ppxscal/embedding_network huggingface dataset:
A Global-Time-Based Approach for High-Quality Real-Time Video Streaming Services
Authors: K. H. Kane Kim, Sheng Liu, Moon H. Kim, Doo-Hyun Kim
Venue: Proceedings of the Seventh IEEE International Symposium on Multimedia (2005)

This paper presents a global-time based approach for realizing high-quality real-time video streaming over networks. The application goal is to play the video streams at a remote site with minimal distortion of the temporal relationship among the video data units. The Time-triggered Message-triggered Object (TMO) programming tool-kit, which enables construction of distributed real-time computing programs in the form of networks of high-level, easily analyzable, real-time objects, facilitates efficient practice of this approach. The experimental results of a feasibility evaluation of this global time based approach for real-time video streaming are also presented.
Calendar
Authors: Charlene O'Hanlon
Venue: Queue (2005)

Web 2.0 October 5-7, 2005 San Francisco, California http://web2con.com/ SoftSummit October 10-11, 2005 Santa Clara, California http://www.softsummit.com
Software Refinement with Perfect Developer
Authors: Gareth Carter, Rosemary Monahan, Joseph M. Morris
Venue: Proceedings of the Third IEEE International Conference on Software Engineering and Formal Methods (2005)

Perfect Developer is a software tool that supports the formal development of object-oriented programs by refinement, including formal verification of code. It is built around a single language that supports both specification and implementation. We critically examine how Perfect Developer supports programming by refinement, focusing on three refinement techniques: algorithm refinement, data re- finement and delta refinement. In particular we examine the extent to which Perfect Developer provides formal verification for these techniques. We assess it as a tool for software construction and compare it with related tools.
Frequency Operators for Condensative Queries over Data Streams
Authors: Lisha Ma, Werner Nutt
Venue: Proceedings of the IEEE International Conference on e-Business Engineering (2005)

Over a traditional Database Management System (DBMS), the answer to an aggregate query is usually much smaller than the answer to a similar non-aggregate query. Therefore, we call such a query "condensative". Current proposals for declarative query languages over data streams do not support such condensative querying. In order to make existing stream query languages more expressive so that they enable a user both, to state more intuitively interesting queries, and to support condensative querying, we propose a new data stream model, referred to as the sequence model, and an extension to SQL-like query languages by operators that allows one to specify the frequency by which a query returns answer tuples. We show that such frequency operators allow one to express sampling over streams. If combined with existing sliding window operators, they support queries with "jumping windows". We show with a number of examples from a sensor monitoring application how complex queries can be elegantly formulated in a stream query language with frequency operators.
Automatic generation of personalized music sports video
Authors: Jinjun Wang, Changsheng Xu, Engsiong Chng, Lingyu Duan, Kongwah Wan, Qi Tian
Venue: Proceedings of the 13th annual ACM international conference on Multimedia (2005)

In this paper, we propose a novel automatic approach for personalized music sports video generation. Two research challenges, semantic sports video content selection and automatic video composition, are addressed. For the first challenge, we propose to use multi-modal (audio, video and text) feature analysis and alignment to detect the semantic of events in sports video. For the second challenge, we propose video-centric and music-centric music video composition schemes to automatically generate personalized music sports video based on user's preference. The experimental results and user evaluations are promising and show that our system's generated music sports video is comparable to manually generated ones. The proposed approach greatly facilitates the automatic music sports video generation for both professionals and amateurs.
Customized Explanation in Expert System for Earthquake Prediction
Authors: Zhang Bofeng, Liu Yue
Venue: Proceedings of the 17th IEEE International Conference on Tools with Artificial Intelligence (2005)

A main line of research for introducing explanation capabilities in Knowledge-Based System supposes that explanations are used to transmit knowledge from the machine to a user and to improve learning ability of the latter. A reasonable explanation should be adapted to different level of users because different users have different knowledge. To describe the difference and then generate a personalized explanation is the main problem. In this paper, a novel method called FUMCE (Fuzzy User Model based Customized Explanation) is proposed, in which a fuzzy user model called FUM is defined, and then several new algorithms are proposed to initialize FUM, update FUM, and extract correlative knowledge for explanation based on the FUM. FUM-CE can provide different and suitable explanation for the different users with different domain knowledge, by which the understandability and acceptability of the expert system for earthquake prediction are improved.
Audio subtle expressions affecting user's perceptions
Authors: Takanori Komatsu
Venue: Proceedings of the 11th international conference on Intelligent user interfaces (2006)

