ppxscal/embedding_network huggingface dataset:
Applying simulation to interative manufacturing cell design
Authors: Sara L. Maas, Charles R. Standridge
Venue: Proceedings of the 37th conference on Winter simulation (2005)

Launching a manufacturing cell to be efficient and lean, yet profitable, is a time-consuming process and is often based on many assumptions. The utilization of simulation models to help design the cell and the logistical structure to support it can expedite and streamline the development process. Assumptions and designs can be validated to help insure effective operations as soon as possible. We have developed a generic simulation model and associated capacity analysis, schedule planning, and target inventory setting software to support the computer based assessment of the operation of cells typical to the plastic manufacturing industry before capital investments are finalized. Model input describes a particular cell, the products it produces, and customer demand for these products. Results show the customer service level, product inventory levels, equipment utilization, and the daily production schedule. Spreadsheet software supports data entry and report examination. All software is integrated in a single simulation environment.
Intelligent Collaborative Tracking by Mining Auxiliary Objects
Authors: Ming Yang, Ying Wu, Shihong Lao
Venue: Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1 (2006)

Many tracking methods face a fundamental dilemma in practice: tracking has to be computationally efficient but verifying if or not the tracker is following the true target tends to be demanding, especially when the background is cluttered and/or when occlusion occurs. Due to the lack of a good solution to this problem, many existing methods tend to be either computationally intensive with the use of sophisticated image observation models, or vulnerable to the false alarms. This greatly threatens long-duration robust tracking. This paper presents a novel solution to this dilemma by integrating into the tracking process a set of auxiliary objects that are automatically discovered in the video on the fly by data mining. Auxiliary objects have three properties at least in a short time interval: (1) persistent co-occurrence with the target; (2) consistent motion correlation with the target; and (3) easy to track. The collaborative tracking of these auxiliary objects leads to an efficient computation as well as a strong verification. Our extensive experiments have exhibited exciting performance in very challenging real-world testing cases.
Self-adjusting Component-Based Fault Management
Authors: Rong Su, Michel R. V. Chaudron
Venue: Proceedings of the 32nd EUROMICRO Conference on Software Engineering and Advanced Applications (2006)

The Trust4All project aims to define an open, component-based framework for the middleware layer in high-volume embedded appliances that enables robust and reliable operation, upgrading and extension. To improve availability of each individual application in a Trust4All system, we propose a runtime configurable fault management mechanism (FMM) which detects deviations from given service specifications by intercepting interface calls. There are two novel contributions associated with FMM. First, when repair is necessary, FMM picks a repair action that incurs the best tradeoff between the success rate and the cost of repair. Second, considering that it is rather difficult to obtain sufficient information about third party components during their early stage of usage, FMM is designed to be able to accumulate appropriate knowledge, e.g. the success rate of a specific repair action in the past and rules that can avoid a specific failure, and self-adjust its capability accordingly.
Multi-Tier Granule Mining for Representations of Multidimensional Association Rules
Authors: Yuefeng Li, Wanzhong Yang, Yue Xu
Venue: Proceedings of the Sixth International Conference on Data Mining (2006)

It is a big challenge to promise the quality of multidimensional association mining. The essential issue is how to represent meaningful multidimensional association rules efficiently. Currently we have not found satisfactory approaches for solving this challenge because of the complicated correlation between attributes. Multi-tier granule mining is an initiative for solving this challenging issue. It divides attributes into some tiers and then compresses the large multidimensional database into granules at each tier. It also builds association mappings to illustrate the correlation between tiers. In this way, the meaningful association rules can be justified according to these association mappings.
Learning executable agent behaviors from observation
Authors: Andrew Guillory, Hai Nguyen, Tucker Balch, Charles Lee Isbell,  Jr.
Venue: Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems (2006)

We present a method for learning a human understandable, executable model of an agent's behavior using observations of its interaction with the environment. By executable we mean that the model is suitable for direct execution by an agent. Traditional models of behavior used for recognition tasks (e.g., Hidden Markov Models) are insufficent for this problem because they cannot respond to input from the environment. We train an Input/Output Hidden Markov Model where the output distributions are mixtures of learned low level actions and the transition distributions are conditional on features detected by the agent's sensors. We show that the system is able to learn both the behavior and human-understandable structure of a simulated model.
Privacy APIs: Access Control Techniques to Analyze and Verify Legal Privacy Policies
Authors: Michael J. May, Carl A. Gunter, Insup Lee
Venue: Proceedings of the 19th IEEE workshop on Computer Security Foundations (2006)

