ppxscal/embedding_network huggingface dataset:
Unified power management in wireless sensor networks
Authors: Chenyang Lu
Venue:  (2006)

Radio power management is of paramount concern in wireless sensor networks (WSNs) that must achieve long lifetimes on scarce amount of energy. Previous work has treated communication and sensing separately, which is insufficient for a common class of sensor networks that must satisfy both sensing and communication requirements. Furthermore, previous approaches focused on reducing energy consumption in individual radio states resulting in suboptimal solutions. Finally, existing power management protocols often assume simplistic models that cannot accurately reflect the sensing and communication properties of real-world WSNs. We develop a unified power management approach to address these issues. We first analyze the relationship between sensing and communication performance of WSNs. We show that sensing coverage often leads to good network connectivity and geographic routing performance, which provides insights into unified power management under both sensing and communication performance requirements. We then develop a novel approach called Minimum Power Configuration that integrates the power consumption in different radio states into a unified optimization framework. Finally, we develop two power management protocols that account for realistic communication and sensing properties of WSNs. Configurable Topology Control can configure a network topology to achieve desired path quality in presence of asymmetric and lossy links. Co-Grid is a coverage maintenance protocol that adopts a probabilistic sensing model. Co-Grid can satisfy desirable sensing QoS requirements (i.e., detection probability and false alarm rate) based on a distributed data fusion model.
Time-Based Haptic Analysis of Protein Dynamics
Authors: Katrin Bidmon, Guido Reina, Fabian Bos, Jurgen Pleiss, Thomas Ertl
Venue: Proceedings of the Second Joint EuroHaptics Conference and Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems (2007)

We present a new approach for evaluating a protein's simulated trajectory via time-based haptic feedback. Molecular-scale trajectories are highly dynamic and thus pose new demands on haptic interaction. Traditionally, the flexibility of each atom within the protein is represented by a scalar, not taking into account the direction of movement. Using our haptic approach for tracking the atoms gives the user this additional information and a more intuitive feedback than numbers or even plain graphics. We combine this with touchable protein and atom surfaces and data-driven surface properties as well as stereo representation. Having conceived this tool in close collaboration between experts from the field of biochemistry and computer scientists ensures the appropriateness of our approach.
Efficient replica maintenance for distributed storage systems
Authors: Byung-Gon Chun, Frank Dabek, Andreas Haeberlen, Emil Sit, Hakim Weatherspoon, M. Frans Kaashoek, John Kubiatowicz, Robert Morris
Venue: Proceedings of the 3rd conference on Networked Systems Design & Implementation - Volume 3 (2006)

This paper considers replication strategies for storage systems that aggregate the disks of many nodes spread over the Internet. Maintaining replication in such systems can be prohibitively expensive, since every transient network or host failure could potentially lead to copying a server's worth of data over the Internet to maintain replication levels. The following insights in designing an efficient replication algorithm emerge from the paper's analysis. First, durability can be provided separately from availability; the former is less expensive to ensure and a more useful goal for many wide-area applications. Second, the focus of a durability algorithm must be to create new copies of data objects faster than permanent disk failures destroy the objects; careful choice of policies for what nodes should hold what data can decrease repair time. Third, increasing the number of replicas of each data object does not help a system tolerate a higher disk failure probability, but does help tolerate bursts of failures. Finally, ensuring that the system makes use of replicas that recover after temporary failure is critical to efficiency. Based on these insights, the paper proposes the Carbonite replication algorithm for keeping data durable at a low cost. A simulation of Carbonite storing 1 TB of data over a 365 day trace of PlanetLab activity shows that Carbonite is able to keep all data durable and uses 44% more network traffic than a hypothetical system that only responds to permanent failures. In comparison, Total Recall and DHash require almost a factor of two more network traffic than this hypothetical system.
Autonomic Model for Managing Complex Healthcare Applications
Authors: Wail M. Omar, K. Samir, A. Taleb-Bendiab
Venue: Proceedings of the Fourth IEEE International Workshop on Engineering of Autonomic and Autonomous Systems (2007)

This paper presents the motivations for adopting autonomic computing architecture for supporting the management of enterprise healthcare applications. The proposed architecture consists of five units namely; health monitoring system, medical analyzer, medical plan, execute and medical knowledge system. The developed system is tested using a remote patients monitoring case-study. Finally, the paper concludes with general remarks and a statement of further work.
TARA: Topology-Aware Resource Adaptation to Alleviate Congestion in Sensor Networks
Authors: Jaewon Kang, Yanyong Zhang, Badri Nath
Venue: IEEE Transactions on Parallel and Distributed Systems (2007)

