ppxscal/embedding_network huggingface dataset:
Efficient Learning Algorithms for Agents Mining Time-Changing Data Streams
Authors: Lior Cohen, Gil Avrahami, Mark Last, Abraham Kandel
Venue: Proceedings of the International Conference on Computational Inteligence for Modelling Control and Automation and International Conference on Intelligent Agents Web Technologies and International Commerce (2006)

Many continuously recorded data streams are generated by non-stationary processes, which may change over time, in some cases even drastically. Some adaptive learning agents deal with time-changing data streams by generating a new model from every incoming window of training examples. Though this solution should ensure an accurate and relevant model at all times, it may waste significant computational resources on continuous re-generation of nearly identical models during periods of stability. In this paper, we evaluate a series of efficient incremental algorithms that are nearly as accurate as existing online methods, sometimes even outperforming them, while being considerably cheaper in terms of the processing time. The proposed incremental techniques are based on the Information Network classification algorithm. The incremental methods efficiency is demonstrated on realworld streams of road traffic and intrusion detection data.
Making a strong business case for multiagent technology
Authors: Steve S. Benfield, Jim Hendrickson, Daniel Galanti
Venue: Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems (2006)

In this paper, we describe lessons learned in commercializing and implementing agent-based systems in real-world business situations. Most notably we discuss gains in programmer productivity achieved by using AdaptivEnterprise, a commercial IDE and J2EE runtime engine based on BDI agents. In a wide range of complex business applications, we show that the use of BDI technology incorporated within an enterprise-level architecture can improve overall developer productivity by an average 350%. For java coding alone, the increase in productivity was over 500%. In competitive bids for large scale enterprise applications, AdaptivEnterprise was able to reduce total cost of ownership between two- and three-fold. In addition, the agent approach allowed the business to change and extend solutions quickly and helped bridge the gap between the business side and IT development.
The computer literacy education using Open Office
Authors: Shinji UCHIDA, Shigenobu FUKUSHIMA, Fumiaki MASAKIYO, Masaya NAKAMORI, Yasuko HONDA, Takeshi KANDA
Venue: Proceedings of the 19th Conference on Software Engineering Education and Training Workshops (2006)

Conventionally, we have taught computer literacy using MS-Office. However, the license cost of MS-Office increased about 2.5 times since we renewed our license. Then, we have built the computer literacy educational environment using Open Office, in order to reduce the license cost. In this paper we reported on this work of building the new environment and some associated problems. We also reported on the evaluation of this environment by questionnaire.
Semantic Relevance and Semantic Disorders
Authors: Giuseppe Sartori, Luigi Lombardi
Venue: Journal of Cognitive Neuroscience (2004)

Semantic features are of different importance in concept representation. The concept elephant may be more easily identified from the feature <trunk> than from the feature <four legs>. We propose a new model of semantic memory to measure the relevance of semantic features for a concept and use this model to investigate the controversial issue of category specificity. Category-specific patients have an impairment in one domain of knowledge (e.g., living), whereas the other domain (e.g., nonliving) is relatively spared. We show that categories differ in the level of relevance and that, when concepts belonging to living and nonliving categories are equated to this parameter, the category-specific disorder disappears. Our findings suggest that category specificity, as well as other semantic-related effects, may be explained by a semantic memory model in which concepts are represented by semantic features with associated relevance values.
Moving forward: the learning sciences and the future of education
Authors: R. Keith Sawyer, Allan Collins, Jere Confrey, Janet L. Kolodner, Marlene Scardamalia
Venue: Proceedings of the 7th international conference on Learning sciences (2006)

In Spring 2006, The Cambridge Handbook of the Learning Sciences (CHLS) was published. CHLS is the first introduction and handbook of the learning sciences, and combines breadth of coverage with definitive statements by leading scientists working in the learning sciences. As such, it is an important milestone for the field. In this interactive session, the handbook's four advisory board members and its editor, along with the session participants, will explore two sets of questions that were raised during the preparation of the CHLS, and which to some extent remain unresolved. The first is inward---how to define the learning sciences, and how it is intellectually structured. The second is outward---how the learning sciences might impact education in the years to come.
On the limit behavior of recurrence coefficients for multiple orthogonal polynomials
Authors: A. I. Aptekarev, V. Kalyagin, G. López Lagomasino, I. A. Rocha
Venue: Journal of Approximation Theory (2006)

In this paper we investigate general properties of the coefficients in the recurrence relation satisfied by multiple orthogonal polynomials. The results include as particular cases Angelesco and Nikishin systems.
A Knowledge-Based Approach For Database Flexible Querying
Authors: N. Hachani, H. Ounelli
Venue: Proceedings of the 17th International Conference on Database and Expert Systems Applications (2006)

