ppxscal/embedding_network huggingface dataset:
A Synthesis Algorithm for Hybrid Systems
Authors: Srikanth Gottipati, Anil Nerode
Venue: Proceedings of the international symposium on Logical Foundations of Computer Science (2007)

Hybrid systems are systems of continuous plants, subject to disturbances, interacting with sequential automata in a network. By the synthesis problem for hybrid systems we mean extracting a finite state digital controller automaton from the system equations, constraints, and cost function which define the hybrid system. This automaton senses system state, and on the basis of its state, changes state and issues a chattering control to the actuators to control the system with epsilon optimal control for a fixed epsilon in real time. We address this problem by extracting a local cost function for the control system which transforms the infinite-dimensional optimization problem into a finite-dimensional problem.
On the intermodal interactions of waves
Authors: Ligia Munteanu
Venue: Proceedings of the 9th WSEAS International Conference on Acoustics & Music: Theory & Applications (2008)

In this paper some physical phenomena are explained by means of intermodal interaction of waves. The subharmonic generation of waves in piezoelectric plates with Cantor-like structure, the interaction of internal solitary waves of different modes in an incompressible fluid with an exponential stratification in densities and the turbulent flow of a micropolar fluid downwards on an inclined open channel, are explained by nonlinear superposition of cnoidal waves in both phonon and fracton vibration regimes.
The association between the use of accelerated math and students' math achievement
Authors: Nancy Dishner
Venue:  (2005)

The purpose of this study was to explore the relationship between time spent on a computer managed integrated learning system entitled Accelerated Math and traditional mathematics instruction on achievement as measured by standardized achievement tests of elementary school students. The variables of ability level, special education, grade, socioeconomic status, gender, classroom teacher, school attended, and degree of implementation were also considered. The population consisted of 542 students who were sixth, seventh, and eighth graders during the 2003-2004 school year and took the TerraNova each year. Data were gathered that covered the three-year period beginning in 2001 and ending in 2004. A t test for independent samples, analysis of variance (ANOVA), and analysis of covariance (ANCOVA) were used to identify the relationship between variables. The researcher&rsquo;s investigation of the relationship between Accelerated Math use and mathematics achievement might assist educators in planning for use of technology as a supplement to traditional instruction. The information gathered from this research might be beneficial to other school systems seeking information on the relationship between a computer-managed integrated learning system and math achievement. The findings in this study were mixed. The use of Accelerated Math was associated with no effects and negative effects depending on the degree of implementation. The findings indicated that there were measurable differences in the performance of students who received Accelerated Math compared to students who did not receive Accelerated Math. Students who did not receive Accelerated Math had higher overall scores than students participating in the intervention. The study indicated that gender, special education, and ability groups did not have a significant interaction with the intervention (participation in Accelerated Math). The research revealed that there was a socioeconomic status interaction intervention with proficiency scores. The study revealed that there was a significant intervention interaction with school, teacher, and grade. There was a significant interaction intervention for both proficiency and value-added scores for each of these three independent variables. In addition, the research revealed that the degree of implementation was a significant factor in students' achievement.
Revisiting Wiener's Attack --- New Weak Keys in RSA
Authors: Subhamoy Maitra, Santanu Sarkar
Venue: Proceedings of the 11th international conference on Information Security (2008)

In this paper we revisit Wiener's method (IEEE-IT, 1990) of continued fraction (CF) to find new weaknesses in RSA. We consider RSA with N = pq, q < p < 2q, public encryption exponent e and private decryption exponent d. Our motivation is to find out when RSA is insecure given d is O(n ¿ ), where we are mostly interested in the range 0.3 ≤ ¿ ≤ 0.5. We use both the upper and lower bounds on ¿(N) and then try to find out what are the cases when $\frac{t}{d}$ is a convergent in the CF expression of $\frac{e}{N - \frac{3}{\sqrt{2}} \sqrt{N} + 1}$. First we show that the RSA keys are weak when d = N ¿ and $\delta , where 2q ¿ p = N ¿ and ¿ is a small value based on certain parameters. This presents additional results over the work of de Weger (AAECC 2002). Further we show that, the RSA keys are weak when $d and e is $O(N^{\frac{3}{2}-2\delta})$ for $\delta \leq \frac{1}{2}$. Using similar idea we also present new results over the work of Blömer and May (PKC 2004).
Exponential Stability of Discrete-Time Cohen-Grossberg Neural Networks with Delays
Authors: Changyin Sun, Liang Ju, Hua Liang, Shoulin Wang
Venue: Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks (2007)