There is a growing interest in establishing rules to regulate the privacy of citizens in the treatment of sensitive personal data such as medical and financial records. Such rules must be respected by software used in these sectors. The regulatory statements are somewhat informal and must be interpreted carefully in the software interface to private data. This paper describes techniques to formalize regulatory privacy rules and how to exploit this formalization to analyze the rules automatically. Our formalism, which we call privacy APIs, is an extension of access control matrix operations to include (1) operations for notification and logging and (2) constructs that ease the mapping between legal and formal language. We validate the expressive power of privacy APIs by encoding the 2000 and 2003 HIPAA consent rules in our system. This formalization is then encoded into Promela and we validate the usefulness of the formalism by using the SPIN model checker to verify properties that distinguish the two versions of HIPAA.
Computational Approaches to Supporting Large-Scale Analysis of Photoreceptor-Enriched Gene Expression
Authors: Haiying Wang, Huiru Zheng, Francisco Azuaje
Venue: Proceedings of the 19th IEEE Symposium on Computer-Based Medical Systems (2006)

Retinal photoreceptor cells are responsible for light detection and phototransduction. The understanding of molecular mechanisms regulating photoreceptor gene expression during retinal development may have important implications in clinical neuroscience. Using self-adaptive neural networks and pattern validation statistical tools, this paper explores large-scale analysis of photoreceptor gene expression. Based on the analysis of data generated by serial analysis of gene expression (SAGE) in the developing mouse retina, significant expression patterns for the in silico detection of photoreceptor-enriched genes were revealed. This study demonstrates how machine learning and statistical techniques may be effectively combined to detect key complex relationships encoded in SAGE data. Such approaches may support inexpensive functional predictions prior to the application of experimental methodologies.
Distributed Coordination for Scalable Multimedia Streaming Model
Authors: Satoshi Itaya, Naohiro Hayashibara, Tomoya Enokido, Makoto Takizawa
Venue: Proceedings of the 26th IEEE International ConferenceWorkshops on Distributed Computing Systems (2006)

We discuss how to realize the multimedia streaming service by using multiple peers in a peer-to-peer (P2P) overlay network. Here, multimedia contents are required to be reliably delivered to processes in a real-time manner. Multimedia contents are distributed to peers in various ways like downloading. A peer which holds a content can provide other peers with the content. In our distributed multi-source streaming model, a collection of peers in parallel and redundantly transmit packets of a multimedia content to a requesting peer to realize the reliability and scalability without centralized controller. Even if some peer is faulty and packets are lost and delayed, a requesting peer receives every data of a content at the required rate. Furthermore, multiple peers start transmitting packets to a leaf peer and change packets to be transmitted and transmission rate without centralized controller to support shorter response time.
A Digital Content Protection Scheme Using MPEG-21 REL with Applications to DVB Systems
Authors: Ying-Tzu Shih, Feng-Cheng Chang, Hsueh-Ming Hang
Venue: Proceedings of the 2006 International Conference on Intelligent Information Hiding and Multimedia (2006)

In a digital TV system, the Conditional Access (CA) system is essential to protect programs from unauthorized access. However, the encryption technique alone is not sufficient to protect or control the use of contents after decryption. To provide flexible and complete Digital Rights Management (DRM) protection on the Digital Video Broadcasting (DVB) programs, we propose a method that adapts the MPEG- 21 REL technology and integrates it into a DVB-T system. By extending the Service Information (SI) section of a DVB stream to include an REL license, the transmitted content can be conveniently consumed and legally protected. Our design is verified by an experimental hardware system. The results show that the proposed method can provide both the conditional access functionality and the usage control of broadcasted contents.
Knowing Where Things Are: Parahippocampal Involvement in Encoding Object Locations in Virtual Large-Scale Space
Authors: E. A. Maguire, C. D. Frith, N. Burgess, J. G. Donnett, J. O'Keefe
Venue: Journal of Cognitive Neuroscience (1998)

The involvement of the medial temporal-lobe region in allocentric mapping of the environment has been observed in human lesion and functional imaging work. Cognitive models of environmental learning ascribe a key role to salient landmarks in representing large-scale space. In the present experiments we examined the neural substrates of the topographical memory acquisition process when environmental landmarks were more specifically identifiable. Using positron emission tomography (PET), we measured regional cerebral blood flow changes while normal subjects explored and learned in a virtual reality environment. One experiment involved an environment containing salient objects and textures that could be used to discriminate different rooms. Another experiment involved a plain empty environment in which rooms were distinguishable only by their shape. Learning in both cases activated a network of bilateral occipital, medial parietal, and occipitotemporal regions. The presence of salient objects and textures in an environment additionally resulted in increased activity in the right parahippocampal gyrus. This region was not activated during exploration of the empty environment. These findings suggest that encoding of salient objects into a representation of large-scale space is a critical factor in instigating parahippocampal involvement in topographical memory formation in humans and accords with previous studies implicating parahippocampal areas in the encoding of object location.
Calculus of Interpolated Fuzzy Relation Type Fuzzy Reasoning Method
Authors: Manabu Shimakawa
Venue: Proceedings of the First International Conference on Innovative Computing, Information and Control - Volume 2 (2006)

