ppxscal/embedding_network huggingface dataset:
A Min-Cover Approach for Finding Salient Curves
Authors: Pedro Felzenszwalb, David McAllester
Venue: Proceedings of the 2006 Conference on Computer Vision and Pattern Recognition Workshop (2006)

We consider the problem of deriving a global interpretation of an image in terms of a small set of smooth curves. The problem is posed using a statistical model for images with multiple curves. Besides having important applications to edge detection and grouping the curve finding task is a special case of a more general problem, where we want to explain the whole image in terms of a small set of objects. We describe a novel approach for estimating the content of scenes with multiple objects using a min-cover framework that is simple and powerful. The min-cover problem is NP-hard but there is a good approximation algorithm that sequentially selects objects minimizing a "cost per pixel" measure. In the case of curve detection we use a type of best-first search to quickly find good curves for the covering algorithm. The method integrates image data over long curves without relying on binary feature detection. We have applied the curve detection method for finding object boundaries in natural scenes and measured its performance using the Berkeley segmentation dataset.
Discrete event simulation & modeling of the transportation element within a supply chain (SC)
Authors: Mansour Toloo
Venue: Proceedings of the 37th conference on Winter simulation (2005)

The SC involves coordinating elements along a value chain delivering the appropriate quantities of goods and services to the right locations while meeting service level requirements and minimizing end-to-end SC costs. Transportation is a significant element of the SC that supports business operations and logistics. This presentation discusses the data collection, the process mapping of carrier delivery flows across all transportation modes and the data analysis of the simulation activity. The conversion of the data analysis outputs and process mapping into the composition of an end-to-end transportation model is described. The presentation discusses the transformation of the information into a modular and serial construct that imitates the serial nature of the transportation element while allowing the involved operations to be included in a logical, expandable and maintainable approach within the capabilities of a given simulation environment. Finally, the presentation addresses the institutionalization of the model within the SC organization. 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
Blind maximum likelihood sequence estimation for fading channels
Authors: D. J. Reader, J. B. Scholz
Venue: Proceedings of the Acoustics, Speech, and Signal Processing,1994. on IEEE International Conference - Volume 04 (1994)

Maximum a posteriori (MAP) sequence estimation for channels with intersymbol interference (ISI) has previously required knowledge of the channel sampled impulse response (SIR). Generally the SIR coefficients are determined via least mean squares (LMS) or recursive least squares (RLS) estimation algorithms. For many unguided media channels such as mobile radio and high frequency (HF) radio exhibiting a time-varying SIR, these estimators must be adaptive. Often they fail to track adequately and are a major source of detector deterioration. A novel blind maximum likelihood sequence estimation (BMLSE) formulation without the need for external channel SIR estimation is proposed and implementation issues discussed. Its performance is simulated and compared to the contemporary technique, MLSE with external LMS channel estimation.
TF-ICF: A New Term Weighting Scheme for Clustering Dynamic Data Streams
Authors: Joel W. Reed, Yu Jiao, Thomas E. Potok, Brian A. Klump, Mark T. Elmore, Ali R. Hurson
Venue: Proceedings of the 5th International Conference on Machine Learning and Applications (2006)

In this paper, we propose a new term weighting scheme called Term Frequency -- Inverse Corpus Frequency (TF-ICF). It does not require term frequency information from other documents within the document collection and thus, it enables us to generate the document vectors of N streaming documents in linear time. In the context of a machine learning application, unsupervised document clustering, we evaluated the effectiveness of the proposed approach in comparison to five widely used term weighting schemes through extensive experimentation. Our results show that TF-ICF can produce document clusters that are of comparable quality as those generated by the widely recognized term weighting schemes and it is significantly faster than those methods.
Pre-registration of arbitrarily oriented 3D surfaces using a genetic algorithm
Authors: Evgeny Lomonosov, Dmitry Chetverikov, Anikó Ekárt
Venue: Pattern Recognition Letters (2006)

