ppxscal/embedding_network huggingface dataset:
Sub-block subsampling based block-matching motion estimation
Authors: Reeba Korah, M. Sankaralingam, J. Raja Paul Perinbam
Venue: Proceedings of the 4th WSEAS International Conference on Applied Informatics and Communications (2004)

Motion estimation has been widely employed in popular video standards like H.26x, MPEG - 1,-2 and - 4 to exploit the temporal redundancies inherent within image frames. Block matching is the most popular method for motion estimation. The disadvantages of full search block matching algorithm (FSBMA) are the computational complexity and the huge memory bandwidth requirement. This paper presents a simple technique by which above mentioned disadvantages can be overcome. At first, the frame is divided into 16×16 blocks. From each 16×16 blocks, one 8×8 sub-block is chosen with an assumption that motion may be uniform within a block. Next a subsample algorithm is applied to these sub-blocks. With Matlab6.5 simulation it is proved that the subjective quality of reconstructed frame is exactly same as the original. Also, MSE and SNR calculation shows that the Mean square error and SNR involved in this method is almost same as that involved in FSBMA. The computational complexity is almost one fourth that of FSBMA.
Fair Exchange Signature Schemes
Authors: Jingwei Liu, Rong Sun, Wenping Ma, Ying Li, Xinmei Wang
Venue: Proceedings of the 22nd International Conference on Advanced Information Networking and Applications - Workshops (2008)

In this paper we propose an efficient Fair Exchange Signature Scheme (FESS) that allows two players to exchange digital signatures in a fair way. It may be considered as an interesting extension of concurrent signature presented in EUROCRYPT 2004 that is constructed from ring signatures. In our scheme, two unwakened signatures signed separately by two participants can be verified easily by the other player, but it would not go into effect until an extra piece of commitment keystone is released by one of the players. Once the keystone revealed, two signatures are both aroused and become effective. A key feature of the proposed scheme is that two players can exchange digital signatures simultaneously through a secret commitment keystone without involvement of any Trusted Third Party. Moreover, the efficiency of our signature scheme is higher than that of concurrent signature.
Maximum likelihood rule ensembles
Authors: Krzysztof Dembczyński, Wojciech Kotłowski, Roman Słowiński
Venue: Proceedings of the 25th international conference on Machine learning (2008)

We propose a new rule induction algorithm for solving classification problems via probability estimation. The main advantage of decision rules is their simplicity and good interpretability. While the early approaches to rule induction were based on sequential covering, we follow an approach in which a single decision rule is treated as a base classifier in an ensemble. The ensemble is built by greedily minimizing the negative loglikelihood which results in estimating the class conditional probability distribution. The introduced approach is compared with other decision rule induction algorithms such as SLIPPER, LRI and RuleFit.
Modified MMI/MPE: a direct evaluation of the margin in speech recognition
Authors: Georg Heigold, Thomas Deselaers, Ralf Schlüter, Hermann Ney
Venue: Proceedings of the 25th international conference on Machine learning (2008)

In this paper we show how common speech recognition training criteria such as the Minimum Phone Error criterion or the Maximum Mutual Information criterion can be extended to incorporate a margin term. Different margin-based training algorithms have been proposed to refine existing training algorithms for general machine learning problems. However, for speech recognition, some special problems have to be addressed and all approaches proposed either lack practical applicability or the inclusion of a margin term enforces significant changes to the underlying model, e.g. the optimization algorithm, the loss function, or the parameterization of the model. In our approach, the conventional training criteria are modified to incorporate a margin term. This allows us to do large-margin training in speech recognition using the same efficient algorithms for accumulation and optimization and to use the same software as for conventional discriminative training. We show that the proposed criteria are equivalent to Support Vector Machines with suitable smooth loss functions, approximating the non-smooth hinge loss function or the hard error (e.g. phone error). Experimental results are given for two different tasks: the rather simple digit string recognition task Sietill which severely suffers from overfitting and the large vocabulary European Parliament Plenary Sessions English task which is supposed to be dominated by the risk and the generalization does not seem to be such an issue.
A Transformational Approach for Pattern-Based Design of User Interfaces
Authors: Costin Pribeanu, Jean Vanderdonckt
Venue: Proceedings of the Fourth International Conference on Autonomic and Autonomous Systems (2008)

A pattern-based approach to user interface development is presented that is explicitly based on artifacts contained in a task and a domain models. Exploiting a task model or a domain model in isolation may lead to patterns that are not user-centered. By combining the exploitation of both models at the same time with priority lead to identifying interaction patterns in a systematic way. Types of relationships in these models help in structuring interaction patterns, that are in turn transformed into design patterns for information systems.
Approximation of an open polygonal curve with a minimum number of circular arcs and biarcs
Authors: R.L. Scot Drysdale, Günter Rote, Astrid Sturm
Venue: Computational Geometry: Theory and Applications (2008)

