ppxscal/embedding_network huggingface dataset:
A Fast Algorithm for MPEG Video Segmentation Based on Macroblock
Authors: Xuejun Wang, Shigang Wang, Hexin Chen
Venue: Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 02 (2007)

A fast algorithm for MPEG compressed video segmen- tation based on macroblock (MB) is presented in this pa- per. The proposed method can detect the scene change boundaries accurately through the macroblock informa- tion of B-frame and P-frame which can be extracted from the encoded bit-stream directly without total decompres- sion for MPEG bit-stream, so the detecting speed is quick. Simulation results in different sequences show that the proposed algorithm is effective and accurate for detecting scene change boundaries in MPEG video.
Combining resources with confidence measures for cross language information retrieval
Authors: Youssef Kadri, Jian-Yun Nie
Venue: Proceedings of the ACM first Ph.D. workshop in CIKM (2007)

Query translation in Cross Language Information Retrieval (CLIR) can be performed using multiple resources. Previous attempts to combine different translation resources use simple methods such as linear combination. Unfortunately, these approaches are insufficient to combine different types of resources such as bilingual dictionaries and statistical translation models. In this paper, we use confidence measures for this combination for the purpose of English-Arabic CLIR. Confidence measure is used to adjust the original scores of translations and to create a weight of the same nature for translations with different resources. We tested this technique on two test CLIR collections from TREC and obtained encouraging improvements compared to the results of linear combination.
Multiple almost periodic solutions in nonautonomous delayed neural networks
Authors: Kuang-Hui Lin, Chih-Wen Shih
Venue: Neural Computation (2007)

A general methodology that involves geometric configuration of the network structure for studying multistability and multiperiodicity is developed. We consider a general class of nonautonomous neural networks with delays and various activation functions. A geometrical formulation that leads to a decomposition of the phase space into invariant regions is employed. We further derive criteria under which the n-neuron network admits 2n exponentially stable sets. In addition, we establish the existence of 2n exponentially stable almost periodic solutions for the system, when the connection strengths, time lags, and external bias are almost periodic functions of time, through applying the contraction mapping principle. Finally, three numerical simulations are presented to illustrate our theory.
The Parameterized Approximability of TSP with Deadlines
Authors: Hans-Joachim Bockenhauer, Juraj Hromkovic, Joachim Kneis, Joachim Kupke
Venue: Theory of Computing Systems (2007)

Modern algorithm theory includes numerous techniques to attack hard problems, such as approximation algorithms on the one hand and parameterized complexity on the other hand. However, it is still uncommon to use these two techniques simultaneously, which is unfortunate, as there are natural problems that cannot be solved using either technique alone, but rather well if we combine them. The problem to be studied here is not only natural, but also practical: Consider TSP, generalized as follows. We impose deadlines on some of the vertices, effectively constraining them to be visited prior to a given point of time. The resulting problem DlTSP (a special case of the well-known TSP with time windows) inherits its hardness from classical TSP, which is both well known from practice and renowned to be one of the hardest problems with respect to approximability: Within polynomial time, not even a polynomial approximation ratio (let alone a constant one) can be achieved (unless P = NP). We will show that DlTSP is even harder than classical TSP in the following sense. Classical TSP, despite its hardness, admits good approximation algorithms if restricted to metric (or near-metric) inputs. Not so DlTSP (and hence, neither TSP with time windows): We will prove that even for metric inputs, no constant approximation ratio can ever be achieved (unless P = NP). This is where parameterization becomes crucial: By combining methods from the field of approximation algorithms with ideas from the theory of parameterized complexity, we apply the concept of parameterized approximation. Thereby, we obtain a 2.5-approximation algorithm for DlTSP with a running time of k! · poly(|G|), where k denotes the number of deadlines. Furthermore, we prove that there is no fpt-algorithm with an approximation guarantee of 2-¿ for any ¿ > 0, unless P = NP. Finally, we show that, unlike TSP, DlTSP becomes much harder when relaxing the triangle inequality. More precisely, for an arbitrary small violation of the triangle inequality, DlTSP does not admit an fpt-algorithm with approximation guarantee ((1-¿)/2)|V| for any ¿ > 0, unless P = NP.
Research on Confusion Network Algorithm Based on Minimum Bayes Risk Decision Rule
Authors: Bin Wu, Gang Liu, Jun Guo
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 03 (2007)