People have often insufficient knowledge about database structure and contents, thus frequently obtaining empty answers or having to reformulate the queries several times. This paper describes an approach extending the search criteria ranges in order to provide approximate answers to the user. This approach takes into account the user preferences. It is based on a knowledge base (KB) related to the application domain. The initial SQL query is transformed into a flexible query based on KB and fuzzy set theory. This flexible query is then rewritten into a boolean query called envelope. The envelope is evaluated with a traditional DBMS to take advantage of its full optimization capabilities. The tuples satisfying the envelope are finally ranked according to their satisfaction degree. Unlike other approaches, this one require to modify neither SQL language nor the database engine.
The role of agents in enterprise system management: a position paper
Authors: Onn Shehory
Venue: Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems (2006)

The size and complexity of enterprise computer systems are growing rapidly. As a result, system management has become increasingly difficult and expensive. In fact, management costs are typically estimated at 50%-70% of the total cost of ownership. Despite large investments in management software and personnel, enterprise computer systems are usually managed sub-optimally. This situation calls for a fundamental change in the way systems are managed.Recent studies suggest that systems manage themselves autonomously. Initial studies towards that goal reside in the fields of Autonomic Computing and Self* Systems. Many of those studies devise mechanisms for system monitoring, data filtering, problem determination, problem fixing and system adjustment and reconfiguration. The mechanisms are based, in large part, on methods from Artificial Intelligence, Statistics, Operations Research and Software Engineering.Current enterprise system management solutions --- theoretical and practical --- are centralized. However, the typical enterprise system is distributed. We claim that a centralized solution presents several risks. For instance, it introduces a management bottleneck, it incurs communication overheads, etc. We hence advocate that enterprise system management should be addressed in a distributed manner. Combining distribution and Al, we believe that an agent-based solution is appropriate. In this paper we present in more detail the suggested approach.
Detection of Interconnect Open Faults with Unknown Values by Ramp Voltage Application
Authors: Yukiya Miura
Venue: Proceedings of the 15th Asian Test Symposium (2006)

We have proposed a method for detecting interconnect open faults of CMOS combinational circuits by applying a ramp voltage to the power supply terminal. The method can assign a known logic value to a fault location automatically by applying a ramp voltage and as a result, it requires only one test vector to detect a fault as a delay fault or an erroneous logic value at primary outputs. In this paper, we show fault detectability and effectiveness of the proposed method by simulation-based and theoretical analysis. We also expose that the method can be applicable to every fault location in a circuit and open faults with unknown value. Finally, we show ATPG results that are suitable to the proposed method.
An Ontology Based Local Index in P2P Networks
Authors: Habib Rostami, Jafar Habibi, Hassan Abolhassani, Mojtaba Amirkhani, Ali Rahnama
Venue: Proceedings of the Second International Conference on Semantics, Knowledge, and Grid (2006)

Peer-to-peer networks (P2P) are beginning to form the infrastructure of future applications. One of the problems with unstructured P2P networks is their scalability limitation. This is also the problem in structured P2P networks that use broadcasting to find objects. These networks can't contain a large number of nodes because of the large amount of traffic that they have to handle. Local indexing is a method to reduce this traffic. But local indexes tend to become large with the growth of the network. Also limiting the size of these indexes causes loss of indexing information. In this paper we introduce a novel ontology based local index which limits the size of the local indexes without losing indexing information. We show that the method can be employed by many P2P networks. We also, as an example, apply this local index on HyperCup overlay network, and show that it reduces the network traffic significantly.
A Query Processing Mechanism for Top-k Query in P2P Networks
Authors: Hidekazu MATSUNAM, Tsutomu TERADA, Shojiro NISHIO
Venue: Proceedings of the 21st International Conference on Data Engineering Workshops (2005)

Recently, there has been an increasing interest in content sharing on peer-to-peer (P2P) networks. Since such a system employs a flooding mechanism for queries and because each peer returns many search results, the system's response to a query creates heavy traffic. Therefore, we propose a new and more efficient query processing method for top-k queries on P2P networks. We focus on the fact that users usually need search results only with a higher score. Our method reduces the reply traffic by controlling the number of query replies. Moreover, we evaluate the proposed method by simulation studies.
Decision support system for fisheries management
Authors: Tu H. Truong, Brian J. Rothschild, Farhad Azadivar
Venue: Proceedings of the 37th conference on Winter simulation (2005)

