ppxscal/embedding_network huggingface dataset:
S/Kademlia: A practicable approach towards secure key-based routing
Authors: Ingmar Baumgart, Sebastian Mies
Venue: Proceedings of the 13th International Conference on Parallel and Distributed Systems - Volume 02 (2007)

Security is a common problem in completely decentralized peer-to-peer systems. Although several suggestions exist on how to create a secure key-based routing protocol, a practicable approach is still unattended. In this paper we introduce a secure key-based routing protocol based on Kademlia that has a high resilience against common attacks by using parallel lookups over multiple disjoint paths, limiting free nodeId generation with crypto puzzles and introducing a reliable sibling broadcast. The latter is needed to store data in a safe replicated way. We evaluate the security of our proposed extensions to the Kademlia protocol analytically and simulate the effects of multiple disjoint paths on lookup success under the influence of adversarial nodes.
The LilyPad Arduino: Toward Wearable Engineering for Everyone
Authors: Leah Buechley, Michael Eisenberg
Venue: IEEE Pervasive Computing (2008)

The LilyPad Arduino toolkit enables novices to design, engineer, and build their own electronic textiles. The tool not only lets artists and craftspeople experience computational design but also gives children and teenagers a chance to develop longer-term interest in computing and engineering in a fun, creative setting.
Digital Color Image Processing
Authors: Andreas Koschan, Mongi A. Abidi
Venue:  (2008)

An introduction to color in three-dimensional image processing and the emerging area of multi-spectral image processing The importance of color information in digital image processing is greater than ever. However, the transition from scalar to vector-valued image functions has not yet been generally covered in most textbooks. Now, Digital Color Image Processing fills this pressing need with a detailed introduction to this important topic. In four comprehensive sections, this book covers: The fundamentals and requirements for color image processing from a vector-valued viewpoint Techniques for preprocessing color images Three-dimensional scene analysis using color information, as well as the emerging area of multi-spectral imaging Applications of color image processing, presented via the examination of two case studies In addition to introducing readers to important new technologies in the field, Digital Color Image Processing also contains novel topics such as: techniques for improving three-dimensional reconstruction, three-dimensional computer vision, and emerging areas of safety and security applications in luggage inspection and video surveillance of high-security facilities. Complete with full-color illustrations and two applications chapters, Digital Color Image Processing is the only book that covers the breadth of the subject under one convenient cover. It is written at a level that is accessible for first- and second-year graduate students in electrical and computer engineering and computer science courses, and that is also appropriate for researchers who wish to extend their knowledge in the area of color image processing.
Using Probabilistic Characterization to Reduce Runtime Faults in HPC Systems
Authors: Jim Brandt, Bert Debusschere, Ann Gentile, Jackson Mayo, Philippe Pébay, David Thompson, Matthew Wong
Venue: Proceedings of the 2008 Eighth IEEE International Symposium on Cluster Computing and the Grid (2008)

The current trend in high performance computing is to aggregate ever larger numbers of processing and interconnection elements in order to achieve desired levels of computational power, This, however, also comes with a decrease in the Mean Time To Interrupt because the elements comprising these systems are not becoming significantly more robust. There is substantial evidence that the Mean Time To Interrupt vs. number of processor elements involved is quite similar over a large number of platforms. In this paper we present a system that uses hardware level monitoring coupled with statistical analysis and modeling to select processing system elements based on where they lie in the statistical distribution of similar elements. These characterizations can be used by the scheduler/resource manager to deliver a close to optimal set of processing elements given the available pool and the reliability requirements of the application.
Regional and Global Dynamics in East Asia: A Data Mining Experience
Authors: Subana Shanmuganathan, Manchuna Shanmuganathan
Venue: Proceedings of the 2008 Second Asia International Conference on Modelling & Simulation (AMS) (2008)

