ppxscal/embedding_network huggingface dataset:
Multi-agent Logics with Interacting Agents Based on Linear Temporal Logic: Deciding Algorithms
Authors: Vladimir Rybakov
Venue: Proceedings of the 9th international conference on Artificial Intelligence and Soft Computing (2006)

We introduce a multi-agent logic ${ {\cal M}{\cal A}_{{\cal L}{\cal T}{\cal L}}}$ --- a variant of the linear temporal logic LTL with embedded multi-agent knowledge with interacting agents. The logic is motivated by semantics based on potentially infinite runs with time points represented by clusters of states with distributed knowledge of the agents. We address properties of local and global knowledge modeled in this framework, consider modeling of interaction between agents by possibility to puss information from one agent to others via possible transitions within time clusters of states. Main question we are focused on is the satisfiability problem and decidability of the logic ${ {\cal M}{\cal A}_{{\cal L}{\cal T}{\cal L}}}$. Key result is proposed algorithm which recognizes theorems of ${ {\cal M}{\cal A}_{{\cal L}{\cal T}{\cal L}}}$ (so we show that ${ {\cal M}{\cal A}_{{\cal L}{\cal T}{\cal L}}}$ is decidable). It is based on verification of validity for special normal reduced forms of rules in models with at most triple exponential size in the testing rules. In the final part we discuss possible variations of the proposed logic.
Leading strategies in competitive on-line prediction
Authors: Vladimir Vovk
Venue: Theoretical Computer Science (2008)

We start from a simple asymptotic result for the problem of on-line regression with the quadratic loss function: the class of continuous limited-memory prediction strategies admits a ''leading prediction strategy'', which not only asymptotically performs at least as well as any continuous limited-memory strategy, but also satisfies the property that the excess loss of any continuous limited-memory strategy is determined by how closely it imitates the leading strategy. More specifically, for any class of prediction strategies constituting a reproducing kernel Hilbert space, we construct a leading strategy, in the sense that the loss of any prediction strategy whose norm is not too large is determined by how closely it imitates the leading strategy. This result is extended to the loss functions given by Bregman divergences and by strictly proper scoring rules.
Hysteresis modeling based on the hysteretic chaotic neural network
Authors: Xiangdong Liu, Chunbo Xiu
Venue: Neural Computing and Applications (2008)

The hysteresis activation function is proposed, and a novel hysteretic chaotic neuron model is constructed by the function. It is shown that the model may exhibit a complex dynamic behavior. On the basis of this neuron model, we propose a novel neural network, which can be applied to hysteresis system modeling. We demonstrate the advantages of the network by experimental results.
Modeling Cross-Cultural Performance on the Visual Oddity Task
Authors: Andrew Lovett, Kate Lockwood, Kenneth Forbus
Venue: Proceedings of the international conference on Spatial Cognition VI: Learning, Reasoning, and Talking about Space (2008)

Cognitive simulation offers a means of more closely examining the reasons for behavior found in psychological studies. This paper describes a computational model of the visual oddity task, in which individuals are shown six images and asked to pick the one that doesn't belong. We show that the model can match performance by participants from two cultures: Americans and the Mundurukú. We use ablation experiments on the model to provide evidence as to what factors might help explain differences in performance by the members of the two cultures.
Joint image and pupil plane reconstruction algorithm based on bayesian techniques
Authors: James D. Phillips
Venue:  (2008)

