ppxscal/embedding_network huggingface dataset:
Rule-Based Fuzzy Logic System for Diagnosing Migraine
Authors: Svetlana Simić, Dragan Simić, Petar Slankamenac, Milana Simić-Ivkov
Venue: Proceedings of the 5th Hellenic conference on Artificial Intelligence: Theories, Models and Applications (2008)

This research focussed on diagnosing migraine types in working people employing the rule-based fuzzy logic system. Migraine is not a disease which typically shortens one's life. However, it can be a serious social as well as a health problem. Approximately 27 billion euros per year are lost through reduced work productivity in the European Community. The diagnostic criteria developed by the International Headache Society (IHS) have been used in epidemiological researches, but there is no such tool which helps physicians make diagnoses. The rules were facilitated by the application of the IHS criteria for migraine types. Clinical experience was used to extend the established rules and improve the system. The proposed system is in the starting phase of the implementation at the Clinical Centre Vojvodina, Institute of Neurology in Novi Sad.
Vibration Fault Diagnosis of Steam Turbine Shafting Based on Probability Neural Networks
Authors: Yanping Zhang, Shuhong Huang, Wei Gao, Tao Shen
Venue: Proceedings of the 2008 Congress on Image and Signal Processing, Vol. 5 - Volume 05 (2008)

Information entropy is an effective description for the uncertainty of a system, and could be used for the symptom to detect the vibration changes of steam turbine. Based on the faulty signals collected from rotor test rig, three information entropy: singular spectrum entropy, power spectrum entropy, wavelet energy spectrum entropy were calculated as information entropy data. Probability neural networks(PNNs) was explored to fuse the three information entropy. Research shows that with the advantages of Bayes classifier and neural networks, PNNs has good classification ability to typical vibration faults of turbine, the classification accuracy is 100% for training data, 80% for unseen data. Compared with the classification accuracy of minimum distance classifier(MDC) and improved MDC, PNNs has higher classification accuracy. It can be deduced that PNNs is a practical fusion diagnosis method for typical fault identification of turbine rotor.
Line Transversals in Large T(3)- and T(4)-Families of&#x00a0;Congruent Discs
Authors: Aladar Heppes
Venue: Discrete Computational Geometry (2008)

A family of closed discs is said to have property T(k) if to every subset of at most k discs there belongs a common line transversal. A family of discs is said to be d-disjoint, d&#x2265;1, if the mutual distance between the centers of the discs is larger than d. It is known that a d-disjoint T(3)-family &#x2131; of unit diameter discs has a line transversal if $d=\sqrt{2}$. Similarly, a d-disjoint T(4)-family has a line transversal if $d=2/\sqrt{3}$. Both results are sharp in d, i.e., they do not hold for smaller values of d. The main result of this paper is that while the above lower bounds on d cannot be relaxed in general, some reduction of d can be compensated by imposing a proper d-dependent lower bound on the size of the family in both cases.
Guest Editorial
Authors: Ernesto Damiani
Venue: Journal of Computer Security (2008)

A new wave of security research is providing theoretical insight and practical techniques for dealing with new vulnerabilities originating from increased application mobility and dynamic set-up of business processes. This special issue contains some high quality research contributions, each focusing on an emerging trend in security and privacy research which is likely to have a high impact on business evolution.
A Systems Analyst's Computer Watch: 1943-2003
Authors: Elizabeth Phillips Williams
Venue: IEEE Annals of the History of Computing (2003)

An abiding interest in computerization and the manner in which it is—or is not—implemented, especially in large organizations, grew out of the author's professional life as a systems analyst and became a lifelong pursuit. In this recollection, she describes what it was like to work as an analyst in the 1940s and 1950s, and she also describes a number of incidents that reflected prevailing attitudes toward women in the workplace. 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
Lessons in the Weird and Unexpected: Some Experiences from Checking Large Real Systems
Authors: Dawson Engler
Venue: Proceedings of the 15th international symposium on Formal Methods (2008)