Data mining (DM) has almost become an essential tool in this digital era. Research into developing novel methodologies to mining the ever-growing data and applying them to analysing a wide range of issues has never been so vigorous. DM applications including that of business intelligence attest remarkable success. This paper elaborates upon such a DM experience on how macro economic digital data from multiple sources could be mined to discover interesting developments in the regional and global dynamics of an emerging East Asian Community (EAC). Following a brief introduction to the former Malaysian Prime Minster Mahathir Mohamed’s initiatives to form an EAC, the World Bank and ASEAN Financial Macroeconomic Surveillance Unit data are analysed to see how the numbers stack up. The application gives an example of how the needs of a modern society, to model regional and global dynamics of nations of interest could be met using DM techniques and digital data.
Processor Verification with hwBugHunt
Authors: Sangeetha Sudhakrishnan, Liying Su, Jose Renau
Venue: Proceedings of the 9th international symposium on Quality Electronic Design (2008)

Functional verification of modern processors and complex ASIC designs is a challenging task. Verification is frequently more complex than the design itself. The time required to find the exact source of an error in complex designs represents a significant part of the verification process. Most test suites only report the existence of a bug, but are unable to ultimately discover the line of HDL code where the bug is located. Designing new tools and techniques that reduce these overheads is very important to keep the verification costs under control. This paper proposes a novel HDL error-discovery tool (hwBugHunt) to pinpoint the line of code where a bug is located. hwBugHunt works by instrumenting Verilog code and gathering statistics during the execution of various testbenches. The proposed infrastructure is tested on an Alpha-like 21264 Verilog implementation. Our evaluation shows that hwBugHunt pinpoints 62% of the bugs introduced on IVM, and it does so with a low overhead and high accuracy.
Coordination of Rescue Robots for Real-Time Exploration Over Disaster Areas
Authors: Hisayoshi Sugiyama, Tetsuo Tsujioka, Masashi Murata
Venue: Proceedings of the 2008 11th IEEE Symposium on Object Oriented Real-Time Distributed Computing (2008)

A coordination procedure is proposed for a multi-robot rescue system that performs real-time exploration over disaster areas. Real-time exploration means that every robot exploring the area always has a communication path to human operators standing by a monitor station and that the communication path is configured by ad hoc wireless networking. The proposed system procedure consists of the autonomous classification of robots into search and relay types and behavior algorithms for each class of robot. Search robots explore the areas and relay robots act as relay terminals between search robots and monitor station. The rule of the classification and the behavior algorithm refer to the forwarding table of each robot constructed for ad hoc networking. Computer simulations are executed with the decision-theoretic approach as the exploration strategy of search robots.
Oscillation criteria for first-order impulsive differential equations with positive and negative coefficients
Authors: Jianhua Shen, Ziran Zou
Venue: Journal of Computational and Applied Mathematics (2008)

Some sufficient conditions are obtained for oscillation of all solutions of the first-order impulsive differential equation with positive and negative coefficients[x(t)-R(t)x(t-r)]^'+P(t)x(t-@t)-Q(t)x(t-@s)=0,@t>=@s>0,t>=t"0,x(t"k^+)=I"k(x(t"k)),k=1,2,....Our results improve the known results in the literature.
Privacy-Preserving Distributed Set Intersection
Authors: Qingsong Ye, Huaxiong Wang, Christophe Tartary
Venue: Proceedings of the 2008 Third International Conference on Availability, Reliability and Security (2008)

With the growing demand of databases outsourcing and its security concerns, we investigate privacy-preserving set intersection in a distributed scenario. We propose a one-round protocol for privacy-preserving set intersection based on a combination of secret sharing scheme and homomorphic encryption. We then show that, with an extra permutation performed by each contacted server, the cardinality of set intersection can be computed efficiently. All protocols constructed in this paper are provably secure against an honest-but-curious adversary under the Decisional Diffie-Hellman assumption.
All (k;g)-cages are k-edge-connected
Authors: Yuqing Lin, Mirka Miller, Chris Rodger
Venue: Journal of Graph Theory (2005)