The focus of this research was to develop an joint pupil and focal plane image recovery algorithm for use with coherent LADAR systems. The benefits of such a system would include increased resolution with little or no increase in system weight and volume as well as allowing for operation in the absence of natural light since the target of interest would be actively illuminated. Since a pupil plane collection aperture can be conformal, such a system would also potentially allow for the formation of large synthetic apertures. The algorithm developed used many frames of coherent pupil and focal plane data. The data frames are summed in the respective planes to give two data set (one for each plane). Appropriate statistical models are used and a joint Maximum Likelihood estimator is formed. The algorithm is tested using a Monte Carlo approach. The system is demonstrated to be robust and in all but extreme cases yield better results than algorithms using a single data set (such as deconvolution). It was shown that the joint algorithm had a resolution increase of 70% over deconvolution alone and a 40% increase over traditional pupil plane algorithms. It is also demonstrated that the new algorithm does not suffer as severely from stagnation problems typical with pupil plane algorithms. A stopping criteria based on the statistics of the data was also developed. 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
Implicit Surface Reconstruction from Scattered Point Data with Noise
Authors: Jun Yang, Zhengning Wang, Changqian Zhu, Qiang Peng
Venue: Proceedings of the 7th international conference on Computational Science, Part II (2007)

This paper addresses the problem of reconstructing implicit function from point clouds with noise and outliers acquired with 3D scanners. We introduce a filtering operator based on mean shift scheme, which shift each point to local maximum of kernel density function, resulting in suppression of noise with different amplitudes and removal of outliers. The "clean" data points are then divided into subdomains using an adaptive octree subdivision method, and a local radial basis function is constructed at each octree leaf cell. Finally, we blend these local shape functions together with partition of unity to approximate the entire global domain. Numerical experiments demonstrate robust and high quality performance of the proposed method in processing a great variety of 3D reconstruction from point clouds containing noise and outliers.
Continuity of triple I methods based on several implications
Authors: Hua-Wen Liu, Guo-Jun Wang
Venue: Computers Mathematics with Applications (2008)

This paper focuses on the continuity problem of fully implicational triple I methods for fuzzy reasoning. Based on the residual implications generated by continuous triangular norms, the residual implication generated by nilpotent minimum with the standard negation and the Zadeh implication, respectively, continuity and uniform continuity properties of triple I methods are examined in Hamming and uniform metrics. We also investigate the continuity of the model of a fuzzy if-then rule corresponding to the triple I methods.
Fault-tolerant performance checking application for distributed computing and supply chain networks
Authors: Umair Hassan, Ben Soh
Venue: Journal of Computational Methods in Sciences and Engineering (2006)

This paper presents a model/simulation of a fault tolerant system along with its implementation. The system also keeps track on the performance of the system and adjust it when a need arises. In order for the system to be fault tolerant we have to provide redundancies in the system. This is extremely important for systems, such as supply chain networks, whereby agents communicate with each other and a problem in the system can induce a ripple effect, leading to system-wide outage. Along with speed/bandwidth a need arises for this data flow to be consistent and the mechanism to be fault tolerant. The architecture is based on the concept of grid computing, but in this paper we focus mainly on developing a simulation of the process and develop components, which can monitor the simulation along with providing fault tolerance. Monitoring and fault tolerance are related to each other, as we can't provide fault tolerance without monitoring the system.
Detection and Tracking of Coronal Mass Ejections
Authors: Goussies Norberto, Mejail Marta, Jacobo Julio, Stenborg Guillermo
Venue: Proceedings of the 13th Iberoamerican congress on Pattern Recognition: Progress in Pattern Recognition, Image Analysis and Applications (2008)

Coronal Mass Ejection (CME) events refer to the appearance of a new, discrete, white-light feature (with outward velocity) in a coronagraph. The huge amount of data provided by the pertinent instruments onboard the Solar and Heliospheric Observatory (SOHO) and, most recently, the Solar Terrestrial Relations Observatory (STEREO) makes the human-based detection of such events excessively time consuming. Although several algorithms have been proposed to address this issue, there is still lack of universal consensus about their reliability. This work presents a novel method for the detection and tracking of CMEs as recorded by the LASCO instruments onboard SOHO. The algorithm we developed is based on level sets and region competition methods, the CMEs texture being characterized by their co-ocurrence matrix. The texture information is introduced in the region competition motion equations, and in order to evolve the curve, a fast level set implementation is used.
Read-Optimized, Cache-Conscious, Page Layouts for Temporal Relational Data
Authors: Khaled Jouini, Geneviève Jomier, Patrick Kabore
Venue: Proceedings of the 19th international conference on Database and Expert Systems Applications (2008)