In mandarin large vocabulary continuous speech recognition, we can obtain recognition result which word error rate(WER) is minimum by using minimum bayes risk(MBR) decoding strategy. One method of MBR decoding is that the word lattice can be transformed into confusion network in order to obtain the recognition result with minimum WER. According to the characteristic of mandarin, we proposed an improved confusion network generation algorithm based on prevenient works. The experimental results of mandarin large vocabulary continuous speech recognition show that the improved algorithm yields a lower WER than the MAP recognition and prevenient two confusion network generation algorithms.
Hybrid Trust Information Exchange for Federated Systems
Authors: Zhengping Wu, Alfred C. Weaver
Venue: Proceedings of the Third IEEE International Symposium on Dependable, Autonomic and Secure Computing (2007)

In federated systems, trust management is critical for information sharing and online collaboration. Security tokens provide a way to convey and exchange trust information for security and privacy protection. Although several communication protocols have mechanisms to exchange security tokens, users may still encounter difficulties when they have to handle security tokens across heterogeneous platforms and security domains. Semantic gaps and incompatibilities are major barriers for trust information exchange in federated trust management. This paper introduces a hybrid approach with intermediary- and query-based mechanisms to resolve semantic gaps and incompatibilities for different types of trust information exchanged by security tokens, and then proposes different exchange models for different types of information. This paper also provides a comprehensive framework to exchange security tokens across security domains with suitable approaches and exchange models. The application of this framework in a healthcare environment provides a new method to interoperate trust information for security- and privacy-critical applications.
The Phonological Syllable Plays a Role in Lexical Access in Korean Visual Word Recognition
Authors: Kwon Youan, Park Kinam, Lim Heuiseok, Nam Kichun
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 05 (2007)

Recently, the influence of phonological information in visual word recognition has attracted a great amount of studies. Especially, languages with a clear syllable boundary, such as Spanish and French, have reported the syllable-based sub-lexical unit in visual word recognition. The present study investigated whether sub-lexical unit in Korean visual word recognition is phonological syllable or orthographic syllable. In Experiment 1, we orthogonally manipulated the number of phonological syllable neighbors and the number of orthographic syllable neighbors in Korean disyllable words and conducted a lexical decision task. In Experiment 2, new words were used in a computational simulation. The results of two experiments showed the inhibitory effect as increasing the number of phonological syllable neighbor. We can account that the inhibitory effect is due to the lexical competition between phonological syllable-based candidates in the lexical level. The present study expands the notion that the syllable is an important sub-lexical unit in visual word recognition and also phonological information is a main function of lexical process.
Evolutionary Conceptual Clustering of Semantically Annotated Resources
Authors: Nicola Fanizzi, Claudia d'Amato, Floriana Esposito
Venue: Proceedings of the International Conference on Semantic Computing (2007)

A clustering method is presented which can be applied to knowledge bases storing semantically annotated resources. The method can be used to discover groupings of structured objects expressed in the standard concept languages employed in the Semantic Web. The method exploits effective language-independent semi-distance measures over the space of resources. These are based on their semantics w.r.t. a number of dimensions corresponding to a committee of features represented by a group of discriminating concept descriptions. We show how to obtain a maximally discriminating group of features through a feature construction procedure based on genetic programming. The evolutionary clustering algorithm employed is based on the notion of medoids applied to relational representations. It is able to induce an optimal set of clusters by means of a proper fitness function based on the defined distance and the discernibility criterion. An experimentation with some real ontologies proves the feasibility of our method.
Image Processing with the Staran Parallel Computer
Authors: D. Rohrbacher
Venue: Computer (1977)

Although not designed with image processing specifically in mind, the Staran parallel processor has had a significant impact on that application area. The machine is full programmable, yet when applied to image processing it has demonstrated speeds usually associated only with hardwired systems. The result is an ability to execute interactively (response time under 10 seconds) a number of sophisitcated image processing algorithms and provide a significant improvement in throughput for batch processing systems.
Fast clonal algorithm
Authors: Nitesh Khilwani, Anoop Prakash, Ravi Shankar, M. K. Tiwari
Venue: Engineering Applications of Artificial Intelligence (2008)

The aim of this paper is to design an efficient and fast clonal algorithm for solving various numerical and combinatorial real-world optimization problems effectively and speedily, irrespective of its complexity. The idea is to accurately read the inherent drawbacks of existing immune algorithms (IAs) and propose new techniques to resolve them. The basic features of IAs dealt in this paper are: hypermutation mechanism, clonal expansion, immune memory and several other features related to initialization and selection of candidate solution present in a population set. Dealing with the above-mentioned features we have proposed a fast clonal algorithm (FCA) incorporating a parallel mutation operator comprising of Gaussian and Cauchy mutation strategy. In addition, a new concept has been proposed for initialization, selection and clonal expansion process. The concept of existing immune memory has also been modified by using the elitist mechanism. Finally, to test the efficacy of proposed algorithm in terms of search quality, computational cost, robustness and efficiency, quantitative analyses have been performed in this paper. In addition, empirical analyses have been executed to prove the superiority of proposed strategies. To demonstrate the applicability of proposed algorithm over real-world problems, Machine-loading problem of flexible manufacturing system (FMS) is worked out and matched with the results present in literature.
Oscillator-Based Reconfigurable Sinusoidal Signal Generator for ADC BIST
Authors: Hsin-Wen Ting, Cheng-Wu Lin, Bin-Da Liu, Soon-Jyh Chang
Venue: Journal of Electronic Testing: Theory and Applications (2007)

