ppxscal/embedding_network huggingface dataset:
Moblogging and belonging: new mobile phone practices and young people's sense of social inclusion
Authors: Ingrid Richardson, Amanda Third, Ian MacColl
Venue: Proceedings of the 2nd international conference on Digital interactive media in entertainment and arts (2007)

Late teens and young adults are prolific users of interactive and networked mobile media, and already possess a certain level of literacy with the capabilities of newer generation mobile phones. That is, they are well-attuned to the recent shift to user-generated micromedia; indeed, their communicative and media practices are characterized by information connectedness, small-scale digital content creation and peer-to-peer file sharing. This paper describes some of the background research to a research project entitled "Moblogging and Belonging" being undertaken jointly by researchers at Murdoch University and the University of Queensland. This project, funded by a Telstra Community Development Fund grant and scheduled for completion in 2009, aims to build on young people's existing mobile media skills by utilising the video capture and web capabilities of newer generation mobile phones, thus enabling them to creatively author, edit and publish their own 'quality' content around local/community events, stories and issues. In doing so, this project hopes to encourage young people to rethink their media practices as community-oriented rather than merely personal.
The Influence of Frame Length on Speaker Identification Performance
Authors: Donato Impedovo, Mario Refice
Venue: Proceedings of the Third International Symposium on Information Assurance and Security (2007)

Speaker recognition/identification is a challenge for the implementation of security applications. Unfortunately, degradation in performance is usually observed for high pitched speakers and also whenever average pitch varies significantly between enrolment and testing. In this paper, a study on the impact of the frame length used to extract features from speech signal on the performance of speaker identification is presented. Tests have been carried out on a text-dependent database. Results show that a combination of different frame sizes between the training and the recognition phases can cope with the degradation. A reduction between 40% and 65% in false rejections has been generally observed.
Capital-Intensive Software Technology Part 4: Accomplishments and Deficiencies of Ada
Venue: IEEE Software (1984)

Ada is a well-documented attempt to make software technology more capital intensive. Its development has taught us a lot, including the fact that we have a great deal more to learn. 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
A Visualization Tool to Improve the Performance of a Classifier Based on Hidden Markov Models
Authors: G. da Silva, M. Nakagawa
Venue: Proceedings of the Ninth International Conference on Document Analysis and Recognition - Volume 02 (2007)

This paper presents a visualization tool to improve the performance of a classifier based on the hidden Markov Model. A specific recognition system for which the visual- ization tool is designed is an on-line handwritten Japanese character recognition system. The recognition system was built from already estimated parameter values, which leads to some difficulties when trying to adjust the system. To tackle this problem we describe how visual information can be helpful to interpret the results and how it can be used to build a set of viewers for helping the tuning task. These viewers were used to examine the data structure and inter- nal procedures of the recognition engine allowing to detect and correct errors in the first implementation. We conclude the paper comparing the two implemented versions of the classifier by showing the increase we achieved in recogni- tion accuracy.
Improved Approach of Seed Point Selection in RPCCL Algorithm for Aerial Remote Sensing Hyper-spectral Data Clustering with Data Dimensionality Reduction
Authors: Xuefeng Liu, Guangrong Ji, Wencang Zhao, Junna Cheng
Venue: Proceedings of the Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing - Volume 01 (2007)

The existing RPCCL (Rival Penalization Controlled Competitive Learning) algorithm has provide an attractive way to perform data clustering. However its performance is sensitive to the selection of the initial cluster center. In this paper, we further investigate the RPCCL and present an improved approach of seed point selection which chooses non-neighbor data points of the greatest local density as seed points. We compare the performance of the RPCCL clustering with the selecting seed points and with the random seed points in red tide and oil spill aerial remote sensing hyper-spectral data (ARSHD) image. The experiments have produced the promising results. Additionally, because of the redundancy of high dimensions in the oil spill hyper-spectral data, a dimensionality reduction method is also described.
Guiding Component-Based Hardware/Software Co-Verification with Patterns
Authors: Juncao Li, Fei Xie, Huaiyu Liu
Venue: Proceedings of the 33rd EUROMICRO Conference on Software Engineering and Advanced Applications (2007)

In component-based hardware/software co-verification, properties of an embedded system are established from properties of its hardware and software components. A major challenge in component-based co-verification is the property formulation problem: (1) what are the system properties to verify, (2) what are the component properties needed for verifying the system properties, and (3) what are the environment assumptions for establishing these properties. We present a pattern-guided approach to the property formulation problem. We develop an embedded architecture description language (EADL). A key feature of EADL is its support to specification of architectural patterns for embedded systems. Such patterns capture recurring system structures and, furthermore, templates for properties to verify on systems following these patterns and strategies for decomposing system properties into component properties. We have applies EADL in co-verification of medical sensor systems, which shows that architectural patterns have major potential in facilitating component-based co-verification.
ANFIS for Adaptive Personal Space Determination for Ubiquitous Robots
Authors: Janaka Chaminda Balasuriya, Chandrajith Ashuboda Marasinghe, Keigo Watanabe
Venue: Proceedings of the 7th IEEE International Conference on Computer and Information Technology (2007)