This talk will draw on our efforts in using static analysis, model checking, and symbolic execution to find bugs in real code, both in academic and commercial settings. The unifying religion driving all these efforts has been: results matter more than anything. That which works is good, that which does not is not. While this worldview is simple, reality is not. I will discuss some what we learned in struggling with this mismatch.
A Retrograde Approximation Algorithm for Multi-player Can't Stop
Authors: James Glenn, Haw-Ren Fang, Clyde P. Kruskal
Venue: Proceedings of the 6th international conference on Computers and Games (2008)

An n-player, finite, probabilistic game with perfect information can be presented as a 2n-partite graph. For Can't Stop, the graph is cyclic and the challenge is to determine the game-theoretical values of the positions in the cycles. We have presented our success on tackling one-player Can't Stop and two-player Can't Stop. In this article we study the computational solution of multi-player Can't Stop (more than two players), and present a retrograde approximation algorithm to solve it by incorporating the multi-dimensional Newton's method with retrograde analysis. Results of experiments on small versions of three- and four-player Can't Stop are presented.
Controlling the formation of nanoparticles for definite growth of carbon nanotubes for interconnect applications
Authors: Sascha Hermann, Ramona Ecke, Stefan Schulz, Thomas Gessner
Venue: Microelectronic Engineering (2008)

Our interest is the integration of carbon nanotubes (CNT) in electronic devices (IC, NEMS). In the scope of this work, we present a study on the preparation of the catalyst Ni particles from ultrathin films and the synthesis of carbon nanotubes by the chemical vapour deposition method. For the preparation, we use a cold-wall CVD reactor especially designed for handling samples up to a size of a 4'' wafer. We show the influence of different process conditions like temperature, initial layer thickness of catalyst and substrate on particle formation characterized by scanning electron microscopy (SEM). We show that the optimization of process conditions in the catalyst preparation phase is constitutive for dense CNT films. Regarding the application of CNTs as electrical interconnects, we studied the arrangement of nanoparticles on Al and TiN supporting layer. Furthermore, we fabricated the first test structures for the selective growth of CNTs out of contact holes on a Cu/TiN metallization layer system. The growth of multi-walled nanotubes (MWNTs) was performed with thermal CVD with ethylene as a precursor gas and hydrogen as supporting gas mixed in a nitrogen gas flow. The effects of growth condition on the quality and morphology of the CNTs were characterized by scanning electron microscopy, transmission electron microscopy (TEM) and Raman spectroscopy. The influence of temperature, gas composition and substrate on CNT growth will be presented. We managed to grow dense CNTs even at temperatures as low as 500^oC.
Gaussianization Based Approach for Post-Nonlinear Underdetermined BSS with Delays
Authors: Alessandro Bastari, Stefano Squartini, Stefania Cecchi, Francesco Piazza
Venue: Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks, Part III (2007)

The principal aim of this work is to demonstrate, from an empirical point of view, the effectiveness of a previously proposed technique for the Blind Source Separation (BSS) with Post Non Linear (PNL) underdetermined instantaneous mixing model (uBSS), in the more complex and realistic case where delayed sources are considered in the linear part of the mixing (PNL-uBSS with delays). The proposed approach is composed of two consecutive stages: in the first stage the inverse nonlinearities are estimated by Gaussianization of the mixtures; in the second stage source signals are extracted from the linearized mixtures using a three step approach already known in the literature for linear delayed uBSS. An improved technique based on Extended Gaussianization is also provided for the estimation of inverse nonlinearities. Experimental results using synthetic mixtures of real world data (speech signals) are given to prove the effectiveness of the proposed approach.
Selective attention to affective value alters how the brain processes olfactory stimuli
Authors: Edmund T. Rolls, Fabian Grabenhorst, Christian Margot, Maria A. A. P. da Silva, Maria Ines Velazco
Venue: Journal of Cognitive Neuroscience (2008)