Network congestion can be alleviated either by reducing demand (traffic control) or by increasing capacity (resource control). Unlike in traditional wired or other wireless counterparts, sensor network deployments provide elastic resource availability for satisfying the fidelity level required by applications. In many cases, using traffic control can violate fidelity requirements. Hence, we propose the use of resource control: increasing capacity by enabling more nodes to become active during periods of congestion. However, a naive approach to increase resources without a careful consideration of the type of congestion, traffic pattern, and network topology will make the situation worse. In this paper, we present TARA, a topology-aware resource adaptation strategy to alleviate congestion. The core of TARA is our capacity analysis model, which can be used to estimate capacity of various topologies. Detailed performance results show that TARA can achieve data delivery rate and energy consumption that is close to an ideal offline resource control algorithm.
Improving evolutionary algorithm performance on maximizing functional test coverage of ASICs using adaptation of the fitness criteria
Authors: B. Aktan, G. Greenwood, M. H. Shor
Venue: Proceedings of the Evolutionary Computation on 2002. CEC '02. Proceedings of the 2002 Congress - Volume 02 (2002)

Adaptation of the fitness criteria can be a very powerful tool, enhancing the feedback scheme employed in standard evolutionary algorithms. When the problem the evolutionary algorithm (EA) is trying to solve is changing over time, the fitness criteria need to change to adapt to the new problem. Significant performance improvements are possible with feedback based adaptation schemes. This work outlines the results of an adaptation scheme applied to maximization of the functional test coverage problem.
Replay debugging for distributed applications
Authors: Dennis Geels, Gautam Altekar, Scott Shenker, Ion Stoica
Venue: Proceedings of the annual conference on USENIX '06 Annual Technical Conference (2006)

We have developed a new replay debugging tool, liblog, for distributed C/C++ applications. It logs the execution of deployed application processes and replays them deterministically, faithfully reproducing race conditions and non-deterministic failures, enabling careful offline analysis. To our knowledge, liblog is the first replay tool to address the requirements of large distributed systems: lightweight support for long-running programs, consistent replay of arbitrary subsets of application nodes, and operation in a mixed environment of logging and nonlogging processes. In addition, it requires no special hardware or kernel patches, supports unmodified application executables, and integrates GDB into the replay mechanism for simultaneous source-level debugging of multiple processes. This paper presents liblog's design, an evaluation of its runtime overhead, and a discussion of our experience with the tool to date.
Internet security and quality-of-service provision via machine-learning theory
Authors: C.-C. Jay Kuo
Venue:  (2006)

To detect DoS (Denial-of-Service) attacks, two mechanisms based on traffic pattern monitoring using HMMs (Hidden Markov Model) and multiple Markov models are proposed in this research. To effectively design a detector against the TCP SYN flooding attack, we first analyze the dynamic behavior of real world attacks and then propose a stateful HMM detector to achieve early detection with high accuracy. Multiple HMMs can achieve the advantages of misuse detection and anomaly detection by training them differently. With the stateful mechanism, the impact of background noise due to the protocol behavior can be mitigated. We compare the proposed HMM detector with the stateless Cumulative Sum (CUSUM) and the stateful CUSUM detector using trace-driven simulations. Simulation results show that the proposed HMM detector provides earlier detection time and a higher detection rate under the same false alarm rate. Furthermore, we develop a detector using multiple Markov models to detect the UDP flooding attack in wireless networks. The high-rate attack using UDP can be detected easily since there are few legitimate users using UDP in the network. However, it is difficult to detect subtle UDP flooding attacks since there are many UDP-based applications with a dynamic traffic rate. A Markov model is used to characterize the traffic pattern. Multiple Markov models are trained with normal traffic and some deviations from the normal traffic, and they are integrated into a single detector. The proposed detector is compared with the batch-sequential detection algorithm in terms of the false alarm rate and detection latency. Finally, to support various Internet services such as QoS, security, and accounting, the Internet traffic classification problem is studied. The proposed classification process consists of two steps: feature selection and classification. Candidate features that can be easily obtained by ISPs are considered. Then, we perform feature reduction to balance the performance and complexity. Decision trees are adopted as classifiers. It is demonstrated by simulations with real data that the proposed classification scheme outperforms existing techniques.
A Bayesian multiscale framework for Poisson inverse problems
Authors: R. Nowak
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 03 (1999)

