ppxscal/embedding_network huggingface dataset:
A privacy-preserving index for range queries
Authors: Bijit Hore, Sharad Mehrotra, Gene Tsudik
Venue: Proceedings of the Thirtieth international conference on Very large data bases - Volume 30 (2004)

Database outsourcing is an emerging data management paradigm which has the potential to transform the IT operations of corporations. In this paper we address privacy threats in database outsourcing scenarios where trust in the service provider is limited. Specifically, we analyze the data partitioning (bucketization) technique and algorithmically develop this technique to build privacy-preserving indices on sensitive attributes of a relational table. Such indices enable an untrusted server to evaluate obfuscated range queries with minimal information leakage. We analyze the worst-case scenario of inference attacks that can potentially lead to breach of privacy (e.g., estimating the value of a data element within a small error margin) and identify statistical measures of data privacy in the context of these attacks. We also investigate precise privacy guarantees of data partitioning which form the basic building blocks of our index. We then develop a model for the fundamental privacy-utility tradeoff and design a novel algorithm for achieving the desired balance between privacy and utility (accuracy of range query evaluation) of the index.
QoS-Resource Graph Model for Web Service Composition in Service Oriented Computing
Authors: Zhiang Wu, Junzhou Luo
Venue: Proceedings of the Sixth International Conference on Grid and Cooperative Computing (2007)

SOC (service oriented computing) becomes a hot topic of research recently because it accelerates rapid application development by service reuse. Delivering end-to-end QoS (quality of service) in SOC environment is a critical and significant challenge. QoS is modeled for a single service based on this view: quality is seen as conformance. Then, QRGM (QoSResource Graph Model) is adopted for service composition. An illustrative example is used to account for how to model end-to-end QoS in service composition using QRGM. At last, QRGM is compare with other current common service composition models. Conclusion is made that QRGM provides better support for QoS than other service composition models.
Logic Programming and Prolog: A Tutorial
Authors: R. E. Davis
Venue: IEEE Software (1985)

Logic programming offers significant advantages for the massively parallel computer systems of tomorrow. This tutorial examines the potential of Prolog to implement those advantages. 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
EDP auditing in the 1980's or the vanishing paper trail
Authors: Richard E. Andersen
Venue: ACM SIGSAC Review (1981)

This paper is designed to provide an overview of (1) traditional auditing methodology and (2) the reasons why these methods must be modified and adapted in order to cope with the "vanishing paper trail" inherent in today's (and tomorrow's) increasingly on-line, data base-oriented, distributed processing, EDP environment. The three basic types off audits (general, administrative, and applications) will be discussed. Examples of flagrant, and not-so-flagrant, computer crimes will be presented. Practical and proposed solutions for the reduction of these types of DP crimes in the 1980's will be examined. The major thrust of the paper, however, will address the importance of the applications-oriented audit. The paper will discuss the concept of Computer Management Technology (CMT), and show that this is in reality a type of on-going auditing task. Alternatives will be examined for measuring, managing and controlling key functional areas that have a definite interactive effect on the availability of resources and the performance of system components (or both) in a data processing installation.
A Design of an Assessment System for UML Class Diagram
Authors: Noraida Haji Ali, Zarina Shukur, Sufian Idris
Venue: Proceedings of the The 2007 International Conference Computational Science and its Applications (2007)

The Unified Modeling Language (UML) is probably the most widely known and used notation for objectoriented analysis and design. UML consists of various graphical notations, which capture the static system structures (class diagrams), system component behaviors (state transition diagrams) and system component interactions (collaboration and sequence diagrams). UML notations can be produced with the help of CASE (Computer-aided software engineering) tools such as Rational Rose. Basically, we proposed the development of an Assessment system for UML class diagram, the UML Class Diagram Assessor (UCDA). This tool will receive a students UML class diagram in the form of Rational Rose petal files. In this paper we present a design of UML Class Diagram Assessor (UCDA) that evaluates UML class diagrams automatically. UCDA evaluates the diagram based on three aspects: its structure; its correctness and language used. The output of UCDA is a list of comments on a diagram that is hoped to guide students in understanding on how to represent the system requirement in UML model correctly.
A Fully Parallel Mixed-Radix Conversion Algorithm for Residue Number Applications
Authors: C. H. Huang
Venue: IEEE Transactions on Computers (1983)