Discrete-time Cohen-Grossberg neural networks(CGNNs) are studied in this paper. Several sufficient conditions are obtained to ensure the global exponential stability of the discrete-time systems of CGNNs with delays based on Lyapunov methods. The obtained results have not assume the symmetry of the connection matrix, and monotonicity, boundness of the activation functions.
Expressive Commerce and Its Application to Sourcing: How We Conducted $25 Billion of Generalized Combinatorial Auctions
Authors: Tuomas Sandholm
Venue: Proceedings of the 3rd international conference on Algorithmic Aspects in Information and Management (2007)

Sourcing professionals buy several trillion dollars worth of goods and services yearly. We introduced a new paradigm called expressive commerce and applied it to sourcing. It combines the advantages of highly expressive human negotiation with the advantages of electronic reverse auctions. The idea is that supply and demand are expressed in drastically greater detail than in traditional electronic auctions, and are algorithmically cleared. This creates a Pareto efficiency improvement in the allocation (a win-win between the buyer and the sellers) but the market clearing problem is a highly complex combinatorial optimization problem. We developed the world's fastest tree search algorithms for solving it. We have hosted $25 billion of sourcing using the technology, and created $3.2 billion of hard-dollar savings plus numerous harder-to-quantify benefits. The suppliers also benefited by being able to express production efficiencies and creativity, and through exposure problem removal. Supply networks were redesigned, with quantitative understanding of the tradeoffs, and implemented in weeks instead of months.URL for the paper: http://www.cs.cmu.edu/~sandholm/Expressive%20commerce.aimag.pdf
Algebraic Cryptanalysis of CTRU Cryptosystem
Authors: Nitin Vats
Venue: Proceedings of the 14th annual international conference on Computing and Combinatorics (2008)

CTRU, a public key cryptosystem was proposed by Gaborit, Ohler and Sole. It is analogue of NTRU, the ring of integers replaced by the ring of polynomials $\mathbb{F}_2[T]$. It attracted attention as the attacks based on either LLL algorithm or the Chinese Remainder Theorem are avoided on it, which is most common on NTRU. In this paper we presents a polynomial-time algorithm that breaks CTRU for all recommended parameter choices that were derived to make CTRU secure against popov normal form attack. The paper shows if we ascertain the constraints for perfect decryption then either plaintext or private key can be achieved by polynomial time linear algebra attack. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
Implementation of Filters for Image Pre-processing for Leaf Analyses in Plantations
Authors: Jacqueline Gomes Mertes, Norian Marranghello, Aledir Silveira Pereira
Venue: Proceedings of the 8th international conference on Computational Science, Part II (2008)

In this work an image pre-processing module has been developed to extract quantitative information from plantation images with various degrees of infestation. Four filters comprise this module: the first one acts on smoothness of the image, the second one removes image background enhancing plants leaves, the third filter removes isolated dots not removed by the previous filter, and the fourth one is used to highlight leaves' edges. At first the filters were tested with MATLAB, for a quick visual feedback of the filters' behavior. Then the filters were implemented in the C programming language. At last, the module as been coded in VHDL for the implementation on a Stratix II family FPGA. Tests were run and the results are shown in this paper.
Real-Time Traffic Packet Scheduling Algorithm in HSDPA System Considering the Maximum Tolerable Delay and Channel Assignment
Authors: Xiaodong Yu, Sung Won Kim, Yong Wan Park
Venue: Proceedings of the 3rd international conference on Embedded Software and Systems (2007)