In order to perform an on-chip test for characterizing both static and transmission parameters of embedded analog-to-digital converters (ADCs), this paper presents an oscillator-based reconfigurable sinusoidal signal generator which can produce both high and low frequency sinusoidal signals by switching the oscillator into different modes. Analog and digital signals can additionally be produced concurrently in both modes to provide not only test stimuli, but also reference responses for the ADC built-in self-test. The generated oscillation signal amplitude and frequency can be easily and precisely controlled by simply setting the oscillator clock frequency and initial condition coefficients. Except for a 1-bit digital-to-analog converter and smoothing filter, this proposed generator is constructed entirely by digital circuits, and hence easily integrates this silicon function and verifies itself before testing the ADCs.
Recommendations in taste related domains: collaborative filtering vs. social filtering
Authors: Georg Groh, Christian Ehmig
Venue: Proceedings of the 2007 international ACM conference on Supporting group work (2007)

We investigate how social networks can be used in recommendation generation in taste related domains. Social Filtering (using social networks for neighborhood generation) is compared to Collaborative Filtering with respect to prediction accuracy in the domain of rating clubs. After reviewing background and related work, we present an extensive empirical study where over thousand participants from a social networking community where asked to provide ratings for clubs in Munich. We then compare a typical traditional CF-approach to a social recommender / social filtering approach where friends from the underlying social network are used as rating neighborhood and analyze the experiments statistically. Surprisingly, the social filtering approach outperforms the CF approach in all variants of the experiment. The implications of the experiment for professional and private-life collaborative environments and services where recommendations play a role are discussed. We conclude with future perspectives on social recommender systems, especially in upcoming mobile environments.
Single-Parameter Solutions for Flip-Flop Equations
Authors: F. M. Brown
Venue: IEEE Transactions on Computers (1971)

General one-parameter solutions are exhibited for the RS, RST, and JK flip-flop input equations.
Some Problems of Professional End User Developers
Authors: Judith Segal
Venue: Proceedings of the IEEE Symposium on Visual Languages and Human-Centric Computing (2007)

By the term "professional end user developers' we mean people such as research scientists who work in highly technical, knowledge-rich domains and who develop software in order to further their professional goals. In common with other end user developers, professional end user developers do not describe themselves as software engineers and have no formal training in software engineering. They differ from most other end user developers, however, in that learning programming languages rarely presents them with any problem. In this paper, drawing on data from field studies of different groups of professional end users, we examine the problems that such people face in meeting the demands of software development given the culture in which they work and their normal development practice. Understanding these problems is an essential prerequisite to developing tools, techniques etcetera to support professional end user development.
A shape hierarchy for 3D modelling from video
Authors: A. van den Hengel, A. Dick, T. Thormählen, B. Ward, P. H. S. Torr
Venue: Proceedings of the 5th international conference on Computer graphics and interactive techniques in Australia and Southeast Asia (2007)

This paper describes an interactive method for generating a model of a scene from image data. The method uses the camera parameters and point cloud typically generated by structure-and-motion estimation as a starting point for developing a higher level model, in which the scene is represented as a set of parameterised shapes. Classes of shapes are represented in a hierarchy which defines their properties but also the method by which they are localised in the scene, using a combination of user interaction, sampling and optimisation. Relations between shapes, such as adjancency and alignment, are also specified interactively. The method thus provides a modelling process which requires the user to provide only high level scene information, the remaining detail being provided through geometric analysis of the image set. This mixture of guided, yet automated, fitting techniques allows a non-expert user to rapidly and intuitively create a visually convincing 3D model of a real world scene from an image set.
A Software Reliability Model Based on Blind Number Theory
Authors: Yongqiang Zhang, Jingjie Yin
Venue: Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 01 (2007)

The paper takes advantage of unascertained theory de- scribed in the subjective cognition uncertainty, and then ap- plies blind number to describe the uncertainty of the soft- ware failure process as well as comes up with a new soft- ware reliability model based on blind number theory (BM Model for short). The practical calculations shows the BM Model embodied the characters of simply, small account of calculation but better forecasting capability, which had the value of macroscopic conference to some extent.
Occlusion-Resistant Camera Design for Acquiring Active Environments
Authors: Daniel G. Aliaga, Yi Xu, Voicu Popescu
Venue: IEEE Computer Graphics and Applications (2007)