Can we assign attitudes to an artifact based on its expressed beep sounds as audio subtle expressions? If so, which kinds of beep sounds are perceived as specific attitudes, such as "disagreement" as a negative attitude, "hesitation" as neutral or "agreement" as positive? To examine this issue, I carried out an experiment to observe and clarify how participants assign an attitude to an artifact according to beeps of different durations and F0 values. The results revealed that 1) sounds with rising tones regardless of duration were perceived by participants as "disagreement," and 2) flat sounds with longer duration were interpreted as "hesitation", and 3) falling tones with shorter duration were taken as "agreement".
A Data Structure Using Hashing and Tries For Efficient Chinese Lexical Access
Authors: Yat-Kin LAM, Qiang HUO
Venue: Proceedings of the Eighth International Conference on Document Analysis and Recognition (2005)

A lexicon is needed in many applications. In the past, different structures such as tries, hash tables and their variants have been investigated for lexicon organization and lexical access. In this paper, we propose a new data structure that combines the use of hash table and tries for storing a Chinese lexicon. The data structure facilitates an efficient lexical access yet requires less memory than that of a trie lexicon. Experiments are conducted to evaluate its performance for in-vocabulary lexical access, out-of-vocabulary word rejection, and substring matching. The effectiveness of the proposed approach is confirmed.
The Tech Hotlist: Grid Computing and P2P
Authors: Milan Lathia
Venue: IEEE Distributed Systems Online (2005)

A review of From P2P to Web Services and Grids: Peers in a Client Server World by Ian J. Taylor.
Identifying Contingency Requirements Using Obstacle Analysis
Authors: Robyn Lutz, Stacy Nelson, Ann Patterson-Hine, Chad R. Frost, Doron Tal
Venue: Proceedings of the 13th IEEE International Conference on Requirements Engineering (2005)

This paper describes the use of Obstacle Analysis to identify anomaly-handling requirements for a safetycritical, autonomous system. The software requirements for the system evolved during operations due to an on-going effort to increase the autonomous system¿s robustness. The resulting increase in autonomy also increased system complexity. This investigation used Obstacle Analysis to identify and to reason incrementally about new requirements for handling failures and other anomalous events. Results reported in the paper show that Obstacle Analysis complemented standard safety-analysis techniques in identifying undesirable behaviors and ways to resolve them. The step-by-step use of Obstacle Analysis identified potential side effects and missing monitoring and control requirements. Adding an Availability Indicator and feature-interaction patterns proved useful for the analysis of obstacle resolutions. The paper discusses the consequences of these results in terms of the adoption of Obstacle Analysis to analyze anomaly-handling requirements in evolving systems. Keywords: contingency requirements, obstacle analysis, safety-critical software, requirements evolution, autonomy, anomaly-handling.
Simulation of blood bank systems
Authors: Morris A. Cohen, William P. Pierskalla
Venue: ACM SIGSIM Simulation Digest (1979)

This paper examines the use of simulations to develop decision procedures for the management of individual hospital blood banks and central blood bank systems. Due to the perishability of blood products and the stochastic nature of both the demand and supply processes, such multi-product, multiechelon systems can only be analyzed effectively by simulation. The hospital and central bank model structures are reviewed, as are the input, output, and validation analysis procedures. A number of issues relevant to the application of simulation to health care systems analysis are raised by the development and application of these models. Of particular interest is the integration of the simulations into a recursive statistics-optimization-simulation approach to systems analysis.
Automating the analysis of design component contracts: Research Articles
Authors: Jing Dong, Paulo S. C. Alencar, Donald D. Cowan
Venue: Software&mdash;Practice Experience (2006)

Software patterns are a new design paradigm used to solve problems that arise when developing software within a particular context. Patterns capture the static and dynamic structure and collaboration among the components in a software design. A key promise of the pattern-based approach is that it may greatly simplify the construction of software systems out of building blocks and thus reuse experience and reduce cost. However, it also introduces significant problems in ensuring the integrity and reliability of these composed systems because of their complex software topologies, interactions and transactions. There is a need to capture these features as a contract through a formal model that allows us to analyze pattern-based designs. In this paper, we provide an overview of a formal framework for ensuring the integrity of the compositions in object-oriented designs by providing mathematically rigorous modeling and analysis techniques for object-oriented systems comprising pattern-based designs as the basic building blocks or design components. A case study related to a hypermedia Web-based application has been presented to illustrate our approach in distributed systems. Copyright &copy; 2005 John Wiley & Sons, Ltd.
Concept Identification in Object-Oriented Domain Analysis: Why Some Students Just Don"t Get It
Authors: Davor Svetinovic, Daniel M. Berry, Michael Godfrey
Venue: Proceedings of the 13th IEEE International Conference on Requirements Engineering (2005)