How does selective attention to affect influence sensory processing? In a functional magnetic resonance imaging investigation, when subjects were instructed to remember and rate the pleasantness of a jasmin odor, activations were greater in the medial orbito-frontal and pregenual cingulate cortex than when subjects were instructed to remember and rate the intensity of the odor. When the subjects were instructed to remember and rate the intensity, activations were greater in the inferior frontal gyrus. These top-down effects occurred not only during odor delivery but started in a preparation period after the instruction before odor delivery, and continued after termination of the odor in a short-term memory period. Thus, depending on the context in which odors are presented and whether affect is relevant, the brain prepares itself, responds to, and remembers an odor differently. These findings show that when attention is paid to affective value, the brain systems engaged to prepare for, represent, and remember a sensory stimulus are different from those engaged when attention is directed to the physical properties of a stimulus such as its intensity. This differential biasing of brain regions engaged in processing a sensory stimulus depending on whether the cognitive demand is for affect-related versus more sensory-related processing may be an important aspect of cognition and attention. This has many implications for understanding the effects not only of olfactory but also of other sensory stimuli.
Agent Methods for Network Intrusion Detection and Response
Authors: Martin Rehák, Michal Pĕchouček, David Medvigy, Magda Prokopová, Jan Tožička, Lukáš Foltýn
Venue: Proceedings of the 3rd international conference on Industrial Applications of Holonic and Multi-Agent Systems: Holonic and Multi-Agent Systems for Manufacturing (2007)

While the need to build the Intrusion Detection Systems (IDS) based on on a distributed and cooperative (P2P) paradigm is being generally acknowledged, the field has been disconnected from the recent advances in the multi-agent research, most notably the field of trust modeling. Our contribution reviews recent implementations of IDS systems and presents them from an agent research perspective. We also identify the opportunities where the agent approaches can be successfully used. Agent techniques can make the IDS more adaptive, scalable and reliable while increasing their autonomy and reducing the maintenance requirements. Besides trust modeling, we propose that the distributed decision-making and planning techniques can be used to shorten the detection-response loop, making the system more robust while facing worm attacks.
Kernel Weighted Scatter-Difference-Based Discriminant Analysis for Face Recognition
Authors: Khalid Chougdali, Mohamed Jedra, Noureddine Zahid
Venue: Proceedings of the 5th international conference on Image Analysis and Recognition (2008)

This paper presents a kernel weighted scatter difference discriminant analysis (KWSDA) method for face recognition. This non-linear dimensionality reduction algorithm has several interesting characteristics. First, using a new optimization criterion it avoids small sample size problem intuitively. Second, by incorporating a weighting function into discriminant criterion, it overcomes overemphasis on well-separated classes and hence can work under more realistic situations. Lastly, applying kernel theory, it handles nonlinearity efficiently. Experiments on the ORL face database show that the proposed method is effective and feasible.
Distribution Stream of Tasks in Dual-Processor System
Authors: Michael Kryzhanovsky, Magomed Malsagov
Venue: Proceedings of the 18th international conference on Artificial Neural Networks, Part II (2008)

The paper offers an associative-neural-net method to optimize resource allocation between independent tasks in a multiprocessor system. In the case of a dual-core CPU the method allows the task to be fully solved in $O\left(M\right)$ operations.
Flexible and Simple User Interfaces in Entertaining Software
Authors: Morten Tollefsen, Are Flyen
Venue: Proceedings of the 11th international conference on Computers Helping People with Special Needs (2008)

The first version of the electronic picture book application was designed in 1998. The target group was visually impaired adults with sighted children. It was soon clear that the application had a much broader target group than was originally thought: visually impaired children, persons with motor disabilities, children with mental disabilities and even those without disabilities. With this in mind work was initiated in 2006 to improve the universal design of the application and the electronic book structure. The result is a user interface which is still simple and with flexibility not typically found in entertaining software.
Using Formal Concept Analysis in Mathematical Discovery
Authors: Simon Colton, Daniel Wagner
Venue: Proceedings of the 14th symposium on Towards Mechanized Mathematical Assistants: 6th International Conference (2007)

Formal concept analysis (FCA) comprises a set of powerful algorithms which can be used for data analysis and manipulation, and a set of visualisation tools which enable the discovery of meaningful relationships between attributes of the data. We explore the potential of combining FCA and mathematical discovery tools in order to better facilitate discovery tasks. In particular, we propose a novel lookup method for the Encyclopedia of Integer Sequences, and we show how conjectures from the Graffiti discovery program can be better understood using FCA visualisation tools. We argue that, not only can FCA tools greatly enhance the management and visualisation of mathematical knowledge, but they can also be used to drive exploratory processes.
Modeling and Control of Molten Carbonate Fuel Cells Based on Feedback Neural Networks
Authors: Yudong Tian, Shilie Weng
Venue: Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks (2007)