In this paper, we consider a new packet scheduling algorithm for real time traffic in the high speed downlink packet access system that has been introduced for WCDMA system to providing high transmission rates. The objective of the design is to meet the maximum tolerable delay and consider the channel assigning based on the received SIR for real-time traffic users. The proposed scheduling algorithm shows that the users are ranked by the ratios of the bits in the buffer to the residual time for transmission, the ranked users are assigned channels based on the SIR value table and get service one by one. The simulation results show that the proposed algorithm can provide the lower packet drop rate for real time quality of service (QoS) requirement.
Clock Synchronization in Cell BE Traces
Authors: Marina Biberstein, Yuval Harel, Andre Heilper
Venue: Proceedings of the 14th international Euro-Par conference on Parallel Processing (2008)

Cell BE is a heterogeneous multicore processor that has been developed as a means for efficient execution of parallel and vectorizable applications with high computation and memory requirements. The transition to multicores introduces the challenge of providing tools that help programmers tune their code running on these architectures. Tracing tools, in particular, often help locate performance problems related to thread and process communication.A major impediment to implementing tracing on Cell is the absence of a common clock that can be accessed at low cost from all cores. The OS clock is costly to access from the auxiliary cores and the hardware timers cannot be simultaneously set on all the cores. In this paper, we describe an offline trace analysis that assigns wall-clock time to trace records based on their thread-local time stamps and event order. Our experiments on several Cell SDK workloads show that the indeterminism in assigning the wall-clock time is low, on average 20---40 clock ticks (1.4---2.8 μs for 14.8 MHz clock). We also show how various practical problems, such as the imprecision of time measurement, can be overcome.
Universal active voltage filter using single minus-type current feedback amplifier
Authors: Chun-Ming Chang, Yi-Chuan Lin, Shu-Hui Tu, Chun-Li Hou, Jiun-Wei Horng
Venue: Proceedings of the 7th WSEAS International Conference on Applied Computer and Applied Computational Science (2008)

The realization of the second-order universal (low-pass, band-pass, high-pass, band-reject, and all-pass) activevoltage filter using a single minus-type current feedback amplifier (CFA), two capacitors, and two resistosrs is proposed in this paper. The different choice of three voltage input signals determines the five generic filtering output signals. H-Spice simulations with 0.35µm process are used to validate the theoretical predictions of the filtering output signals, and show its low sensitivities and the sensitivity frequency responses.
Turing degrees of reals of positive effective packing dimension
Authors: Rod Downey, Noam Greenberg
Venue: Information Processing Letters (2008)

A relatively longstanding question in algorithmic randomness is Jan Reimann's question whether there is a Turing cone of broken dimension. That is, is there a real A such that {B:B=
Model-Driven Platform-Specific Testing through Configurable Simulations
Authors: Thomas Kuhn, Reinhard Gotzhein
Venue: Proceedings of the 4th European conference on Model Driven Architecture: Foundations and Applications (2008)

The increasing size and complexity of software systems requires sophisticated testing methodologies. Since platform limitations could void the results of test suites, especially the embedded systems domain requires testing methodologies that also consider hardware resources. Current approaches for specifying and executing test cases, e.g. approaches based on the UML testing model, do not support the concept of platform testing very well. Deployment descriptions are only used for documentation. In this work, we address this problem by providing an extension to the UML testing profile that covers the modeling of platform testing models, which include realistic deployments, and by C-PartsSim, our simulation tool that is capable of executing these platform testing models. With C-PartsSim, it is possible to connect specialized simulators at runtime, thereby providing a configurable, platform-specific system simulation for testing. We describe the automatic transformation from scenario models to a tailored simulator instance for a concrete testing scenario and present case studies to demonstrate the flexibility and accuracy of our approach.
A Methodology Using Neural Network to Cluster Validity Discovered from a Marketing Database
Authors: Renato José Sassi, Leandro Augusto da Silva, Emilio Del Moral Hernandez
Venue: Proceedings of the 2008 10th Brazilian Symposium on Neural Networks (2008)