This paper presents a decision support system that is oriented toward fisheries policy and management decisions. The important current issues involve the development of an optimal harvesting plan for the fishing industry. A simulation optimization has been built to assist authorities in scheduling for a fleet of hundreds of vessels in terms of time and location of fishing, as well as amount and target species to be fished. Marine fisheries are highly complex and stochastic. A simulation model, therefore, is required. Simulation-based optimization utilizes the simulation model in obtaining the objective function values of a particular fishing schedule. A Genetic Algorithm is used as the optimization routine to determine the optimal fishing schedule, subject to fleet capacity and conservation requirements. The decision support system is then applied to the real situation in the Northeastern U.S.
Topological Equivalence between a 3D Object and the Reconstruction of Its Digital Image
Authors: Peer Stelldinger, Longin Jan Latecki, Marcelo Siqueira
Venue: IEEE Transactions on Pattern Analysis and Machine Intelligence (2007)

Digitization is not as easy as it looks. If one digitizes a 3D object even with a dense sampling grid, the reconstructed digital object may have topological distortions and, in general, there exists no upper bound for the Hausdorff distance. This explains why so far no algorithm has been known which guarantees topology preservation. However, as we will show, it is possible to repair the obtained digital image in a locally bounded way so that it is homeomorphic and close to the 3D object. The resulting digital object is always well-composed, which has nice implications for a lot of image analysis problems. Moreover, we will show that the surface of the original object is homeomorphic to the result of the marching cubes algorithm. This is really surprising since it means that the well-known topological problems of the marching cubes reconstruction simply do not occur for digital images of r-regular objects. Based on the trilinear interpolation, we also construct a smooth isosurface from the digital image that has the same topology as the original surface. Finally, we give a surprisingly simple topology preserving reconstruction method by using overlapping balls instead of cubical voxels. This is the first approach of digitizing 3D objects which guarantees topology preservation and gives an upper bound for the geometric distortion. Since the output can be chosen as a pure voxel presentation, a union of balls, a reconstruction by trilinear interpolation, a smooth isosurface, or the piecewise linear marching cubes surface, the results are directly applicable to a huge class of image analysis algorithms. Moreover, we show how one can efficiently estimate the volume and the surface area of 3D objects by looking at their digitizations. Measuring volume and surface area of digital objects are important problems in 3D image analysis. Good estimators should be multigrid convergent, i.e., the error goes to zero with increasing sampling density. We will show that every presented reconstruction method can be used for volume estimation and we will give a solution for the much more difficult problem of multigrid-convergent surface area estimation. Our solution is based on simple counting of voxels and we are the first to be able to give absolute bounds for the surface area.
Design of One-Sided Screening Specifications for Multi-characteristic Product
Authors: Hui-Chung Yeh, Hsien-Tang Tsai, Min-Chun Yu
Venue: Proceedings of the First International Conference on Innovative Computing, Information and Control - Volume 2 (2006)

Screening procedure is one of the effective approaches for quality assurance. Most researches study in the situation of single characteristic. However, many products have more than one quality characteristics. This research examined a multi-characteristic screening procedure using multiple screening variables. An extended OMS procedure using a heuristic algorithm is employed to reach the required average outgoing quality (AOQ) or conforming rate. Then two optimal models, namely the individual cut and linear cut approaches, are proposed to determine the optimal cutoff points of screening variables by maximizing the selected rate under a prespecified AOQ or conforming rate. An example of a complete inspection process is presented to illustrate the use of the proposed models.
Analyzing large DDoS attacks using multiple data sources
Authors: Z. Morley Mao, Vyas Sekar, Oliver Spatscheck, Jacobus van der Merwe, Rangarajan Vasudevan
Venue: Proceedings of the 2006 SIGCOMM workshop on Large-scale attack defense (2006)

We present a measurement study analyzing DDoS attacks from multiple data sources, relying on both direct measurements of flow-level information, and more traditional indirect measurements using backscatter analysis. Understanding the nature of DDoS attacks is critically important to the development of effective counter measures to this pressing problem. While much of the community's current understanding of DDoS attacks result from indirect measurements, our analysis suggests that such studies do not give a comprehensive view of DDoS attacks witnessed in today's Internet. Specifically, our results suggest little use of address spoofing by attackers, which imply that such attacks will be invisible to indirect backscatter measurement techniques. Further, at the detailed packet-level characterization (e.g., attack destination ports), there are significant differences between direct and indirect measurements. Thus, there is tremendous value in moving towards direct observations to better understand DDoS attacks. Direct measurements additionally provide information inaccessible to indirect measurements, enabling us to better understand how to defend against attacks. We find that for 70% of the attacks fewer than 50 source ASes are involved and a relatively small number of ASes produce nearly 72% of the total attack volume. This suggests that network providers can reduce a substantial volume of malicious traffic with targeted deployment of DDoS defenses.
Effective classification of noisy data streams with attribute-oriented dynamic classifier selection
Authors: Xingquan Zhu, Xindong Wu, Ying Yang
Venue: Knowledge and Information Systems (2006)

