ppxscal/embedding_network huggingface dataset:
Comparison of Simulation and Performance Modeling - A Case Study
Authors: Marcel Seelig, Stephan Kluth, Tomasz Porzucek, Flavius Copaciu, Nico Naumann, Steffen Kühn
Venue: Proceedings of the 15th Annual IEEE International Conference and Workshop on the Engineering of Computer Based Systems (2008)

The prediction of the performance at early stages of the development of large software systems has turned out to be a very challenging task. There are already several techniques and methodologies available, each having its own advantages and limitations. This paper discusses using different techniques, one analytical and one simulative, for performance analysis in one case study and compares the results and thereby validates the accuracy of each technique. This paper is a proof of concept for a new modeling technique called FMC-QE (Fundamental Modeling Concepts for Quantitative Evaluation) and the simulation framework Perfact. Perfact simulates the performance of early prototypes in the real application environment. The examined case study is a Web service application run in the SAP environment. It was modeled with use of FMC-QE and simulated with the Perfact framework.
A Classification of Emerging and Traditional Grid Systems
Authors: Heba Kurdi, Maozhen Li, Hamed Al-Raweshidy
Venue: IEEE Distributed Systems Online (2008)

Advances in grid computing are stimulating the emergence of novel types of grids, such as accessible, manageable, interactive, and personal grids. More and more researchers are realizing emerging grids' potential to bridge the gap between grid technologies and users. This review of emerging grids sets out to develop a comprehensive classification of both traditional and emerging grid systems, with an aim to motivate further research and to help establish a solid foundation in this rapidly developing field.
Exploiting correlated keywords to improve approximate information filtering
Authors: Christian Zimmer, Christos Tryfonopoulos, Gerhard Weikum
Venue: Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval (2008)

Information filtering, also referred to as publish/subscribe, complements one-time searching since users are able to subscribe to information sources and be notified whenever new documents of interest are published. In approximate information filtering only selected information sources, that are likely to publish documents relevant to the user interests in the future, are monitored. To achieve this functionality, a subscriber exploits statistical metadata to identify promising publishers and index its continuous query only in those publishers. The statistics are maintained in a directory, usually on a per-keyword basis, thus disregarding possible correlations among keywords. Using this coarse information, poor publisher selection may lead to poor filtering performance and thus loss of interesting documents.1 Based on the above observation, this work extends query routing techniques from the domain of distributed information retrieval in peer-to-peer (P2P) networks, and provides new algorithms for exploiting the correlation among keywords in a filtering setting. We develop and evaluate two algorithms based on single-key and multi-key statistics and utilize two different synopses (Hash Sketches and KMV synopses) to compactly represent publishers. Our experimental evaluation using two real-life corpora with web and blog data demonstrates the filtering effectiveness of both approaches and highlights the different tradeoffs.
Priority encoding transmission
Authors: A. Albanese
Venue: Proceedings of the 35th Annual Symposium on Foundations of Computer Science (1994)

We introduce a novel approach for sending messages over lossy packet-based networks. The new method, called Priority Encoding Transmission, allows a user to specify a different priority on each segment of the message. Based on the priorities, the sender uses the system to encode the segments into packets for transmission. The system ensures recovery of the segments in order of their priority. The priority of a segment determines the minimum number of packets sufficient to recover the segment. We define a measure for a set of priorities, called the rate, which dictates how much information about the message must be contained in each bit of the encoding. We develop systems for implementing any set of priorities with rate equal to one. We also give an information-theoretic proof that there is no system that implements a set of priorities with rate greater than one. This work has applications to multi-media and high speed networks applications, especially in those with bursty sources and multiple receivers with heterogeneous capabilities.
A New Authentication Method with Distributed Hash Table for P2P Network
Authors: Atushi Takeda, Kazuo Hashimoto, Gen Kitagata, Salahuddin Muhammad Salim Zabir, Tetsuo Kinoshita, Norio Shiratori
Venue: Proceedings of the 22nd International Conference on Advanced Information Networking and Applications - Workshops (2008)