This paper describes a maximum a posteriori (MAP) estimation method for linear inverse problems involving Poisson data based on a novel multiscale framework. The framework itself is founded on a carefully designed multiscale prior probability distribution placed on the "splits" in the multiscale partition of the underlying intensity, and it admits a remarkably simple MAP estimation procedure using an expectation-maximization (EM) algorithm. Unlike many other approaches to this problem, the EM update equations for our algorithm have simple, closed-form expressions. Additionally, our class of priors has the interesting feature that the "non-informative" member yields the traditional maximum likelihood solution; other choices are made to reflect prior belief as to the smoothness of the unknown intensity.
Combining statistical and knowledge-based spoken language understanding in conditional models
Authors: Ye-Yi Wang, Alex Acero, Milind Mahajan, John Lee
Venue: Proceedings of the COLING/ACL on Main conference poster sessions (2006)

Spoken Language Understanding (SLU) addresses the problem of extracting semantic meaning conveyed in an utterance. The traditional knowledge-based approach to this problem is very expensive --- it requires joint expertise in natural language processing and speech recognition, and best practices in language engineering for every new domain. On the other hand, a statistical learning approach needs a large amount of annotated data for model training, which is seldom available in practical applications outside of large research labs. A generative HMM/CFG composite model, which integrates easy-to-obtain domain knowledge into a data-driven statistical learning framework, has previously been introduced to reduce data requirement. The major contribution of this paper is the investigation of integrating prior knowledge and statistical learning in a conditional model framework. We also study and compare conditional random fields (CRFs) with perceptron learning for SLU. Experimental results show that the conditional models achieve more than 20% relative reduction in slot error rate over the HMM/CFG model, which had already achieved an SLU accuracy at the same level as the best results reported on the ATIS data.
Symbol-Based Machine Learning Approach for Supervised Segmentation of Follicular Lymphoma Images
Authors: Milan Zorman, Peter Kokol, Mitja Lenic, Jose Luis Sanchez de la Rosa, Jose Francisco Sigut, Silvia Alayon
Venue: Proceedings of the Twentieth IEEE International Symposium on Computer-Based Medical Systems (2007)

Lymphoma is a broad term encompassing a variety of cancers of the lymphatic system. Lymphoma is differentiated by the type of cell that multiplies and how the cancer presents itself. It is very important to get an exact diagnosis regarding lymphoma and to determine the treatments that will be most effective for the patient's condition. Our work was focused on the identification of lymphomas by finding follicles in microscopy images provided by the Laboratory of Pathology in the University Hospital of Tenerife, Spain. Roughly we can divide our work in two stages: in the first stage we did image pre-processing and feature extraction, and in the second stage we used different rough set approaches for pixel classification. These results were compared to decision tree results we obtained earlier. Symbolic machine learning approaches are often neglected when looking for image analysis tools. The results we got are very promising and show that symbolic approaches can be successful in image analysis applications.
Positive-definite Toeplitz completion in DOA estimation for fully-augmentable nonuniform linear antenna arrays
Authors: Y. I. Abramovich
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 05 (1996)

This paper considers the problem of DOA (direction-of-arrival) estimation for multiple uncorrelated plane waves incident upon so-called "fully-augmentable" sparse linear arrays. When the number of waves, m, is less than the number of antenna sensors, M, a new approach is presented which constructs a full-sized positive definite (p.d.) Toeplitz matrix from the M/spl times/M direct data covariance matrix R/spl circ/. Alternating projections are then applied to find a p.d. Toeplitz matrix with truncated signal subspace. When m/spl ges/M, direct augmentation is used to form an initial Toeplitz estimate which is then treated as in the previous case. Results on simulated data demonstrate that this new approach has superior DOA-estimation performance compared with existing methods.
Computer Model of Geological Faults in 3D and the Application in Beijing Olympic Green District
Authors: Liangfeng Zhu
Venue: Proceedings of the 16th International Conference on Artificial Reality and Telexistence--Workshops (2006)

The structural modeling techniques of complex geological entities contained reverse faults are discussed and a series of approaches are proposed. We discusses the principle and the process of computer modeling of geological faults in 3D, and establishes a series of applied technical proposal. Two kinds of modeling approaches for faults, such as modeling technique of fault based on stratum recover and based on interpolation in subareas, are compared, and a novel approach, named Unified Modeling Technique for stratum and fault, is presented to solve the puzzled problems of reverse faults, syn-sedimentary faults and faults terminated within geological models. A case study of fault model of bed rock in Beijing Olympic Green District is presented and shows the practical result of this method. It deepens the profound comprehension of geological phenomenon and the modeling approach, and establishes the basic techniques of 3D geological modeling for the practical apply in geosciences field.
The spelling bee: an augmented physical block system that knows how to spell
Authors: Amnon Dekel, Galit Yavne, Ela Ben-Tov, Yulia Roschak
Venue: Proceedings of the international conference on Advances in computer entertainment technology (2007)

