ppxscal/embedding_network huggingface dataset:
The P2P war: Someone is monitoring your activities
Authors: Anirban Banerjee, Michalis Faloutsos, Laxmi Bhuyan
Venue: Computer Networks: The International Journal of Computer and Telecommunications Networking (2008)

In an effort to legally prosecute P2P users, the RIAA and MPAA have reportedly started to create decoy users: they participate in P2P networks in order to identify illegal sharing of content. This has reportedly scared some users who are afraid of being caught and prosecuted. The question we would like to answer is how prevalent is this phenomenon: how likely is it that a user will run into such a ''fake user'' and thus run the risk of a lawsuit? The first challenge is identifying these ''fake users''. We collect this information from a number of free open-source software projects which are trying to identify such addresses by forming the, so-called, blocklists. The second challenge is to quantify the probability of a user contacting such a fake user by conducting a large scale experiment in order to obtain reliable statistics. Using PlanetLab, we conduct active measurements, spanning a period of 90 days, from January to March 2006, spread over three continents. Analyzing over 100GB of TCP header data, we quantify the probability of a P2P user contacting fake users. We observe that 100% of our peers run into entities in these lists. In fact, 12-17% of all distinct IPs contacted by any node were listed on blocklists. Interestingly, a little caution can have significant effect: the top five most prevalent blocklisted IP ranges contribute to nearly 94% of all blocklisted IPs we ran into. Avoiding these can reduce the probability of a user being tracked to about 1%. In addition, we examine the identity of these blocklisted IPs. The majority of blocklisted IPs belong to the commercial and government domains and are nearly 2.5 times more than IPs belonging to educational, spyware or adware entities. Interestingly, less than 0.5% of all unique IPs contacted, belong explicitly to media companies. However, this may not be reassuring for P2P users, since the other blocklist users (government or commercial) could be collaborating with media companies.
Towards Empirical Aspects of Secure Scalar Product
Authors: I-Cheng Wang, Chih-Hao Shen, Tsan-Sheng Hsu, Churn-Chung Liao, Da-Wei Wang, Justin Zhan
Venue: Proceedings of the 2008 International Conference on Information Security and Assurance (isa 2008) (2008)

Privacy is ultimately important, and there is a fair amount of research about it. However, few empirical studies about the cost of privacy are conducted. In the area of secure multiparty computation, the scalar product has long been reckoned as one of the most promising building blocks in place of the classic logic gates. The reason is not only the scalar product complete, which is as good as logic gates, but also the scalar product is much more efficient than logic gates. As a result, we set to study the computation and communication resources needed for some of the most well-known and frequently referred secure scalar-product protocols, including the composite-residuosity, the invertible-matrix, the polynomial-sharing, and the commodity-based approaches. Besides the implementation remarks of these approaches, we analyze and compare their execution time, computation time, and random number consumption, which are the most concerned resources when talking about secure protocols. Moreover, Fairplay, the benchmark approach implementing Yao's famous circuit evaluation protocol, is included in our experiments in order to demonstrate the potentialfor the scalar product to replace logic gates.
2008 Special Issue: Threshold control of chaotic neural network
Authors: Guoguang He, Manish Dev Shrimali, Kazuyuki Aihara
Venue: Neural Networks (2008)

The chaotic neural network constructed with chaotic neurons exhibits rich dynamic behaviour with a nonperiodic associative memory. In the chaotic neural network, however, it is difficult to distinguish the stored patterns in the output patterns because of the chaotic state of the network. In order to apply the nonperiodic associative memory into information search, pattern recognition etc. it is necessary to control chaos in the chaotic neural network. We have studied the chaotic neural network with threshold activated coupling, which provides a controlled network with associative memory dynamics. The network converges to one of its stored patterns or/and reverse patterns which has the smallest Hamming distance from the initial state of the network. The range of the threshold applied to control the neurons in the network depends on the noise level in the initial pattern and decreases with the increase of noise. The chaos control in the chaotic neural network by threshold activated coupling at varying time interval provides controlled output patterns with different temporal periods which depend upon the control parameters.
On the design of reliable Boolean circuits that contain partially unreliable gates
Authors: D. Kleitman, T. Leighton, Y. Ma
Venue: Proceedings of the 35th Annual Symposium on Foundations of Computer Science (1994)