This paper reports on a successful application of genetic optimisation in 3D data registration. We consider the problem of Euclidean alignment of two arbitrarily oriented, partially overlapping surfaces represented by measured point sets contaminated by noise and outliers. Recently, we have proposed the Trimmed Iterative Closest Point algorithm (TrICP) [Chetverikov, D., Stepanov, D., Krsek, P., (2005). Robust Euclidean alignment of 3d point sets: the trimmed iterative closest point algorithm. Image Vision Comput. 23, 299-309] which is fast, applicable to overlaps under 50% and robust to erroneous and incomplete measurements. However, like other iterative methods, TrICP only works with roughly pre-registered surfaces. In this study, we propose a genetic algorithm for pre-alignment of arbitrarily oriented surfaces. Precision and robustness of TrICP are combined with generality of genetic algorithms. This results in a precise and fully automatic 3D data alignment system that needs no manual pre-registration.
IPv6 Secure Multicast Conferencing
Authors: Dowon Hyun, Wookyung Sung, Dohyun Pyon, Taehwan Kim, Woojin Han, Jinhyuk Lee, Juwook Jang
Venue: Proceedings of the 2006 International Conference on Hybrid Information Technology - Volume 02 (2006)

This paper describes the implementation of a system to provide IPv6 secure multicast conferencing, to prove that it can be developed with existing technologies. In these IPv6 secure multicast conferencing systems, there is a set of conferencing clients that can send and receive audio/video data, and a GCKS (Group Controller Key Server) that can manage multicast group. The main problem in such a system is the management and distribution of the keying data including rekeying when a user leaves the multicast group. Standardization of structure and keying data exchange for secure multicast by IETF Multicast Security Working Group (MSEC). We propose a system that integrates different existing technologies into a Windows-based environment. Audio and video data are transmitted using RTP (Real Time Protocol) through multicast protocols. Also we evaluate performance of IPv6 secure multicast application and conclude adding security in application does not damage a real-time characteristic.
Face Detection by using Skin Color Model based on One Class Classifier
Authors: Rudra N. Hota, Vijendran Venkoparao, Saad Bedros
Venue: Proceedings of the 9th International Conference on Information Technology (2006)

Human face detection plays an important role in real life application such as Face recognition, Human computer interface, Video surveillance and Face image database management. Automatic Face detection in such scenario is a challenging task. Here we propose to use skin color cue to detect face in a video sequence by modeling the skin color by an one class classifier named SVDD (Support Vector Data Descriptor). We apply the one class classifier for facial skin model on Various color transformations (YCrCb, HSV, Normalized RGB). We also examine SVDD on all the three Y, Cb and Cr and their combinations for the skin model as it is known that the non linear combination of the three gives better skin model and experiments on large set of data sets proves the robustness of the method.
A Comparison of Software Fault Imputation Procedures
Authors: Jason Van Hulse, Taghi M. Khoshgoftaar, Chris Seiffert
Venue: Proceedings of the 5th International Conference on Machine Learning and Applications (2006)

This work presents a detailed comparison of three imputation techniques, Bayesian multiple imputation, regression imputation and k nearest neighbor imputation, at various missingness levels. Starting with a complete real-world software measurement dataset called CCCS, missing values were injected into the dependent variable at four levels according to three different missingness mechanisms. The three imputation techniques are evaluated by comparing the imputed and actual values. Our analysis includes a three-way analysis of variance (ANOVA) model, which demonstrates that Bayesian multiple imputation obtains the best performance, followed closely by regression.
Constraint based structural testing criteria
Authors: Silvia Regina Vergilio, José Carlos Maldonado, Mario Jino, Inali Wisniewski Soares
Venue: Journal of Systems and Software (2006)