The databases of real world contains a huge volume of data and among them there are hidden piles of interesting relations that are actually very hard to find out. The knowledge discovery databases (KDD) appear as a possible solution to find out such relations aiming at converting information into knowledge. However, not a data presented in the bases are useful to a KDD. Usually, data are processed before being presented to a KDD aiming at reducing the amount of data and also at selecting more relevant data to be used by the system. The purpose of this paper is to describe a validation methodology, through of a MLP neural network, to the knowledge discovered by a Hybrid Architecture composed by Rough Sets Theory used to pre-processing the data to be presented to Self-Organizing Maps neural network, which data cluster.
Detection of AIBO and Humanoid Robots Using Cascades of Boosted Classifiers
Authors: Matías Arenas, Javier Ruiz-Del-Solar, Rodrigo Verschae
Venue: RoboCup 2007: Robot Soccer World Cup XI (2008)

In the present article a framework for the robust detection of mobile robots using nested cascades of boosted classifiers is proposed. The boosted classifiers are trained using Adaboost and domain-partitioning weak hypothesis. The most interesting aspect of this framework is its capability of building robot detection systems with high accuracy in dynamical environments (RoboCup scenario), which achieve, at the same time, high processing and training speed. Using the proposed framework we have built robust AIBO and humanoid robot detectors, which are analyzed and evaluated using real-world video sequences.
A Faster Estimation Algorithm for Periodic Preventive Rejuvenation Schedule Maximizing System Availability
Authors: Koichiro Rinsaka, Tadashi Dohi
Venue: Proceedings of the 4th international symposium on Service Availability (2007)

It is of great importance to perform preventive rejuvenation of software systems with service degradation. In this paper we develop a faster estimation algorithm for the optimal periodic rejuvenation schedule which maximizes the steady-state system availability. In the case with unknown system failure time distribution, a non-parametric estimation approach based on the empirical distribution of system failure time has been proposed in the literature, but often failed to obtain the exact estimates for the small sample cases. We improve the existing availability estimation algorithm in terms of convergence speed and derive the more effective estimation scheme based on the kernel density of system failure time. Throughout simulation experiments, the proposed estimation scheme is compared with the existing approach and can be validated in the sense of asymptotic optimality.
Impact of Buffer Map Cheating on the Streaming Quality in DONet
Authors: Yong Cui, Dan Li, Jianping Wu
Venue: Proceedings of the 7th international conference on Computational Science, Part IV: ICCS 2007 (2007)

Data-driven Overlay Network (DONet) is especially suitable for live stream in P2P environment. However, it demands the cooperation of individual nodes to exchange their buffer maps. Since these nodes are selfish and have their own interests, they might cheat about their buffer maps to reduce the forwarding burden. We analyze the impact of this kind of cheating behavior on the streaming quality of DONet by experiment in this paper. The experimental results show that buffer map cheating has considerable negative impact on the streaming quality in DONet.
An efficient dynamic resource allocation algorithm for packet-switched communication networks based on Hopfield neural excitation method
Authors: D. Calabuig, J. F. Monserrat, D. Gómez-Barquero, O. Lázaro
Venue: Neurocomputing (2008)

Dynamic Resource Allocation (DRA) algorithms set up different connections over the same resources and perform a scheduling policy to distribute the resources usage. Recently, intelligent DRA techniques based on Hopfield Neural Networks computational methods have been proposed, showing their potential for solving this kind of complex optimization problems. However, the initial algorithms suffer from severe instability problems impacting performance. This paper addresses these specific limitations stressing the proper neuron dynamics and proposing an efficient energy formulation and an optimum calculation of the weighting coefficients. These changes result in a maximum resource utilization together with an optimized neural network convergence.
Case-Based Reasoning in Robot Indoor Navigation
Authors: Alessandro Micarelli, Stefano Panzieri, Giuseppe Sansonetti
Venue: Proceedings of the 7th international conference on Case-Based Reasoning: Case-Based Reasoning Research and Development (2007)