We investigate a model of gate failure for Boolean circuits in which a faulty gate is restricted to output one of its input values. For some types of gates, the model (which we call the short-circuit model of gate failure) is weaker than the traditional von Neumann model where faulty gates always output precisely the wrong value. Our model has the advantage that it allows us to design Boolean circuits that can tolerate worst-case faults, as well as circuits that have arbitrarily high success probability in the case of random faults. Moreover, the short-circuit model captures a particular type of fault that commonly appears in practice, and it suggests a simple method for performing post-test alterations to circuits that have more severe types of faults. A variety of bounds on the size of fault-tolerant circuits are proved in the paper. Perhaps, the most important is a proof that any k-fault-tolerant circuit for any input-sensitive function using any type of gates (even arbitrarily powerful, multiple-input gates) must have size at least /spl Omega/(k log k/log log k). Obtaining a tight bound on the size of a circuit for computing the AND of two values if up to k of the gates are faulty is one of the central questions left open in the paper.
siRNA specificity searching incorporating mismatch tolerance data
Authors: Alistair M. Chalk, Erik L. L. Sonnhammer
Venue: Bioinformatics (2008)

Artificially synthesized short interfering RNAs (siRNAs) are widely used in functional genomics to knock down specific target genes. One ongoing challenge is to guarantee that the siRNA does not elicit off-target effects. Initial reports suggested that siRNAs were highly sequence-specific; however, subsequent data indicates that this is not necessarily the case. It is still uncertain what level of similarity and other rules are required for an off-target effect to be observed, and scoring schemes have not been developed to look beyond simple measures such as the number of mismatches or the number of consecutive matching bases present. We created design rules for predicting the likelihood of a non-specific effect and present a web server that allows the user to check the specificity of a given siRNA in a flexible manner using a combination of methods. The server finds potential off-target matches in the corresponding RefSeq database and ranks them according to a scoring system based on experimental studies of specificity. Availability: The server is available at http://informatics-eskitis.griffith.edu.au/SpecificityServer. Contact: Erik.Sonnhammer@sbc.su.se Supplementary information: Supplementary analysis and figures are available at Bioinformatics online.
Coordinating with the Future: The Anticipatory Nature of Representation
Authors: Giovanni Pezzulo
Venue: Minds and Machines (2008)

Humans and other animals are able not only to coordinate their actions with their current sensorimotor state, but also to imagine, plan and act in view of the future, and to realize distal goals. In this paper we discuss whether or not their future-oriented conducts imply (future-oriented) representations. We illustrate the role played by anticipatory mechanisms in natural and artificial agents, and we propose a notion of representation that is grounded in the agent's predictive capabilities. Therefore, we argue that the ability that characterizes and defines a true cognitive mind, as opposed to a merely adaptive system, is that of building representations of the non-existent, of what is not currently (yet) true or perceivable, of what is desired. A real mental activity begins when the organism is able to endogenously (i.e. not as the consequence of current perceptual stimuli) produce an internal representation of the world in order to select and guide its conduct goal-directed: the mind serves to coordinate with the future.
Speaker Independent Phoneme Recognition Based on Fisher Weight Map
Authors: Takashi Muroi, Tetsuya Takiguchi, Yasuo Ariki
Venue: Proceedings of the 2008 International Conference on Multimedia and Ubiquitous Engineering (2008)