A new, fully parallel mixed-radix conversion (MRC) algorithm which utilizes the maximum parallelism that exists in the residues (RNS) to mixed-radix (MR) digits conversion to achieve high throughput rate and very short conversion time is presented. The new algorithm has a conversion time of two table look-up cycles for moduli sets consisting of up to 15 moduli. As a comparison, the classical Szabo and Tanaka MRC algorithm has a conversion time of (n - 1) clock cycles for an n-moduli RNS. This algorithm can be implemented by off-the-shelf ECL IC's to achieve a conversion time of 50 ns and a throughput rate of 40 MHz for a 150-bit RNS.
A constraint-based probabilistic framework for name disambiguation
Authors: Duo Zhang, Jie Tang, Juanzi Li, Kehong Wang
Venue: Proceedings of the sixteenth ACM conference on Conference on information and knowledge management (2007)

This paper is concerned with the problem of name disambiguation. By name disambiguation, we mean distinguishing persons with the same name. It is a critical problem in many knowledge management applications. Despite much research work has been conducted, the problem is still not resolved and becomes even more serious, in particular with the popularity of Web 2.0. Previously, name disambiguation was often undertaken in either a supervised or unsupervised fashion. This paper first gives a constraint-based probabilistic model for semi-supervised name disambiguation. Specifically, we focus on investigating the problem in an academic researcher social network (http://arnetminer.org). The framework combines constraints and Euclidean distance learning, and allows the user to refine the disambiguation results. Experimental results on the researcher social network show that the proposed framework significantly outperforms the baseline method using unsupervised hierarchical clustering algorithm.
Cluster delegation: high-performance, fault-tolerant data sharing in NFS
Authors: A. Batsakis, R. Burns
Venue: Proceedings of the High Performance Distributed Computing, 2005. HPDC-14. Proceedings. 14th IEEE International Symposium (2005)

We present cluster delegation, an enhancement to the NFSv4 file system, that improves both performance and recoverability in computing clusters. Cluster delegation allows data sharing among clients by extending the NFSv4 delegation model so that multiple clients manage a single file without interacting with the server. Based on cluster delegation, we implement a fast commit primitive, cooperative caching, and the ability to recover the uncommitted updates of a failed computer. Cluster delegation supports both read and write operations in the cooperative cache, while preserving the consistency guarantees of NFSv4. We have implemented cluster delegation by modifying the Linux NFSv4 client and show that it improves client performance and reduces server load by more than half.
CSL^TA: an Expressive Logic for Continuous-Time Markov Chains
Authors: Susanna Donatelli, Serge Haddad, Jeremy Sproston
Venue: Proceedings of the Fourth International Conference on Quantitative Evaluation of Systems (2007)

The stochastic temporal logic CSL can be used to describe formally properties of continuous-time Markov chains, and has been extended with expressions over states and actions to obtain the logic asCSL. However, properties referring to the probability of a finite sequence of timed events (such as "with probability at least 0.75, the system will be in state set A at time 5, then in state set B at time 7, then in state set C at time 20") cannot be expressed in either CSL or asCSL. With the aim of increasing the expressive power of temporal logics for continuous-time Markov chains, we introduce the logic CSL^TA and its model-checking algorithm. CSL^TA extends CSL and asCSL by allowing the specification of timed properties through a deterministic one-clock timed automata.
Large-scale Evaluation Infrastructure for Information Access Technologies Enhancement and Creativity
Authors: Noriko Kando
Venue: Proceedings of the 7th IEEE International Conference on Computer and Information Technology (2007)