When robots are interacting with humans and other ob- jects, they always have a safe distance between them and the objects. One of the problems in concern is, how can this dis- tance be arranged when interacting with humans. In order to "humanize" robots, they (robots) should also have cer- tain understanding of such emotions that we, humans have concerning this distance. In this research project, authors are trying to "teach" one such human understanding, com- monly known as "personal space" to ubiquitous robots.
Reliable on-demand management operations for large-scale distributed applications
Authors: Jin Liang, Indranil Gupta, Klara Nahrstedt
Venue: ACM SIGOPS Operating Systems Review (2007)

This paper argues for attention to, and proposes a novel direction to solving, instant monitoring and management tasks for large-scale distributed applications running across hundreds of hosts. We present the MON (Management Overlay Networks) approach1, which uses a novel concept called on-demand overlays, in order to support instant commands such as queries and software pushes. On-demand overlays are built on-the-fly and probabilistically, by leveraging weakly-consistent gossip-style membership information underneath. Thus, they are lightweight in terms of memory, computation, and bandwidth. We augment on-demand overlays with several notions of application-specified reliability, and show how MON detects and adheres to these. MON is available atop PlanetLab, and we present experimental results. We conclude with a series of promising open problems in this direction.
Wildlife net-gamekeepers using sensor network
Authors: Leonardo M. Trejos, Masaru Kamada, Tatsuhiro Yonekura, Mamun Bin Ibne Reaz
Venue: Proceedings of the 6th ACM SIGCOMM workshop on Network and system support for games (2007)

Wildlife lies in vast and wide areas where human gamekeepers work as protectors. The task of recognizing poachers in protected areas is tedious, tiring, and requires huge manpower and computational overhead. A fully automated system cannot accurately identify every such poacher. This paper proposes a conceptual system based on sensor network, which will provide amusement for cyberspace gamekeepers while protecting the wildlife. For this, the sensory data from the park is mapped to a game-like virtual environment. Cyberspace gamekeepers will access the system and play the game. While playing, they will help to conserve the wildlife in national parks by pattern recognition of intruders in the game. The sensor network in the proposed system will use microphone, accelerometers and wireless transmission system.
Bifurcation of elastoplastic pressure-sensitive spheres
Authors: Y. Hollander, D. Durban
Venue: Computers Mathematics with Applications (2008)

Instability of a full sphere, under uniform compression or tension, is investigated within the framework of linear bifurcation theory. Material response is modeled by a Hookean-type hypoelastic relation with pressure dependent instantaneous moduli. Exploiting a formal analogy with Navier equations of linear elasticity we obtain exact solution for the bifurcated field. Two families of eigenmodes and eigenvalues are identified and discussed. We examine, in particular, surface instabilities in compression, and twisting modes with absence of radial velocity. The results are further specified for pressure-sensitive plastic solids with an elliptic yield surface. The deformation theory prediction of bifurcation loads for that material are much lower than those obtained from the flow theory version.
Supercharging Your Creative Skills
Authors: Philip Emma
Venue: IEEE Micro (2007)

The author discusses advanced techniques for unleashing the creative self through subconscious and superconscious awarenesses. He discusses brain waves, the hypnogogic state, and two powerful creativity tools known as lucid dreaming and image streaming.
B74-6 PL/I Programming for Engineering and Science
Authors: P. C. Jorgensen
Venue: IEEE Transactions on Computers (1974)

This is an excellent text! The title implies a purpose of presenting the PL/I language with respect to scientific and engineering programming, but the book accomplishes much more. In addition to a good general introduction to computers, the author works in valuable background material from computer science, mathematics, and good programming techniques. The reader who masters this text will have acquired a strong general background in scientific computing in addition to extreme competence in PL/I programming.
Optimizing Investments in Security Countermeasures: A Practical Tool for Fixed Budgets
Authors: Jonathan Caulkins, Eric D. Hough, Nancy R. Mead, Hassan Osman
Venue: IEEE Security and Privacy (2007)

As a software engineer or client, how much of your budget should you spend on software security mitigation for the applications and networks on which you depend? The authors introduce a novel way to optimize a combination of security countermeasures under fixed resources.
Topological Visualization of Brain Diffusion MRI Data
Authors: Thomas Schultz, Holger Theisel, Hans-Peter Seidel
Venue: IEEE Transactions on Visualization and Computer Graphics (2007)