The efficient management of temporal data is crucial for many traditional and emerging database applications. A major performance bottleneck for database systems is the memory hierarchy. The performance of the memory hierarchy is directly related to how the content of disk pages maps to the L2 cache lines, i.e. to the organization of data within a page or the page layout. The prevalent page layout in database systems is the N-ary Storage Model (NSM). As demonstrated in this paper, using NSM for temporal data deteriorates memory hierarchy performance for query-intensive workloads. This paper proposes, new cache-conscious, read-optimized, page layouts specifically tailored for temporal data. The proposed page layouts optimize accesses to all levels of the memory hierarchy by avoiding fetching the same data several times (as opposed to NSM). Experiments show that the proposed page layouts are substantially faster than NSM.
Iconic Interfacing
Authors: Kenneth Lodding
Venue: IEEE Computer Graphics and Applications (1983)

Icons are not just religious images from Czarist Russia¿ they are also pictures used by computer graphics designers to help improve the man-machine interface.
To Snoop or Not to Snoop: Evaluation of Fine-Grain and Coarse-Grain Snoop Filtering Techniques
Authors: Jessica Young, Srihari Makineni, Ravishankar Iyer, Don Newell, Adrian Moga
Venue: Proceedings of the 14th international Euro-Par conference on Parallel Processing (2008)

Cache coherency protocols implemented in today's shared memory multiprocessor systems use snooping mechanism to keep the data correct and consistent between the caches and the system memory. This requires a large number of snoops sent out on the system interconnection links. However, published research has been shown that a large percentage of these snoops are not necessary or can be eliminated. To detect and eliminate these unnecessary snoops, several techniques have been proposed. But these techniques have not been evaluated using commercial server benchmarks and large caches that are common on today's server platforms. In this paper, we evaluate three popular snoop filtering techniques, namely Region Scout (RS), Region Coherence Array (RCA) and Directory Cache (DC), using four different commercial server workloads. We compare and contrast these three techniques and show how effective these techniques are in eliminating unnecessary snoops. These techniques differ in implementation approaches and the implementation differences yield accuracy and areas tradeoffs. We show 38% to 98% of the last level cache snoops are unnecessary in major commercial server benchmarks. With the snoop filtering techniques we are able to eliminate 35% to 97% of the unnecessary snoops with 1-3% additional die area.
A Black Box for Online Approximate Pattern Matching
Authors: Raphaël Clifford, Klim Efremenko, Benny Porat, Ely Porat
Venue: Proceedings of the 19th annual symposium on Combinatorial Pattern Matching (2008)

We present a deterministic black box solution for online approximate matching. Given a pattern of length m and a streaming text of length n that arrives one character at a time, the task is to report the distance between the pattern and a sliding window of the text as soon as the new character arrives. Our solution requires $O(\Sigma_{j=1}^{\log_2{m}} T(n,2^{j-1})/n)$ time for each input character, where T(n,m) is the total running time of the best offline algorithm. The types of approximation that are supported include exact matching with wildcards, matching under the Hamming norm, approximating the Hamming norm, k-mismatch and numerical measures such as the L 2 and L 1 norms. For these examples, the resulting online algorithms take O(log2 m), $O(\sqrt{m\log{m}})$, O(log2 m/¿ 2), $O(\sqrt{k \log k} \log{m})$, O(log2 m) and $O(\sqrt{m\log{m}})$ time per character respectively. The space overhead is O(m) which we show is optimal.
Fuzzy K-Nearest Neighbor Classifier to Predict Protein Solvent Accessibility
Authors: Jyh-Yeong Chang, Jia-Jie Shyu, Yi-Xiang Shi
Venue: Neural Information Processing: 14th International Conference, ICONIP 2007, Kitakyushu, Japan, November 13-16, 2007, Revised Selected Papers, Part II (2008)