This paper introduces the NTCIR iNII Test Collection for Information Retrieval and access technologies jProject and its evaluation workshop series called NTCIR Workshops, which are designed to enhance research in information access technologies, such as information retrieval, text summarization, question answering, text mining, and their cross-lingual efforts by providing infrastructure for large-scale evaluations.
Integrated Injection Logic: A Bipolar LSI Technique
Authors: R. A. Pedersen
Venue: Computer (1976)

Integrated injection logic or merged transistor logic is a novel bipolar circuit design approach to achieve high-density large-scale integration. As the basic logic units it uses multicollector npn transistors which are powered from merged multicollector lateral pnp transistors. I2L can be fabricated with standard buried collector technology and is therefore compatible with conventional bipolar circuitry on the same chip. The feature of having special interface circuitry digital and/or linear on the same chip renders I2L a powerful LSI technique. 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
Locally Rotation, Contrast, and Scale Invariant Descriptors for Texture Analysis
Authors: Matthew Mellor, Byung-Woo Hong, Michael Brady
Venue: IEEE Transactions on Pattern Analysis and Machine Intelligence (2008)

Textures within real images vary in brightness, contrast, scale and skew as imaging conditions change. To enable recognition of textures in real images, it is necessary to employ a similarity measure which is invariant to these properties. Furthermore, since textures often appear on undulating surfaces, such invariances must necessarily be local rather than global. Despite these requirements, it is only relatively recently that texture recognition algorithms with local scale and affine invariance properties have begun to be reported. Typically, they comprise detecting feature points followed by geometric normalization prior to description. We describe a method based on invariant combinations of linear filters. Unlike previous methods, we introduce a novel family of filters, which provide scale invariance, resulting in a texture description invariant to local changes in orientation, contrast and scale and robust to local skew. Significantly, the family of filters enable local scale invariants to be defined without using a scale selection principle or a large number of filters. A texture discrimination method based on the Â2 similarity measure applied to histograms derived from our filter responses outperforms existing methods for retrieval and classification results for both the Brodatz textures and the UIUC database, which has been designed to require local invariance.
Fuzzy reasoning approach for QoS routing in B-ISDN
Authors: Emad Aboelela, Christos Douligeris
Venue: Journal of Intelligent Fuzzy Systems: Applications in Engineering and Technology (2000)

Efficient routing algorithms are required to guarantee the various quality of service (QoS) characteristics requested by the wide range of applications supported by Broadband Integrated Services Digital Networks (B-ISDN). However, it is known that various formulations of such a routing problem, with two or more additive or multiplicative QoS metrics in any possible combination, is NP-complete. In this paper, we propose a heuristic approach based on fuzzy logic. For each metric, a fuzzy membership function is defined to reflect the QoS requirements from that metric. A fuzzy-inference rule base is implemented to generate the fuzzy cost of each path based on the crisp values of the different metrics possibly used in the network links. The proposed approach is tested with a wide variety of loads and the effect on different measures of performance is analyzed. Simulation results demonstrate the capability of this approach to increase the throughput and utilization of the communication network, and provide a fair distribution of different connection requests.
Collarette Area Localization and Asymmetrical Support Vector Machines for Efficient Iris Recognition
Authors: Kaushik Roy, Prabir Bhattacharya
Venue: Proceedings of the 14th International Conference on Image Analysis and Processing (2007)

This paper presents an efficient iris recognition technique based on the zigzag collarette area localization and asymmetrical support vector machine. Thedeterministic feature sequence extracted from the iris images using the ID log-Gabor filters is applied to train the support vector machine (SVM). We use the multi-objective generic algorithm (MOGA) to optimize the features and also to increase the overall recognition accuracy. The traditional SVM is modified to anassymetrical SVM to treat the cases of the False Accept and the False Reject differently and also to handle the unbalanced data of a specific class with respect to the other classes. The proposed technique is computationallyeffective with a recognition rate of 97.70% on the ICE(Iris Challenge Evaluation) iris dataset.
Video Object Motion Segmentation for Intelligent Visual Surveillance
Authors: M. Jiang, D. Crookes
Venue: Proceedings of the International Machine Vision and Image Processing Conference (2007)

