a unified framework. We relate the nature of delay-capacity trade-off to the nature of node motion, thereby providing a better understanding of the delay-capacity relationship in ad hoc networks in comparison to earlier works.
Thinking otherwise: Ethics, technology and other subjects
Authors: David J. Gunkel
Venue: Ethics and Information Technology (2007)

Ethics is ordinarily understood as being concerned with questions of responsibility for and in the face of an other. This other is more often than not conceived of as another human being and, as such, necessarily excludes others --- most notably animals and machines. This essay examines the ethics of such exclusivity. It is divided into three parts. The first part investigates the exclusive anthropocentrism of traditional forms of moral¿thinking and, following the example of recent innovations in animal rights philosophy, questions the mechanisms of such exclusion. Although recent work in animal- and bio-ethics has successfully implemented strategies for the inclusion of the animal as a legitimate subject of moral consideration, its other, the machine, has remained conspicuously excluded. The second part looks at recent attempts to include these machinic others in moral thinking and critiques the assumptions, values, and strategies that have been employed by these various innovations. And the third part proposes a means for thinking otherwise. That is, it introduces an alternative way to consider these other forms of otherness that is not simply reducible to the conceptual order that has structured and limited moral philosophy's own concern with and for others.
2D Euclidean distance transform algorithms: A comparative survey
Authors: Ricardo Fabbri, Luciano Da F. Costa, Julio C. Torelli, Odemir M. Bruno
Venue: ACM Computing Surveys (CSUR) (2008)

The distance transform (DT) is a general operator forming the basis of many methods in computer vision and geometry, with great potential for practical applications. However, all the optimal algorithms for the computation of the exact Euclidean DT (EDT) were proposed only since the 1990s. In this work, state-of-the-art sequential 2D EDT algorithms are reviewed and compared, in an effort to reach more solid conclusions regarding their differences in speed and their exactness. Six of the best algorithms were fully implemented and compared in practice.
SINS/GPS Integrated Navigation for Autonomous Underwater Vehicle with Wavelet Package Analysis and Neural Networks
Authors: Qi Wang, Xiao-su Xu
Venue: Proceedings of the Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing - Volume 03 (2007)

The strapdown inertial navigation system is usually employed to determine the attitude, velocity and position of an Autonomous Underwater Vehicle (AUV) for its specific advantage of small volume. The navigation accuracy provided by the SINS which employs accelerometers and gyroscopes deteriorates with time. Consequently, an external aiding source such as Global Positioning System (GPS) can be employed to reduce the error growth in the SINS. The GPS aided SINS system provides enhanced positioning accuracy of the AUV compared to that of a stand-alone SINS technique. A new method based on Kalman filtering and RBF neural network to fuse the GPS and the SINS data for an AUV application was presented in this paper. It was proved from the experiments that navigation accuracy was improved substantially between GPS position fixes with the proposed method.
Towards high-performance flow-level packet processing on multi-core network processors
Authors: Yaxuan Qi, Bo Xu, Fei He, Baohua Yang, Jianming Yu, Jun Li
Venue: Proceedings of the 3rd ACM/IEEE Symposium on Architecture for networking and communications systems (2007)

There is a growing interest in designing high-performance network devices to perform packet processing at flow level. Applications such as stateful access control, deep inspection and flow-based load balancing all require efficient flow-level packet processing. In this paper, we present a design of high-performance flow-level packet processing system based on multi-core network processors. Main contribution of this paper includes: a) A high performance flow classification algorithm optimized for network processors; b) An efficient flow state management scheme leveraging memory hierarchy to support large number of concurrent flows; c) Two hardware-optimized order-preserving strategies that preserve internal and external per-flow packet order. Experimental results show that: a) The proposed flow classification algorithm, AggreCuts, outperforms the well-known HiCuts algorithm in terms of classification rate and memory usage; b) The presented SigHash scheme can manage over 10M concurrent flow states on the Intel IXP2850 NP with extremely low collision rate; c) The performance of internal packet order-preserving scheme using SRAM queue-array is about 70% of that of external packet order-preserving scheme realized by ordered-thread execution.
Discovery of microRNA–mRNA modules via population-based probabilistic learning
Authors: Je-Gun Joung, Kyu-Baek Hwang, Jin-Wu Nam, Soo-Jin Kim, Byoung-Tak Zhang
Venue: Bioinformatics (2007)

