ppxscal/embedding_network huggingface dataset:
Data Fusion Using Improved Dempster-Shafer Evidence Theory for Vehicle Detection
Authors: Wentao Zhao, Tao Fang, Yan Jiang
Venue: Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 01 (2007)

Data fusion is an important tool for improving the performance of detecting system when various sensors are available. The Dempster-Shafer evidence theory for fusion has similar reasoning logic with human. So we apply the data fusion method which is based on Dempster-Shafer theory, in a vehicle detecting system to increase the detection accuracy. In this paper, the Dempster-Shafer evidence theory and its problem are discussed, and an improved Reliability Revaluated Dempster-Shafer Fusion (RRDSF) algorithm is proposed and applied. The experiments show promising results and encourage us to do further work.
Visualization of Complex Automotive Data: A Tutorial
Authors: Jeffrey A. Stevens
Venue: IEEE Computer Graphics and Applications (2007)

Making complicated data easier to understand has always been a challenge. Four types of visualization applications (CAD, generalized, specialized, and custom) have successfully been used by automotive manufacturers such as General Motors to help meet this goal. Here are some ways that common processes can be developed for all types of visualization.
Fuzzy Logic Based Segmentation of Microcalcification in Breast Using Digital Mammograms Considering Multiresolution
Authors: Mahua Bhattacharya, Arpita Das
Venue: Proceedings of the International Machine Vision and Image Processing Conference (2007)

Breast cancer is one of the leading causes of death for women. Small clusters of microcalcifications appearing as collection of white spots on mammograms show an early warning of breast cancer. In present paper a novel approach of segmentation implemented on X-ray mammograms for more accurate detection of microcalcification clusters has been introduced. The method is based on discrete wavelet transform due to its multiresolution properties. Morphological tophat algorithm is applied for contrast enhancement of the calcification clusters. Finally fuzzy c-means clustering (FCM) algorithm has been implemented for intensity-based segmentation. The proposed technique is compared with conventional global thresholding method and experimental results show the good properties of the proposed technique.
Mining Maximal Frequent Itemsets with Frequent Pattern List
Authors: Jin Qian, Feiyue Ye
Venue: Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 01 (2007)

Mining frequent itemsets is a major aspect of association rule research. However, the mining of the complete of frequent itemsets will lead to a huge number of itemsets. Fortunately, this problem can be reduced to the mining of maximal frequent itemsets. In this paper, we adopt frequent pattern list (FPL) and bit string technique, propose a novel algorithm for mining maximal frequent itemsets based on frequent pattern list (FPLMFI-Mining). It conducts various operations on FPL according to the frequency of frequent items. Moreover, it utilizes bit string and-operation to test maximal frequent itemsets. This algorithm can be scaled up to very large databases by parallel projection and compress technique.
Design of an FPGA logic element for implementing asynchronous NULL convention logic circuits
Authors: Scott C. Smith
Venue: IEEE Transactions on Very Large Scale Integration (VLSI) Systems (2007)

Two versions of a reconfigurable logic element are developed for use in constructing a NULL convention logic (NCL) field-programmable gate array (FPGA): one with extra embedded registration capability, which requires additional area, and one without. Both versions can be configured as any of the 27 fundamental NCL gates, including resettable and inverting variations, and both can utilize embedded registration for gates with three or fewer inputs; however, only the version with the additional embedded registration capability can utilize embedded registration with four-input gates. These two approaches are compared with each other and with an existing approach, showing that both versions developed herein yield a more area efficient NCL circuit implementation, compared to the previous work. The two FPGA logic elements are simulated at the transistor level using the 1.8-V, 180-nm TSMC CMOS process.
PLZ-SYS PL/65 PL/M RPL/2 Mistral PLZ Special Feature A Survey of Microprocessor Languages
Authors: S. Crespi-Reghizzi
Venue: Computer (1980)

At least 20 different microprocessor languages are in use today spawned in part by marketing policies, fashion, and the "not invented here" attitude. Here is an attempt at orderly classification.
Information Processing with an Associative Parallel Processor
Authors: R. M. Lea
Venue: Computer (1975)

Research into new computer structures, which would be better suited to non-numerical information processing tasks, has been in progress for some years.1,2,3The problem has been to design a computing system with high hardware efficiency and low software complexity over a wide range of these applications. Recent research4,5,6has indicated that these apparently conflicting requirements could possibly be achieved by a parallel processing system containing content-addressable storage. Hence there is a revival of interest in associative memories and associative processors.
Cryptanalysis and Improvement of a Certificateless Proxy Signature Scheme from Bilinear Pairings
Authors: Rongbo Lu, Dake He, Changji Wang
Venue: Proceedings of the Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing - Volume 03 (2007)