Topological methods give concise and expressive visual representations of flow fields. The present work suggests acomparable method for the visualization of human brain diffusion MRI data. We explore existing techniques for the topological analysis of generic tensor fields, but find them inappropriate for diffusion MRI data. Thus, we propose a novel approach that considers the asymptotic behavior of a probabilistic fiber tracking method and define analogs of the basic concepts of flow topology, like critical points, basins, and faces, with interpretations in terms of brain anatomy. The resulting features are fuzzy, reflecting the uncertainty inherent in any connectivity estimate from diffusion imaging. We describe an algorithm to extract the new type of features, demonstrate its robustness under noise, and present results for two regions in a diffusion MRI dataset to illustrate that the method allows a meaningful visual analysis of probabilistic fiber tracking results.
N-Best Optimal Path Ant Routing Algorithm for State-Dependent N Best Quality of service Routes in IP Networks
Authors: Farid Baguenine, Abdelhamid Mellouk
Venue: Proceedings of the 32nd IEEE Conference on Local Computer Networks (2007)

As Routing mechanism is a key to success of future communication networking, computing constrained shortest paths is fundamental to some important network functions such as QoS routing or traffic engineering. The problem is to find feasible paths satisfying QoS requirements and optimizing resource usage and degrading gracefully during periods of heavy load. This paper introduces a Quality of Service (QoS) routing protocol aimed to offload congested links while optimizing end-to-end delay. The proposed algorithm, called NOPAR "N-best Optimal Paths Ant Routing", extends the earlier N best Optimal path Q Routing Algorithm (NOQRA) by integrating the exploration and reinforcement function inspired by Ant Colony Optimization approaches. NOPAR uses a model combining both a stochastic planned pre-navigation for the exploration phase (forward ant) and a deterministic approach for the backward phase (backward ant). The introduced algorithm is compared with earlier version of NOQRA and the well-known routing algorithms such as SPF or OSPF. The performance analysis under simulation environment using OPNET demonstrates that NOPAR performs better than the classical approach especially over load high networks or link failures conditions.
Middleware Framework for Resource Discovery in Mobile Environments
Authors: Jameela Al-Jaroodi, Nader Mohamed
Venue: Proceedings of the The 2007 International Conference on Next Generation Mobile Applications, Services and Technologies (2007)

In this paper, we introduce a middleware framework for collaborative resource discovery in pervasive environments. Collaborative resource discovery mechanisms are available to handle static to semistatic resources. However, incorporating dynamic mobile users introduces a different set of problems. First, how do we know when a resource becomes available? How do we identify the resource, its current location and its moving patterns? How do users know when a resource moves out? The introduced middleware framework provides mechanisms to dynamically discover resources, include them in the collective, and manage their mobility requirements. The framework involves the collaboration of software agents residing on the group members' nodes to collect, organize and efficiently exchange information. Through this exchange the resources will be updated and the members will be able to maintain connectivity and collaboration while they are on the move.
Mining of Reuse Patterns in CDMA Network Optimization
Authors: Wen Ye, Hongxu Cui
Venue: Proceedings of the Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing - Volume 03 (2007)

CAP, a classical problem in cellular mobile communication networks such as GSM/GPRS or CDMA cellular mobile networks, refers to assigning a limited number of available channels to many mobile voice or data users while minimizing electromagnetic interferences. Most existing researches on CAP focus mainly on channel separation constraints, but pay little attention to geometric constraints defined by reuse patterns that is of great value in engineering applications. An extended CAP model named RCAP (Reuse-pattern-oriented CAP) is proposed, which takes account of both of these two constraints. A systematic solution to RCAP is elaborated, which includes two sequential steps, i.e., partition of reuse groups and channel assignment in the groups. Partition of reuse groups is reduced to subgraph isomorphism and can be tackled by subgraph mining while channel assignment in groups is solved in a heuristic manner. The effectiveness of RCAP and its solution was verified by three benchmarks. RCAP was applied to PN offsets assignment in the CDMA networks in several cities of Liaoning Province, and a case study is illustrated in the paper. These results indicate that the proposed RCAP scheme is a very promising solution to channel assignment problems in practical CDMA networks.
Modeling of a Bubble-Memory Organization with Self-Checking Translators to Achieve High Reliability
Authors: W. G. Bouricius
Venue: IEEE Transactions on Computers (1973)