Motivation: MicroRNAs (miRNAs) and mRNAs constitute an important part of gene regulatory networks, influencing diverse biological phenomena. Elucidating closely related miRNAs and mRNAs can be an essential first step towards the discovery of their combinatorial effects on different cellular states. Here, we propose a probabilistic learning method to identify synergistic miRNAs involving regulation of their condition-specific target genes (mRNAs) from multiple information sources, i.e. computationally predicted target genes of miRNAs and their respective expression profiles. Results: We used data sets consisting of miRNA–target gene binding information and expression profiles of miRNAs and mRNAs on human cancer samples. Our method allowed us to detect functionally correlated miRNA–mRNA modules involved in specific biological processes from multiple data sources by using a balanced fitness function and efficient searching over multiple populations. The proposed algorithm found two miRNA–mRNA modules, highly correlated with respect to their expression and biological function. Moreover, the mRNAs included in the same module showed much higher correlations when the related miRNAs were highly expressed, demonstrating our method's ability for finding coherent miRNA–mRNA modules. Most members of these modules have been reported to be closely related with cancer. Consequently, our method can provide a primary source of miRNA and target sets presumed to constitute closely related parts of gene regulatory pathways. Contact: btzhang@bi.snu.ac.kr Supplementary information: Supplementary data are available at Bioinformatics online.
Stream Processing in a Relational Database: a Case Study
Authors: Andrzej Hoppe, Jarek Gryz
Venue: Proceedings of the 11th International Database Engineering and Applications Symposium (2007)

A consensus seems to have emerged that streams cannot be processed efficiently by relational database engines. This point has been strongly advocated by Michael Stonebreaker, whose StreamBase [19] offers two orders of magnitude better performance in stream processing than a standard DBMS. We faced the challenge and investigated how much improvement in stream processing can be achieved in a standard DBMS just by appropriate tuning and use of features already available there. In this paper, we describe some of the techniques useful for stream processing and show how dramatic performance improvements they can provide. We tend to agree with Stonebreaker that the idea "One Size Fits All" in no longer applicable to all data-centric applications. However, we also believe that dismissing DBMS as irrelevant in stream processing applications is premature. We hope to show that relational database systems are sufficiently flexible to make the idea "One Size May Fit You" worth looking into.
On the Interactive Visualization of Very Large Image Data Sets
Authors: Frank Ekpar, Masaaki Yoneda, Hiroyuki Hase
Venue: Proceedings of the 7th IEEE International Conference on Computer and Information Technology (2007)

This paper presents a system for real-time visualization of very large image data sets using on- demand loading and dynamic view prediction. We use a robust image representation scheme for efficient adaptive rendering and a perspective view generation module to extend the applicability of the system to panoramic images. We demonstrate the effectiveness of the system by applying it both to imagery that does not require perspective correction and to very large panoramic data sets requiring perspective view generation. The system permits smooth, real-time interactive navigation of very large panoramic and non-panoramic image data sets on average personal computers without the use of specialized hardware.
TrueLink: A Practical Countermeasure to the Wormhole Attack in Wireless Networks
Authors: Jakob Eriksson, Srikanth Krishnamurthy, Michalis Faloutsos
Venue: Proceedings of the Proceedings of the 2006 IEEE International Conference on Network Protocols (2006)

In a wormhole attack, wireless transmissions are recorded at one location and replayed at another, creating a virtual linkunder attacker control. Proposed countermeasures to this attack use tight clock synchronization, specialized hardware, oroverhearing, making them difficult to realize in practice. TrueLink is a timing based countermeasure to the wormhole attack.Using TrueLink, a node i can verify the existence of a direct link to an apparent neighbor, j. Verification of a link i ¿j operates in two phases. In the rendezvous phase, the nodes exchange nonces ¿j and βi. This is done with tight timing constraints,within which it is impossible for attackers to forward the exchange between distant nodes. In the authentication phase, iand j transmit a signed message (¿j, βi), mutually authenticating themselves as the originator of their respective nonce.TrueLink does not rely on precise clock synchronization, GPS coordinates, overhearing, geometric inconsistencies, or statisticalmethods. It can be implemented using only standard IEEE 802.11 hardware with a minor backwards compatible firmware update.TrueLink is meant to be used together with a secure routing protocol. Such protocols require an authentication mechanism,which will also be used by TrueLink. TrueLink is virtually independent of the routing protocol used. Our performance evaluationshows that TrueLink provides effective protection against potentially devastating wormhole attacks.
Automatic Audio Genre Classification Based on Support Vector Machine
Authors: Yingying Zhu, Zhong Ming, Qiang Huang
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 01 (2007)