We have already proposed a new feature extraction method based on higher-order local auto-correlation and Fisher weight map (FWM) at Interspeech 2006. This papershows effectiveness of the proposed FWM in speaker dependent and speaker independent phoneme recognition. Widely used MFCC features lack temporal dynamics. To solve this problem, local auto-correlation features are computed and accumulated by weighting high scores on the discriminative areas. This score map is called Fisher weight map. From the speaker dependent phoneme recognition, the proposed FWM showed 79.5% recognition rate, by 5.0 points higher than the result by MFCC. Further more by combing FWM with MFCC and delta-MFCC, the recognition rate improved to 88.3%. In the speaker independent phoneme recognition, it showed 84.2% recognition rate, by 11.0 points higher than the result by MFCC. By combining FWM with MFCC and delta-MFCC, the recognition rate improved to 89.0%.
Virtual cognitive model for Miyazawa Kenji based on speech and facial images recognition
Authors: Hamido Fujita, Jun Hakura, Masaki Kurematsu
Venue: Proceedings of the 6th WSEAS International Conference on Signal, Speech and Image Processing (2006)

In this paper we a representing a virtual interactive model based on cognitive model of Miyazawa Kenji. We created a computer model based on cognitive thinking of Kenji literature on story telling. The user can interact in real time with Virtual Kenji. The facial gestures been collected and analyzed through Motion capture system of six camera. These six camera has been used to collect all emotional facial gestures of several people who read one assigned Kenji experiment. These people have 50 markers of 3 mm size attached to all parts of face (lips, mouth, eyebrow, cheek, moustache, eyelash, forehead), the emotional linkage between these facials parts and cognitive emotion been analyzed and recorded. We created a database we called Facial recognition database based on Miyzawa Kenji cognitive model, Also we have speech synthesis part who also analyzed the emotional part of speech. These two parts is been presented on hologram that represents the actual character of Kenji who has face with gestures harmonize with speech and facial images generated by the system and interact with the human user based on collected response from the human user and inference by the system in real time.
Kalman-based power control for DS-CDMA cellular mobile systems
Authors: H. Rohi, H. Hajghassem, S. H. Mohseni Armaki
Venue: Proceedings of the 4th international conference on mobile technology, applications, and systems and the 1st international symposium on Computer human interaction in mobile technology (2007)

By increasing the request for mobile services, the CDMA cellular system has been used extensively. This is due to advantages of spread spectrum techniques used in CDMA systems, and their higher capacity in compare to the FDMA & the TDMA systems. Power control is a very important issue in the CDMA systems. Different types of power control are used in the CDMA. Closed loop power control which is used for solving the fast fading problem is one of these types. However, proper estimation of received signal to interference ratio (SIR), related to mobile power adjustment is essential. In this paper we will present a new and efficient method using Kalman filter for SIR estimation. This method is compared with other methods such as linear prediction and Grey prediction. Outage probability calculation for the above methods is performed. The results are presented and compared in different curves. Based on our simulation results, outage probability obtained with this new method is less than previously reported methods.
Process innovation laboratory: a new approach to business process innovation based on enterprise information systems
Authors: C. MØller
Venue: Enterprise Information Systems (2007)

Most organizations today are required not only to operate effective business processes but also to allow for changing business conditions at an increasing rate. Today nearly every business relies on their enterprise information systems (EIS) for process integration and future generations of EIS will increasingly be driven by business process models. Consequently business process modelling and improvement is becoming a serious challenge. The aim of this paper is to establish a conceptual framework for business process innovation (BPI) in the supply chain based on advanced EIS. The challenge is thus to create a new methodology for developing and exploring process models and applications. The paper outlines the process innovation laboratory (Π-Lab) as a new approach to BPI. The Π-Lab is a comprehensive framework and a collaborative workspace for experimenting with process models. The Π-Lab facilitates innovation by using an integrated action learning approach to process modelling in a controlled environment. The study is based on design science and the paper also discusses the implications to EIS research and practice.
On four-connecting a triconnected graph
Authors: T. Hsu
Venue: Proceedings of the 33rd Annual Symposium on Foundations of Computer Science (1992)