A (k;g)-cage is a k-regular graph with girth g and with the least possible number of vertices. In this paper, we prove that (k;g)-cages are k-edge-connected if g is even. Earlier, Wang, Xu, and Wang proved that (k;g)-cages are k-edge-connected if g is odd. Combining our results, we conclude that the (k;g)-cages are k-edge-connected. &copy; 2005 Wiley Periodicals, Inc. J Graph Theory 48: 219&ndash;227, 2005
M-Ring: A Distributed, Self-Organized, Load-Balanced Communication Method on Super Peer Network
Authors: Tsung-Han Lin, Tsung-Hsuan Ho, Yu-Wei Chan, Yeh-Ching Chung
Venue: Proceedings of the The International Symposium on Parallel Architectures, Algorithms, and Networks (2008)

Many peer-to-peer file sharing systems have been proposed to take the locality and heterogeneity into account. The two-layered architecture is one of the most wide spread systems with abilities by classifying peers into groups and serving some powerful peers as the super peers. In order to communicate with other sets of super peers, each super peer has to connect with all the other super peers within its neighboring group or other groups by some gateway-like super peers. However, it may be the problem of the single-point-of-failure if using peers as the gateway-like peers. In this paper, we propose a distributed, self-organized and load-balanced communication method – M-Ring. In this method, each super peer connects with other sets of super peers within its neighboring group by constructing its link table. Also, each super peer in the different groups has a unique identity within the same identity space. Besides, we notice a “overlap handle scope” feature while all super peers who are in the different groups are in the same identity space. We use this feature to enhance the efficiency of query of super peers. Our method can reduce the total requirements of storage space and bandwidth by storing different portion of metadata. The simulation results show that our approach efficiently reduces the overhead of connections among super peers within their neighboring groups.
MMsINC®: A New Public Large-Scale Chemoinformatics Database System
Authors: M. Fanton, M. Floris, G. Frau, M. Sturlese, J. Masciocchi, P. Palla, F. Cedrati, P. Rodriguez-Tomé, S. Moro
Venue: Proceedings of the 2008 International Conference on Biocomputation, Bioinformatics, and Biomedical Technologies (2008)

MMsINC is a free web-oriented database of commercially available compounds for virtual screening and chemoinformatic applications. MMsINC contains over 4 million non-redundant chemical compounds in 3D format. The whole database was studied in term of uniqueness, diversity, frameworks, chemical reactivity, drug-like and lead-like properties. This study shows that there are more than 175.000 frameworks in our database. There are 3.89 millions (98%) of drug-like molecules among which more than 3.61 millions (91%) are lead-like. Moreover, 3.45 million (87%) are considered chemically stable compounds. The druglikeness and leadlikeness are estimated using Lipinski and Oprea cut-off values. The compounds are stored in a PostgreSQL database and the code to manage this database is in Java. Moreover, MMsINC is nicely integrated with PubChem and PDB databases facilitating the cross exchange of ligand information. In consequence, we have a free and easily updatable system for chemical databases management and screening sets generation. MMsINC is accessible at the following web address: http://mms.dsfarm.unipd.it/MMsINC/.
A Value-Added Predictive Defect Type Distribution Model Based on Project Characteristics
Authors: Youngki Hong, Jongmoon Baik, In-Young Ko, Ho-Jin Choi
Venue: Proceedings of the Seventh IEEE/ACIS International Conference on Computer and Information Science (icis 2008) (2008)

In software project management, there are three major factors to predict and control; size, effort, and quality. Much software engineering work has focused on these. When it comes to software quality, there are various possible quality characteristics of software, but in practice, quality management frequently revolves around defects, and delivered defect density has become the current de facto industry standard. Thus, research related to software quality has been focused on modeling residual defects in software in order to estimate software reliability. Currently, software engineering literature still does not have a complete defect prediction for a software product although much work has been performed to predict software quality.On the other side, the number of defects alone cannot be sufficient information to provide the basis for planning quality assurance activities and assessing them during execution. That is, for project management to be improved, we need to predict other possible information about software quality such as in-process defects, their types, and so on. In this paper, we propose a new approach for predicting the distribution of defects and their types based on project characteristics in the early phase. For this approach, the model for prediction was established using the curve-fitting method and regression analysis. The maximum likelihood estimation (MLE) was used in fitting the Weibull probability density function to the actual defect data, and regression analysis was used in identifying the relationship between the project characteristics and the Weibull parameters. The research model was validated by cross-validation.
Detection and segmentation of moving vehicles and trains using Gaussian mixtures, shadow detection and morphological processing
Authors: Piotr Dalka
Venue: Machine Graphics Vision International Journal (2006)