We present an algorithm for approximating a given open polygonal curve with a minimum number of circular arcs. In computer-aided manufacturing environments, the paths of cutting tools are usually described with circular arcs and straight line segments. Greedy algorithms for approximating a polygonal curve with curves of higher order can be found in the literature. Without theoretical bounds it is difficult to say anything about the quality of these algorithms. We present an algorithm which finds a series of circular arcs that approximate the polygonal curve while remaining within a given tolerance region. This series contains the minimum number of arcs of any such series. Our algorithm takes O(n^2logn) time for an original polygonal chain with n vertices. Using a similar approach, we design an algorithm with a runtime of O(n^2logn), for computing a tangent-continuous approximation with the minimum number of biarcs, for a sequence of points with given tangent directions.
Identity protection factor (IPF)
Authors: Arshad Noor
Venue: Proceedings of the 7th symposium on Identity and trust on the Internet (2008)

Since the dawn of computing, operating systems and applications have used many schemes to identify and authenticate entities accessing resources within computers. While the technologies and schemes have varied, there appears to have been little attempt to classify them based on their ability to resist attacks from unauthorized entities. With the proliferation of identity management technologies in the market today, it is becoming increasingly difficult to assess and compare them with each other. As the threat level continues to rise on the internet, and regulations governing information technology continue to grow, risk managers need more objective mechanisms to assign risk to their systems so they may apply appropriate mitigating controls. This paper attempts to describe a classification scheme that will permit the comparison of seemingly different identification and authentication (I&A) technologies on the basis of their vulnerability to attacks. With a better understanding of related authentication technologies, companies can determine the appropriate technology to use for mitigating authentication risks.
Geographical Routing in Intermittently Connected Ad Hoc Networks
Authors: Erik Kuiper, Simin Nadjm-Tehrani
Venue: Proceedings of the 22nd International Conference on Advanced Information Networking and Applications - Workshops (2008)

In intermittently connected ad hoc networks standard routing protocols like AODV, DSR and GPSR fail since they generally cannot find a contemporaneous path from source to destination. In this paper we present LAROD, a geographical routing protocol for intermittently connected networks. Combining beacon less geographical routing with store-carry-forward LAROD greedily searches for the shortest way to the destination and when no progress is possible packets are temporarily stored until node mobility has created a new path. In the paper we have shown by a comparative study that LAROD has almost as good delivery rate as an epidemic routing scheme, but at a substantially lower overhead.
Prediction schemes to enhance the routing process in geographical GPSR ad hoc protocol
Authors: Raed Saqour, Mohamad Shanuldin, Mahamod Ismail
Venue: Mobile Information Systems (2007)

Geographical routing protocols have received a serious attention due to more advantages they have in comparison to the conventional routing protocols. They require information about the physical position of nodes needed to be available. Commonly, each node determines its own position through the use of Global Positioning System (GPS) or some other type of positioning service. Greedy Perimeter Stateless Routing (GPSR) protocol, which is one of geographical routing protocols, limits the forwarding decision of the packet based on the node's own position, the destination's position and the position of the forwarding node's neighbors. Location information has some inaccuracy depending on the localization system and the environment exists in. This paper aims to study the impact of mobility metrics (beacon interval, and node speed) on introducing location information error in GPSR protocol using different mobility models. The effect of these metrics is identified in GPSR as Neighbor Break Link (NBL) problem. Based on simulation analysis, mobility prediction schemes are proposed to migrate the observed problem.
Speeding-up linear programming using fast matrix multiplication
Authors: P. M. Vaidya
Venue: Proceedings of the 30th Annual Symposium on Foundations of Computer Science (1989)

The author presents an algorithm for solving linear programming problems that requires O((m+n)/sup 1.5/nL) arithmetic operations in the worst case, where m is the number of constraints, n the number of variables, and L a parameter defined in the paper. This result improves on the best known time complexity for linear programming by about square root n. A key ingredient in obtaining the speedup is a proper combination and balancing of precomputation of certain matrices by fast matrix multiplication and low-rank incremental updating of inverses of other matrices. Specializing the algorithm to problems such as minimum-cost flow, flow with losses and gains, and multicommodity flow leads to algorithms whose time complexity closely matches or is better than the time complexity of the best known algorithms for these problems.
Effective Visual Masking Techniques in JPEG2000
Authors: Thomas Richter
Venue: Proceedings of the Data Compression Conference (2008)