This paper presents a video object motion segmentation method for object tracking in visual surveillance. In the first step, the frames are first decomposed into small facets (regions), using colour information. Then, based on the detected motion, the motion segmentation is performed at facet level. A Bayesian approach is applied in clustering facets into moving objects and tracking moving video objects. Experiments have verified that the proposed method can efficiently tackle the complexity of video motion tracking.
Symbolic Path Sensitization Analysis and Applications
Authors: Jian Kang, Sharad C. Seth, Shashank K. Mehta
Venue: Proceedings of the 16th Asian Test Symposium (2007)

A new symbolic approach models the sensitization paths to selected primary output(s) as Boolean equations, with satisfying solutions representing the set of all sources of single and multiple sensitizations in the circuit. The paper discusses two applications of this idea: model-free fault diagnosis and input sensitization analysis.
Video Abrupt Transition Detection Based on K-L Transform
Authors: Peng Tianqiang, Zhao Keke, Li Bicheng
Venue: Proceedings of the Fourth International Conference on Image and Graphics (2007)

Shot boundary detection is the first step of the video analysis and retrieval. In this paper we propose a new technique of abrupt transition detection based on K-L transform according to the characteristics of human visual system. Firstly, the algorithm uses K-L transform of the RGB color space to produce image parameter modal that is consisted of eigenvectors. Secondly, the algorithm calculates the frame distance with the first and second principle axis's direction differences in the two adjacent frames and weighting coefficients. Thirdly the algorithm uses a changeable width sliding window in front of current frame to detect abrupt transition, and at the same time disposes the static shot. The experimental results show that the proposed algorithm outperforms the traditional HSV histogram method, executes in real time and is robust to illumination changes or camera motion occur.
Execution-time Prediction for Dynamic Streaming Applications with Task-level Parallelism
Authors: Peter Poplavko, Twan Basten, Jef van Meerbergen
Venue: Proceedings of the 10th Euromicro Conference on Digital System Design Architectures, Methods and Tools (2007)

Programmable multiprocessor systems-on-chip are becoming the preferred implementation platform for embedded streaming applications. This enables using more software components, which leads to large and frequent dynamic variations of data-dependent execution times. In this context, accurate and conservative prediction of execution times helps in maintaining good audiolvideo quality and reducing energy consumption by dynamic evaluation of the amount of on-chip resources needed by applications. To be effective, multiprocessor systems have to employ the available parallelism. The combination of task-level parallelism and task delay variations makes predicting execution times a very hard problem. So far, under these conditions, no appropriate techniques exist for the conservative prediction of execution times with the required accuracy. In this paper, we present a novel technique for this problem, exploiting the concept of scenario-based prediction, and taking into account the transient and periodic behavior of scenarios and the effect of scenario transitions. In our MPEG-4 shape-decoder case study, we observe no more than 11% average overestimation.
A Byzantine Fault Tolerant Distributed Commit Protocol
Authors: Wenbing Zhao
Venue: Proceedings of the Third IEEE International Symposium on Dependable, Autonomic and Secure Computing (2007)

In this paper, we present a Byzantine fault tolerant distributed commit protocol for transactions running over untrusted networks. The traditional two-phase commit protocol is enhanced by replicating the coordinator and by running a Byzantine agreement algorithm among the coordinator replicas. Our protocol can tolerate Byzantine faults at the coordinator replicas and a subset of malicious faults at the participants. A decision certificate, which includes a set of registration records and a set of votes from participants, is used to facilitate the coordinator replicas to reach a Byzantine agreement on the outcome of each transaction. The certificate also limits the ways a faulty replica can use towards non-atomic termination of transactions, or semantically incorrect transaction outcomes.
Note: On the asymptotic minimum number of monochromatic 3-term arithmetic progressions
Authors: Pablo A. Parrilo, Aaron Robertson, Dan Saracino
Venue: Journal of Combinatorial Theory Series A (2008)