Physical games have always been with us. In this paper we explore the utility of adding tangible interfaces and embedded computing into a well known children's ABC spelling blocks game and thus enable it to offer intelligent, immediate and meaningful feedback to the players. We developed a prototype using simple low cost elements and tested it with five children aged 7 - 12. The children understood the functionality of the system almost immediately and found the game easy to use and familiar in appearance, yet at the same time it inspired them to try and spell words in order to elicit feedback. A number of problems were identified and possible solutions are offered.
Research on the Collaborative Virtual Products Development Based on Web and X3D
Authors: Li Haiqing, Yin Guofu, Fu Jie
Venue: Proceedings of the 16th International Conference on Artificial Reality and Telexistence--Workshops (2006)

After analyzing the current development trend of the products virtual design technique, the key technique of virtual products design and development is discussed in this paper. The frame of mechanical products virtual development has been put forward. Discuss the internal running mechanism of X3D (Extensible 3D) after analyzing the similarities and differences of X3D and VRML. Manipulate the virtual scene by the means of SAI (Scene Access Interface). The system allows users to manage products information in 3D scene and the revised information could be saved to database automatically. The 3D scene would be rebuilt according to the newly database when system is refreshed. Present the application instance of interaction for double-suction centrifugal pump in the virtual environment with using X3D-EDIT as the development tool of prototype system.
A plan for assessment and continuous improvement in a civil engineering technology program
Authors: T. W. Zeigler
Venue: Proceedings of the Frontiers in Education Conference, 2001. on 31st Annual - Volume 01 (2001)

The Civil Engineering Technology faculty of Southern Polytechnic State University (GA, USA) are in the process of developing and implementing an Assessment and Continuous Improvement Plan to insure the ongoing quality and effectiveness of the Civil Engineering Technology Program. Key program constituents involved in the plan's on-going development are faculty, students, alumni and employers of graduates. The plan's overall success will be critical to continued program accreditation. 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
Proceedings - 12th Annual IEEE Symposium on High Performance Interconnects [2004] - Title
Venue: Proceedings of the High Performance Interconnects, 2004. on Proceedings. 12th Annual IEEE Symposium (2004)

Summary form only given. The Internet has grown enormously over the last decade and has become ubiquitous. Most past research has focused on improving the performance and scalability of the Internet. The issue of securing the Internet has become a central issue due to a series of attacks that shut down some of the world's most high profile Web sites. Moreover, the growing concerns for cyber terrorism have made governments and researchers realize the importance of Internet security. Securing the Internet, as in any other field of computers, is based on the principle of confidentiality and integrity. This principle exists in every field, but the presence of packet sniffers, malicious routers, covert channels, eavesdroppers, denial-of-service (DoS) in the Internet makes this problem quite challenging. There has been a surge of Internet security research in the field of information assurance, which primarily focused on protecting the data using techniques such as authentication and encryption. However, information assurance assumes that the devices responsible for encrypting, forwarding and sending are trustworthy. Researchers are now questioning these assumptions, as instances have occurred where the network infrastructure (e.g., routers, servers) is compromised to the advantage of the malicious adversaries. Therefore, Internet infrastructure security is the need of the hour. 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
Realtime classification with structure adapting neuro-fuzzy systems
Authors: Saman K. Halgamuge
Venue: Integrated Computer-Aided Engineering (2003)

Neural networks with a structure adaptation capability that are equivalent to fuzzy systems are investigated with the goal of designing hardware architectures for application in time critical classification problems. The consecutive steps adopted to build a realtime prototype of a structure adapting neural network include the modification of learning algorithms making them suitable for hardware implementation, the development of a hardware architecture, and the system implementation and test. Structure adaptation must be integrated into the learning algorithm implementable in hardware. Fusion of information hidden in data with the existing knowledge expressed in rules should also be possible. Three types of structure adapting algorithms have been mapped onto the proposed hardware architecture. Performance of the system implementation is evaluated comparing the speeds using software implementations for benchmarks and real applications.
A Web-Based Runtime-Reconfigurable Role Management Service
Authors: Martin Karusseit, Tiziana Margaria
Venue: Proceedings of the 2nd Int'l. Workshop on Automated Specification and Verification of Web Systems (2006)

Today web-based applications are very complex and provide several hundred users with access to sensible data. Adequate access control mechanisms that prevent unauthorized access and gives policy-compliant access to users depending on their status are thus central. The Online Conference Service (OCS) is a system of services which collectively provide all necessary workflows and functionalities an online decision support service needs. Here we describe its flexible role-based access control mechanism and introduce the embedded Role Management Service, which is extensible, modifiable and reconfigurable online, during the service operations. We also discuss a first version of the Personalized Role Management Service as used in the OJS, the journal member of the product line initiated by the OCS.