This paper reports a study on the design and modeling of a highly reliable bubble-memory system. This system has the capability of correcting a single 16-adjacent bit-group error resulting from failures in a single basic storage module (BSM), and detecting with a probability greater than 0.99 any double errors resulting from failures in BSM's. The encoding/decoding network (memory translator) is designed to be self-checking, i.e., a single circuit failure in the translator wiH not produce an erroneous output that goes undetected. The system is able to perform reliable configuration in the event of uncorrectable BSM failures, memory translator failures, and dual-memory buffer failures; even in the presence of a single failure in the status registers controlling the configuration network. The bubble memory under study permits serial accessing of the store with 64 x 1024 bit blocks at a 100-kHz rate. The objective of this study is to develop good fault-tolerant design and analysis methods adequate for newly emerging technologies and prove the practicality by example. The reliability modeling study justifies the design philosophy adopted of employing memory data encoding and a translator to correct single group errors and detect double group errors to enhance the overall system reliability. By a proper design of the memory translator based on a new checking technique, a uniformly high percentage of multiple b-adjacent bit-group error detection is achieved through the use of a proposed code (detects 99.99695 percent of double b-adjacent bit-group errors and 99.9985 percent of triple or more b-adjacent bit-group errors).
Generalized Connection Networks for Parallel Processor Intercommunication
Authors: C. D. Thompson
Venue: IEEE Transactions on Computers (1978)

A generalized connection network (GCN) is a switching network with N inputs and N outputs that can be set to pass any of the NNmappings of inputs onto outputs. This paper demonstrates an intimate connection between the problems of GCN construction, message routing on SIMD computers, and "resource partitioning." A GCN due to Ofman [7] is here improved to use less than 7.6N log N contact
A simple and efficient estimation method for stream expression cardinalities
Authors: Aiyou Chen, Jin Cao, Tian Bu
Venue: Proceedings of the 33rd international conference on Very large data bases (2007)

Estimating the cardinality (i.e. number of distinct elements) of an arbitrary set expression defined over multiple distributed streams is one of the most fundamental queries of interest. Earlier methods based on probabilistic sketches have focused mostly on the sketching algorithms. However, the estimators do not fully utilize the information in the sketches and thus are not statistically efficient. In this paper, we develop a novel statistical model and an efficient yet simple estimator for the cardinalities based on a continuous variant of the well known Flajolet-Martin sketches. Specifically, we show that, for two streams, our estimator has almost the same statistical efficiency as the Maximum Likelihood Estimator (MLE), which is known to be optimal in the sense of Cramer-Rao lower bounds under regular conditions. Moreover, as the number of streams gets larger, our estimator is still computationally simple, but the MLE becomes intractable due to the complexity of the likelihood. Let N be the cardinality of the union of all streams, and &verbar;S&verbar; be the cardinality of a set expression S to be estimated. For a given relative standard error &delta;, the memory requirement of our estimator is O(&delta;-2&verbar;S&verbar;-1 N log log N), which is superior to state-of-the-art algorithms, especially for large N and small &verbar;S&verbar;/N where the estimation is most challenging.
Interactive Back-annotation of Worst-case Execution Time Analysis for Java Microprocessors
Authors: Trevor Harmon, Raymond Klefstad
Venue: Proceedings of the 13th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications (2007)

As real-time systems become more prevalent, there is a need to guarantee that these increasingly complex systems perform as designed. One technique involves a static analysis to place an upper bound on worst-case execution time (WCET). Tools for conducting this analysis typically require the developer to digest assembly opcodes, hexadecimal addresses, and other low-level details in order to make sense of the results. Java-specific processors offer a way out of this complexity. Such processors make Java software more predictable, and as a consequence, timing analysis of a real-time system becomes less computationally intensive. WCET analysis tools based on these processors can thus offer more powerful features at higher levels of abstraction. As proof of this concept, we present a tool for static WCET analysis of Java processors. Our performance measurements show that this tool makes WCET analysis interactive, offering continuous feedback to the developer in the form of back-annotations.
Yarn Properties Prediction Using Support Vector Machines: An Intelligent Reasoning Method
Authors: Jian-guo Yang, Zhi-Jun Lv, Qian Xiang
Venue: Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 01 (2007)

Although many works have been done to construct prediction models on yarn processing quality, the relation between spinning variables and yarn properties has not been established conclusively so far. Support vector machines (SVMs), based on statistical learning theory, are gaining applications in the areas of machine learning and pattern recognition because of the high accuracy and good generalization capability. This study briefly introduces the SVM regression algorithms, and presents the SVM model for predicting yarn properties. Model selection which amounts to search in hyper-parameter space is performed for study of suitable parameters with grid- research method. Experimental results have been compared with those of Artificial Neural Network (ANN) models. The investigation indicates that in the small data sets and real-life production, SVM models are capable of maintaining the stability of predictive accuracy, and more suitable for noisy and dynamic spinning process