In recent years, P2P networks have been evolving at a rapid pace. Authentication of nodes in P2P networks, however, remains a difficult task to conduct efficiently. In this paper, we therefore propose a new authentication method called Hash-based Distributed Authentication Method (HDAM). HDAM realizes a decentralized efficient mutual authentication mechanism for each pair of nodes in the P2P network. It performs a distributed management of public keys by using Web of Trust and Distributed Hash Table. Our proposal significantly reduces both the memory size requirement and the overhead of communication data sent by the nodes.
The edge-pancyclicity of dual-cube extensive networks
Authors: Shih-Yan Chen, Shin-Shin Kao
Venue: Proceedings of the 2nd WSEAS International Conference on Computer Engineering and Applications (2008)

The hypercube family Qn is one of the most well-known interconnection networks in parallel computers, e.g. see [3, 6]. Using Qn, Li et al. introduced dual-cube networks DC(n) and show the vertex symmetry and some fault-tolerant hamiltonian properties of DC(n) [7, 8]. By replacing Qn with any arbitrary graph G in DC(n), a new family of interconnection networks called dual-cube extensive networks, denoted by DCEN(G), was introduced recently [4]. It is proved in [4] that DCEN(G) preserves the hamiltonian connectivity and the globally-3*-connectivity of G. In this article, we prove that DCEN(G) "preserves" the edge-pancyclicity of G as well. More precisely, suppose that every edge G lies on a cycle of length l, where l is an arbitrary integer with 3 ≤ l ≤ |G|. Then for any edge ê of DCEN(G), there exists a cycle in DCEN(G), denoted by Cl, such that ê ∈ Cl and the length of Cl is l for every lmin ≤ l ≤ |DCEN(G)|, where lmin ∈ {3, 8}. The result is shown to be optimal. Furthermore, we prove that the similar results hold when G is a bipartite graph.
Homology modeling, agonist binding site identification, and docking in octopamine receptor of Periplaneta americana
Authors: Akinori Hirashima, Hongwei Huang
Venue: Computational Biology and Chemistry (2008)

AY333178 (from Periplaneta americana, 628 AAs) was selected as a target octopamine receptor (OAR) class OAR2 for this study using Discovery Studio (DS Modeling1.1/1.2, Accelrys Inc.). Blast similarity search was performed and identified that AY333178 contains N-terminal domain of GPCR. Based upon Blast and Pfam results, Rhodopsin 1U19 (protein data bank) was considered as an ideal homologue and used as a template for homology modeling due to its higher X-ray resolution at 2.2A. Sequence alignment between AY333178 and 1U19 was done using Align123 followed by a manual modification. The final alignment was carefully evaluated and evidenced to be matching the conserved residue data for class A GPCR fairly well. The 3D model of AY333178 was generated with MODELER, and further refined using CHARMm. Superimposition of the model was done over the template 1U19. Two fairly consistent profiles were observed demonstrating AY333178 model was reasonable and could be employed for the further docking study. Agonist docking into OAR2 model was done using LigandFit. The superimposition of two top poses of representative agonists was performed with a soft surface generated. Those models are considered to be used in designing new leads for hopefully more active compounds. Further research on the comparison of models for the agonists may elucidate the mechanisms of OAR2-ligand interactions.
A Multiple Regression Approach for Building Genetic Networks
Authors: Shu-Qin Zhang, Wai-Ki Ching, Nam-Kiu Tsing, Ho-Yin Leung, Diane D. Guo
Venue: Proceedings of the 2008 International Conference on BioMedical Engineering and Informatics - Volume 01 (2008)