Interpolated Fuzzy Relation Type (IFRT) fuzzy reasoning method has the following two features: (1) the membership function of a reasoning result fuzzy set is not likely to produce a complicated shape, so it is easy to interpret its meaning, (2) if the fuzziness of an input fuzzy set increases, the fuzziness of the reasoning result fuzzy set also increases. Reasoning process of IFRT method is simple in case of given a real number as input. But fuzzy number input case, its reasoning process is not easy as compared with real number input case. This paper shows practical calculus technique of reasoning process for real number input case and fuzzy number input case with concrete example.
Speculative Parallelization
Authors: Arturo Gonzalez-Escribano, Diego R. Llanos
Venue: Computer (2006)

Some emerging technologies try to exploit the parallel capabilities of modern processors.
A Fuzzy Paradigm Approach for Business Process Intelligence
Authors: Oliver Thomas, Otmar Adam, Katrina Leyking, Peter Loos
Venue: Proceedings of the The 8th IEEE International Conference on E-Commerce Technology and The 3rd IEEE International Conference on Enterprise Computing, E-Commerce, and E-Services (2006)

The controllability of business processes and their agility in the sense of their easy adjustment to changes in the business environment are critical success factors. A special form of business intelligence targeted towards business processes and extended by the methods of soft computing with the name "Soft Business Process Intelligence" will be recommended in this article. First, the modeling of business processes with regard to the structuring of models and the formalization of fuzziness using the Fuzzy-Set-Theory will be adjusted. Then, a prototypical software implementation will be presented which will provide insights as to how artificial neural networks can be used to uncover business logic in processes (process mining), as well as for the improvement of business processes through learning.
Hybrid wireless mesh network deployment: a communication testbed for disaster scenarios
Authors: Raheleh B. Dilmaghani, Ramesh R. Rao
Venue: Proceedings of the 1st international workshop on Wireless network testbeds, experimental evaluation characterization (2006)

The application of a reliable communication infrastructure in emergency situations is the focus of this project. Communication and interoperability between different organizations of first responders has been a problem for a long time. There have been examples of failure in communication between different organizations at World Trade Center on 9/11: for example some of the police warnings were not heard by fire fighters that resulted in several lives lost. In most cases, network unavailability or incapability of coordination among networks causes much damage. A communication infrastructure has specific requirements to be widely deployable at emergency applications such as high reliability, robustness, interoperability with existing technologies, quick reconfiguration, and low cost. It must be able to operate in a highly distributed and infrastructure-less manner, quickly deployable, easy to reconfigure, and allocate network resources efficiently. We propose a Hybrid Wireless Mesh Network as a well-suited candidate capable of creating a communication infrastructure where the existing communication infrastructure is damaged or unavailable. This infrastructure has the ability to work in a heterogeneous environment where different technologies might be available as backhaul through multiple interface cards designed in Calit2's CalMesh boxes. In addition to the technical constraints in such a demanding environment, we must consider some of the sociological problems that arise when new technologies are introduced, including resistance to technology adoption, and designing new warning systems to utilize the new infrastructure, and concerns surrounding sharing information and privacy.In our research to date, we have deployed a HWMN made up of Calit2's interoperable CalMesh nodes at a full-scale crisis response drill organized by the San Diego Metropolitan Medical Strike Team (MMST) in which we were able to collect network statistical data from the medical first responders' communication over the network we deployed.We are also developing our simulation results in cellular networks investigating different real scenarios that may occur at ground zero. We would like to extract mobility patterns and channel characterization from real world scenarios to integrate this simulation results with other transportation and evacuation simulators in order to allocate network resources more efficiently, and route traffic effectively to insure that cellular infrastructures are not overloaded so that broadcast warnings and messages are still received by evacuees.
Stability of delayed feedback controllers for discrete time systems
Authors: O. Morgul
Venue: Proceedings of the 2003 International Conference on Physics and Control - Volume 2 (2003)

We consider the delayed feedback control (DFC) scheme for one dimensional discrete time systems. To analyze the stability, we construct a map whose fixed points correspond to the periodic orbits of the system to be controlled. Then the stability of the DFC is equivalent to the stability of the corresponding equilibrium point of the constructed map. 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
High-resolution magnetohydrodynamic equilibrium code for unity beta plasmas
Authors: P.-A. Gourdain, J.-N. Leboeuf, R. Y. Neches
Venue: Journal of Computational Physics (2006)