Structural criteria generally divide the input domain of the program under test and require the execution of at least one point from each derived sub-domain without addressing the most relevant question: ''Which points from each sub-domain should be selected?''. This question is related to data-sensitive faults which lead to one of the drawbacks of the testing activity. The constraints and conditions used by fault-based data generation techniques describe faults related to the boundaries of these sub-domains. Our conjecture is that we would improve the efficacy of the adequate test case sets by associating those constraints and conditions to the elements required by a criterion. With this goal, this work presents Constraint Based Criteria (CBC) that associate a constraint C to an element E, required by a structural criterion. CBC allow to combine the fundamentals of different testing generation techniques with structural testing, increasing the probability of revealing faults described by C. We also discuss complexity, inclusion relation and automation aspects of CBC. Results from three experiments of CBC evaluation using the factors cost, efficacy and strength provide evidence that our objectives have been achieved. We also present some results from the evaluation of random test sets.
Dynamic TXOP Assignment for Fairness (DTAF) in IEEE 802.11e WLAN under Heavy Load Conditions
Authors: Nan Guo, Chen Chen, Chang-xing Pei
Venue: Proceedings of the Seventh International Conference on Parallel and Distributed Computing, Applications and Technologies (2006)

The IEEE 802.11e is an extension of the IEEE 802.11 to provide Quality of Service (QoS) for applications requiring real time services. However, when used with the multi-rate scheme, they suffer unfairness problem. On the other hand, the traditional contention window size (CW) update method actually depends on the collision times of the investigated station, which would possibly causes more contentions especially under heavy load conditions. In this paper, we propose a scheme, which utilizes the collision times to estimate contention degree before transmission, turn TXOP, and at the same time, solves the unfairness problem in the IEEE 802.11e networks employing the multi-rate scheme.
Toward Standards for Reporting Research: A Review of the Lliterature on Computer-Supported Collaborative Learning
Authors: Allyson F. Hadwin, Carmen L. Z. Gress, Jessica Page
Venue: Proceedings of the Sixth IEEE International Conference on Advanced Learning Technologies (2006)

We conducted a meta-review of the computer supported collaborative learning (CSCL) literature. This literature included a rich array of methodologies, theoretical and operational definitions, and collaborative models. However, the literature lacked an overall framework for reporting important design and research details. This paper highlights key findings from our systematic review. The paper: (a) presents the array of definitions, tools, and supports researched in the CSCL literature and (b) proposes standards for reporting collaborative models, tools, and research. These standards, which have implications for both the CSCL and computersupported collaborative work areas, have potential to build a shared language upon which cross-disciplinary communication and collaboration may be based.
Robust signal modeling through nonlinear least squares
Authors: Y. Yardimci, J. A. Cadzow, A. E. Cetin
Venue: Proceedings of the Acoustics, Speech, and Signal Processing,1994. on IEEE International Conference - Volume 04 (1994)

A nonlinear least-squares (LS) method is developed for modeling empirically obtained data in array signal processing. The new method is robust with respect to modeling errors in the noise distribution. Robustness is achieved by introducing a nonlinear function which weights the squared error term in the LS criterion. Weighting functions for various observation noise scenarios are determined by using maximum likelihood estimation theory. The computational complexity of the new method is comparable to the standard least-squares estimation procedures. Simulation examples of direction-of-arrival (DOA) estimation are presented.
Experience Report: Using Internal CMMI Appraisals to Institutionalize Software Development Performance Improvement
Authors: Fredrik Ekdahl, Stig Larsson
Venue: Proceedings of the 32nd EUROMICRO Conference on Software Engineering and Advanced Applications (2006)

Critical to any successful performance improvement initiative is to achieve a state of continuous or institutionalized improvement. Some improvement can happen quickly, but long-term improvement is typically a matter of sustaining focus. This requires an infrastructure that keeps activities focused and drives them forward. In ABB, the IDEALSM model is used as a guide for setting up improvement activities in development centers. Central to the IDEALSM model is the diagnostic activity, i.e. the evaluation of current performance in the unit against a suitable reference model. Over the last eight years, ABB has used diagnostics in the form of internal CMM/CMMI appraisals to lay the foundation for improvement activities. In this experience report, the use of internal appraisals as a means for sustaining improvement focus will be discussed. Experiences and lessons learnt, as well as some of the specifics of ABB's internal appraisals will be presented.
Fully fuzzified linear programming, solution and duality
Authors: S. M. Hashemi, M. Modarres, E. Nasrabadi, M. M. Nasrabadi
Venue: Journal of Intelligent Fuzzy Systems: Applications in Engineering and Technology (2006)