The construction of genetic regulatory networks from time series gene expression data is an important research topic in bioinformatics as large amounts of quantitative gene expression data can be routinely generated nowadays. One of the main difficulties in building such genetic networks is that the data set has huge number of genes but small number of time points. In this paper, we propose a linear regression model for uncovering the relations among the genes by using multiple regression method with filtering. The model takes into account of the fact that real biological networks have the scale-free property. Based on this property and the statistical tests, a filter can be constructed and the interactions among the genes can be inferred by minimizing the distance between the observed data and the predicted data. Numerical examples based on yeast gene expression data are given to demonstrate our method.
SD Builder®: A production rules-based tool for on-line simulation, decision making and discrete process control
Authors: Serguei Iassinovski, Abdelhakim Artiba, Christophe Fagnart
Venue: Engineering Applications of Artificial Intelligence (2008)

The paper presents and discusses a structure and components of a distributed decision-making system for complex discrete systems (CDSs) and processes control. The decision-making nucleus of the system-system dynamics builder (SD Builder)-is described. The SD Builder is based on a hierarchical object-based representation of a CDS and on a production rules-based representation of discrete processes. It allows the using of on-line simulations, state-graph search, expert systems and other methods for decision making. A conceptual prototype of a sawmill in a timber factory illustrates the concepts described in the paper. In a case of a manufacturing system, the decision-making system makes a part of a manufacturing execution system (MES).
Authenticated routing for ad hoc networks protocol and misbehaving nodes
Authors: Abdalla Mahmoud, Ahmed Sameh, Sherif El Kassas
Venue: Proceedings of the 4th WSEAS International Conference on Telecommunications and Informatics (2005)

In this paper, we analyze one of the secure mobile ad hoc networks protocols, which is Authenticated routing for ad hoc networks (ARAN). Such protocol is classified as a secure reactive routing protocol, which is based on some type of query-reply dialog. That means ARAN does not attempt to continuously maintain the up-to-date topology of the network, but rather when there is a need, it invokes a function to find a route to the destination. Here, we detail how ARAN works, criticize how an authenticated misbehaving node can abuse the bandwidth and propose different solutions for this flaw in the protocol.
Guilt by association as a search principle
Authors: Limsoon Wong
Venue: Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval (2008)

The exploitation of fundamental invariants is among the most elegant solutions to many computational problems in a wide variety of domains. One of the more powerful approaches to exploit invariants is the principle of "guilt by association". In particular, the principle of guilt by association is the foundation of remote homolog detection, protein function prediction, disease subtype diagnosis, treatment plan prognosis, and other challenges in computational biology. The principle suggests that two entities are in a specific relationship if they exhibit invariant properties underlying that relationship. For example, a protein is predicted to have a particular biological function if it exhibits the underlying invariant properties of that functional group---viz., guilty by association to other members of that functional group through the shared invariant properties. In my talk, I plan to present several facets of guilt by association in the computational prediction of protein function and draw parallels of these facets in information retrieval. Specifically, I plan to touch on the following facets: (a) the issue of chance associations; (b) novel generalizable forms of association; (c) fusion of multiple heterogeneous sources of evidence; (d) the dichotomy of knowing to a high degree of reliability that two entities are in some relationship and yet not knowing what that relationship is. I hope this talk will be, for the informational retrieval community, a window to the opportunities in computational biology that may benefit from the depth and variety of solutions information retrieval has to offer.
Assessment of the universal pattern decomposition method using MODIS and ETM data
Authors: Lifu Zhang, N. Fujiwara, S. Furumi, K. Muramatsu, M. Daigo, Liangpei Zhang
Venue: International Journal of Remote Sensing (2007)