The authors propose a family of occlusion-resistant camera (ORC) designs for acquiring active environments despite the presence of moving interfering occluders. Capturing images in an in-use environment increases acquisition efficiency and quality without having to close off the targeted site. The authors' cameras explicitly remove interfering dynamic occluders from acquired data in real-time and during live capture. The key idea is to capture the scene at least twice from each viewpoint as the camera moves continually to sweep the scene and sample all surfaces. The approach creates a single portable device combining the benefits of a stationary camera, which detects moving interfering occluders by image differencing, with those of a dynamic camera, which achieves scene coverage for inside-looking-out modeling. The authors describe their family of designs that progressively trades complexity for stricter camera orientation constraints, analyze their performance, and present a first ORC implementation.
Collaborative Detection of DDoS Attacks over Multiple Network Domains
Authors: Yu Chen, Kai Hwang, Wei-Shinn Ku.
Venue: IEEE Transactions on Parallel and Distributed Systems (2007)

This paper presents a new distributed approach to detecting DDoS (distributed denial of services) flooding attacks at the traffic flow level. The new defense system is suitable for efficient implementation over the core networks operated by Internet service providers (ISP). At the early stage of a DDoS attack, some traffic fluctuations are detectable at Internet routers or at gateways of edge networks. We develop a distributed change-point detection (DCD) architecture using change aggregation trees (CAT). The idea is to detect abrupt traffic changes across multiple network domains at the earliest time. Early detection of DDoS attacks minimizes the flooding damages to the victim systems serviced by the provider.The system is built over attack-transit routers, which work together cooperatively. Each ISP domain has a CAT server to aggregate the flooding alerts reported by the routers. CAT domain servers collaborate among themselves to make the final decision. To resolve policy conflicts at different ISP domains, a new secure infrastructure protocol (SIP) is developed to establish the mutual trust or consensus. We simulated the DCD system up to 16 network domains on the DETER testbed, a 220-node PC cluster for Internet emulation experiments at USC Information Science Institute. Experimental results show that 4 network domains are sufficient to yield a 98% detection accuracy with only 1% false-postive alarms. Based on a 2006 Internet report on AS (autonomous system) domain distribution, we prove that this DDoS defense systrem can scale well to cover 84 AS domains. This security coverage is wide enough to safeguard most ISP core networks from real-life DDoS flooding attacks.
Incremental learning approach and SAT model for Boolean matching with don't cares
Authors: Kuo-Hua Wang, Chung-Ming Chan
Venue: Proceedings of the 2007 IEEE/ACM international conference on Computer-aided design (2007)

In this paper, we will propose an incremental learning approach to solve Boolean matching for incompletely specified functions. This approach can incrementally analyze current feasible partial mappings, detect and eliminate redundant manipulations in a proactive way. A new type of signature exploiting single variable symmetries is also given to reduce the searching space. Moreover, a SAT model of Boolean matching will be proposed to handle large Boolean functions. Through the utilization of these novel mechanisms, a drastic improvement on the performance of our Boolean matching algorithms are achieved. The experimental results demonstrate the effectiveness and efficiency of the proposed learning-based and SAT-based Boolean matching algorithms on many large benchmarking circuits.
More Hot Stuff
Authors: David H. Albonesi
Venue: IEEE Micro (2007)

While leading computing corporations have instituted "green data center" and "eco-responsible computing" initiatives, the computer architecture community as a whole has drifted away from power-aware architecture and on to the next topic. Arguably, power remains the computer architecture topic with the most potential for societal impact. Albonesi exhorts Micro readers to re-emphasize power-related research and outlines a few of the most pressing issues.
Metadata management for federated databases
Authors: Carlos Ordonez, Zhibo Chen, Javier García-García
Venue: Proceedings of the ACM first workshop on CyberInfrastructure: information management in eScience (2007)

A federated database consists of several loosely integrated databases, where each database may contain hundreds of tables and thousands of columns,interrelated by complex foreign key relationships. In general, there exists a lot of semistructured data elements outside the database represented by documents (files), created and updated by multiple users and programs. Documents have references to multiple databases and subsets of their tables and columns. Manually tracking which specific tables and columns are referred to by a document, accessed by a specific program or user is a daunting task. With such a goal in mind, we present a system that builds metadata models for a federated database using a relational database as a central object type and metadata repository. Metadata includes table and columns coming from logical data models corresponding to each database, as well as documents representing external semistructured data sources. SQL statements assemble metadata and data types to create objects and relationships as relational tables for easy querying. We discuss potential applications in federated scientific databases.