The author considers the problem of finding a smallest set of edges whose addition four-connects a triconnected graph. This is a fundamental graph-theoretic problem that has applications in designing reliable networks. He presents an O(n alpha (m,n)+m) time sequential algorithm for four-connecting an undirected graph G that is triconnected by adding the smallest number of edges, where n and m are the number of vertices and edges in G, respectively, and alpha (m, n) is the inverse Ackermann function. He presents a new lower bound for the number of edges needed to four-connect a triconnected graph. The form of this lower bound is different from the form of the lower bound known for biconnectivity augmentation and triconnectivity augmentation. The new lower bound applies for arbitrary k, and gives a tighter lower bound than the one known earlier for the number of edges needed to k-connect a (k-1)-connect graph. For k=4, he shows that this lower bound is tight by giving an efficient algorithm for finding a set edges with the required size whose addition four-connects a triconnected graph.
Nearest neighbor sampling for cross company defect predictors: abstract only
Authors: Burak Turhan, Ayşe Bener, Tim Menzies
Venue: Proceedings of the 2008 workshop on Defects in large software systems (2008)

Several research in defect prediction focus on building models with available local data (i.e. within company predictors). To employ these models, a company should have a data repository, where project metrics and defect information from past projects are stored. However, few companies apply this practice. In a recent work, we have shown that cross company data can be used for building predictors with the cost of increased false alarms. Thus, we argued that the practical application of cross-company predictors is limited to mission critical projects and companies should starve for local data. In this paper, we show that nearest neighbor (NN) sampling of cross-company data removes the increased false alarm rates. We conclude that cross company defect predictors can be practical tools with NN sampling, yet local predictors are still the best and companies should keep starving for local data.
The cubic semilocal convergence on two variants of Newton's method
Authors: Quan Zheng, Rongxia Bai, Zhongli Liu
Venue: Journal of Computational and Applied Mathematics (2008)

In this paper, we discuss two variants of Newton's method without using any second derivative for solving nonlinear equations. By using the majorant function and confirming the majorant sequences, we obtain the cubic semilocal convergence and the error estimation in the Kantorovich-type theorems. The numerical examples are presented to support the usefulness and significance.
Image-based visual servoing schemes for nonholonomic mobile manipulators
Authors: Alessandro De luca, Giuseppe Oriolo, Paolo robuffo Giordano
Venue: Robotica (2007)

We consider the task-oriented modeling of the differential kinematics of nonholonomic mobile manipulators (NMMs). A suitable NMM Jacobian is defined that relates the available input commands to the time derivative of the task variables, and can be used to formulate and solve kinematic control problems. When the NMM is redundant with respect to the given task, we provide an extension of two well-known redundancy resolution methods for fixed-base manipulators (Projected Gradient and Task Priority) and introduce a novel technique (Task Sequencing) aimed at improving performance, e.g., avoiding singularities. The proposed methods are applied then to the specific case of image-based visual servoing, where the NMM image Jacobian combines the interaction matrix and the kinematic model of the mobile manipulator. Comparative numerical results are presented for two case studies.
FTC Sues N-Data for Violating Standards Commitment to IEEE
Authors: Richard Stern
Venue: IEEE Micro (2008)

The Federal Trade Commission announced that it simultaneously filed suit against N-Data and settled the case by entering into a consent order with N-Data. The FTC charged N-Data with violating section 5 of the FTC Act by violating a commitment to the IEEE to license NWay Ethernet patents on previously agreed upon royalty terms; the higher royalties demanded by N-Data caused higher prices to be passed on to consumers. Micro's legal columnist, Richard Stern, explicates the case.
Feature Selection using Multi-Layer Perceptron in HIV-1 Protease Cleavage Data
Authors: Gilhan Kim, Yeonjoo Kim, Hyeoncheol Kim
Venue: Proceedings of the 2008 International Conference on BioMedical Engineering and Informatics - Volume 01 (2008)