In this paper, we propose a two-phase approach to find the optimal solutions of a class of fuzzy linear programming problems called fully fuzzified linear programming (FFLP), where all decision parameters and variables are fuzzy numbers. Our approach is constructed on the basis of comparison of mean and standard deviation of fuzzy numbers. In this approach, the first phase maximizes the possibilistic mean value of fuzzy objective function and obtains a set of feasible solutions. The second phase minimizes the standard deviation of the original fuzzy objective function, by considering all basic feasible solutions obtained at the end of the first phase. The advantage of the proposed approach is its simplicity in programming and computation. Moreover, we also generalize the concept of linear programming duality and extend the duality as well as the weak duality theory to FFLP.
A New Deformable Model for Boundary Tracking in Cardiac MRI and Its Application to the Detection of Intra-Ventricular Dyssynchrony
Authors: Paulo F. U. Gotardo, Kim L. Boyer, Joel Saltz, Subha V. Raman
Venue: Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1 (2006)

We present a new deformable model technique following a snake-like approach and using a complex Fourier shape descriptors parameterization to efficiently formulate the forces that constrain contour deformation. The method was successfully applied to track the left ventricle's (LV) endocardial and epicardial boundaries in sequences of shortaxis magnetic resonance images depicting complete cardiac cycles. The extracted shapes show the method's robustness to weak contrast, noisy edge maps and to papillary muscle anatomy. Our second contribution is a statistical pattern recognition approach for the detection of asynchronous activation of the LV walls. We applied our deformable model method to provide spatio-temporal characterizations of complete cardiac cycles and then designed a linear classifier using the popular combination of Principal Component Analysis and Linear Discriminant Analysis. From a database comprising 33 patients, our approach provided a correct classification performance of 90.9% showing its potential in providing improved dyssynchrony characterization as an adjunct to current criteria for selecting patients for therapy, which provided a classification accuracy of just 62.5% on the same database.
Drivers Status Monitor
Authors: Michimasa ITOH, Yoshiyuki MIZUNO, Satoshi MORI, Shin YAMAMOTO
Venue: Proceedings of the 21st International Conference on Data Engineering Workshops (2005)

We made a prototype rear-view mirror with a built in image sensor. Useful driver assistance systems must provide information and warnings that adapt to a driver's status, such as awareness and attention levels. Image processing is one of the best approaches to monitor the driver's status, however it is necessary to develop a suitable image sensor to acquire the driver's image. Described in this paper, are superior characteristics of the prototype rear-view mirror that can acquire the driver's image under several environments and the methods used to detect features of the driver's status.
Avenues to Flexible Data Integrity Checking
Authors: Hendrik Decker, Davide Martinenghi
Venue: Proceedings of the 17th International Conference on Database and Expert Systems Applications (2006)

Traditional methods for integrity checking in relational or deductive databases heavily rely on the assumption that data have integrity before the execution of updates. In this way, as has always been claimed, one can automatically derive strategies to check, in an incremental way, whether data preserve their integrity after the update. On the other hand, this consistency assumption greatly reduces applicability of such methods, since it is most often the case that small parts of a database do not comply with the integrity constraints, especially when the data are distributed or have been integrated from different sources. In this paper we revisit integrity checking from an inconsistency-tolerant viewpoint. We show that most methods for integrity checking (though not all) are still applicable in the presence of inconsistencies and may be used to guarantee that the satisfied instances of the integrity constraints will continue to be satisfied after the update.
Utility-based anonymization using local recoding
Authors: Jian Xu, Wei Wang, Jian Pei, Xiaoyuan Wang, Baile Shi, Ada Wai-Chee Fu
Venue: Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining (2006)