Due to avoiding the inherent escrow of identity-based cryptography and yet not requiring certificates to guarantee the authenticity of public keys, Li et al. proposed a certificateless proxy signature scheme from bilinear pairings. As for the security, they claimed their scheme satisfies the security requirements of proxy signature such as strong identifiability, verifiability ,strong undeniabilty, preventions of misuse, and strong unforgeability; and any third party who can even get the signed warrant generated by the original signer can not forge a proxy signature. In this paper, however, we successfully identify a forgery attack against their scheme. That is, based on the proxy signature generated by a proxy signer on a message on behalf of an original signer, an adversary can forge a valid proxy signature on the same message which seemed generated by the proxy signer on behalf of this adversary himself. After production a forged proxy signature, the adversary has the same authority with the original signer to the proxy signer, and the verifier cannot distinguish which one is the real original signer. To thwart this attacks, an improvement is further proposed.
Software Considerations for Microprocessors
Authors: T. Opdendyk
Venue: Computer (1976)

For computers of all sizes, software has become a critical element in systems design and implementation. As dramatically as the costs of hardware have dropped, the labor-intensive costs of software have risen. In addition, there are no widely accepted and practiced techniques for controlling and estimating software development and manufacturing (size) costs, or forecasting software capability and reliability. To be sure, these problems are being addressed by software engineering, but today that is still a very primitive discipline in comparison with other computer engineering fields. 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
Validation of the awareness net model for the Australian security investment processes
Authors: Farhad Daneshgar, Jim Wang
Venue: Knowledge-Based Systems (2007)

This study evaluates the appropriateness of an existing collaborative business process model for representation of the collaboration context within the Australian security investment market (ASIM). It is an initial step towards developing knowledge-base system of a management support system for investment decision processes within the ASIM. The three aspects of appropriateness evaluated correspond to the three quality categories namely, syntactic, semantic and pragmatic qualities using the conceptual model quality framework (CMQF) which is based on semiotic theory. An interpretivist case study methodology is adopted using a combination of theory building and sense-making case study strategies. Seven in-depth interviews were conducted in order to assess the above three appropriateness measures by the actors within the ASIM whose roles correspond to those in the awareness model. The study highlighted required modifications to the concept descriptions of the initial version of the model. A modified awareness net was then constructed accordingly.
Intelligent Control for Robotic Rehabilitation after Stroke
Authors: Duygun Erol, Nilanjan Sarkar
Venue: Journal of Intelligent and Robotic Systems (2007)

The paper presents a new control approach to robot-assisted rehabilitation for stroke patients. The control architecture is represented in terms of a hybrid system model combining a high-level and a low-level assistive controller. The high-level controller is designed to monitor the progress and safety of the rehabilitation task. The high-level controller also makes decisions on the modification of the task that might be needed for the therapy. A design of a low-level assistive controller that provides robotic assistance for an upper arm rehabilitation task and works in coordination with the proposed high-level controller is discussed. Experimental results on unimpaired participants are presented to demonstrate the efficacy of both the high-level and low-level assistive controllers.
Unsupervised Learning of Manifolds via Linear Approximations
Authors: Hassan A. Kingravi, M. Emre Celebi, Pragya P. Rajauria
Venue: Proceedings of the 18th International Conference on Database and Expert Systems Applications (2007)

In this paper, we examine the application of manifold learning to the clustering problem. The method used is Locality Preserving Projections (LPP), which is chosen because of its computational efficiency. A detailed derivation of the method is presented, as well as the theoretical justi- fication behind it. Experiments performed on CMU's PIE database show that the projections created by LPP yield better clustering results than those obtained by k-means alone.
Kernel Modified Quadratic Discriminant Function for Online Handwritten Chinese Characters Recognition
Authors: D. Yang, L. Jin, Q. Huo, T. He
Venue: Proceedings of the Ninth International Conference on Document Analysis and Recognition - Volume 01 (2007)

The Modified Quadratic Discriminant Function has been used successfully in handwriting recognition, which can be seen as a dot-product method by eigen- decomposition of the covariance matrix. Therefore, it is possible to expand MQDF to high dimension space by kernel trick. This paper presents a new kernel- based method, Kernel Modified Quadratic Discriminant Function (KMQDF) for online Chinese Characters Recognition. Experimental results show that the performance of MQDF is improved by the kernel approach.
Detecting abrupt changes in a piecewise locally stationary time series
Authors: Michael Last, Robert Shumway
Venue: Journal of Multivariate Analysis (2008)