The molten carbonate fuel cell (MCFC) is a complex system, and MCFC modeling and control are very difficult in the present MCFC research and development because MCFC has the complicated characteristics such as nonlinearness, uncertainty and time-change. To aim at the problem, the MCFC mechanism is analyzed, and then MCFC modeling based on feedback neural networks is advanced. At last, as a result of applying the model, a new MCFC control strategy is presented in detail so that it gets rid of the limits of the controlled object, which has the imprecision, uncertainty and time-change, to achieve its tractability and robustness. The computer simulation and the experiment indicate that it is reasonable and effective.
Fast Distributed Computation of Cuts Via Random Circulations
Authors: David Pritchard
Venue: Proceedings of the 35th international colloquium on Automata, Languages and Programming, Part I (2008)

We describe a new circulation-based method to determine cuts in an undirected graph. A circulation is an oriented labeling of edges with integers so that at each vertex, the sum of the in-labels equals the sum of out-labels. For an integer k, our approach is based on simple algorithms for sampling a circulation (mod k) uniformly at random. We prove that with high probability, certain dependencies in the random circulation correspond to cuts in the graph. This leads to simple new linear-time sequential algorithms for finding all cut edges and cut pairs (a set of 2 edges that form a cut) of a graph, and hence 2-edge-connected and 3-edge-connected components.In the model of distributed computing in a graph G = (V, E) with O(log|V|)-bit messages, our approach yields faster algorithms for several problems. The diameter of G is denoted by ${\mathcal{D}}$. Previously, Thurimella [J. Algorithms, 1997] gave a $O({\mathcal{D}}+\sqrt{|V|}\log^* |V|)$-time algorithm to identify all cut vertices, 2-edge-connected components, and cut edges, and Tsin [Int. J. Found. Comput. Sci., 2006] gave a $O(|V|+{\mathcal{D}}^2)$-time algorithm to identify all cut pairs and 3-edge-connected components.We obtain simple $O({\mathcal{D}})$-time distributed algorithms to find all cut edges, 2-edge-connected components, and cut pairs, matching or improving previous time bounds on all graphs. Under certain assumptions these new algorithms are universally optimal, due to a $\Omega({\mathcal{D}})$-time lower bound on every graph. These results yield the first distributed algorithms with sub-linear time for cut pairs and 3-edge-connected components. Let Δ denote the maximum degree. We obtain a $O({\mathcal{D}}+\Delta/\log|V|)$-time distributed algorithm for finding cut vertices; this is faster than Thurimella's algorithm on all graphs with $\Delta, {\mathcal{D}} = O(\sqrt{|V|})$. The basic distributed algorithms are Monte Carlo, but can be made Las Vegas without increasing the asymptotic complexity.
Required level of motivation to revitalize the workforce in software industry of Pakistan
Authors: Muhammad Wasim Bhatti, Ali Ahsan, Ali Sajid
Venue: Proceedings of the 7th WSEAS International Conference on Software Engineering, Parallel and Distributed Systems (2008)

Pakistan's IT industry is currently one of the top performers as compared to other industrial sectors within Pakistan. As per the findings of Ahsan (2008), despite the fact that Pakistan's IT industry is competitive, its true potential is yet to be unfolded. Ahsan (2008); states that Pakistan's so called competitive IT industry has to be in lined with the international performers. A simple proof of this statement can be obtained from the fact that Pakistan's general economy is 1/5th of Indian economy. This must be true for IT sector of both the economies as well, which, unfortunately is not the case as because Pakistan's IT sector is currently 1/27th of the Indian IT Sector. Ahsan (2008) believes that partial reason of this unwanted difference may be revenue models, business practices and political situations of the two countries. Other than these Ahsan (2008) believes that several soft issues are also responsible for this industrial difference. Out of the soft issues 'motivation' is one such important factor. In this research report several motivational factors' are identified and a 'table' is developed to measure the motivation level of employees working in IT Industry of Pakistan. Frequency, Variance and Score of all the motivational factors is identified. These computations and certain numerical calculations and priorities are set against the identified factors in order to perform necessary analysis. Recommendations and findings are given to improve the motivation level of employees working in IT Industry of Pakistan.
The Rich Transcription 2007 Meeting Recognition Evaluation
Authors: Jonathan G. Fiscus, Jerome Ajot, John S. Garofolo
Venue: Multimodal Technologies for Perception of Humans: International Evaluation Workshops CLEAR 2007 and RT 2007, Baltimore, MD, USA, May 8-11, 2007, Revised Selected Papers (2008)