There is great interest in the properties of extremely high-β magnetohydrodynamic equilibria in axisymmetric toroidal geometry and the stability of such equilibria. However, few equilibrium codes maintain solid numerical behavior as beta approaches unity. The free-boundary algorithm presented herein utilizes a numerically stabilized multigrid method, current density input, position control, magnetic axis search, and dynamically adjusted simulated annealing. This approach yields numerically robust behavior in the spectrum of cases ranging from low to very high-β configurations. As the convergence time depends linearly on the total number of grid points, the production of extremely fine, low-error equilibria becomes possible. Such a code facilitates a variety of intriguing applications which include the exploration of the stability of extreme Shafranov shift equilibria.
Internet nuggets
Authors: Mark Thorson
Venue: ACM SIGARCH Computer Architecture News (2006)

This column consists of selected traffic from the comp.arch newsgroup, a forum for discussion of computer architecture on the Internet---an international computer network.As always, the opinions expressed in this column are the personal views of the authors, and do not necessarily represent the institutions to which they are affiliated.Text which sets the context of a message appears underlined or in italics; this is usually text the author has quoted from earlier messages. The code-like expressions below the authors' names are their addresses on Internet.
A scaleable document clustering approach for large document corpora
Authors: Niall Rooney, David Patterson, Mykola Galushka, Vladimir Dobrynin
Venue: Information Processing and Management: an International Journal (2006)

In this paper, the scalability and quality of the contextual document clustering (CDC) approach is demonstrated for large data-sets using the whole Reuters Corpus Volume 1 (RCV1) collection. CDC is a form of distributional clustering, which automatically discovers contexts of narrow scope within a document corpus. These contexts act as attractors for clustering documents that are semantically related to each other. Once clustered, the documents are organized into a minimum spanning tree so that the topical similarity of adjacent documents within this structure can be assessed. The pre-defined categories from three different document category sets are used to assess the quality of CDC in terms of its ability to group and structure semantically related documents given the contexts. Quality is evaluated based on two factors, the category overlap between adjacent documents within a cluster, and how well a representative document categorizes all the other documents within a cluster. As the RCV1 collection was collated in a time ordered fashion, it was possible to assess the stability of clusters formed from documents within one time interval when presented with new unseen documents at subsequent time intervals. We demonstrate that CDC is a powerful and scaleable technique with the ability to create stable clusters of high quality. Additionally, to our knowledge this is the first time that a collection as large as RCV1 has been analyzed in its entirety using a static clustering approach.
An approximation algorithm for maximum P3-packing in subcubic graphs
Authors: Adrian Kosowski, Michał Małafiejski, Paweł Zyliński
Venue: Information Processing Letters (2006)

We give a linear time 4/3-approximation algorithm for the problem of finding the maximum number of vertex-disjoint paths of order 3 in subcubic graphs without pendant vertices, which improves previously known results [K. Kawarabayashi, H. Matsuda, Y. Oda, K. Ota, Path factors in cubic graphs, Journal of Graph Theory 39 (2002) 188-193; A. Kelmans, D. Mubayi, How many disjoint 2-edge paths must a cubic graph have?, Journal of Graph Theory 45 (2004) 57-79].
Block Selection in the Local Appearance-based Face Recognition Scheme
Authors: Hazim Kemal Ekenel, Rainer Stiefelhagen
Venue: Proceedings of the 2006 Conference on Computer Vision and Pattern Recognition Workshop (2006)

In this paper we investigate the benefits of using a local appearance-based face recognition scheme against the problem of facial occlusion. We proposed two separate automatic block selection approaches to select the local image blocks that could be used for classification. Proposed approaches are tested against both upper and lower facial occlusions using the AR face database. Significant improvements are observed in the face recognition performance.
A novel information geometric approach to variable selection in MLP networks
Authors: A. Eleuteri, R. Tagliaferri, L. Milano
Venue: Neural Networks (2005)

In this paper, a novel information geometric-based variable selection criterion for multi-layer perceptron networks is described. It is based on projections of the Riemannian manifold defined by a multi-layer perceptron network on submanifolds defined by multi-layer perceptron networks with reduced input dimension. We show how the divergence between models can be used as a criterion for an efficient search in the space of networks with different inputs. Then, we show how the posterior probabilities of the models can be evaluated to rank the projected models. Finally, we test our algorithm on synthetic and real data, and compare its performances with other methods reported in literature.