Non-stationary time series arise in many settings, such as seismology, speech-processing, and finance. In many of these settings we are interested in points where a model of local stationarity is violated. We consider the problem of how to detect these change-points, which we identify by finding sharp changes in the time-varying power spectrum. Several different methods are considered, and we find that the symmetrized Kullback-Leibler information discrimination performs best in simulation studies. We derive asymptotic normality of our test statistic, and consistency of estimated change-point locations. We then demonstrate the technique on the problem of detecting arrival phases in earthquakes.
Introducing QoS mechanisms into the IPsec packet processing
Authors: Lars Volker, Marcus Scholler, Martina Zitterbart
Venue: Proceedings of the 32nd IEEE Conference on Local Computer Networks (2007)

The deployment and use of IPsec has consistently increased in recent years. IPsec is a protocol that allows, besides other things, secure branch offices connectivity and secure VPN access for road warriors. The limitations of IPsec are much better understood today, and efforts to improve IPsec are still underway. One aspect of improvement is the integration of IPsec with other functions and protocols of the network. Quality of Service (QoS) is one example. QoS is used to prioritize demanding traffic like Voice over IP, network control messages, and traffic for other mission-critical systems. QoS can be used to mitigate risks of DoS attacks, ill-behaving hosts, and other attacks by separating traffic classes and treating packets according to the respective class. In order to facilitate all the advantages QoS can offer, an IPsec implementation must not only be superficially changed, but needs thorough modifications or, even better, should be designed with QoS support as an objective. The current IPsec standard does hardly offer any guidance to do this. In this paper, we detail our QoS-capable IPsec and compare it with a widely-used regular IPsec implementation. Furthermore, we show that these QoS extensions prove to be valuable, even in difficult scenarios, e.g. using host CPUs for packet processing.
Description of Key Performance Index States based on Cloud Theory and Weight Mean method for Multi-sensor
Authors: Qiuyu Zhang, Lei Sun, Yanfeng Jin
Venue: Proceedings of the Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing - Volume 01 (2007)

Key Performance Index Analysis is a good complementing to the evaluation of past system security states, and the study on it has realistic meanings accordingly. It is realized that Cloud Theory and the Weighted Mean Method for Multi-Sensor could qualitatively describe Key Performance Index States. The data gathered from the multi-sensor under normal states will be tested for consistency by using distributing graph method firstly and will come out the fusion of the minimum average mean variance value by using the Weighted Mean Method for Multi-Sensor secondly. Then the above data fusion will be compared with the key performance index data at every arbitrary moment and each amount of deviation by forgoing compare will be gained. At last the five remark sets constructed from Cloud Theory combining with the amount of deviation will realize the qualitative description of Key Performance Index States. The experiment result shows the validity of this method.
Static analysis summit II
Authors: Paul E. Black
Venue: Proceedings of the 2007 ACM international conference on SIGAda annual international conference (2007)

Funded by the Department of Homeland Security (DHS), the National Institute of Standards and Technology (NIST) started a long-term, ambitious project to identify, enhance and develop software assurance tools. The Software Assurance Metrics And Tool Evaluation (SAMATE) project is leading in (A) developing tests for software evaluation tools, (B) measuring the effectiveness of tools, and (C) identifying gaps in tools and methods. See the workshop web site at http://samate.nist.gov/ SASII.
A Framework for Time Consistency Verification for Web Processes Based on Annotated OWL-S
Authors: Guilan Dai, Xiaoying Bai, Chongchong Zhao
Venue: Proceedings of the Sixth International Conference on Grid and Cooperative Computing (2007)

The paper presents a timing constraint modeling and analyzing method for Web processes based on annotated OWL-S. The method allows us to find whether Web processes are schedulable and which processes in Web processes are not schedulable without actual execution based on its specification. This also suggests replacement of corresponding components or relaxing timing constraints. The contributions of the paper mainly include two aspects: 1) The paper presents a method for extending OWL-S model based on annotation layers. By using annotation layers, the OWL-S model is extended with auxiliary information such as time constraints. This method can be extended to verify other properties of the Web processes by using different annotation layers. 2) The paper describes how to model Web services based systems and determine whether the specification satisfies time consistency. First, we model a Web process in extended OWL-S with timing constraints. Then, we transform the system specification along with its imposed timing constraints into a TPPN (Time Predicate Petri Net) model. Final, TPPN analyzer can automatically simulate and analyze to verify whether the system specification is schedulable under the imposed timing constraints.
Periodic oscillation of discrete-time bidirectional associative memory neural networks
Authors: Hongyong Zhao, Li Sun, Guanglan Wang
Venue: Neurocomputing (2007)

In this paper, a discrete-time bidirectional associative memory neural networks model is considered. By employing the theory of coincidence degree and using Halanay-type inequality technique we give some sufficient conditions ensuring the existence and globally exponential stability of periodic solutions for the discrete-time bidirectional neural networks. An example with the numerical simulations is provided to show the correctness of our analysis.
Power plant start-up scheduling: a reinforcement learning approach combined with evolutionary computation
Authors: Akimoto Kamiya, Hajime Kimura, Masayuki Yamamura, Shigenobu Kobayashi
Venue: Journal of Intelligent Fuzzy Systems: Applications in Engineering and Technology (1998)