Anyone who has taught object-oriented domain analysis or any other software process requiring concept identification has undoubtedly observed that some students just don¿t get it. Our evaluation of the work of over 740 University of Waterloo students on over 135 Software Requirements Speci fications during the last four years supports this same observation. The students¿ task was to specify a telephone exchange or a voice-over-IP telephone system and the related accounts management subsystem, based on models they developed using object-oriented analysis. A detailed comparative study of three much smaller specifications, all of an elevator system, suggests that object orientation is poorly suited to domain analysis, even of small-sized domains, and that the difficulties we have observed are independent both of the size of the system under specification and of the overall abilities of the students.
Analyzing Software Quality with Limited Fault-Proneness Defect Data
Authors: Naeem Seliya, Taghi M. Khoshgoftaar, Shi Zhong
Venue: Proceedings of the Ninth IEEE International Symposium on High-Assurance Systems Engineering (2005)

Assuring whether the desir ed software quality and reliability is met for a project is as important as deliveringit within scheduled budget and time. This is especially vital for high-assurance software systems where software failures can have severe consequences. To achieve the desired software quality, practitioners utilize software quality models to identify high-risk program modules: e.g., software quality classification models are built using training data consisting of software measurements and fault-proneness data from previous development experiences similar to the project currently under-development. However, various practical issues can limit availability of fault-proneness data for all modules in the training data, leading to the data consisting of many modules with no fault-proneness data, i.e., unlabeled data. To address this problem, we propose a novel semi-supervised clustering scheme for software quality analysis with limited fault-proneness data. It is a constraint-based semi-supervised clustering scheme based on the k-means algorithm. The proposed approach is investigated with software measurement data of two NASA software projects, JM1 and KC2. Empirical results validate the promise of our semi-supervised clustering technique for software quality modeling and analysis in the presence of limited defect data. Additionally, the approach provides some valuable insight into the characteristics of certain program modules that remain unlabeled subsequent to our semi-supervised clustering analysis.
Artificial and Biological Intelligence
Authors: Subhash Kak, Donald C., Elaine T. Delaune
Venue: Ubiquity (2005)

Subhash Kak of Louisiana State University says that "humans will eventually create silicon machines with minds that will slowly spread all over the world, and the entire universe will eventually become a conscious machine."
The framework of selective interleaving functions and the modular assembly kit
Authors: Heiko Mantel
Venue: Proceedings of the 2005 ACM workshop on Formal methods in security engineering (2005)

The Framework of Selective Interleaving Functions and the Modular Assembly Kit for Security Properties both provide a basis for the uniform representation and formal analysis of noninterference-like properties. In this article, we clarify the relationship between these two frameworks. Our main result is that each property that can be represented in the Framework of Selective Interleaving Functions can also be represented in the assembly kit. In fact, the latter framework is strictly more expressive, which we demonstrate by several example properties.
Active learning for Hidden Markov Models: objective functions and algorithms
Authors: Brigham Anderson, Andrew Moore
Venue: Proceedings of the 22nd international conference on Machine learning (2005)

Hidden Markov Models (HMMs) model sequential data in many fields such as text/speech processing and biosignal analysis. Active learning algorithms learn faster and/or better by closing the data-gathering loop, i.e., they choose the examples most informative with respect to their learning objectives. We introduce a framework and objective functions for active learning in three fundamental HMM problems: model learning, state estimation, and path estimation. In addition, we describe a new set of algorithms for efficiently finding optimal greedy queries using these objective functions. The algorithms are fast, i.e., linear in the number of time steps to select the optimal query and we present empirical results showing that these algorithms can significantly reduce the need for labelled training data.
Vision-based automatic process control
Authors: Yuan Cheng
Venue:  (2005)

This dissertation combines automated visual inspection and process control strategy into an efficient vision-based process control system. The purpose of our surface inspection, in addition to monitoring and classification of defects, is to improve the manufacturing process to reduce defects in subsequent stages. In the defect detection module, we examine the surface pattern using intensity image combined with CAD information. The CAD-based model is used to define shape and dimension of the surface, as well as the way the surface is constructed. A hybrid strategy is used for defect analysis, where the randomly occurred defects are detected by 2D texture analysis and assignable defects are obtained from 3D shape reconstruction using shape-from-shading. In 3D shape reconstruction we reconstruct 2D profile from representative signatures) and the 3D surface is obtained from sweeping the profile along the path defined in CAD file. In the profile reconstruction, we apply a parametric approach to improve efficiency. Compared with traditional 3D shape-from-shading, our approach is more computationally efficient in reconstructing patterned surface shapes. For process control we take defect information obtained from defect detection module as input to determine the appropriate control parameters in order to minimize the possible defects in later stages of production. Our global control scheme considers process dynamics, disturbances and inter-surface relationships. A linear autoregressive model is developed based on deposition mechanics. The results show the existence of correlations among adjacent layers and validate our presented model. In addition to the linear model, we developed a fuzzy controller based on Takagi-Sugeno model. The fuzzy model serves as an alternative process controller considering complexity and uncertainties for both process dynamics and defect measurements. It enhances the linear model by considering overfills and underfills separately. The results show that the fuzzy model performs as well as the linear model when the data is linear and improves when the data demonstrates non-linearity. A Matlab simulation model is developed to illustrate the concepts and evaluate our vision-based process control results. It simulates the manufacturing and vision-based process control system, which includes deposition process, surface construction, intensity image generation, defect detection, and process control.
Policies and IT Technologies: A Puzzle of Two Pieces
Authors: Elisa Bertino, Steve Ruth
Venue: IEEE Internet Computing (2006)