This paper introduces a very low complexity visual masking algorithm for the JPEG2000 image compression standard and evaluates its impact on the visual image quality by means of the Multi-scale SSIM index. The algorithm derives suitable weighting masks indirectly from a statistical model of the wavelet data which is defined from the second moment and the average absolute amplitude of the data. If combined with an a priori rate allocation algorithm, the computation of the visual masking weights has almost no overhead at all.
BehaviorScope: Real-Time Remote Human Monitoring Using Sensor Networks
Authors: Dimitrios Lymberopoulos, Athanasios Bamis, Thiago Teixeira, Andreas Savvides
Venue: Proceedings of the 7th international conference on Information processing in sensor networks (2008)

In this demonstration we present the Behavior Scope, a system for interpreting human activity patterns using a sensor network and its application to elder monitoring in assisted living. The Behavior Scope provides a runtime,user-programmable framework that processes streams of timestamped sensor data along with prior context informationto infer activities and generate appropriate notifications. Human activities are described in high-levelscripts that are directly mapped to a hierarchy of probabilistic grammars that parse low-level sensor measurements into high-level distinguishable activities. Activities of interestare pre-programmed into a specification that is used by the system to interpret the incoming sensor data stream. The system interprets the activities to generate summaries andother triggered notifications that are propagated to stakeholders via email and cell-phone text messages.
DARA: Data Summarisation with Feature Construction
Authors: Rayner Alfred
Venue: Proceedings of the 2008 Second Asia International Conference on Modelling & Simulation (AMS) (2008)

This paper addresses the question whether or not the descriptive accuracy of the DARA (Dynamic Aggregation of Relational Attributes) algorithm benefits from the feature construction process. This involves solving the problem of constructing a set of relevant features used to generate patterns representing records in the TF-IDF weighted frequency matrix. In this paper, feature construction will be applied to enhance the results of the data summarisation approach in learning data stored in multiple tables with a high number of one-to-many relations. It is expected that the predictive accuracy of a classfication problem can be improved by improving the descriptive accuracy of the data summarisation approach, provided that the summarised data is fed into the target table as one of the features considered in the classification task.
Implicitization and parametrization of quadratic surfaces with one simple base point
Authors: Xuhui Wang, Falai Chen, Jiansong Deng
Venue: Proceedings of the twenty-first international symposium on Symbolic and algebraic computation (2008)

This paper discusses implicitization and parametrization of quadratic surfaces with one simple base point. The key point to fulfill the conversion between the implicit and the parametric form is to compute three linearly independent moving planes which we call the weak u-basis of the quadratic surface. Beginning with the parametric form, it is easy to compute the weak u-basis, and then to find its implicit equation. Inversion formulas can also be obtained easily from the weak u-basis. For conversion from the implicit into the parametric form, we present a method based on the observation that there exists one self-intersection line on a quadratic surface with one base point. After computing the self-intersection line, we are able to derive the weak u-basis, from which the parametric equation can be easily obtained. A method is also presented to compute the self-intersection line of a quadratic surface with one base point.
Limit cycles of polynomial differential systems with homogeneous nonlinearities of degree 4 via the averaging method
Authors: Jinlong Cao
Venue: Journal of Computational and Applied Mathematics (2008)

By using the averaging method, we study the limit cycles for a class of quartic polynomial differential systems as well as their global shape in the plane. More specifically, we analyze the global shape of limit cycles bifurcating from a Hopf bifurcation and also from periodic orbits with linear center x@?=-y, y@?=x. The perturbation of these systems is made inside the class of quartic polynomial differential systems without quadratic and cubic terms.
Efficient sanitization of informative association rules
Authors: Shyue-Liang Wang, Rajeev Maskey, Ayat Jafari, Tzung-Pei Hong
Venue: Expert Systems with Applications: An International Journal (2008)

Recent development in privacy-preserving data mining has proposed many efficient and practical techniques for hiding sensitive patterns or information from been discovered by data mining algorithms. In hiding association rules, current approaches require hidden rules or patterns to be given in advance. In addition, for Apriori algorithm based techniques [Verykios, V., Elmagarmid, A., Bertino, E., Saygin, Y., & Dasseni, E. (2004). Association rules hiding. IEEE Transactions on Knowledge and Data Engineering, 16(4) 434-447], multiple scanning of the entire database is required. For direct sanitization of itemsets from transaction techniques [Oliveira, S., & Zaiane, O. (2003). An efficient on-scan sanitization for improving the balance between privacy and knowledge discovery. Technical report TR 03-15, Department of Computing Science, University of Alberta, Canada], one scanning of each window in the database is processed independently. However, the accumulated information among windows is not considered. In this work, we propose an efficient one database scanning sanitization algorithm to sanitize informative association rules. For a given predicting item, an informative association rule set [Li, Jiuyong, Shen, Hong, & Topor, Rodney. (2001). Mining the smallest association rule set for predictions, In Proceedings of the 2001 IEEE international conference on data mining (pp. 361-368)] is the smallest association rule set that makes the same prediction as the entire association rule set by confidence priority. A new data structure called pattern-inversion tree is proposed to store related information so that only one scan of database is required. The pre-process of finding these informative association rules can be integrated into the sanitization process. Numerical experiments show that the performance of the proposed algorithm is more efficient than previous algorithms with similar side effects. Running time complexity of the algorithm is presented and compared to similar algorithm with better complexity.
Very Low Cost Algorithms for Predicting the File Size of JPEG Images Subject to Changes of Quality Factor and Scaling
Authors: Steven Pigeon, Stéphane Coulombe
Venue: Proceedings of the Data Compression Conference (2008)