Audio classification is very important in audio indexing, analysis and content-based video retrieval. In this paper, we have proposed a clip-based support vector machine (SVM) approach to classify audio signals into six classes, which are pure speech, music, silence, environmental sound, speech with music and speech with environmental sound. The classification results are then used to partition a video into homogeneous audio segments, which is used to analyze and retrieve its high-level content. The experimental results show that the proposed system not only improves classification accuracy, but also performs better than the other classification systems using the decision tree (DT), K Nearest Neighbor (K-NN) and Neural Network (NN).
Inner Product Computers
Authors: E. E. ,  Jr. Swartzlander
Venue: IEEE Transactions on Computers (1978)

The inner product computer is a special-purpose computational unit intended to be used as an adjunct to a general-purpose digital computer to perform numerical processing tasks which previously exceeded the capacity of the general-purpose computer. The algorithmic structure of the inner product is briefly reviewed in the first section of this paper. Methods are described for computing the inner product of complex vectors with a series of four real inner products. Several hardware implementations of the inner product computer are described and then compared in terms of speed and complexity; a figure of merit is developed to simplify the comparison. The utility of this computational unit is demonstrated via the examination of a large-scale numerical problem, computerized three-dimensional x-ray reconstruction (computerized tomography) arising in the biomedical sciences. Finally, a comparison is given of the size of a general-purpose computer required to execute a large-scale processing task with that of an inner product computer to execute the same task. The inner product computer greatly reduces computational costs for the solution of a large class of problems, including computerized tomography, image restoration, weather forecasting, and economic modeling.
Classification of Incomplete Pattern Vectors Using Modified Discrminant Functions
Authors: J. Kittler
Venue: IEEE Transactions on Computers (1978)

The problem of classifying incomplete pattern vectors with the discriminant function classifier designed using the MSE criterion design approach is considered. A method for modifying the complete space parameter matrix of the discriminant functions is developed. The method allows the classifier to maintain MSE optimality for operating in any subspace of the pattern space. For full flexibility, only the inverse of the covariance matrix of the data in the F-space need be stored in addition to storing the parameters of the complete space discriminant functions.
Linear Operators on Hyperbola and Hyperboloid
Authors: Moon Ho Lee, Zhu Chen
Venue: Proceedings of the Second International Conference on Systems and Networks Communications (2007)

Jacket matrices which are defined to be m x m matrices J = [j_ik]over a field F with the property JJ^\dag = mI_m , J^\dag is the transpose matrix of elements inverse of J , i.e., J^\dag = [j^{-1}_ik]^T , was introduced by Lee in 1984 and are used for Digital Signal Processing and Coding theory. This paper presents some square matrices A_2n which can be eigenvalue decomposed by Jacket matrices. Specially, A_2 and its extension A_3 can be used for modifying the properties of hyperbola and hyperboloid, respectively. The ideas that we will develop here have applications in computer graphics and used in many important numerical algorithms.
LCS-TRIM: dynamic programming meets XML indexing and querying
Authors: Shirish Tatikonda, Srinivasan Parthasarathy, Matthew Goyder
Venue: Proceedings of the 33rd international conference on Very large data bases (2007)

In this article, we propose a new approach for querying and indexing a database of trees with specific applications to XML datasets. Our approach relies on representing both the queries and the data using a sequential encoding and then subsequently employing an innovative variant of the longest common subsequence (LCS) matching algorithm to retrieve the desired results. A key innovation here is the use of a series of inter-linked early pruning steps, coupled with a simple index structure that enable us to reduce the search space and eliminate a large number of false positive matches prior to applying the more expensive LCS matching algorithm. Additionally, we also present mechanisms that enable the user to specify constraints on the retrieved output and show how such constraints can be pushed deep into the retrieval process, leading to improved response times. Mechanisms supporting the retrieval of approximate matches are also supported. When compared with state-of-the-art approaches, the query processing time of our algorithms is shown to be up to two to three orders of magnitude faster on several real datasets on realistic query workloads. Finally, we show that our approach is suitable for emerging multi-core server architectures when retrieving data for more expensive queries.
An Automatic Tool for Generating Test Cases from the System's Requirements
Authors: Rosziati Ibrahim, Mohd Zainura Saringat, Noraini Ibrahim, Noraida Ismail
Venue: Proceedings of the 7th IEEE International Conference on Computer and Information Technology (2007)

An automatic generator is used to generate programming codes from a specific domain. We use this concept to introduce an automatic tool for software testing, where the tool is used to generate the test cases automatically according to the system's requirements. Manual creation of test cases is time consuming and high costing. The purpose of producing the tool to generate test cases automatically is to reduce the cost of testing the system as well as to save the time of deriving test cases manually. The system's requirements are transformed using use case diagrams, flow of events and sequence diagrams. The flow of events and sequence diagrams are used to check the consistency of the use cases as well as the validity of test cases.
A new bio-inspired location search algorithm for peer to peer network based internet telephony
Authors: Sachin Kulkarni, Niloy Ganguly, Geoffrey Canright, Andreas Deutsch
Venue: Proceedings of the 1st international conference on Bio inspired models of network, information and computing systems (2006)