The solution presented in this paper combines background modelling, shadow detection and morphological and temporal processing into a single system responsible for detection and segmentation of moving objects recorded with a static camera. Vehicles and trains are detected based on their pixel-level difference with respect to a continually updated background model, using a Gaussian mixture calculated separately for every pixel. The shadow detection method utilizes a colour model which allows for estimating chromatic and brightness differences between the pixel colour and the background model. Morphological and temporal operations performed on binary images denoting moving objects include connecting the components, closing and temporal filtering. Experiments carried out involve employing implemented algorithms to detect vehicles and trains in video sequences. The results achieved are described and illustrated in figures.
Teaching Service-Oriented Computing and STEM Topics via Robotic Games
Authors: W. T. Tsai, Xin Sun, Yinong Chen, Qian Huang, Gary Bitter, Mary White
Venue: Proceedings of the 2008 11th IEEE Symposium on Object Oriented Real-Time Distributed Computing (2008)

This paper proposes a new approach to teach the STEM (Science, Technology, Engineering, and Mathematics) knowledge informally via robotic games. In this approach, a robotic playground is built to provide a hands-on programming and playing experience with robots controlled by Service-Oriented Computing (SOC) software, which is based on a new approach that uses reusable services (components) with standard interfaces and platform-independent interoperability. Services in the repository are annotated with STEM knowledge to enforce the required contents. In this way, students can learn computing and STEM in an entertaining manner.
HPC for iterative image reconstruction in CT
Authors: Cameron Melvin, Meilian Xu, Parimala Thulasiraman
Venue: Proceedings of the 2008 C3S2E conference (2008)

Algebraic Reconstruction Techniques (ART) for computed tomography (CT) have proven to produce better images with fewer projections, hence, reducing the side-effects of the carcinogenic nature of X-ray imaging. However, the iterative nature of ART prohibits its commercial use because of the long processing time. Parallel processing through high performance computers (HPC) is one solution to speedup ART algorithm. The work discussed in the literature on parallel computing and CT primarily focuses on the algorithms based on Fourier techniques, with a lack of development of parallel approaches for ART techniques. The main reason for this has been the extensive computational requirements needed for this algorithm. With the boom in information technology and advanced architectures, we show in this paper that the ART algorithm can be parallelized on high performance computers, with significant performance gain while maintaining the image quality. In this paper, we examine the efficiency of ART on a shared memory machine available on the Western Canada Research Grid consortium without impeding image quality. We show that a 6 processor IBM P-server could reconstruct the same image from 36 angles in approximately 5.038 seconds (36 processors is 1.183 seconds), with an efficiency of 93.35%. In other words, a parallel algorithm reconstruction could be done in about the same amount of time as a 180 angle sequential Fourier back projection reconstruction, yielding approximately equivalent image quality, with an 80% reduction in dose.
Micro-Injection System for Localized Drug Delivery Using Embedded Solid Chemical Propellant
Authors: Jae-won Ban, Kyo-in Koo, Sunkil Park, Gilsub Kim, Dong-il "Dan Cho
Venue: Proceedings of the 2007 Frontiers in the Convergence of Bioscience and Information Technologies (2007)