This work presents two new algorithms to predict the file size of a JPEG image subject to transformations consisting of simultaneous changes in resolution (scaling) and in quality factor (QF). To be computationally efficient, the prediction is based solely on easily accessible image parameters such as the quality factor andthe original file size. A large image corpus (100 000 images), gathered by a crawler, is divided into a training set used to optimize the predictors and into a test set used to validate the predictors. For both algorithms the prediction error is shown to be of a few percents when the output parameters are close to those of the original image while remaining reasonably attractive elsewhere. Both algorithms are simple to implementand require very little processing for the prediction itself; making them good choices for implementation in transcoding servers.
The UniTESK Approach to Specification-Based Validation of Hardware Designs
Authors: Alexander Kamkin
Venue: Proceedings of the Second International Symposium on Leveraging Applications of Formal Methods, Verification and Validation (2006)

Functional validation is a major bottleneck in hardware design. Two main approaches to ensure functional correctness of hardware systems are based on formal verification and simulation techniques. It is widely recognized that formal verification techniques are exhaustive but do not scale well; simulation-based techniques are scalable but are not exhaustive. Possible compromise is provided by semi-formal approaches combining formal specifications, functional coverage definition, and simulation. This paper describes the UniTESK approach to specification-based validation of hardware designs in which a good balance of exhaustiveness and scalability is found. UniTESK is originally intended for the development of high-quality functional tests for software systems. The paper shows how to adapt it for functional validation of Verilog HDL and SystemC designs. 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
Detecting deforestation with multitemporal L-band SAR imagery: a case study in western Brazilian Amazônia
Authors: R. Almeida-Filho, A. Rosenqvist, Y. E. Shimabukuro, R. Silva-Gomez
Venue: International Journal of Remote Sensing (2007)

Applications of L-band SAR data to map deforestation are generally based on the assumption that undisturbed forests consistently exhibit higher radar backscatter than deforested areas. In this Letter we show that depending on the stage of the deforestation process (slashing, burning and terrain clearing), this assumption is not always valid, and deforested areas may display a stronger radar return backscatter than primary forest. The analysis of multitemporal SAR images, supported by several Landsat Thematic Mapper (TM) images and field knowledge, showed that wood materials left following the deforestation practices function as corner reflectors, causing an initial increase in the radar backscatter, which then subsequently decreases over time as the debris on these fields are removed.
RN-Cluster: Discovering Coherent Biclusters Which is Robust to Noise
Authors: Jaegyoon Ahn, Youngmi Yoon, Sanghyun Park
Venue: Proceedings of the 2008 International Conference on Biocomputation, Bioinformatics, and Biomedical Technologies (2008)

A bicluster is a subset of genes that show similar behavior within a subset of conditions. Biclustering algorithm is a useful tool to uncover groups of genes involved in the same cellular process and groups of conditions which take place in this process. We are proposing a polynomial time algorithm to identify functionally highly correlated biclusters. Our algorithm identifies 1) the gene set that follows additive, multiplicative, and combined patterns simultaneously that allow high level of noise, 2) the multiple, possibly overlapped, and diverse gene sets, 3) biclusters with negatively correlated as well as positively correlated gene set simultaneously, and 4) gene sets whose functional association is strongly high. We validated the level of functional association of our method, and compared with current methods using GO.
DBPowder-mdl: Mapping Description Language between Applications and Databases
Authors: Tadashi Murakami
Venue: Proceedings of the Seventh IEEE/ACIS International Conference on Computer and Information Science (icis 2008) (2008)

A few decade years have passed since the Object/Relational mapping problem was recognized. However, it still remains to be a hard problem. Simple declaration cannot overcome the impedance mismatch, however, detailed declaration tends to get into a number of duplicated definitions of elements. Duplicated definitions are not preferable in order for productivity and maintainability.In this paper, we propose DBPowder-mdl to address the problem above. DBPowder-mdl describes mappings between object models and relational models. Both object models and relational models are derived from the mapping declaration. DBPowder-mdl keeps simple declaration with having a descriptive power of detailed declaration such as inheritance in object models.We developed a prototype system of DBPowder-mdl and evaluated it.