The universal pattern decomposition method (UPDM) is a sensor-independent method in which each satellite pixel is expressed as the linear sum of fixed, standard spectral patterns for water, vegetation and soil. The same normalized spectral patterns can be used for different solar-reflected spectral satellite sensors. Supplementary patterns are included when necessary. The UPDM has been applied successfully to simulated data for Landsat/ETM+, Terra/MODIS, ADEOS-II/GLI and 92-band CONTINUE sensors using ground-measured data. This study validates the UPDM using MODIS and ETM+ data acquired over the Three Gorges region of China. The reduced χ2 values for selected area D, that with the smallest terrain influences, are 0.000409 (MODIS) and 0.000181 (ETM+), and the average linear regression factor between MODIS and ETM+ is 1.0077, with root mean square (rms) value 0.0082. The linear regression factor for the vegetation index based on the UPDM (VIUPD) between MODIS and ETM+ data for area D is 1.0089 with rms 0.0696. Both UPDM coefficients and VIUPD are sensor independent for the above sensors.
Biomedical image analysis on a cooperative cluster of GPUs and multicores
Authors: Timothy D.R. Hartley, Umit Catalyurek, Antonio Ruiz, Francisco Igual, Rafael Mayo, Manuel Ujaldon
Venue: Proceedings of the 22nd annual international conference on Supercomputing (2008)

We are currently witnessing the emergence of two paradigms in parallel computing: streaming processing and multi-core CPUs. Represented by solid commercial products widely available in commodity PCs, GPUs and multi-core CPUs bring together an unprecedented combination of high performance at low cost. The scientific computing community needs to keep pace with application models and middleware which scale efficiently to hundreds of internal processing units. The purpose of the work we present here is twofold: first, a cooperative environment is designed so that both parallel models can coexist and complement one another. Second, beyond the parallelism of multiple internal cores, further parallelism is introduced when multiple CPU sockets, multiple GPUs, and multiple nodes are combined within a unique multi-processor platform which exceeds 10 TFLOPS when using 16 nodes. We illustrate our cooperative parallelization approach by implementing a large-scale, biomedical image analysis application which contains a number of assorted kernels including typical streaming operators, co-occurrence matrices, convolutions, and histograms. Experimental results are compared among different implementation strategies and almost linear speed-up is achieved when all coexisting methods in CPUs and GPUs are combined.
An Adaptive Software-Based Deadlock Recovery Technique
Authors: Mohammad Mirza-Aghatabar, Arash Tavakkol, Hamid Sarbazi-Azad, Abbas Nayebi
Venue: Proceedings of the 22nd International Conference on Advanced Information Networking and Applications - Workshops (2008)

Deadlock management has a direct effect on making a reliable connection between processing nodes in parallel computers. Networks using wormhole switching are the most vulnerable networks to deadlock occurrence due to chained blocking nature of this switching method. Different hardware based techniques for deadlock recovery were proposed in the literature which have considerable design complexity, while deadlock occurrence in a network is rare. A software based technique can reduce this cost while preserving performance. The only software based technique proposed in the literature is static and independent of network workload and working conditions. In this paper we present an adaptive software based technique for deadlock recovery, and validate its performance in the presence of different traffic patterns including uniform, hot spot, local and first matrix transpose (FMT) patterns in 8-ary 3-cube network (torus). Simulation results exhibit about 21%, 20%, 98% and 20% performance improvement under local, FMT, hotspot and uniform traffic patterns, respectively.
Automatic evaluation of assistive interfaces
Authors: Pradipta Biswas, Peter Robinson
Venue: Proceedings of the 13th international conference on Intelligent user interfaces (2008)

Computers offer valuable assistance to people with physical disabilities. However designing human-computer interfaces for these users is complicated. The range of abilities is more diverse than for able-bodied users, which makes analytical modelling harder. Practical user trials are also difficult and time consuming. We are developing a simulator to help with the evaluation of assistive interfaces. It can predict the likely interaction patterns when undertaking a task using a variety of input devices, and estimate the time to complete the task in the presence of different disabilities and for different levels of skill. In this paper we describe the different components of the simulator in detail and present a prototype of its implementation.
A Study on Digital Audio Watermarking Internet Applications
Authors: Yiju Wu, Shigeru Shimamoto
Venue: Proceedings of the 2008 IEEE International Conference on Sensor Networks, Ubiquitous, and Trustworthy Computing (sutc 2008) (2008)