In this paper, we propose a p2p network based location search algorithm which can be used to establish connections in Internet Telephony. By using the location search algorithm, the caller can identify the peer it is calling. The algorithm is based upon the concept of gradient search and is applicable upon unstructured networks. It is inspired by a biological phenomenon called haptotaxis. The algorithm performs at par with DHT-based location search algorithms, however it is much more robust than such structured algorithms. We also present some initial analysis to explain the reason behind the superiority of the algorithm.
A Super-resolution Reconstruction via Local and Contextual Information Driven Partial Differential Equations
Authors: Liang Xiao, Zhihui Wei
Venue: Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 04 (2007)

This paper addressed the issue of solving the image super-resolution reconstruction from the single or multi- frame low-resolution (LR) image to the required high resolution (HR) image. According to the LR image degradation model, we present a maximum a posteriori estimation (MAP) framework and point out that the problem of the image super-resolution reconstruction can be regarded as the inverse problem considering the minimization of the variational energy functional. Three different energy functionals including total variation integrals, Huber integrals and improved entropic integrals are considered to solve this problem. However, the above mentioned models have not local, contextual information, and thus the mosaic phenomena along image edges can not be effectively reduced. To overcome the bad phenomena, we first present a new contextual magnitude of spatial gradient definition, then propose a new class of local and contextual information driven PDE for super- resolution reconstruction. Finally, a numerical scheme and corresponding iterative algorithm is presented. The performance of all the above mentioned algorithms is compared from the PSNR and edge preservation ability points of view.
Unification of lower-bound analyses of the lift-and-project rank of combinatorial optimization polyhedra
Authors: Sung-Pil Hong, Levent Tunçel
Venue: Discrete Applied Mathematics (2008)

We present a unifying framework to establish a lower bound on the number of semidefinite-programming-based lift-and-project iterations (rank) for computing the convex hull of the feasible solutions of various combinatorial optimization problems. This framework is based on the maps which are commutative with the lift-and-project operators. Some special commutative maps were originally observed by Lovasz and Schrijver and have been used usually implicitly in the previous lower-bound analyses. In this paper, we formalize the lift-and-project commutative maps and propose a general framework for lower-bound analysis, in which we can recapture many of the previous lower-bound results on the lift-and-project ranks.
The Long Tail Takes Over Music
Authors: Greg Goth
Venue: IEEE Internet Computing (2007)

The old idea of radio as the vehicle by which labels introduce new artists to mass audiences and create hit records is rapidly falling by the wayside as artists of all levels of accomplishment use the Internet to launch "do-it-yourself" careers.
Securing Scan Control in Crypto Chips
Authors: David Hély, Frédéric Bancel, Marie-Lise Flottes, Bruno Rouzeyre
Venue: Journal of Electronic Testing: Theory and Applications (2007)

The design of secure ICs requires fulfilling means conforming to many design rules in order to protect access to secret data. On the other hand, designers of secure chips cannot neglect the testability of their chip since high quality production testing is primordial to a good level of security. However, security requirements may be in conflict with test needs and testability improvement techniques that increase both observability and controllability. In this paper, we propose to merge security and testability requirements in a control-oriented design for security scan technique. The proposed security scan design methodology induces an adaptation of two main aspects of testability technique design: protection at protocol level and at scan path level. Without loss of generality, the proposed solution is evaluated on a simple crypto chip in terms of security and design cost.
Computing frequent itemsets inside oracle 10G
Authors: Wei Li, Ari Mozes
Venue: Proceedings of the Thirtieth international conference on Very large data bases - Volume 30 (2004)

Frequent itemset counting is the first step for most association rule algorithms and some classification algorithms. It is the process of counting the number of occurrences of a set of items that happen across many transactions. The goal is to find those items which occur together most often. Expressing this functionality in RDBMS engines is difficult for two reasons. First, it leads to extremely inefficient execution when using existing RDBMS operations since they are not designed to handle this type of workload. Second, it is difficult to express the special output type of itemsets. In Oracle 10G, we introduce a new SQL table function which encapsulates the work of frequent itemset counting. It accepts the input dataset along with some user-configurable information, and it directly produces the frequent itemset results. We present examples of typical computations with frequent itemset counting inside Oracle 10G. We also describe how Oracle dynamically adapts during frequent itemset execution as a result of changes in the nature of the data as well as changes in the available system resources.