Recently, mining from data streams has become an important and challenging task for many real-world applications such as credit card fraud protection and sensor networking. One popular solution is to separate stream data into chunks, learn a base classifier from each chunk, and then integrate all base classifiers for effective classification. In this paper, we propose a new dynamic classifier selection (DCS) mechanism to integrate base classifiers for effective mining from data streams. The proposed algorithm dynamically selects a single "best" classifier to classify each test instance at run time. Our scheme uses statistical information from attribute values, and uses each attribute to partition the evaluation set into disjoint subsets, followed by a procedure that evaluates the classification accuracy of each base classifier on these subsets. Given a test instance, its attribute values determine the subsets that the similar instances in the evaluation set have constructed, and the classifier with the highest classification accuracy on those subsets is selected to classify the test instance. Experimental results and comparative studies demonstrate the efficiency and efficacy of our method. Such a DCS scheme appears to be promising in mining data streams with dramatic concept drifting or with a significant amount of noise, where the base classifiers are likely conflictive or have low confidence.
Investigation of ocean acoustics using autonomous instrumentation to quantify the water-sediment boundary properties
Authors: William M. Carey
Venue:  (2007)

Sound propagation in shallow water is characterized by interaction with the oceans surface, volume, and bottom. In many coastal margin regions, including the Eastern U.S. continental shelf and the coastal seas of China, the bottom is composed of a depositional sandy-silty top layer. Previous measurements of narrow and broadband sound transmission at frequencies from 100 Hz to 1 kHz in these regions are consistent with waveguide calculations based on depth and frequency dependent sound speed, attenuation and density profiles. Theoretical predictions for the frequency dependence of attenuation vary from quadratic for the porous media model of M.A. Biot to linear for various competing models. Results from experiments performed under known conditions with sandy bottoms, however, have agreed with attenuation proportional to f 1.84, which is slightly less than the theoretical value of f2 [Zhou and Zhang, J. Acoust. Soc. Am. 117, 2494]. This dissertation presents a reexamination of the fundamental considerations in the Biot derivation and leads to a simplification of the theory that can be coupled with site-specific, depth dependent attenuation and sound speed profiles to explain the observed frequency dependence. Long-range sound transmission measurements in a known waveguide can be used to estimate the site-specific sediment attenuation properties, but the costs and time associated with such at-sea experiments using traditional measurement techniques can be prohibitive. Here a new measurement tool consisting of an autonomous underwater vehicle and a small, low noise, towed hydrophone array was developed and used to obtain accurate long-range sound transmission measurements efficiently and cost effectively. To demonstrate this capability and to determine the modal and intrinsic attenuation characteristics, experiments were conducted in a carefully surveyed area in Nantucket Sound. A best-fit comparison between measured results and calculated results, while varying attenuation parameters, revealed the estimated power law exponent to be 1.87 between 220.5 and 1228 Hz. These results demonstrate the utility of this new cost effective and accurate measurement system. The sound transmission results, when compared with calculations based on the modified Biot theory, are shown to explain the observed frequency dependence.
International real-time streaming of 4K digital cinema
Authors: Takashi Shimizu, Daisuke Shirai, Hirokazu Takahashi, Takahiro Murooka, Kazuaki Obana, Yoshihide Tonomura, Takeru Inoue, Takahiro Yamaguchi, Tetsuro Fujii, Naohisa Ohta, Sadayasu Ono, Tomonori Aoyama, Laurin Herr, Natalie van Osdol, Xi Wang, Maxine D. Brown, Thomas A. DeFanti, Rollin Feld, Jacob Balser, Steve Morris, Trevor Henthorn, Greg Dawe, Peter Otto, Larry Smarr
Venue: Future Generation Computer Systems (2006)

This paper describes the world's first real-time, international transmission of 4K digital cinema and 4K Super High Definition (SHD) digital video at iGrid 2005, hosted at the California Institute of Telecommunications and Information Technology (Calit2) at the University of California, San Diego. Nearly six hours of live and pre-recorded 4K motion picture and audio content was streamed to iGrid in San Diego from the Research Institute for Digital Media and Content (DMC) at Keio University in Tokyo.To implement this demonstration, several new technologies were introduced, including a prototype high-performance 4K compressed multicasting system called "JPEG 2000 Flexcast", and "Soundscape", a practical scheme for synchronizing audio and video transmitted from different locations over IP networks.These iGrid 2005 demonstrations proved that it is now feasible to implement networked professional audio/video applications - production, post-production and distribution - even at 4K quality over IP networks up to 15,000 km long. The demonstrations also showed the new 4K motion picture technology being introduced for digital cinema can be usefully applied to other network applications such as remote telepresence, distance learning and scientific visualization.