This paper aims to explore the feasibility of embedding Cellophane's QR Code in sound watermarking and conducting simultaneous linkage of hidden information through the principles of psychological and physiological models. In the research, we tried to realize the theory through Visual Basic and observed that different type of music would indirectly affect the identifiably of sound watermarking.
Application of Emotional Recognition in Intelligent Tutoring System
Authors: Yanwen Wu, Wei Liu, Jianbo Wang
Venue: Proceedings of the First International Workshop on Knowledge Discovery and Data Mining (2008)

To meet the emotional need in traditional Intelligent Tutoring System (ITS), an intelligent tutoring system model based on emotional recognition technique was proposed in the paper. This model was added the emotional recognition module on the model of traditional intelligent tutoring system. The model of tutoring system based on emotional recognition was constructed with facial expression recognition and text recognition techniques, which can get, recognize and analyze emotional information of students' learning performance, then implement emotional stimulation and emotional tutoring according to different students' learning emotion.
Intra Prediction via Edge-Based Inpainting
Authors: Dong Liu, Xiaoyan Sun, Feng Wu
Venue: Proceedings of the Data Compression Conference (2008)

We investigate the usage of edge-based inpainting as an intra prediction method in block-based image compression. The joint utilization of edge information and the well-known Laplace equation yields a simple and effective inpainting algorithm. As for intra prediction, the edge-based inpainting is a uniform solution, yet adaptive to local image features. During the integration of edge-based inpainting into a block-based coding scheme, edge extraction and coding are jointly considered to achieve the rate-distortion optimization. Our proposed schemes are compared with JPEG2000, and experimental results demonstrate that both PSNR gain and visible quality improvement are achieved.
Exponential Integral Methods for Burgers Equation
Authors: Jing-jun Zhao, Shu-xin Bao, Yu Li
Venue: Proceedings of the Seventh IEEE/ACIS International Conference on Computer and Information Science (icis 2008) (2008)

This paper is concerned with the quasi-linear Burgers equation by using the exponential integral methods. Spatial discretization of this kind of partial differential equations leads to a system of ordinary differential equations, which can be solved by the numerical methods. Furthermore, numerical results show that the exponential integral method has explicit stability, and has the same accuracy as the corresponding Runge-Kutta method.
Distributed selection: a missing piece of data aggregation
Authors: Fabian Kuhn, Thomas Locher, Roger Wattenhofer
Venue: Communications of the ACM (2008)

In this article, we study the problem of distributed selection from a theoretical point of view. Given a general connected graph of diameter D consisting of n nodes in which each node holds a numeric element, the goal of a k-selection algorithm is to determine the kth smallest of these elements. We prove that distributed selection indeed requires more work than other aggregation functions such as, e.g., the computation of the average or the maximum of all elements. On the other hand, we show that the kth smallest element can be computed efficiently by providing both a randomized and a deterministic k-selection algorithm, dispelling the misconception that solving distributed selection through in-network aggregation is infeasible.
Detection SYN Flooding Attacks Using Fuzzy Logic
Authors: Taner Tuncer, Yetkin Tatar
Venue: Proceedings of the 2008 International Conference on Information Security and Assurance (isa 2008) (2008)

Denial of Service attacks are one of the major types of problems in the computer network security. Because they include many other type of attacks they are one of the most frequently used attack methods. In general, DoS attacks are used to block access to the computer networks or personal computers. SYN flooding attack is the most widespread of the DoS attacks. In these attacks normal SYN packets cannot be distinguished from the SYN attack packets. In this paper, we proposea fuzzy logic based system for detecting SYN flooding attacks. Performance of the proposed system has been compared with Cumulative Sum (CUSUM) algorithm.The simulation results show that the proposed system has better performance for low and high intensity attacks than the CUSUM algorithm.