Privacy becomes a more and more serious concern in applications involving microdata. Recently, efficient anonymization has attracted much research work. Most of the previous methods use global recoding, which maps the domains of the quasi-identifier attributes to generalized or changed values. However, global recoding may not always achieve effective anonymization in terms of discernability and query answering accuracy using the anonymized data. Moreover, anonymized data is often for analysis. As well accepted in many analytical applications, different attributes in a data set may have different utility in the analysis. The utility of attributes has not been considered in the previous methods.In this paper, we study the problem of utility-based anonymization. First, we propose a simple framework to specify utility of attributes. The framework covers both numeric and categorical data. Second, we develop two simple yet efficient heuristic local recoding methods for utility-based anonymization. Our extensive performance study using both real data sets and synthetic data sets shows that our methods outperform the state-of-the-art multidimensional global recoding methods in both discernability and query answering accuracy. Furthermore, our utility-based method can boost the quality of analysis using the anonymized data.
Revisiting IP multicast
Authors: Sylvia Ratnasamy, Andrey Ermolinskiy, Scott Shenker
Venue: Proceedings of the 2006 conference on Applications, technologies, architectures, and protocols for computer communications (2006)

This paper revisits a much explored topic in networking - the search for a simple yet fully-general multicast design. The many years of research into multicast routing have led to a generally pessimistic view that the complexity of multicast routing-and inter-domain multicast routing in particular - can only be overcome by restricting the service model (as in single-source) multicast. This paper proposes a new approach to implementing IP multicast that we hope leads to a reevaluation of this commonly held view.
Disaster Hardening for Software Systems
Authors: C. V. Ramamoorth
Venue: Proceedings of the 17th International Symposium on Software Reliability Engineering (2006)

Software products never grow old, or fade away. The designs, their patterns and the ideas embodied in them are carried over and over again for a long time. In this presentation we explore the venues of immortalizing the software systems and the intellectual components they are made up of. We argue that such indestructible systems must embody crucial application ideas and functions but also exemplify user oriented architectural forms that personify ease of use, crash free operations, and user maintainable and /or maintenance free within the specified constraints. We approach the issue by recognizing the implicit fact that a software malfunction is a disaster, however small it is. Based on our previous studies in disaster hardening systems, we apply the ideas used in preventing and mitigating disasters to the methods of designing and developing software systems. We show the mutual commonality as well as areas where methods used in one can be carried over effectively into the other.
Trust and Mobility-based Clustering Algorithm for Secure Mobile Ad Hoc Networks
Authors: Abderrezak Rachedi, Abderrahim Benslimane
Venue: Proceedings of the International Conference on Systems and Networks Communication (2006)

An Mobile Ad-hoc network (MANET) is formed when group of mobile wireless nodes collaborate between them to communicate through wireless links in the absence of the fixed infrastructure and any centralized control. Theses characteristics make it able to adapt and operate in difficult conditions, but also vulnerable to new security attacks not present in a traditional wired network. In this paper a new approach to secure MANETs has been proposed. Our solution is based on our efficient trust model and distributed algorithm to clustering network in order to distribute role of certification authority (CA) in each cluster. We use fully self-organized security and monitoring process to supervise behaviors of nodes with low trust level. Also, we propose clustering algorithm based on the trust and mobility metric to select CA and to establish public key infrastructure (PKI) in each cluster. Furthermore, we introduce new concept Dynamic Demilitarized Zone (DDMZ) to protect CAs and avoid the single point of failure in each cluster. The DDMZ is formed by set of the dispensable nodes which must be confident and located at one-hop from the CA. Our approach can be easily extended to other hierarchical routing protocols. The simulation results include an evaluation of the stability, availability and security.