Let V(n) be the minimum number of monochromatic 3-term arithmetic progressions in any 2-coloring of {1,2,...,n}. We show that167532768n^2(1+o(1))=
Detection of Single, Stuck-Type Failures in Multivalued Combinational Networks
Authors: R. J. Spillman
Venue: IEEE Transactions on Computers (1977)

This paper examines the problem of detecting single stuck-type faults in multivalued combinational circuits. The algebra employed is the generalized ternary algebra developed by Vranesic, Lee, and Smith. Many of the concepts already developed for fault detection in binary circuits generalized easily to the multivalued case. The special properties of multivalued circuits for this algebra simplifies fault detection. Specifically, this paper introduces the concept of a partially enabled gate, K-paths in combinational circuits and a new notation for multivalued fault detection. In addition, a modified form of the D-algorithm is developed for fault detection in multivalued circuits as well as a d algorithm for the simplification of multivalued test sets.
Associative Memory and Successive Learning in Chaotic Neural Network
Authors: Shukai Duan, Lidan Wang
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 03 (2007)

In this paper, a new chaotic neural network (CNN) with partial spatio-temporal summation and a new output function is proposed. Associative memory and successive learning in the CNN is also considered. A series of computer simulations show the effectiveness of the proposed model.
Fuzzy-Logic Control System of a Variable-Speed Variable-Pitch Wind-Turbine and a Double-Fed Induction Generator
Authors: C. A. M. Amandola, D. P. Gonzaga
Venue: Proceedings of the Seventh International Conference on Intelligent Systems Design and Applications (2007)

The utilization of variable-speed variable-pitch wind, or aeolic, turbines jointly with double-fed induc- tion generator (DFIG) is one of several strategies on the aeolic energy capture and the aeolic-electrical en- ergy conversion, according to local power system standards. The aeolic energy captured must be con- trolled, such as to be maximized for weak winds and to be limited for strong winds to avoid damages and overvoltages in the DFIG. In this work the energy cap- ture control is made applying a fuzzy-logic controller directly on the turbine pitch-angle and the speed con- trol is made by a field-oriented fuzzy-logic controller, that acts on DFIG electromotive torque so that to fol- low the reference value generated by an optimum an- gular speed estimator. The simulation results of the whole aeolic-electrical energy conversion system show a stable and smooth dynamic behavior for three differ- ent real conditions of wind, even though under strong and turbulent winds.
A Hybrid System for Robust Recognition of Ethiopic Script
Authors: Y. Assabie, J. Bigun
Venue: Proceedings of the Ninth International Conference on Document Analysis and Recognition - Volume 01 (2007)

In real life, documents contain several font types, styles, and sizes. However, many character recognition systems show good results for specific type of documents and fail to produce satisfactory results for others. Over the past decades, various pattern recognition techniques have been applied with the aim to develop recognition systems insensitive to variations in the characteristics of documents. In this paper, we present a robust recognition system for Ethiopic script using a hybrid of classifiers. The complex structures of Ethiopic characters are structurally and syntactically analyzed, and represented as a pattern of simpler graphical units called primitives. The pattern is used for classification of characters using similarity-based matching and neural network classifier. The classification result is further refined by using template matching. A pair of directional filters is used for creating templates and extracting structural features. The recognition system is tested by real life documents and experimental results are reported.
The 15-Billion-Dollar Broadband Bonus
Authors: Shane Greenstein
Venue: IEEE Micro (2007)

What is the economic value created by the increasing use of broadband? There are two alternative economic concepts for understanding the value created by a new good, one pertaining to gross domestic product (GDP) and another pertaining to users. Greenstein combines the two concepts to estimate the overall economic value created by broadband. He estimates that broadband created at least an additional 15 billion dollars of economic value in 2006, but less than half of that shows up in GDP.