This paper presents a novel micro-injection system for localized drug delivery using embedded solid chemical propellant, azobisisobutyronitrile (AIBN). This system consists of in-plane type of microneedles, a drug reservoir, a chemical fluid source, a chemical fluid source chamber, and a microheater. The AIBN decomposes and produces nitrogen gas and a free radical at about 70. Using this phenomenon, the AIBN on the microheater generates nitrogen gas by supplying an electrical power, and then the generated nitrogen gas injects a drug in the drug reservoir through the micro channel buried at the microneedles. This micro-injection system injects 2.29 ~ 2.9 µl blue ink during about 6 seconds by supplying 30.4 V and 164 mA. This novel injection system is expected to be applicable to the highly precise biological equipments. Key words: micro-injection, drug delivery, azobisisobutyronitrile (AIBN), microneedles, microheater
Assigning functional linkages to proteins using phylogenetic profiles and continuous phenotypes
Authors: Orland Gonzalez, Ralf Zimmer
Venue: Bioinformatics (2008)

Motivation: A class of non-homology-based methods for protein function prediction relies on the assumption that genes linked to a phenotypic trait are preferentially conserved among organisms that share the trait. These methods typically compare pairs of binary strings, where one string encodes the phylogenetic distribution of a trait and the other of a protein. In this work, we extended the approach to automatically deal with continuous phenotypes. Results: Rather than use a priori rules, which can be very subjective, to construct binary profiles from continuous phenotypes, we propose to systematically explore thresholds which can meaningfully separate the phenotype values. We illustrate our method by analyzing optimal growth temperatures, and demonstrate its usefulness by automatically retrieving genes which have been associated with thermophilic growth. We also apply the general approach, for the first time, to optimal growth pH, and make novel predictions. Finally, we show that our method can also be applied to other properties which may not be classically considered as phenotypes. Specifically, we studied correlations between genome size and the distribution of genes. Contact: orlandgonzalez@gmail.com Supplementary information: Supplementary data are available at Bioinformatics online.
Ensemble Methods for Ontology Learning - An Empirical Experiment to Evaluate Combinations of Concept Acquisition Techniques
Authors: Ricardo Gacitua, Pete Sawyer
Venue: Proceedings of the Seventh IEEE/ACIS International Conference on Computer and Information Science (icis 2008) (2008)

Most approaches to ontology learning combine techniques from different areas (hybrid approaches) to increase the efficiency of the ontology learning process. However, the results from the ontology learning process do not fully satisfy the users at present. An important problem is that there is a lack of quantitative and comparative data about the efficiency of techniques and technique combinations applied to ontology learning. Combination methods are an effective way of improving system performance, but there is not enough information about how to use, configure and combine techniques from a diverse spectrum of fields, and what the contribution of a specific technique or technique combination. In this paper we present a quantitative comparison of technique combinations for concept extraction and a software system (OntoLancs) to support the evaluation of techniques. By applying OntoLancs, users are able to assist the process of building ontologies by semi-automatically acquiring concepts from large-scale domain document collections and experiment with different combinations of knowledge acquisition techniques to refine and organize domain concepts into a taxonomy. Quantitative and comparative studies about the performance of several techniques and user experiences indicate the applicability and usefulness of our approach.
A new multiobjective genetic algorithm with heterogeneous population for solving flowshop scheduling problems
Authors: Hiroyuki Tamura
Venue: International Journal of Computer Integrated Manufacturing (2007)

The present paper discusses the application of a new genetic algorithm (GA) featuring heterogeneous population to solve multiobjective flowshop scheduling problems. Many GAs have been developed to solve multiobjective scheduling problems, but they used a non-heterogeneous population approach, which could lead to premature convergence and local Pareto-optimum solutions. Our experiments with a 20-job and 20-machine benchmark problem given in Taillard (1993) show that the heterogeneous multiobjective genetic algorithm (hMGA) developed in this research outperforms NSGA-II (Deb 2001) one of the widely used algorithms with non-heterogeneous population. Moreover, in this paper we also present the comparison of hMGA with another meta-heuristic method, i.e. multi-objective simulated annealing (MOSA), proposed by Varadharajan and Rajendran (2005). This research concludes that hMGA developed in this work is promising as it can produce a new set of Pareto-optimum solutions that have not been found by MOSA before.