The prediction of protein solvent accessibility is an intermediate step for predicting the tertiary structure of proteins. Knowledge of solvent accessibility has proved useful for identifying protein function, sequence motifs, and domains. Using a position-specific scoring matrix (PSSM) generated from PSI-BLAST in this paper, we develop the modified fuzzy k-nearest neighbor method to predict the protein relative solvent accessibility. By modifying the membership functions of the fuzzy k-nearest neighbor method by Sim et al. [1], has recently been applied to protein solvent accessibility prediction with excellent results. Our modified fuzzy k-nearest neighbor method is applied on the three-state, E, I, and B, and two-state, E, and B, relative solvent accessibility predictions, and its prediction accuracy compares favorly with those by the fuzzy k-NN and other approaches.
User-activity aware strategies for mobile information access
Authors: Raghupathy Sivakumar
Venue:  (2008)

Information access suffers tremendously in wireless networks because of the low correlation between content transferred across low-bandwidth wireless links and actual data used to serve user requests. As a result, conventional content access mechanisms face such problems as unnecessary bandwidth consumption and large response times, and users experience significant performance degradation, to this dissertation, we analyze the cause of those problems and find that the major reason for inefficient information access in wireless networks is the absence of any user-activity awareness in current mechanisms. To solve these problems, we propose three user-activity aware strategies for mobile information access. Through simulations and implementations, we show that our strategies can outperform conventional information access schemes in terms of bandwidth consumption and user-perceived response times.
Distributed Systems and Automated Biodiversity Informatics: Genomic Analysis and Geographic Visualization of Disease Evolution
Authors: Andrew W. Hill, Robert P. Guralnick
Venue: Proceedings of the 25th British national conference on Databases: Sharing Data, Information and Knowledge (2008)

A core mission in biodiversity informatics is to build a computing infrastructure for rapid, real-time analysis of biodiversity information. We have created the information technology to mine, analyze, interpret and visualize how diseases are evolving across the globe. The system rapidly collects the newest and most complete data on dangerous strains of viruses that are able to infect human and animal populations. Following completion, the system will also test whether positions in the genome are under positive selection or purifying selection, a useful feature to monitor functional genomic charac-teristics such as, drug resistance, host specificity, and transmissibility. Our system's persistent monitoring and reporting of the distribution of dangerous and novel viral strains will allow for better threat forecasting. This information system allows for greatly increased efficiency in tracking the evolution of disease threats.
On the possibility of learning in reactive environments with arbitrary dependence
Authors: Daniil Ryabko, Marcus Hutter
Venue: Theoretical Computer Science (2008)

We address the problem of reinforcement learning in which observations may exhibit an arbitrary form of stochastic dependence on past observations and actions, i.e. environments more general than (PO)MDPs. The task for an agent is to attain the best possible asymptotic reward where the true generating environment is unknown, but belongs to a known countable family of environments. We find some sufficient conditions on the class of environments under which an agent exists which attains the best asymptotic reward for any environment in the class. We analyze how tight these conditions are, and how they relate to different probabilistic assumptions known in reinforcement learning and related fields, such as Markov Decision Processes and mixing conditions.
A note on a theorem of Perles concerning non-crossing paths in convex geometric graphs
Authors: Ana Paulina Figueroa
Venue: Computational Geometry: Theory and Applications (2009)

During the last decade a Turan-type result of Perles about the length of the longest non-crossing paths in convex geometric graphs has been receiving some attention in the community studying geometric graphs. In this note we prove that it implies a theorem of Merino, Salazar and Urrutia about the length of the longest alternating paths for a multicoloured point set in convex position. We also give an alternative proof of Perles's theorem based on some ideas from the Merino et al. paper.
Preliminary Analysis of the Cell BE Processor Limitations for Sequence Alignment Applications
Authors: Sebastian Isaza, Friman Sánchez, Georgi Gaydadjiev, Alex Ramirez, Mateo Valero
Venue: Proceedings of the 8th international workshop on Embedded Computer Systems: Architectures, Modeling, and Simulation (2008)