In this paper, we advance a novel approach to the problem of autonomous robot navigation. The environment is a complex indoor scene with very little a priori knowledge, and the navigation task is expressed in terms of natural language directives referring to natural features of the environment itself. The system is able to analyze digital images obtained by applying a sensor fusion algorithm to ultrasonic sensor readings. Such images are classified in different categories using a case-based approach. The architecture we propose relies on fuzzy theory for the construction of digital images, and wavelet functions for their representation and analysis.
Applying Neural Networks to Control Gait of Simulated Robots
Authors: Milton Roberto Heinen, Fernando Santos Osório
Venue: Proceedings of the 2008 10th Brazilian Symposium on Neural Networks (2008)

This paper describes LegGen simulator, used to automatically create and control stable gaits for legged robots into a physically based simulation environment. In our approach, the gait is defined using two different methods: a finite state machine based on robot's leg joint angles sequences; and a recurrent neural network. The parameters for both methods are optimized using genetic algorithms. The model validation was performed by several experiments realized with a robot simulated using Open Dynamics Engine (ODE) physical simulation engine. The results showed that it is possible to generate stable gaits using genetic algorithms in an efficient manner, using these two different methods.
Optimal control for stochastic nonlinear singular system using neural networks
Authors: N. Kumaresan, P. Balasubramaniam
Venue: Computers Mathematics with Applications (2008)

In this paper, optimal control for stochastic nonlinear singular system with quadratic performance is obtained using neural networks. The goal is to provide optimal control with reduced calculus effort by comparing the solutions of the matrix Riccati differential equation (MRDE) obtained from the well-known traditional Runge-Kutta (RK) method and nontraditional neural network method. To obtain the optimal control, the solution of MRDE is computed by feedforward neural network (FFNN). The accuracy of the solution of the neural network approach to the problem is qualitatively better. The advantage of the proposed approach is that, once the network is trained, it allows instantaneous evaluation of solution at any desired number of points spending negligible computing time and memory. The computation time of the proposed method is shorter than the traditional RK method. An illustrative numerical example is presented for the proposed method.
A strategy to reduce the control packet load of MANETs with bidirectional links using DSR
Authors: Muthu Tamilarasi, T. G. Palanivelu
Venue: International Journal of Network Management (2008)

Dynamic source routing (DSR) is a robust protocol commonly applied to multi-hop wireless mobile ad hoc networks (MANETs). In this paper, an algorithm is proposed for modifying the basic DSR protocol to enhance its performance by reducing the number of redundant route reply packets (RREPs). In the modified DSR (MDSR), for a source destination pair, the destination responds to the first received route request packet (RREQ) with an RREP, and the subsequently received RREQs, bearing the same request ID, are responded to only if the hop count is less than that of all the previously received RREQs. The performance of MDSR has been compared with that of the basic DSR for different network densities and for different mobility of nodes. Simulation results show that MDSR gives fewer control packets, less latency and a higher packet delivery ratio than DSR.
Automatic Individual Detection and Separation of Multiple Overlapped Nematode Worms Using Skeleton Analysis
Authors: Nikzad Babaii Rizvandi, Aleksandra Pižurica, Wilfried Philips
Venue: Proceedings of the 5th international conference on Image Analysis and Recognition (2008)

We present a new method for detection and separation of individual nematode worms in a still image. After pre-processing stage, which includes image binarization, filling the small holes, obtaining the skeleton of the new image and pruning the extra branches of skeleton, we split a skeleton into several branches by eliminating the connection pixels (pixels with more than 2 neighbors). Then we compute angles of all branches and compare the angles of the neighboring branches. The neighbor branches with angle differences less than a threshold are connected. Our method has been applied to a database of 54 overlap worms and results in 82% accuracy as automatic and 89% as semi-automatic with some limited user interaction.