This new public policy technology track will appear in each installment of IEEE Internet Computing in 2006 and will cover a wide range of topics. The authors describe their vision of what to expect in future issues along with a call to arms to build a like-minded community.
Enable Efficient Stage Construction for Replication based Fault-tolerant Execution of Mobile Agent
Authors: Zhaoxia Lu, Guangzhou Zeng, Yaping Zhong, Gongping Yang
Venue: Proceedings of the IEEE International Conference on e-Business Engineering (2005)

Reliability as well as fault-tolerance is a fundamental issue for the development of robust mobile agent system. A number of research works is done in these areas. Some researchers adopt the use of spatial replication based approach since it can reduce blocking possibility of mobile agent execution. Unfortunately, this fault-tolerance scheme is not cost effective because it incurs great costs of time and communication, which leads to increased system load. In this paper, we present a dynamic stage construction protocol for mobile agent execution to maintain high performance without being forced to make tradeoffs in reliability. The protocol schedules task execution dynamically according to the execution ability of visited nodes, hence avoid the unnecessary revisit to them at latter stage and cut down total execution time. On the other hand, it has specific node selection strategy to guarantee reliability, decrease communication overhead between two consecutive stages and improve efficiency.
A method to detect single and multiple delamination problems using a combined neural network technique and genetic algorithm optimization
Authors: Hieu The Le
Venue:  (2004)

This thesis develops a new method to detect delaminations in composite laminates using a combination of finite element method, artificial neural networks, and genetic algorithms. Next, this newly developed method is applied to successfully solve delamination detection problems. Delaminations in a composite laminate with various sizes and locations are considered in the present studies. The improved layerwise shear deformation theory is implemented into the finite element method and used to calculate responses of laminates with single and multiple delaminations. Mappings between the natural frequencies and delamination characteristics are first determined from the developed models. These data are then used to train artificial neural networks of multiplayer perceptron using back-propagation. These trained artificial neural networks are in turn used as an approximate tool to calculate the responses of the delaminated laminates and to feed the data to the delamination detection process. Two different approaches for handling the neural network models are applied in the work and are presented for comparison. The delamination detection problem is formulated as an optimization problem with mixed type design variables. A genetic algorithm, which is a guided probabilistic search technique based on the simulation of Darwin's principle of evolution and natural selection, is developed to solve this optimization problem. Single through-the-width delamination, single internal delamination, and multiple through-the-width delaminations are separately considered for detection study. At last, the application is extended to the most challenging problem, which is the detection of general delamination. Various factors affecting the detection process such as the finite element convergence factor and the laminate geometry factor are also examined. Case studies are made and the findings are summarized in detail in each chapter of the dissertation. It is found that the newly developed method successfully detects delaminations with remarkable accuracy for all four types of delamination problems. It is also found that this newly developed method successfully solves the inverse problems of single delamination, internal delamination, multiple delaminations, and the generalized delamination detection, none of which have been solved previously.
Integrating K-Means Clustering with a Relational DBMS Using SQL
Authors: Carlos Ordonez
Venue: IEEE Transactions on Knowledge and Data Engineering (2006)

Integrating data mining algorithms with a relational DBMS is an important problem for database programmers. We introduce three SQL implementations of the popular K-means clustering algorithm to integrate it with a relational DBMS: 1) a straightforward translation of K-means computations into SQL, 2) an optimized version based on improved data organization, efficient indexing, sufficient statistics, and rewritten queries, and 3) an incremental version that uses the optimized version as a building block with fast convergence and automated reseeding. We experimentally show the proposed K-means implementations work correctly and can cluster large data sets. We identify which K-means computations are more critical for performance. The optimized and incremental K-means implementations exhibit linear scalability. We compare K-means implementations in SQL and C++ with respect to speed and scalability and we also study the time to export data sets outside of the DBMS. Experiments show that SQL overhead is significant for small data sets, but relatively low for large data sets, whereas export times become a bottleneck for C++.