The fast growth of bioinformatics field has attracted the attention of computer scientists in the last few years. At the same time the increasing database sizes require greater efforts to improve the computational performance. From a computer architecture point of view, we intend to investigate how bioinformatics applications can benefit from future multi-core processors. In this paper we present a preliminary study of the Cell BE processor limitations when executing two representative sequence alignment applications (Ssearch and ClustalW). The inherent large parallelism of the targeted algorithms makes them ideal for architectures supporting multiple dimensions of parallelism (TLP and DLP). However, in the case of Cell BE we identified several architectural limitations that need a careful study and quantification.
Identity Based Strong Designated Verifier Signature Scheme
Authors: Phani Kumar Kancharla, Shailaja Gummadidala, Ashutosh Saxena
Venue: Informatica (2007)

We propose an Identity Based Strong Designated Verifier Signature (IBSDVS) scheme using bilinear pairings. Designated Verifier Signature finds application in e-voting, auctions and call for tenders. We prove that the scheme is secure against existential forgery under adaptively chosen message and identity attack in random oracle model. We also show that the problem of delegatability does not exist in our scheme. Part of work was carried out when the author was affiliated to Secure Technology Lab., IDRBT, Hyderabad, India.
Power management for networked embedded systems
Authors: Cheng-Zhong Xu
Venue:  (2007)

A design challenge in embedded systems is power-efficiency because most embedded systems are powered by battery with limited capacity. It is important to prolong lifetimes of embedded systems while providing performance guarantee. To this end, we study techniques to build power-efficient embedded systems. Dynamic voltage and frequency scaling (DVS) is an effective technique for battery-powered systems to conserve energy consumption. We first study savings for dynamic energy consumption of a processor and present a time-variant scaling algorithm for aperiodic tasks. It is optimal in the sense it is on-line without assumed information about future task releases. We further establish two relationships between computation capacity and deadline misses to provide a statistical real-time guarantee with reduced capacity. Transmission speed slowdown is a technique to save power consumption for wireless transmitters. To deal with the dynamic nature of input arrivals, we model packet scheduling and queuing system in linear time-invariant systems and propose an energy-efficient packet scheduling policy that takes input time-correlation into account. Meanwhile, a slower transmission rate implies that packets stay in the transmitter for a longer time, which may result in unexpected transmitter overload and buffer overflow. We derive upper bounds of the maximum transmission rate under an overload probability, and upper bounds of required buffer size under a packet drop rate. Embedded systems usually consist of processors and a number of other components. Energy-aware processors can be run in different speed levels; components like memory and I/O subsystems and network interface cards can be in a standby state when they are active but idle. We study system-wide energy minimization and develop an exact dynamic programming algorithm for periodic tasks on processors with discrete speed levels. An approximation algorithm in polynomial running time is also proposed to provide bounded performance degradation. Similar optimization and approximation algorithms can also be adapted for on-line scheduling of aperiodic tasks with irregular task releases. A limitation of most DVS-based system-wide energy optimization techniques is that they assume the number of worst-case execution cycles (WCEC) of a task is a constant, independent of CPU frequency. This is not the case when other system components such as memory are taken into account. We decompose task execution time into two parts: on-chip inside the CPU and off-chip outside the CPU. We propose a frequency-aware system-wide energy minimization approach and establish necessary and sufficient conditions for the optimality. By exploiting properties of the conditions, we derive efficient algorithms for the optimal solutions. To evaluate the effectiveness of our approach, we have built a prototype embedded system with our policies. Preliminary results demonstrate the applicability and effectiveness of our approach.