We present the design and results of the Spring 2007 (RT-07) Rich Transcription Meeting Recognition Evaluation; the fifth in a series of community-wide evaluations of language technologies in the meeting domain. For 2007, we supported three evaluation tasks: Speech-To-Text (STT) transcription, "Who Spoke When" Diarization (SPKR), and Speaker Attributed Speech-To-Text (SASTT). The SASTT task, which combines STT and SPKR tasks, was a new evaluation task. The test data consisted of three test sets: Conference Meetings, Lecture Meetings, and Coffee Breaks from lecture meetings. The Coffee Break data was included as a new test set this year. Twenty-one research sites materially contributed to the evaluation by providing data or building systems. The lowest STT word error rates with up to four simultaneous speakers in the multiple distant microphone condition were 40.6 %, 49.8 %, and 48.4 % for the conference, lecture, and coffee break test sets respectively. For the SPKR task, the lowest diarization error rates for all speech in the multiple distant microphone condition were 8.5 %, 25.8 %, and 25.5 % for the conference, lecture, and coffee break test sets respectively. For the SASTT task, the lowest speaker attributed word error rates for segments with up to three simultaneous speakers in the multiple distant microphone condition were 40.3 %, 59.3 %, and 68.4 % for the conference, lecture, and coffee break test sets respectively.
Detecting Communication Protocol Security Flaws by Formal Fuzz Testing and Machine Learning
Authors: Guoqiang Shu, Yating Hsu, David Lee
Venue: Proceedings of the 28th IFIP WG 6.1 international conference on Formal Techniques for Networked and Distributed Systems (2008)

Network-based fuzz testing has become an effective mechanism to ensure the security and reliability of communication protocol systems. However, fuzz testing is still conducted in an ad-hoc manner with considerable manual effort, which is mainly due to the unavailability of protocol model. In this paper we present our on-going work of developing an automated and measurable protocol fuzz testing approach that uses a formally synthesized approximate formal protocol specification to guide the testing process. We adopt the Finite State Machine protocol model and study two formal methods for protocol synthesis: an active black-box checking algorithm that has provable optimality and a passive trace minimization algorithm that is less accurate but much more efficient. We also present our preliminary results of using this method to implementations of the MSN instant messaging protocol: MSN clients Gaim (pidgin) and aMSN. Our testing reveals some serious reliability and security flaws by automatically crashing both of them.
Transforming dependence graphs into signal flow graphs during systolic array processors design
Authors: Argiris Mokios, Stavros Dokouzyannis
Venue: Proceedings of the 7th WSEAS International Conference on Electronics, Hardware, Wireless and Optical Communications (2008)

The algorithm for the transformation of Dependence Graphs, DGs, into Signal Flow Graphs, SFGs, during the design of Systolic Array Processors, SAPs, is presented. The transformation is a complex process, employing task scheduling, projection and the formation of recursive surfaces, i.e., hyperplanes corresponding to simultaneously executed processes during a common clock phase. A matrix method is developed, in order to overcome the limitation of more than 3-Dimensional euclidean space graphical modeling, used up to now, and based on the designer imagination. The proposed method is intended to be used, in the near future, by Design Automation CAD tools.
Scan Conversion of Regions Bounded by Parabolic Splines
Authors: Theo Pavlidis
Venue: IEEE Computer Graphics and Applications (1985)

A scan-conversion Algorithm has Been Implemented as Part of an on-line Program for Interactive Graphics and Document preparation.