Recently, several machine learning approaches have been applied to modeling of the specificity for HIV-1 proteasecleavage domain. However, HIV-1 protease cleavagedomain with high dimensionality and small number ofsamples could misguide classification modeling and its interpretation. Thus, a method to select a smaller number of relevant features is required. Appropriate feature selection could eliminate irrelevant and redundant features, and thus, improves prediction performance and provides faster and more cost-effective models. As a result, we can gain deeper insight about dataset. In this paper, we introduce anew feature selection method, called FS-MLP, that extracts relevant features using multi-layered perceptron learning. With the method, we could extract a set of effective featuresin a multi-variate and non-linear way. Our experimental results on three types of artificial datasets and HIV-1 protease cleavage dataset show that performance of the FS-MLP is higher than other methods.
Grey video compression methods using fractals
Authors: Meiqing Wang, Choi-Hong Lai
Venue: International Journal of Computer Mathematics (2007)

The authors' experience in the treatment of grey video compression using fractals is summarized and compared with other research in the same field. Experience with parallel and distributed computing is also discussed.
Feedback reduction in uplink MIMO OFDM systems by chunk optimization
Authors: Eduard Jorswieck, Aydin Sezgin, Björn Ottersten, Arogyaswami Paulraj
Venue: EURASIP Journal on Advances in Signal Processing (2008)

The performance of multiuser MIMO systems can be significantly increased by channel-aware scheduling and signal processing at the transmitters based on channel state information. In the multipleantenna uplink multicarrier scenario, the base station decides centrally on the optimal signal processing and spectral power allocation as well as scheduling. An interesting challenge is the reduction of the overhead in order to inform the mobiles about their transmit strategies. In this work, we propose to reduce the feedback by chunk processing and quantization. We maximize the weighted sum rate of a MIMO OFDM MAC under individual power constraints and chunk size constraints. An efficient iterative algorithm is developed and convergence is proved. The feed-back overhead as a function of the chunk size is considered in the rate computation and the optimal chunk size is determined by numerical simulations for various channel models. Finally, the issues of finite modulation and coding schemes as well as quantization of the precoding matrices are addressed.
CARVER: A Slicing Tool for Communicating Automata Specifications
Authors: Sébastien Labbé, Arnault Lapitre
Venue: Proceedings of the Second International Symposium on Leveraging Applications of Formal Methods, Verification and Validation (2006)

Slicing communicating automata specifications is a model reduction technique that has been shown to be efficient in our previous works. This paper introduces Carver, a tool for slicing communicating automata specifications, that underlies dependence-based slicing techniques. It is described how this tool can extract slices from specifications, and how it can be integrated in the environment of other tools, for the purpose of reducing the complexity of formal analyses.
Efficient pattern matching over event streams
Authors: Jagrati Agrawal, Yanlei Diao, Daniel Gyllstrom, Neil Immerman
Venue: Proceedings of the 2008 ACM SIGMOD international conference on Management of data (2008)

Pattern matching over event streams is increasingly being employed in many areas including financial services, RFIDbased inventory management, click stream analysis, and electronic health systems. While regular expression matching is well studied, pattern matching over streams presents two new challenges: Languages for pattern matching over streams are significantly richer than languages for regular expression matching. Furthermore, efficient evaluation of these pattern queries over streams requires new algorithms and optimizations: the conventional wisdom for stream query processing (i.e., using selection-join-aggregation) is inadequate. In this paper, we present a formal evaluation model that offers precise semantics for this new class of queries and a query evaluation framework permitting optimizations in a principled way. We further analyze the runtime complexity of query evaluation using this model and develop a suite of techniques that improve runtime efficiency by exploiting sharing in storage and processing. Our experimental results provide insights into the various factors on runtime performance and demonstrate the significant performance gains of our sharing techniques.