Power plant start-up scheduling is aimed at minimizing the start-up time while limiting turbine rotor stresses to acceptable values. In order to increase on-line performance of searching an optimal or near-optimal start-up schedule during power plant operation, we propose to integrate neural network-based reinforcement learning with evolutionary computation implemented by means of Genetic Algorithms (GA). GA guides reinforcement learning to learn optimal schedules with respect to a number of representative sets of stress limits prior to the start-up process. During start-up, GA combined with reinforcement learning will search an optimal or near-optimal start-up schedule at a given set of stress limits. This approach significantly reduces the time needed for learning and searching. On a SPARC station 20, experiments show that it can search an optimal or near-optimal schedule within tens of seconds of CPU time, a time range which should be acceptable in power plant operations.
Classroom Presenter: Enhancing Interactive Education with Digital Ink
Authors: Richard Anderson, Ruth Anderson, Peter Davis, Natalie Linnell, Craig Prince, Valentin Razmov, Fred Videon
Venue: Computer (2007)

Classroom Presenter is a Tablet PC-based interaction system that supports the sharing of digital ink on slides between instructors and students. Initial deployments show that using the technology can achieve a wide range of educational goals and foster a more participatory classroom environment.
Pareto-dominated Hypervolume Measure: An Alternative Approach to Color Morphology
Authors: Mario Koppen, Katrin Franke
Venue: Proceedings of the 7th International Conference on Hybrid Intelligent Systems (2007)

In this paper, an alternative approach to the non-linear filtering of Mathematical Morphology for color and multispectral images based on the Pareto-dominated Hypervolume measure is presented. Parteo-set theory is studied in this context, and among others, successfully implemented in the morphological filtering of color images. The demand to assess the quality of a multi-objective optimization algorithms, in particular, has put forth several kind of measures. One of these measures, the Hypervolume, bases on the Lebesque measure of all points dominated by a set of points and maps a set of Pareto-optimal points to a nonnegative scalar. By considering the Hypervolume in the color-image domain, it can be shown that this Hypervolume corresponds to another kind of Color Morphology, were each pixel in the filtered image represents the Hypervolume of its set of neighbours in the original color image. In the following, some properties of the Hypervolume, as used as an image-processing filter will be derived, and some potential applications of this approach to Color Morphology will be suggested.
Epipolar Geometry of Opti-Acoustic Stereo Imaging
Authors: Shahriar Negahdaripour
Venue: IEEE Transactions on Pattern Analysis and Machine Intelligence (2007)

Optical and acoustic cameras are suitable imaging systems to inspect underwater structures, both in regular maintenance and security operations. Despite high resolution, optical systems have limited visibility range when deployed in turbid waters. In contrast, the new generation of high-frequency (MHz) acoustic cameras can provide images with enhanced target details in highly turbid waters, though their range is reduced by one to two orders of magnitude compared to traditional low-/midfrequency (10s-100s KHz) sonar systems. It is conceivable that an effective inspection strategy is the deployment of both optical and acoustic cameras on a submersible platform, to enable target imaging in a range of turbidity conditions. Under this scenario and where visibility allows, registration of the images from both cameras arranged in binocular stereo configuration provides valuable scene information that cannot be readily recovered from each sensor alone. We explore and derive the constraint equations for the epipolar geometry and stereo triangulation in utilizing these two sensing modalities with different projection models. Theoretical results supported by computer simulations show that an opti-acoustic stereo imaging system outperforms a traditional binocular vision with optical cameras, particularly for increasing target distance and (or) turbidity.
Patterns for Authentication and Authorisation Infrastructures
Authors: Roland Erber, Christian Schlager, Gunther Pernul
Venue: Proceedings of the 18th International Conference on Database and Expert Systems Applications (2007)

In line with the growing success of e-commerce demands for an open infrastructure providing security services are growing stronger. Authentication and Authorisation Infrastructures (AAIs) enhanced with an attribute-based access control model (ABAC) offer such services to service federations and customers. As AAIs are a security enhancing technology, design and implementation must comply with extremely high quality standards. Failures and vulnerabilities in the provided basic security services exponentially affect the service providing processes. Various AAI concepts, frameworks, and products have been developed in the past. Building on these experiences, we define a pattern system for AAIs. It will ensure interoperability and quality of future AAI solutions. The derived pattern system consists of security patterns already published and in use, as well as on open standards like SAML and XACML and related patterns. It can be directly used in the software development cycle, as proposed by different methodologies.